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metrics</title> <meta name="description" content="Search results for: quality metrics"> <meta name="keywords" content="quality metrics"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="quality metrics"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 10203</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: quality metrics</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10203</span> A New Categorization of Image Quality Metrics Based on a Model of Human Quality Perception</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maria%20Grazia%20Albanesi">Maria Grazia Albanesi</a>, <a href="https://publications.waset.org/abstracts/search?q=Riccardo%20Amadeo"> Riccardo Amadeo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=eye-tracking" title="eye-tracking">eye-tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20quality%20assessment%20metric" title=" image quality assessment metric"> image quality assessment metric</a>, <a href="https://publications.waset.org/abstracts/search?q=MOS" title=" MOS"> MOS</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20user%20experience" title=" quality of user experience"> quality of user experience</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20perception" title=" visual perception"> visual perception</a> </p> <a href="https://publications.waset.org/abstracts/8906/a-new-categorization-of-image-quality-metrics-based-on-a-model-of-human-quality-perception" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8906.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">411</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10202</span> Evaluating the Performance of Existing Full-Reference Quality Metrics on High Dynamic Range (HDR) Video Content</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maryam%20Azimi">Maryam Azimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Amin%20Banitalebi-Dehkordi"> Amin Banitalebi-Dehkordi</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuanyuan%20Dong"> Yuanyuan Dong</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahsa%20T.%20Pourazad"> Mahsa T. Pourazad</a>, <a href="https://publications.waset.org/abstracts/search?q=Panos%20Nasiopoulos"> Panos Nasiopoulos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> While there exists a wide variety of Low Dynamic Range (LDR) quality metrics, only a limited number of metrics are designed specifically for the High Dynamic Range (HDR) content. With the introduction of HDR video compression standardization effort by international standardization bodies, the need for an efficient video quality metric for HDR applications has become more pronounced. The objective of this study is to compare the performance of the existing full-reference LDR and HDR video quality metrics on HDR content and identify the most effective one for HDR applications. To this end, a new HDR video data set is created, which consists of representative indoor and outdoor video sequences with different brightness, motion levels and different representing types of distortions. The quality of each distorted video in this data set is evaluated both subjectively and objectively. The correlation between the subjective and objective results confirm that VIF quality metric outperforms all to their tested metrics in the presence of the tested types of distortions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HDR" title="HDR">HDR</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20range" title=" dynamic range"> dynamic range</a>, <a href="https://publications.waset.org/abstracts/search?q=LDR" title=" LDR"> LDR</a>, <a href="https://publications.waset.org/abstracts/search?q=subjective%20evaluation" title=" subjective evaluation"> subjective evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20compression" title=" video compression"> video compression</a>, <a href="https://publications.waset.org/abstracts/search?q=HEVC" title=" HEVC"> HEVC</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20quality%20metrics" title=" video quality metrics"> video quality metrics</a> </p> <a href="https://publications.waset.org/abstracts/18171/evaluating-the-performance-of-existing-full-reference-quality-metrics-on-high-dynamic-range-hdr-video-content" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18171.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">524</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10201</span> Back to Basics: Redefining Quality Measurement for Hybrid Software Development Organizations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Satya%20Pradhan">Satya Pradhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Venky%20Nanniyur"> Venky Nanniyur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the software industry transitions from a license-based model to a subscription-based Software-as-a-Service (SaaS) model, many software development groups are using a hybrid development model that incorporates Agile and Waterfall methodologies in different parts of the organization. The traditional metrics used for measuring software quality in Waterfall or Agile paradigms do not apply to this new hybrid methodology. In addition, to respond to higher quality demands from customers and to gain a competitive advantage in the market, many companies are starting to prioritize quality as a strategic differentiator. As a result, quality metrics are included in the decision-making activities all the way up to the executive level, including board of director reviews. This paper presents key challenges associated with measuring software quality in organizations using the hybrid development model. We introduce a framework called Prevention-Inspection-Evaluation-Removal (PIER) to provide a comprehensive metric definition for hybrid organizations. The framework includes quality measurements, quality enforcement, and quality decision points at different organizational levels and project milestones. The metrics framework defined in this paper is being used for all Cisco systems products used in customer premises. We present several field metrics for one product portfolio (enterprise networking) to show the effectiveness of the proposed measurement system. As the results show, this metrics framework has significantly improved in-process defect management as well as field quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quality%20management%20system" title="quality management system">quality management system</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20metrics%20framework" title=" quality metrics framework"> quality metrics framework</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20metrics" title=" quality metrics"> quality metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=agile" title=" agile"> agile</a>, <a href="https://publications.waset.org/abstracts/search?q=waterfall" title=" waterfall"> waterfall</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20development%20system" title=" hybrid development system"> hybrid development system</a> </p> <a href="https://publications.waset.org/abstracts/110606/back-to-basics-redefining-quality-measurement-for-hybrid-software-development-organizations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110606.