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patient-specific decision path</title> <meta name="description" content="Search results for: patient-specific decision path"> <meta name="keywords" content="patient-specific decision path"> <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" 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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="patient-specific decision path"> <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> 5136</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: patient-specific decision path</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5136</span> Patient-Specific Modeling Algorithm for Medical Data Based on AUC</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guilherme%20Ribeiro">Guilherme Ribeiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexandre%20Oliveira"> Alexandre Oliveira</a>, <a href="https://publications.waset.org/abstracts/search?q=Antonio%20Ferreira"> Antonio Ferreira</a>, <a href="https://publications.waset.org/abstracts/search?q=Shyam%20Visweswaran"> Shyam Visweswaran</a>, <a href="https://publications.waset.org/abstracts/search?q=Gregory%20Cooper"> Gregory Cooper</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=approach%20instance-based" title="approach instance-based">approach instance-based</a>, <a href="https://publications.waset.org/abstracts/search?q=area%20under%20the%20ROC%20curve" title=" area under the ROC curve"> area under the ROC curve</a>, <a href="https://publications.waset.org/abstracts/search?q=patient-specific%20decision%20path" title=" patient-specific decision path"> patient-specific decision path</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20predictions" title=" clinical predictions"> clinical predictions</a> </p> <a href="https://publications.waset.org/abstracts/35519/patient-specific-modeling-algorithm-for-medical-data-based-on-auc" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35519.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">479</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">5135</span> Decision Support System for Solving Multi-Objective Routing Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ismail%20El%20Gayar">Ismail El Gayar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ossama%20Ismail"> Ossama Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Yousri%20El%20Gamal"> Yousri El Gamal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bus%20scheduling%20problem" title="bus scheduling problem">bus scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title=" decision support system"> decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=shortest%20path" title=" shortest path"> shortest path</a> </p> <a href="https://publications.waset.org/abstracts/45065/decision-support-system-for-solving-multi-objective-routing-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45065.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">415</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">5134</span> Critical Path Segments Method for Scheduling Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sherif%20M.%20Hafez">Sherif M. Hafez</a>, <a href="https://publications.waset.org/abstracts/search?q=Remon%20F.%20Aziz"> Remon F. Aziz</a>, <a href="https://publications.waset.org/abstracts/search?q=May%20S.%20A.%20Elalim"> May S. A. Elalim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Project managers today rely on scheduling tools based on the Critical Path Method (CPM) to determine the overall project duration and the activities’ float times which lead to greater efficiency in planning and control of projects. CPM was useful for scheduling construction projects, but researchers had highlighted a number of serious drawbacks that limit its use as a decision support tool and lacks the ability to clearly record and represent detailed information. This paper discusses the drawbacks of CPM as a scheduling technique and presents a modified critical path method (CPM) model which is called critical path segments (CPS). The CPS scheduling mechanism addresses the problems of CPM in three ways: decomposing the activity duration of separated but connected time segments; all relationships among activities are converted into finish–to–start relationship; and analysis and calculations are made with forward path. Sample cases are included to illustrate the shortages in CPM, CPS full analysis and calculations are explained in details, and how schedules can be handled better with the CPS technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=construction%20management" title="construction management">construction management</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20path%20method" title=" critical path method"> critical path method</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20path%20segments" title=" critical path segments"> critical path segments</a>, <a href="https://publications.waset.org/abstracts/search?q=forward%20pass" title=" forward pass"> forward pass</a>, <a href="https://publications.waset.org/abstracts/search?q=float" title=" float"> float</a>, <a href="https://publications.waset.org/abstracts/search?q=project%20control" title=" project control"> project control</a> </p> <a href="https://publications.waset.org/abstracts/17760/critical-path-segments-method-for-scheduling-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17760.