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">174</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10200</span> Developing Fault Tolerance Metrics of Web and Mobile Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Mohsin">Ahmad Mohsin</a>, <a href="https://publications.waset.org/abstracts/search?q=Irfan%20Raza%20Naqvi"> Irfan Raza Naqvi</a>, <a href="https://publications.waset.org/abstracts/search?q=Syda%20Fatima%20Usamn"> Syda Fatima Usamn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Applications with higher fault tolerance index are considered more reliable and trustworthy to drive quality. In recent years application development has been shifted from traditional desktop and web to native and hybrid application(s) for the web and mobile platforms. With the emergence of Internet of things IOTs, cloud and big data trends, the need for measuring Fault Tolerance for these complex nature applications has increased to evaluate their performance. There is a phenomenal gap between fault tolerance metrics development and measurement. Classic quality metric models focused on metrics for traditional systems ignoring the essence of today’s applications software, hardware & deployment characteristics. In this paper, we have proposed simple metrics to measure fault tolerance considering general requirements for Web and Mobile Applications. We have aligned factors – subfactors, using GQM for metrics development considering the nature of mobile we apps. Systematic Mathematical formulation is done to measure metrics quantitatively. Three web mobile applications are selected to measure Fault Tolerance factors using formulated metrics. Applications are then analysed on the basis of results from observations in a controlled environment on different mobile devices. Quantitative results are presented depicting Fault tolerance in respective applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=web%20and%20mobile%20applications" title="web and mobile applications">web and mobile applications</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability" title=" reliability"> reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20tolerance%20metric" title=" fault tolerance metric"> fault tolerance metric</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20metrics" title=" quality metrics"> quality metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=GQM%20based%20metrics" title=" GQM based metrics"> GQM based metrics</a> </p> <a href="https://publications.waset.org/abstracts/46344/developing-fault-tolerance-metrics-of-web-and-mobile-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46344.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">344</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10199</span> Routing Metrics and Protocols for Wireless Mesh Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samira%20Kalantary">Samira Kalantary</a>, <a href="https://publications.waset.org/abstracts/search?q=Zohre%20Saatzade"> Zohre Saatzade</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless Mesh Networks (WMNs) are low-cost access networks built on cooperative routing over a backbone composed of stationary wireless routers. WMNs must deal with the highly unstable wireless medium. Thus, routing metrics and protocols are evolving by designing algorithms that consider link quality to choose the best routes. In this work, we analyse the state of the art in WMN metrics and propose taxonomy for WMN routing protocols. Performance measurements of a wireless mesh network deployed using various routing metrics are presented and corroborate our analysis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20mesh%20networks" title="wireless mesh networks">wireless mesh networks</a>, <a href="https://publications.waset.org/abstracts/search?q=routing%20protocols" title=" routing protocols"> routing protocols</a>, <a href="https://publications.waset.org/abstracts/search?q=routing%20metrics" title=" routing metrics"> routing metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a> </p> <a href="https://publications.waset.org/abstracts/2240/routing-metrics-and-protocols-for-wireless-mesh-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2240.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">453</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10198</span> The Influence of Audio on Perceived Quality of Segmentation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Silvio%20Ricardo%20Rodrigues%20Sanches">Silvio Ricardo Rodrigues Sanches</a>, <a href="https://publications.waset.org/abstracts/search?q=Bianca%20Cogo%20Barbosa"> Bianca Cogo Barbosa</a>, <a href="https://publications.waset.org/abstracts/search?q=Beatriz%20Regina%20Brum"> Beatriz Regina Brum</a>, <a href="https://publications.waset.org/abstracts/search?q=Cl%C3%A9ber%20Gimenez%20Corr%C3%AAa"> Cléber Gimenez Corrêa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To evaluate the quality of a segmentation algorithm, the authors use subjective or objective metrics. Although subjective metrics are more accurate than objective ones, objective metrics do not require user feedback to test an algorithm. Objective metrics require subjective experiments only during their development. Subjective experiments typically display to users some videos (generated from frames with segmentation errors) that simulate the environment of an application domain. This user feedback is crucial information for metric definition. In the subjective experiments applied to develop some state-of-the-art metrics used to test segmentation algorithms, the videos displayed during the experiments did not contain audio. Audio is an essential component in applications such as videoconference and augmented reality. If the audio influences the user’s perception, using only videos without audio in subjective experiments can compromise the efficiency of an objective metric generated using data from these experiments. This work aims to identify if the audio influences the user’s perception of segmentation quality in background substitution applications with audio. The proposed approach used a subjective method based on formal video quality assessment methods. The results showed that audio influences the quality of segmentation perceived by a user. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=background%20substitution" title="background substitution">background substitution</a>, <a href="https://publications.waset.org/abstracts/search?q=influence%20of%20audio" title=" influence of audio"> influence of audio</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation%20evaluation" title=" segmentation evaluation"> segmentation evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation%20quality" title=" segmentation quality"> segmentation quality</a> </p> <a href="https://publications.waset.org/abstracts/148456/the-influence-of-audio-on-perceived-quality-of-segmentation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148456.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">116</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10197</span> Determining the Most Efficient Test Available in Software Testing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qasim%20Zafar">Qasim Zafar</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthew%20Anderson"> Matthew Anderson</a>, <a href="https://publications.waset.org/abstracts/search?q=Esteban%20Garcia"> Esteban Garcia</a>, <a href="https://publications.waset.org/abstracts/search?q=Steven%20Drager"> Steven Drager</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Software failures can present an enormous detriment to people's lives and cost millions of dollars to repair when they are unexpectedly encountered in the wild. Despite a significant portion of the software development lifecycle and resources are dedicated to testing, software failures are a relatively frequent occurrence. Nevertheless, the evaluation of testing effectiveness remains at the forefront of ensuring high-quality software and software metrics play a critical role in providing valuable insights into quantifiable objectives to assess the level of assurance and confidence in the system. As the selection of appropriate metrics can be an arduous process, the goal of this paper is to shed light on the significance of software metrics by examining a range of testing techniques and metrics as well as identifying key areas for improvement. Additionally, through this investigation, readers will gain a deeper understanding of how metrics can help to drive informed decision-making on delivering high-quality software and facilitate continuous improvement in testing practices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20testing" title="software testing">software testing</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20metrics" title=" software metrics"> software metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=testing%20effectiveness" title=" testing effectiveness"> testing effectiveness</a>, <a href="https://publications.waset.org/abstracts/search?q=black%20box%20testing" title=" black box testing"> black box testing</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20testing" title=" random testing"> random testing</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20random%20testing" title=" adaptive random testing"> adaptive random testing</a>, <a href="https://publications.waset.org/abstracts/search?q=combinatorial%20testing" title=" combinatorial testing"> combinatorial testing</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzz%20testing" title=" fuzz testing"> fuzz testing</a>, <a href="https://publications.waset.org/abstracts/search?q=equivalence%20partition" title=" equivalence partition"> equivalence partition</a>, <a href="https://publications.waset.org/abstracts/search?q=boundary%20value%20analysis" title=" boundary value analysis"> boundary value analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=white%20box%20testing" title=" white box testing"> white box testing</a> </p> <a href="https://publications.waset.org/abstracts/169666/determining-the-most-efficient-test-available-in-software-testing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169666.