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">353</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">5133</span> Decision Making for Industrial Engineers: From Phenomenon to Value</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Abbas">Ali Abbas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. In out current environment, the path from a phenomenon to value involves numerous people with expertise in various areas including domain knowledge of a field and the ability to make decisions within an operating environment that lead to value creation. We propose some skills that industrial engineering programs should focus on, and argue that an industrial engineer is a decision maker instead of a problem solver. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20analysis" title="decision analysis">decision analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=problem-solving" title=" problem-solving"> problem-solving</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20creation" title=" value creation"> value creation</a>, <a href="https://publications.waset.org/abstracts/search?q=industrial%20engineering" title=" industrial engineering"> industrial engineering</a> </p> <a href="https://publications.waset.org/abstracts/50988/decision-making-for-industrial-engineers-from-phenomenon-to-value" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50988.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">373</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">5132</span> Genetic Algorithm for In-Theatre Military Logistics Search-and-Delivery Path Planning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jean%20Berger">Jean Berger</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Barkaoui"> Mohamed Barkaoui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=search%20path%20planning" title="search path planning">search path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=false%20alarm" title=" false alarm"> false alarm</a>, <a href="https://publications.waset.org/abstracts/search?q=search-and-delivery" title=" search-and-delivery"> search-and-delivery</a>, <a href="https://publications.waset.org/abstracts/search?q=entropy" title=" entropy"> entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a> </p> <a href="https://publications.waset.org/abstracts/2263/genetic-algorithm-for-in-theatre-military-logistics-search-and-delivery-path-planning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2263.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">360</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">5131</span> A New Multi-Target, Multi-Agent Search and Rescue Path Planning Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jean%20Berger">Jean Berger</a>, <a href="https://publications.waset.org/abstracts/search?q=Nassirou%20Lo"> Nassirou Lo</a>, <a href="https://publications.waset.org/abstracts/search?q=Martin%20Noel"> Martin Noel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=search%20path%20planning" title="search path planning">search path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=search%20and%20rescue" title=" search and rescue"> search and rescue</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent" title=" multi-agent"> multi-agent</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed-integer%20linear%20programming" title=" mixed-integer linear programming"> mixed-integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/5918/a-new-multi-target-multi-agent-search-and-rescue-path-planning-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5918.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">372</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">5130</span> Top-K Shortest Distance as a Similarity Measure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andrey%20Lebedev">Andrey Lebedev</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilya%20Dmitrenok"> Ilya Dmitrenok</a>, <a href="https://publications.waset.org/abstracts/search?q=JooYoung%20Lee"> JooYoung Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Leonard%20Johard"> Leonard Johard</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=graph%20matching" title="graph matching">graph matching</a>, <a href="https://publications.waset.org/abstracts/search?q=link%20prediction" title=" link prediction"> link prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=shortest%20path" title=" shortest path"> shortest path</a>, <a href="https://publications.waset.org/abstracts/search?q=similarity" title=" similarity"> similarity</a> </p> <a href="https://publications.waset.org/abstracts/63488/top-k-shortest-distance-as-a-similarity-measure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63488.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">5129</span> A Review on Comparative Analysis of Path Planning and Collision Avoidance Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Divya%20Agarwal">Divya Agarwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Pushpendra%20S.%20Bharti"> Pushpendra S. Bharti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title="path planning">path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title=" obstacle avoidance"> obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=autonomous%20mobile%20robots" title=" autonomous mobile robots"> autonomous mobile robots</a>, <a href="https://publications.waset.org/abstracts/search?q=algorithms" title=" algorithms"> algorithms</a> </p> <a href="https://publications.waset.org/abstracts/93693/a-review-on-comparative-analysis-of-path-planning-and-collision-avoidance-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93693.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">232</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">5128</span> Optimised Path Recommendation for a Real Time Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Likewin%20Thomas">Likewin Thomas</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20V.%20Manoj%20Kumar"> M. V. Manoj Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Annappa"> B. Annappa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cross-organization%20process%20mining" title="cross-organization process mining">cross-organization process mining</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20behaviour" title=" process behaviour"> process behaviour</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20of%20execution" title=" path of execution"> path of execution</a>, <a href="https://publications.waset.org/abstracts/search?q=polynomial%20regression%20model" title=" polynomial regression model"> polynomial regression model</a> </p> <a href="https://publications.waset.org/abstracts/45002/optimised-path-recommendation-for-a-real-time-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45002.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">334</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">5127</span> An Application to Predict the Best Study Path for Information Technology Students in Learning Institutes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=L.%20S.%20Chathurika">L. S. Chathurika</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithm" title="algorithm">algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation" title=" evaluation"> evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=features" title=" features"> features</a>, <a href="https://publications.waset.org/abstracts/search?q=testing" title=" testing"> testing</a>, <a href="https://publications.waset.org/abstracts/search?q=training" title=" training"> training</a> </p> <a href="https://publications.waset.org/abstracts/132862/an-application-to-predict-the-best-study-path-for-information-technology-students-in-learning-institutes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132862.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">119</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">5126</span> Three-Dimensional Off-Line Path Planning for Unmanned Aerial Vehicle Using Modified Particle Swarm Optimization </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lana%20Dalawr%20Jalal">Lana Dalawr Jalal </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the problem of ofﬂine path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=obstacle%20avoidance" title="obstacle avoidance">obstacle avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=three-dimensional%20path%20planning%20unmanned%20aerial%20vehicles" title=" three-dimensional path planning unmanned aerial vehicles"> three-dimensional path planning unmanned aerial vehicles</a> </p> <a href="https://publications.waset.org/abstracts/26160/three-dimensional-off-line-path-planning-for-unmanned-aerial-vehicle-using-modified-particle-swarm-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26160.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">410</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">5125</span> Joint Path and Push Planning among Moveable Obstacles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Victor%20Emeli">Victor Emeli</a>, <a href="https://publications.waset.org/abstracts/search?q=Akansel%20Cosgun"> Akansel Cosgun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=motion%20planning" title="motion planning">motion planning</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title=" path planning"> path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=push%20planning" title=" push planning"> push planning</a>, <a href="https://publications.waset.org/abstracts/search?q=robot%20navigation" title=" robot navigation"> robot navigation</a> </p> <a href="https://publications.waset.org/abstracts/128403/joint-path-and-push-planning-among-moveable-obstacles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128403.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">165</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">5124</span> Path Planning for Orchard Robot Using Occupancy Grid Map in 2D Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Satyam%20Raikwar">Satyam Raikwar</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Herlitzius"> Thomas Herlitzius</a>, <a href="https://publications.waset.org/abstracts/search?q=Jens%20Fehrmann"> Jens Fehrmann</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, the autonomous navigation of orchard and field robots is an emerging technology of the mobile robotics in agriculture. One of the core aspects of autonomous navigation builds upon path planning, which is still a crucial issue. Generally, for simple representation, the path planning for a mobile robot is performed in a two-dimensional space, which creates a path between the start and goal point. This paper presents the automatic path planning approach for robots used in orchards and vineyards using occupancy grid maps with field consideration. The orchards and vineyards are usually structured environment and their topology is assumed to be constant over time; therefore, in this approach, an RGB image of a field is used as a working environment. These images undergone different image processing operations and then discretized into two-dimensional grid matrices. The individual grid or cell of these grid matrices represents the occupancy of the space, whether it is free or occupied. The grid matrix represents the robot workspace for motion and path planning. After the grid matrix is described, a probabilistic roadmap (PRM) path algorithm is used to create the obstacle-free path over these occupancy grids. The path created by this method was successfully verified in the test area. Furthermore, this approach is used in the navigation of the orchard robot. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=orchard%20robots" title="orchard robots">orchard robots</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic%20path%20planning" title=" automatic path planning"> automatic path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=occupancy%20grid" title=" occupancy grid"> occupancy grid</a>, <a href="https://publications.waset.org/abstracts/search?q=probabilistic%20roadmap" title=" probabilistic roadmap"> probabilistic roadmap</a> </p> <a href="https://publications.waset.org/abstracts/110023/path-planning-for-orchard-robot-using-occupancy-grid-map-in-2d-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110023.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">156</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">5123</span> A Straightforward Approach for Determining the Weights of Decision Makers Based on Angle Cosine and Projection Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qiang%20Yang">Qiang Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ping-An%20Du"> Ping-An Du</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Group decision making with multiple attribute has attracted intensive concern in the decision analysis area. This paper assumes that the contributions of all the decision makers (DMs) are not equal to the decision process based on different knowledge and experience in group setting. The aim of this paper is to develop a novel approach to determine weights of DMs in the group decision making problems. In this paper, the weights of DMs are determined in the group decision environment via angle cosine and projection method. First of all, the average decision of all individual decisions is defined as the ideal decision. After that, we define the weight of each decision maker (DM) by aggregating the angle cosine and projection between individual decision and ideal decision with associated direction indicator μ. By using the weights of DMs, all individual decisions are aggregated into a collective decision. Further, the preference order of alternatives is ranked in accordance with the overall row value of collective decision. Finally, an example in a chemical company is provided to illustrate the developed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=angel%20cosine" title="angel cosine">angel cosine</a>, <a href="https://publications.waset.org/abstracts/search?q=ideal%20decision" title=" ideal decision"> ideal decision</a>, <a href="https://publications.waset.org/abstracts/search?q=projection%20method" title=" projection method"> projection method</a>, <a href="https://publications.waset.org/abstracts/search?q=weights%20of%20decision%20makers" title=" weights of decision makers"> weights of decision makers</a> </p> <a href="https://publications.waset.org/abstracts/35292/a-straightforward-approach-for-determining-the-weights-of-decision-makers-based-on-angle-cosine-and-projection-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35292.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">378</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">5122</span> Independence and Path Independence on Cayley Digraphs of Left Groups and Right Groups</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nuttawoot%20Nupo">Nuttawoot Nupo</a>, <a href="https://publications.waset.org/abstracts/search?q=Sayan%20Panma"> Sayan Panma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A semigroup S is said to be a left (right) zero semigroup if S satisfies the equation xy=x (xy=y) for all x,y in S. In addition, the semigroup S is called a left (right) group if S is isomorphic to the direct product of a group and a left (right) zero semigroup. The Cayley digraph Cay(S,A) of a semigroup S with a connection set A is defined to be a digraph with the vertex set S and the arc set E(Cay(S,A))={(x,xa) | x∈S, a∈A} where A is any subset of S. All sets in this research are assumed to be finite. Let D be a digraph together with a vertex set V and an arc set E. Let u and v be two different vertices in V and I a nonempty subset of V. The vertices u and v are said to be independent if (u,v)∉E and (v,u)∉E. The set I is called an independent set of D if any two different vertices in I are independent. The independence number of D is the maximum cardinality of an independent set of D. Moreover, the vertices u and v are said to be path independent if there is no dipath from u to v and there is no dipath from v to u. The set I is called a path independent set of D if any two different vertices in I are path independent. The path independence number of D is the maximum cardinality of a path independent set of D. In this research, we describe a lower bound and an upper bound of the independence number of Cayley digraphs of left groups and right groups. Some examples corresponding to those bounds are illustrated here. Furthermore, the exact value of the path independence number of Cayley digraphs of left groups and right groups are also presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cayley%20digraphs" title="Cayley digraphs">Cayley digraphs</a>, <a href="https://publications.waset.org/abstracts/search?q=independence%20number" title=" independence number"> independence number</a>, <a href="https://publications.waset.org/abstracts/search?q=left%20groups" title=" left groups"> left groups</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20independence%20number" title=" path independence number"> path independence number</a>, <a href="https://publications.waset.org/abstracts/search?q=right%20groups" title=" right groups"> right groups</a> </p> <a href="https://publications.waset.org/abstracts/59306/independence-and-path-independence-on-cayley-digraphs-of-left-groups-and-right-groups" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59306.