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">89</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10196</span> Evaluation of Video Quality Metrics and Performance Comparison on Contents Taken from Most Commonly Used Devices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pratik%20Dhabal%20Deo">Pratik Dhabal Deo</a>, <a href="https://publications.waset.org/abstracts/search?q=Manoj%20P."> Manoj P.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increasing number of social media users, the amount of video content available has also significantly increased. Currently, the number of smartphone users is at its peak, and many are increasingly using their smartphones as their main photography and recording devices. There have been a lot of developments in the field of Video Quality Assessment (VQA) and metrics like VMAF, SSIM etc. are said to be some of the best performing metrics, but the evaluation of these metrics is dominantly done on professionally taken video contents using professional tools, lighting conditions etc. No study particularly pinpointing the performance of the metrics on the contents taken by users on very commonly available devices has been done. Datasets that contain a huge number of videos from different high-end devices make it difficult to analyze the performance of the metrics on the content from most used devices even if they contain contents taken in poor lighting conditions using lower-end devices. These devices face a lot of distortions due to various factors since the spectrum of contents recorded on these devices is huge. In this paper, we have presented an analysis of the objective VQA metrics on contents taken only from most used devices and their performance on them, focusing on full-reference metrics. To carry out this research, we created a custom dataset containing a total of 90 videos that have been taken from three most commonly used devices, and android smartphone, an IOS smartphone and a DSLR. On the videos taken on each of these devices, the six most common types of distortions that users face have been applied on addition to already existing H.264 compression based on four reference videos. These six applied distortions have three levels of degradation each. A total of the five most popular VQA metrics have been evaluated on this dataset and the highest values and the lowest values of each of the metrics on the distortions have been recorded. Finally, it is found that blur is the artifact on which most of the metrics didn’t perform well. Thus, in order to understand the results better the amount of blur in the data set has been calculated and an additional evaluation of the metrics was done using HEVC codec, which is the next version of H.264 compression, on the camera that proved to be the sharpest among the devices. The results have shown that as the resolution increases, the performance of the metrics tends to become more accurate and the best performing metric among them is VQM with very few inconsistencies and inaccurate results when the compression applied is H.264, but when the compression is applied is HEVC, SSIM and VMAF have performed significantly better. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distortion" title="distortion">distortion</a>, <a href="https://publications.waset.org/abstracts/search?q=metrics" title=" metrics"> metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a>, <a href="https://publications.waset.org/abstracts/search?q=resolution" title=" resolution"> resolution</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20quality%20assessment" title=" video quality assessment"> video quality assessment</a> </p> <a href="https://publications.waset.org/abstracts/145939/evaluation-of-video-quality-metrics-and-performance-comparison-on-contents-taken-from-most-commonly-used-devices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145939.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">203</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10195</span> MRI Quality Control Using Texture Analysis and Spatial Metrics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kumar%20Kanudkuri">Kumar Kanudkuri</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Sandhya"> A. Sandhya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ACR%20MRI%20phantom" title="ACR MRI phantom">ACR MRI phantom</a>, <a href="https://publications.waset.org/abstracts/search?q=MRI%20image%20quality%20metrics" title=" MRI image quality metrics"> MRI image quality metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=SNRU" title=" SNRU"> SNRU</a>, <a href="https://publications.waset.org/abstracts/search?q=VIF" title=" VIF"> VIF</a>, <a href="https://publications.waset.org/abstracts/search?q=FSIM" title=" FSIM"> FSIM</a>, <a href="https://publications.waset.org/abstracts/search?q=GLCM" title=" GLCM"> GLCM</a>, <a href="https://publications.waset.org/abstracts/search?q=slice%20thickness%20accuracy" title=" slice thickness accuracy"> slice thickness accuracy</a>, <a href="https://publications.waset.org/abstracts/search?q=slice%20position%20accuracy" title=" slice position accuracy"> slice position accuracy</a> </p> <a href="https://publications.waset.org/abstracts/163983/mri-quality-control-using-texture-analysis-and-spatial-metrics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163983.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">170</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10194</span> User-Perceived Quality Factors for Certification Model of Web-Based System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jamaiah%20H.%20Yahaya">Jamaiah H. Yahaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Aziz%20Deraman"> Aziz Deraman</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Razak%20Hamdan"> Abdul Razak Hamdan</a>, <a href="https://publications.waset.org/abstracts/search?q=Yusmadi%20Yah%20Jusoh"> Yusmadi Yah Jusoh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20certification%20model" title="software certification model">software certification model</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20centric%20approach" title=" user centric approach"> user centric approach</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20quality%20factors" title=" software quality factors"> software quality factors</a>, <a href="https://publications.waset.org/abstracts/search?q=metrics%20and%20measurements" title=" metrics and measurements"> metrics and measurements</a>, <a href="https://publications.waset.org/abstracts/search?q=web-based%20system" title=" web-based system"> web-based system</a> </p> <a href="https://publications.waset.org/abstracts/7247/user-perceived-quality-factors-for-certification-model-of-web-based-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7247.