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">233</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">5121</span> Optimizing Network Latency with Fast Path Assignment for Incoming Flows</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qing%20Lyu">Qing Lyu</a>, <a href="https://publications.waset.org/abstracts/search?q=Hang%20Zhu"> Hang Zhu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flow%20path" title="flow path">flow path</a>, <a href="https://publications.waset.org/abstracts/search?q=latency" title=" latency"> latency</a>, <a href="https://publications.waset.org/abstracts/search?q=middlebox" title=" middlebox"> middlebox</a>, <a href="https://publications.waset.org/abstracts/search?q=network" title=" network"> network</a> </p> <a href="https://publications.waset.org/abstracts/103177/optimizing-network-latency-with-fast-path-assignment-for-incoming-flows" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103177.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">207</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">5120</span> Complex Decision Rules in the Form of Decision Trees</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Avinash%20S.%20Jagtap">Avinash S. Jagtap</a>, <a href="https://publications.waset.org/abstracts/search?q=Sharad%20D.%20Gore"> Sharad D. Gore</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajendra%20G.%20Gurao"> Rajendra G. Gurao </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Decision rules become more and more complex as the number of conditions increase. As a consequence, the complexity of the decision rule also influences the time complexity of computer implementation of such a rule. Consider, for example, a decision that depends on four conditions A, B, C and D. For simplicity, suppose each of these four conditions is binary. Even then the decision rule will consist of 16 lines, where each line will be of the form: If A and B and C and D, then action 1. If A and B and C but not D, then action 2 and so on. While executing this decision rule, each of the four conditions will be checked every time until all the four conditions in a line are satisfied. The minimum number of logical comparisons is 4 whereas the maximum number is 64. This paper proposes to present a complex decision rule in the form of a decision tree. A decision tree divides the cases into branches every time a condition is checked. In the form of a decision tree, every branching eliminates half of the cases that do not satisfy the related conditions. As a result, every branch of the decision tree involves only four logical comparisons and hence is significantly simpler than the corresponding complex decision rule. The conclusion of this paper is that every complex decision rule can be represented as a decision tree and the decision tree is mathematically equivalent but computationally much simpler than the original complex decision rule <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=strategic" title="strategic">strategic</a>, <a href="https://publications.waset.org/abstracts/search?q=tactical" title=" tactical"> tactical</a>, <a href="https://publications.waset.org/abstracts/search?q=operational" title=" operational"> operational</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive" title=" adaptive"> adaptive</a>, <a href="https://publications.waset.org/abstracts/search?q=innovative" title=" innovative"> innovative</a> </p> <a href="https://publications.waset.org/abstracts/77189/complex-decision-rules-in-the-form-of-decision-trees" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77189.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">288</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">5119</span> Copula-Based Estimation of Direct and Indirect Effects in Path Analysis Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alam%20Ali">Alam Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Ashok%20Kumar%20Pathak"> Ashok Kumar Pathak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Path analysis is a statistical technique used to evaluate the direct and indirect effects of variables in path models. One or more structural regression equations are used to estimate a series of parameters in path models to find the better fit of data. However, sometimes the assumptions of classical regression models, such as ordinary least squares (OLS), are violated by the nature of the data, resulting in insignificant direct and indirect effects of exogenous variables. This article aims to explore the effectiveness of a copula-based regression approach as an alternative to classical regression, specifically when variables are linked through an elliptical copula. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=path%20analysis" title="path analysis">path analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=copula-based%20regression%20models" title=" copula-based regression models"> copula-based regression models</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20and%20indirect%20effects" title=" direct and indirect effects"> direct and indirect effects</a>, <a href="https://publications.waset.org/abstracts/search?q=k-fold%20cross%20validation%20technique" title=" k-fold cross validation technique"> k-fold cross validation technique</a> </p> <a href="https://publications.waset.org/abstracts/186900/copula-based-estimation-of-direct-and-indirect-effects-in-path-analysis-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186900.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">43</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">5118</span> Eliminating Cutter-Path Deviation For Five-Axis Nc Machining</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alan%20C.%20Lin">Alan C. Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Tsong%20Der%20Lin"> Tsong Der Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study proposes a deviation control method to add interpolation points to numerical control (NC) codes of five-axis machining in order to achieve the required machining accuracy. Specific research issues include: (1) converting machining data between the CL (cutter location) domain and the NC domain, (2) calculating the deviation between the deviated path and the linear path, (3) finding interpolation points, and (4) determining tool orientations for the interpolation points. System implementation with practical examples will also be included to highlight the applicability of the proposed methodology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CAD%2FCAM" title="CAD/CAM">CAD/CAM</a>, <a href="https://publications.waset.org/abstracts/search?q=cutter%20path" title=" cutter path"> cutter path</a>, <a href="https://publications.waset.org/abstracts/search?q=five-axis%20machining" title=" five-axis machining"> five-axis machining</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20control" title=" numerical control"> numerical control</a> </p> <a href="https://publications.waset.org/abstracts/30394/eliminating-cutter-path-deviation-for-five-axis-nc-machining" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30394.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">424</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">5117</span> Framework for the Modeling of the Supply Chain Collaborative Planning Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20P%C3%A9rez">D. Pérez</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20M.%20E.%20Alemany"> M. M. E. Alemany</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work a Framework to model the Supply Chain (SC) Collaborative Planning (CP) Process is proposed, and particularly its Decisional view. The main Framework contributions with regards to previous related works are the following, 1) the consideration of not only the Decision view, the most important one due to the Process type, but other additional three views which are the Physical, Organisation and Information ones, closely related and complementing the Decision View, 2) the joint consideration of two interdependence types, the Temporal (among Decision Centres belonging to different Decision Levels) and Spatial (among Decision Centres belonging to the same Decision Level) to support the distributed Decision-Making process in SC where several decision Centres interact among them in a collaborative manner. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=collaborative%20planning" title="collaborative planning">collaborative planning</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20view" title=" decision view"> decision view</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20decision-making" title=" distributed decision-making"> distributed decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=framework" title=" framework"> framework</a> </p> <a href="https://publications.waset.org/abstracts/32456/framework-for-the-modeling-of-the-supply-chain-collaborative-planning-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32456.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">468</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">5116</span> Nonparametric Path Analysis with Truncated Spline Approach in Modeling Rural Poverty in Indonesia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Usriatur%20Rohma">Usriatur Rohma</a>, <a href="https://publications.waset.org/abstracts/search?q=Adji%20Achmad%20Rinaldo%20Fernandes"> Adji Achmad Rinaldo Fernandes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best nonparametric truncated spline path function between linear and quadratic polynomial degrees with 1, 2, and 3-knot points and to determine the significance of estimating the best nonparametric truncated spline path function in the model of the effect of population migration and agricultural economic growth on rural poverty through the variable unemployment rate using the t-test statistic at the jackknife resampling stage. The data used in this study are secondary data obtained from statistical publications. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3-knot points. In addition, the significance of the best-truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonparametric%20path%20analysis" title="nonparametric path analysis">nonparametric path analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=truncated%20spline" title=" truncated spline"> truncated spline</a>, <a href="https://publications.waset.org/abstracts/search?q=linear" title=" linear"> linear</a>, <a href="https://publications.waset.org/abstracts/search?q=quadratic" title=" quadratic"> quadratic</a>, <a href="https://publications.waset.org/abstracts/search?q=rural%20poverty" title=" rural poverty"> rural poverty</a>, <a href="https://publications.waset.org/abstracts/search?q=jackknife%20resampling" title=" jackknife resampling"> jackknife resampling</a> </p> <a href="https://publications.waset.org/abstracts/186676/nonparametric-path-analysis-with-truncated-spline-approach-in-modeling-rural-poverty-in-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186676.