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">405</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10193</span> Reasons for Non-Applicability of Software Entropy Metrics for Bug Prediction in Android </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arvinder%20Kaur">Arvinder Kaur</a>, <a href="https://publications.waset.org/abstracts/search?q=Deepti%20Chopra"> Deepti Chopra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Software Entropy Metrics for bug prediction have been validated on various software systems by different researchers. In our previous research, we have validated that Software Entropy Metrics calculated for Mozilla subsystem’s predict the future bugs reasonably well. In this study, the Software Entropy metrics are calculated for a subsystem of Android and it is noticed that these metrics are not suitable for bug prediction. The results are compared with a subsystem of Mozilla and a comparison is made between the two software systems to determine the reasons why Software Entropy metrics are not applicable for Android. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=android" title="android">android</a>, <a href="https://publications.waset.org/abstracts/search?q=bug%20prediction" title=" bug prediction"> bug prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=mining%20software%20repositories" title=" mining software repositories"> mining software repositories</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20entropy" title=" software entropy"> software entropy</a> </p> <a href="https://publications.waset.org/abstracts/49619/reasons-for-non-applicability-of-software-entropy-metrics-for-bug-prediction-in-android" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49619.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">578</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10192</span> Modeling Metrics for Monitoring Software Project Performance Based on the GQM Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mariayee%20Doraisamy">Mariayee Doraisamy</a>, <a href="https://publications.waset.org/abstracts/search?q=Suhaimi%20bin%20Ibrahim"> Suhaimi bin Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Naz%E2%80%99ri%20Mahrin"> Mohd Naz’ri Mahrin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=component" title="component">component</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20project%20performance" title=" software project performance"> software project performance</a>, <a href="https://publications.waset.org/abstracts/search?q=goal%20question%20metrics" title=" goal question metrics"> goal question metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20measurement%20criteria" title=" performance measurement criteria"> performance measurement criteria</a>, <a href="https://publications.waset.org/abstracts/search?q=metrics" title=" metrics"> metrics</a> </p> <a href="https://publications.waset.org/abstracts/11761/modeling-metrics-for-monitoring-software-project-performance-based-on-the-gqm-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11761.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">356</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10191</span> Software Quality Measurement System for Telecommunication Industry in Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nor%20Fazlina%20Iryani%20Abdul%20Hamid">Nor Fazlina Iryani Abdul Hamid</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamad%20Khatim%20Hasan"> Mohamad Khatim Hasan </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Evolution of software quality measurement has been started since McCall introduced his quality model in year 1977. Starting from there, several software quality models and software quality measurement methods had emerged but none of them focused on telecommunication industry. In this paper, the implementation of software quality measurement system for telecommunication industry was compulsory to accommodate the rapid growth of telecommunication industry. The quality value of the telecommunication related software could be calculated using this system by entering the required parameters. The system would calculate the quality value of the measured system based on predefined quality metrics and aggregated by referring to the quality model. It would classify the quality level of the software based on Net Satisfaction Index (NSI). Thus, software quality measurement system was important to both developers and users in order to produce high quality software product for telecommunication industry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20quality" title="software quality">software quality</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20measurement" title=" quality measurement"> quality measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20model" title=" quality model"> quality model</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20metric" title=" quality metric"> quality metric</a>, <a href="https://publications.waset.org/abstracts/search?q=net%20satisfaction%20index" title=" net satisfaction index"> net satisfaction index</a> </p> <a href="https://publications.waset.org/abstracts/15875/software-quality-measurement-system-for-telecommunication-industry-in-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15875.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">592</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10190</span> On Projective Invariants of Spherically Symmetric Finsler Spaces in Rn</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nasrin%20Sadeghzadeh">Nasrin Sadeghzadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we study projective invariants of spherically symmetric Finsler metrics in Rn. We find the necessary and sufficient conditions for the metrics to be Douglas and Generalized Douglas-Weyl (GDW) types. Also we show that two classes of GDW and Douglas spherically symmetric Finsler metrics coincide. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spherically%20symmetric%20finsler%20metrics%20in%20Rn" title="spherically symmetric finsler metrics in Rn">spherically symmetric finsler metrics in Rn</a>, <a href="https://publications.waset.org/abstracts/search?q=finsler%20metrics" title=" finsler metrics"> finsler metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=douglas%20metric" title=" douglas metric"> douglas metric</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%0D%0ADouglas-Weyl%20%28GDW%29%20metric" title=" generalized Douglas-Weyl (GDW) metric"> generalized Douglas-Weyl (GDW) metric</a> </p> <a href="https://publications.waset.org/abstracts/33315/on-projective-invariants-of-spherically-symmetric-finsler-spaces-in-rn" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33315.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">358</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10189</span> Code Refactoring Using Slice-Based Cohesion Metrics and AOP</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jagannath%20Singh">Jagannath Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Durga%20Prasad%20Mohapatra"> Durga Prasad Mohapatra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Software refactoring is very essential for maintaining the software quality. It is an usual practice that we first design the software and then go for coding. But after coding is completed, if the requirement changes slightly or our expected output is not achieved, then we change the codes. For each small code change, we cannot change the design. In course of time, due to these small changes made to the code, the software design decays. Software refactoring is used to restructure the code in order to improve the design and quality of the software. In this paper, we propose an approach for performing code refactoring. We use slice-based cohesion metrics to identify the target methods which requires refactoring. After identifying the target methods, we use program slicing to divide the target method into two parts. Finally, we have used the concepts of Aspects to adjust the code structure so that the external behaviour of the original module does not change. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20refactoring" title="software refactoring">software refactoring</a>, <a href="https://publications.waset.org/abstracts/search?q=program%20slicing" title=" program slicing"> program slicing</a>, <a href="https://publications.waset.org/abstracts/search?q=AOP" title=" AOP"> AOP</a>, <a href="https://publications.waset.org/abstracts/search?q=cohesion%20metrics" title=" cohesion metrics"> cohesion metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=code%20restructure" title=" code restructure"> code restructure</a>, <a href="https://publications.waset.org/abstracts/search?q=AspectJ" title=" AspectJ"> AspectJ</a> </p> <a href="https://publications.waset.org/abstracts/10366/code-refactoring-using-slice-based-cohesion-metrics-and-aop" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10366.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">512</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10188</span> From Responses of Macroinvertebrate Metrics to the Definition of Reference Thresholds</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Houny%C3%A8m%C3%A8%20Romuald">Hounyèmè Romuald</a>, <a href="https://publications.waset.org/abstracts/search?q=Mama%20Daouda"> Mama Daouda</a>, <a href="https://publications.waset.org/abstracts/search?q=Argillier%20Christine"> Argillier Christine</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study focused on the use of benthic macrofauna to define the reference state of an anthropized lagoon (Nokoué-Benin) from the responses of relevant metrics to proxies. The approach used is a combination of a joint species distribution model and Bayesian networks. The joint species distribution model was used to select the relevant metrics and generate posterior probabilities that were then converted into posterior response probabilities for each of the quality classes (pressure levels), which will constitute the conditional probability tables allowing the establishment of the probabilistic graph representing the different causal relationships between metrics and pressure proxies. For the definition of the reference thresholds, the predicted responses for low-pressure levels were read via probability density diagrams. Observations collected during high and low water periods spanning 03 consecutive years (2004-2006), sampling 33 macroinvertebrate taxa present at all seasons and sampling points, and measurements of 14 environmental parameters were used as application data. The study demonstrated reliable inferences, selection of 07 relevant metrics and definition of quality thresholds for each environmental parameter. The relevance of the metrics as well as the reference thresholds for ecological assessment despite the small sample size, suggests the potential for wider applicability of the approach for aquatic ecosystem monitoring and assessment programs in developing countries generally characterized by a lack of monitoring data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pressure%20proxies" title="pressure proxies">pressure proxies</a>, <a href="https://publications.waset.org/abstracts/search?q=bayesian%20inference" title=" bayesian inference"> bayesian inference</a>, <a href="https://publications.waset.org/abstracts/search?q=bioindicators" title=" bioindicators"> bioindicators</a>, <a href="https://publications.waset.org/abstracts/search?q=acadjas" title=" acadjas"> acadjas</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20traits" title=" functional traits"> functional traits</a> </p> <a href="https://publications.waset.org/abstracts/159732/from-responses-of-macroinvertebrate-metrics-to-the-definition-of-reference-thresholds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159732.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">83</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10187</span> Cross Project Software Fault Prediction at Design Phase</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pradeep%20Singh">Pradeep Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Shrish%20Verma"> Shrish Verma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20metrics" title="software metrics">software metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20prediction" title=" fault prediction"> fault prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=cross%20project" title=" cross project"> cross project</a>, <a href="https://publications.waset.org/abstracts/search?q=within%20project." title=" within project. "> within project. </a> </p> <a href="https://publications.waset.org/abstracts/27206/cross-project-software-fault-prediction-at-design-phase" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27206.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">344</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10186</span> A Study of Agile Based Approaches to Improve Software Quality</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gurmeet%20Kaur">Gurmeet Kaur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Agile software development methods are being recognized as popular, and efficient approach to the development of software system that has a short delivery period with high quality also that meets customer requirements with zero defect. In agile software development, quality means quality of code where in the quality is maintained through the use of methods or approaches like refactoring, test driven development, behavior driven development, acceptance test driven development, and demand driven development. Software quality is measured in term of metrics such as the number of defects during development of software. Usage of above mentioned methods or approaches, reduces the possibilities of defects in developed software, and hence improve quality. This paper focuses on study of agile based quality methods or approaches for software development that ensures improved quality of software as well as reduced cost, and customer satisfaction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ATDD" title="ATDD">ATDD</a>, <a href="https://publications.waset.org/abstracts/search?q=BDD" title=" BDD"> BDD</a>, <a href="https://publications.waset.org/abstracts/search?q=DDD" title=" DDD"> DDD</a>, <a href="https://publications.waset.org/abstracts/search?q=TDD" title=" TDD"> TDD</a> </p> <a href="https://publications.waset.org/abstracts/118869/a-study-of-agile-based-approaches-to-improve-software-quality" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118869.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10185</span> Empirical Investigation for the Correlation between Object-Oriented Class Lack of Cohesion and Coupling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jehad%20Al%20Dallal">Jehad Al Dallal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design of the internal relationships among object-oriented class members (i.e., attributes and methods) and the external relationships among classes affects the overall quality of the object-oriented software. The degree of relatedness among class members is referred to as class cohesion and the degree to which a class is related to other classes is called class coupling. Well designed classes are expected to exhibit high cohesion and low coupling values. In this paper, using classes of three open-source Java systems, we empirically investigate the relation between class cohesion and coupling. In the empirical study, five lack-of-cohesion metrics and eight coupling metrics are considered. The empirical study results show that class cohesion and coupling internal quality attributes are inversely correlated. The strength of the correlation highly depends on the cohesion and coupling measurement approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=class%20cohesion%20measure" title="class cohesion measure">class cohesion measure</a>, <a href="https://publications.waset.org/abstracts/search?q=class%20coupling%20measure" title=" class coupling measure"> class coupling measure</a>, <a href="https://publications.waset.org/abstracts/search?q=object-oriented%20class" title=" object-oriented class"> object-oriented class</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20quality" title=" software quality"> software quality</a> </p> <a href="https://publications.waset.org/abstracts/45455/empirical-investigation-for-the-correlation-between-object-oriented-class-lack-of-cohesion-and-coupling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45455.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">236</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10184</span> A Comparative Assessment of Daylighting Metrics Assessing the Daylighting Performance of Three Shading Devices under Four Different Orientations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Boubekri">Mohamed Boubekri</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaewook%20Lee"> Jaewook Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The assessment of the daylighting performance of a design solution is a complex task due to the changing nature of daylight. A few quantitative metrics are available to designers to assess such a performance, among them are the mean hourly illuminance (MHI), the daylight factor (DF), the daylight autonomy (DA) and the useful daylight illuminance (UDI). Each of these metrics has criteria and limitations that affect the outcome of the evaluation. When to use one metric instead of another depends largely on the design goals to be achieved. Using Design Iterate Validate Adapt (DIVA) daylighting simulation program we set out to examine the performance behavior of these four metrics with the changing dimensions of three shading devices: a horizontal overhang, a horizontal louver system, and a vertical louver system, and compare their performance behavior as the orientation of the window changes. The context is a classroom of a prototypical elementary school in South Korea. Our results indicate that not all four metrics behave similarly as we vary the size of each shading device and as orientations changes. The UDI is the metric that leads to outcome most different than the other three metrics. Our conclusion is that not all daylighting metrics lead to the same conclusions and that it is important to use the metric that corresponds to the specific goals and objectives of the daylighting solution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=daylight%20factor" title="daylight factor">daylight factor</a>, <a href="https://publications.waset.org/abstracts/search?q=hourly%20daylight%20illuminance" title=" hourly daylight illuminance"> hourly daylight illuminance</a>, <a href="https://publications.waset.org/abstracts/search?q=daylight%20autonomy" title=" daylight autonomy"> daylight autonomy</a>, <a href="https://publications.waset.org/abstracts/search?q=useful%20daylight%20illuminance" title=" useful daylight illuminance"> useful daylight illuminance</a> </p> <a href="https://publications.waset.org/abstracts/70527/a-comparative-assessment-of-daylighting-metrics-assessing-the-daylighting-performance-of-three-shading-devices-under-four-different-orientations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70527.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">284</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10183</span> Evaluation Metrics for Machine Learning Techniques: A Comprehensive Review and Comparative Analysis of Performance Measurement Approaches</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyed-Ali%20Sadegh-Zadeh">Seyed-Ali Sadegh-Zadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Kaveh%20Kavianpour"> Kaveh Kavianpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamed%20Atashbar"> Hamed Atashbar</a>, <a href="https://publications.waset.org/abstracts/search?q=Elham%20Heidari"> Elham Heidari</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Shiry%20Ghidary"> Saeed Shiry Ghidary</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20M.%20Hajiyavand"> Amir M. Hajiyavand</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=evaluation%20metrics" title="evaluation metrics">evaluation metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20measurement" title=" performance measurement"> performance measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=supervised%20learning" title=" supervised learning"> supervised learning</a>, <a href="https://publications.waset.org/abstracts/search?q=unsupervised%20learning" title=" unsupervised learning"> unsupervised learning</a>, <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title=" reinforcement learning"> reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20robustness%20and%20stability" title=" model robustness and stability"> model robustness and stability</a>, <a href="https://publications.waset.org/abstracts/search?q=comparative%20analysis" title=" comparative analysis"> comparative analysis</a> </p> <a href="https://publications.waset.org/abstracts/184552/evaluation-metrics-for-machine-learning-techniques-a-comprehensive-review-and-comparative-analysis-of-performance-measurement-approaches" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184552.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10182</span> Software Component Identification from Its Object-Oriented Code: Graph Metrics Based Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manel%20Brichni">Manel Brichni</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelhak-Djamel%20Seriai"> Abdelhak-Djamel Seriai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Systems are increasingly complex. To reduce their complexity, an abstract view of the system can simplify its development. To overcome this problem, we propose a method to decompose systems into subsystems while reducing their coupling. These subsystems represent components. Consisting of an existing object-oriented systems, the main idea of our approach is based on modelling as graphs all entities of an oriented object source code. Such modelling is easy to handle, so we can apply restructuring algorithms based on graph metrics. The particularity of our approach consists in integrating in addition to standard metrics, such as coupling and cohesion, some graph metrics giving more precision during the components identication. To treat this problem, we relied on the ROMANTIC approach that proposed a component-based software architecture recovery from an object oriented system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20reengineering" title="software reengineering">software reengineering</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20component%0D%0Aand%20interfaces" title=" software component and interfaces"> software component and interfaces</a>, <a href="https://publications.waset.org/abstracts/search?q=metrics" title=" metrics"> metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=graphs" title=" graphs"> graphs</a> </p> <a href="https://publications.waset.org/abstracts/13322/software-component-identification-from-its-object-oriented-code-graph-metrics-based-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13322.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">501</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10181</span> Reframing Service Oriented Architecture Design Principles in Software Design Quality</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Purnomo%20Yustianto">Purnomo Yustianto</a>, <a href="https://publications.waset.org/abstracts/search?q=Robin%20Doss"> Robin Doss</a>, <a href="https://publications.waset.org/abstracts/search?q=Novianto%20B.%20Kurniawan%20Suhardi"> Novianto B. Kurniawan Suhardi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Since its inception, the design activities of Service Oriented Architecture (SOA) has been guided with aspects from the Service Design Principles (SDP), such as cohesion, granularity, loose coupling, discoverability, and autonomy, etc. The goal of this paper is two folds. The first is to examine the position of SDP within the context of software quality, and the second is to reframe the aspects of SDP into a more concise terms and relations. This paper is divided into four parts, in which after the introduction, a review on related software quality is provided to determine the quality context of SDP. The third part reviews the original SDP and offers a relation model among the SDP aspects. The fourth part explores the design quality metrics available for SOA and proposes a relationship representing the design quality. Among the aspects of design principles, the cohesion and coupling aspect is determined to be the two important aspects for achieving reusability of a service. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SOA" title="SOA">SOA</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20quality" title=" software quality"> software quality</a>, <a href="https://publications.waset.org/abstracts/search?q=service%20design%20principle" title=" service design principle"> service design principle</a>, <a href="https://publications.waset.org/abstracts/search?q=reusability" title=" reusability"> reusability</a>, <a href="https://publications.waset.org/abstracts/search?q=cohesion" title=" cohesion"> cohesion</a>, <a href="https://publications.waset.org/abstracts/search?q=coupling" title=" coupling"> coupling</a> </p> <a href="https://publications.waset.org/abstracts/107939/reframing-service-oriented-architecture-design-principles-in-software-design-quality" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107939.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">171</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10180</span> Map Matching Performance under Various Similarity Metrics for Heterogeneous Robot Teams</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20C.%20Akay">M. C. Akay</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Aybakan"> A. Aybakan</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Temeltas"> H. Temeltas </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aerial and ground robots have various advantages of usage in different missions. Aerial robots can move quickly and get a different sight of view of the area, but those vehicles cannot carry heavy payloads. On the other hand, unmanned ground vehicles (UGVs) are slow moving vehicles, since those can carry heavier payloads than unmanned aerial vehicles (UAVs). In this context, we investigate the performances of various Similarity Metrics to provide a common map for Heterogeneous Robot Team (HRT) in complex environments. Within the usage of Lidar Odometry and Octree Mapping technique, the local 3D maps of the environment are gathered.  In order to obtain a common map for HRT, informative theoretic similarity metrics are exploited. All types of these similarity metrics gave adequate as allowable simulation time and accurate results that can be used in different types of applications. For the heterogeneous multi robot team, those methods can be used to match different types of maps. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=common%20maps" title="common maps">common maps</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneous%20robot%20team" title=" heterogeneous robot team"> heterogeneous robot team</a>, <a href="https://publications.waset.org/abstracts/search?q=map%20matching" title=" map matching"> map matching</a>, <a href="https://publications.waset.org/abstracts/search?q=informative%20theoretic%20similarity%20metrics" title=" informative theoretic similarity metrics"> informative theoretic similarity metrics</a> </p> <a href="https://publications.waset.org/abstracts/99098/map-matching-performance-under-various-similarity-metrics-for-heterogeneous-robot-teams" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99098.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">167</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10179</span> Exploration of Various Metrics for Partitioning of Cellular Automata Units for Efficient Reconfiguration of Field Programmable Gate Arrays (FPGAs)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peter%20Tabatt">Peter Tabatt</a>, <a href="https://publications.waset.org/abstracts/search?q=Christian%20Siemers"> Christian Siemers</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Using FPGA devices to improve the behavior of time-critical parts of embedded systems is a proven concept for years. With reconfigurable FPGA devices, the logical blocks can be partitioned and grouped into static and dynamic parts. The dynamic parts can be reloaded 'on demand' at runtime. This work uses cellular automata, which are constructed through compilation from (partially restricted) ANSI-C sources, to determine the suitability of various metrics for optimal partitioning. Significant metrics, in this case, are for example the area on the FPGA device for the partition, the pass count for loop constructs and communication characteristics to other partitions. With successful partitioning, it is possible to use smaller FPGA devices for the same requirements as with not reconfigurable FPGA devices or – vice versa – to use the same FPGAs for larger programs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reconfigurable%20FPGA" title="reconfigurable FPGA">reconfigurable FPGA</a>, <a href="https://publications.waset.org/abstracts/search?q=cellular%20automata" title=" cellular automata"> cellular automata</a>, <a href="https://publications.waset.org/abstracts/search?q=partitioning" title=" partitioning"> partitioning</a>, <a href="https://publications.waset.org/abstracts/search?q=metrics" title=" metrics"> metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20computing" title=" parallel computing"> parallel computing</a> </p> <a href="https://publications.waset.org/abstracts/56244/exploration-of-various-metrics-for-partitioning-of-cellular-automata-units-for-efficient-reconfiguration-of-field-programmable-gate-arrays-fpgas" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56244.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10178</span> Call-Back Laterality and Bilaterality: Possible Screening Mammography Quality Metrics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samson%20Munn">Samson Munn</a>, <a href="https://publications.waset.org/abstracts/search?q=Virginia%20H.%20Kim"> Virginia H. Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Huija%20Chen"> Huija Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Sean%20Maldonado"> Sean Maldonado</a>, <a href="https://publications.waset.org/abstracts/search?q=Michelle%20Kim"> Michelle Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Paul%20Koscheski"> Paul Koscheski</a>, <a href="https://publications.waset.org/abstracts/search?q=Babak%20N.%20Kalantari"> Babak N. Kalantari</a>, <a href="https://publications.waset.org/abstracts/search?q=Gregory%20Eckel"> Gregory Eckel</a>, <a href="https://publications.waset.org/abstracts/search?q=Albert%20Lee"> Albert Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In terms of screening mammography quality, neither the portion of reports that advise call-back imaging that should be bilateral versus unilateral nor how much the unilateral call-backs may appropriately diverge from 50–50 (left versus right) is known. Many factors may affect detection laterality: display arrangement, reflections preferentially striking one display location, hanging protocols, seating positions with respect to others and displays, visual field cuts, health, etc. The call-back bilateral fraction may reflect radiologist experience (not in our data) or confidence level. Thus, laterality and bilaterality of call-backs advised in screening mammography reports could be worthy quality metrics. Here, laterality data did not reveal a concern until drilling down to individuals. Bilateral screening mammogram report recommendations by five breast imaging, attending radiologists at Harbor-UCLA Medical Center (Torrance, California) 9/1/15--8/31/16 and 9/1/16--8/31/17 were retrospectively reviewed. Recommended call-backs for bilateral versus unilateral, and for left versus right, findings were counted. Chi-square (χ²) statistic was applied. Year 1: of 2,665 bilateral screening mammograms, reports of 556 (20.9%) recommended call-back, of which 99 (17.8% of the 556) were for bilateral findings. Of the 457 unilateral recommendations, 222 (48.6%) regarded the left breast. Year 2: of 2,106 bilateral screening mammograms, reports of 439 (20.8%) recommended call-back, of which 65 (14.8% of the 439) were for bilateral findings. Of the 374 unilateral recommendations, 182 (48.7%) regarded the left breast. Individual ranges of call-backs that were bilateral were 13.2–23.3%, 10.2–22.5%, and 13.6–17.9%, by year(s) 1, 2, and 1+2, respectively; these ranges were unrelated to experience level; the two-year mean was 15.8% (SD=1.9%). The lowest χ² p value of the group's sidedness disparities years 1, 2, and 1+2 was > 0.4. Regarding four individual radiologists, the lowest p value was 0.42. However, the fifth radiologist disfavored the left, with p values of 0.21, 0.19, and 0.07, respectively; that radiologist had the greatest number of years of experience. There was a concerning, 93% likelihood that bias against left breast findings evidenced by one of our radiologists was not random. Notably, very soon after the period under review, he retired, presented with leukemia, and died. We call for research to be done, particularly by large departments with many radiologists, of two possible, new, quality metrics in screening mammography: laterality and bilaterality. (Images, patient outcomes, report validity, and radiologist psychological confidence levels were not assessed. No intervention nor subsequent data collection was conducted. This uncomplicated collection of data and simple appraisal were not designed, nor had there been any intention to develop or contribute, to generalizable knowledge (per U.S. DHHS 45 CFR, part 46)). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mammography" title="mammography">mammography</a>, <a href="https://publications.waset.org/abstracts/search?q=screening%20mammography" title=" screening mammography"> screening mammography</a>, <a href="https://publications.waset.org/abstracts/search?q=quality" title=" quality"> quality</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20metrics" title=" quality metrics"> quality metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=laterality" title=" laterality"> laterality</a> </p> <a href="https://publications.waset.org/abstracts/133741/call-back-laterality-and-bilaterality-possible-screening-mammography-quality-metrics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133741.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10177</span> Subjective versus Objective Assessment for Magnetic Resonance (MR) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Heshalini%20Rajagopal">Heshalini Rajagopal</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Sze%20Chow"> Li Sze Chow</a>, <a href="https://publications.waset.org/abstracts/search?q=Raveendran%20Paramesran"> Raveendran Paramesran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20resonance%20%28MR%29%20images" title="medical resonance (MR) images">medical resonance (MR) images</a>, <a href="https://publications.waset.org/abstracts/search?q=difference%20mean%20opinion%20score%20%28DMOS%29" title=" difference mean opinion score (DMOS)"> difference mean opinion score (DMOS)</a>, <a href="https://publications.waset.org/abstracts/search?q=full%20reference%20image%20quality%20assessment%20%28FR-IQA%29" title=" full reference image quality assessment (FR-IQA)"> full reference image quality assessment (FR-IQA)</a> </p> <a href="https://publications.waset.org/abstracts/39606/subjective-versus-objective-assessment-for-magnetic-resonance-mr-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39606.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">458</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10176</span> An Empirical Evaluation of Performance of Machine Learning Techniques on Imbalanced Software Quality Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruchika%20Malhotra">Ruchika Malhotra</a>, <a href="https://publications.waset.org/abstracts/search?q=Megha%20Khanna"> Megha Khanna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=change%20proneness" title="change proneness">change proneness</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20validation" title=" empirical validation"> empirical validation</a>, <a href="https://publications.waset.org/abstracts/search?q=imbalanced%20learning" title=" imbalanced learning"> imbalanced learning</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20techniques" title=" machine learning techniques"> machine learning techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=object-oriented%20metrics" title=" object-oriented metrics"> object-oriented metrics</a> </p> <a href="https://publications.waset.org/abstracts/41990/an-empirical-evaluation-of-performance-of-machine-learning-techniques-on-imbalanced-software-quality-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41990.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">418</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10175</span> Leveraging Quality Metrics in Voting Model Based Thread Retrieval</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Atefeh%20Heydari">Atefeh Heydari</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammadali%20Tavakoli"> Mohammadali Tavakoli</a>, <a href="https://publications.waset.org/abstracts/search?q=Zuriati%20Ismail"> Zuriati Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Naomie%20Salim"> Naomie Salim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=content%20quality" title="content quality">content quality</a>, <a href="https://publications.waset.org/abstracts/search?q=forum%20search" title=" forum search"> forum search</a>, <a href="https://publications.waset.org/abstracts/search?q=thread%20retrieval" title=" thread retrieval"> thread retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=voting%20techniques" title=" voting techniques"> voting techniques</a> </p> <a href="https://publications.waset.org/abstracts/42749/leveraging-quality-metrics-in-voting-model-based-thread-retrieval" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42749.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">213</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10174</span> Quantifying Spatiotemporal Patterns of Past and Future Urbanization Trends in El Paso, Texas and Their Impact on Electricity Consumption</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Joanne%20Moyer">Joanne Moyer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> El Paso, Texas is a southwest border city that has experienced continuous growth within the last 15-years. Understanding the urban growth trends and patterns using data from the National Land Cover Database (NLCD) and landscape metrics, provides a quantitative description of growth. Past urban growth provided a basis to predict 2031 future land-use for El Paso using the CA-Markov model. As a consequence of growth, an increase in demand of resources follows. Using panel data analysis, an understanding of the relation between landscape metrics and electricity consumption is further analyzed. The studies’ findings indicate that past growth focused within three districts within the City of El Paso. The landscape metrics suggest as the city has grown, fragmentation has decreased. Alternatively, the landscape metrics for the projected 2031 land-use indicates possible fragmentation within one of these districts. Panel data suggests electricity consumption and mean patch area landscape metric are positively correlated. The study provides local decision makers to make informed decisions for policies and urban planning to ensure a future sustainable community. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landscape%20metrics" title="landscape metrics">landscape metrics</a>, <a href="https://publications.waset.org/abstracts/search?q=CA-Markov" title=" CA-Markov"> CA-Markov</a>, <a href="https://publications.waset.org/abstracts/search?q=El%20Paso" title=" El Paso"> El Paso</a>, <a href="https://publications.waset.org/abstracts/search?q=Texas" title=" Texas"> Texas</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data" title=" panel data"> panel data</a> </p> <a href="https://publications.waset.org/abstracts/128976/quantifying-spatiotemporal-patterns-of-past-and-future-urbanization-trends-in-el-paso-texas-and-their-impact-on-electricity-consumption" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128976.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=quality%20metrics&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=quality%20metrics&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=quality%20metrics&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=quality%20metrics&page=5">5</a></li> <li class="page-item"><a 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