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">47</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">5115</span> Analysis of Path Nonparametric Truncated Spline Maximum Cubic Order in Farmers Loyalty Modeling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adji%20Achmad%20Rinaldo%20Fernandes">Adji Achmad Rinaldo Fernandes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Path analysis tests the relationship between variables through cause and effect. Before conducting further tests on path analysis, the assumption of linearity must be met. If the shape of the relationship is not linear and the shape of the curve is unknown, then use a nonparametric approach, one of which is a truncated spline. The purpose of this study is to estimate the function and get the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in modeling farmer loyalty through the jackknife resampling method. This study uses secondary data through questionnaires to farmers in Sumbawa Regency who use SP-36 subsidized fertilizer products as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonparametric%20path%20analysis" title="nonparametric path analysis">nonparametric path analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=farmer%20loyalty" title=" farmer loyalty"> farmer loyalty</a>, <a href="https://publications.waset.org/abstracts/search?q=jackknife%20resampling" title=" jackknife resampling"> jackknife resampling</a>, <a href="https://publications.waset.org/abstracts/search?q=truncated%20spline" title=" truncated spline"> truncated spline</a> </p> <a href="https://publications.waset.org/abstracts/186760/analysis-of-path-nonparametric-truncated-spline-maximum-cubic-order-in-farmers-loyalty-modeling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186760.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">47</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">5114</span> Generalized Central Paths for Convex Programming</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li-Zhi%20Liao">Li-Zhi Liao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The central path has played the key role in the interior point method. However, the convergence of the central path may not be true even in some convex programming problems with linear constraints. In this paper, the generalized central paths are introduced for convex programming. One advantage of the generalized central paths is that the paths will always converge to some optimal solutions of the convex programming problem for any initial interior point. Some additional theoretical properties for the generalized central paths will be also reported. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=central%20path" title="central path">central path</a>, <a href="https://publications.waset.org/abstracts/search?q=convex%20programming" title=" convex programming"> convex programming</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20central%20path" title=" generalized central path"> generalized central path</a>, <a href="https://publications.waset.org/abstracts/search?q=interior%20point%20method" title=" interior point method"> interior point method</a> </p> <a href="https://publications.waset.org/abstracts/58039/generalized-central-paths-for-convex-programming" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58039.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">327</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">5113</span> Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carlos%20Gordon">Carlos Gordon</a>, <a href="https://publications.waset.org/abstracts/search?q=Patricio%20Encalada"> Patricio Encalada</a>, <a href="https://publications.waset.org/abstracts/search?q=Henry%20Lema"> Henry Lema</a>, <a href="https://publications.waset.org/abstracts/search?q=Diego%20Leon"> Diego Leon</a>, <a href="https://publications.waset.org/abstracts/search?q=Dennis%20Chicaiza"> Dennis Chicaiza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autonomous%20navigation" title="autonomous navigation">autonomous navigation</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title=" path planning"> path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=robotic%20operative%20system" title=" robotic operative system"> robotic operative system</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20source%20computer%20vision%20library" title=" open source computer vision library"> open source computer vision library</a> </p> <a href="https://publications.waset.org/abstracts/101726/autonomous-kuka-youbot-navigation-based-on-machine-learning-and-path-planning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101726.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">177</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">5112</span> Construction Project Planning Using Fuzzy Critical Path Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Omar%20M.%20Aldenali">Omar M. Aldenali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Planning is one of the most important phases of the management science and network planning, which represents the project activities relationship. Critical path is one of the project management techniques used to plan and control the execution of a project activities. The objective of this paper is to implement a fuzzy logic approach to arrange network planning on construction projects. This method is used to finding out critical path in the fuzzy construction project network. The trapezoidal fuzzy numbers are used to represent the activity construction project times. A numerical example that represents a house construction project is introduced. The critical path method is implemented on the fuzzy construction network activities, and the results showed that this method significantly affects the completion time of the construction projects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=construction%20project" title="construction project">construction project</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20path" title=" critical path"> critical path</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20network%20project" title=" fuzzy network project"> fuzzy network project</a>, <a href="https://publications.waset.org/abstracts/search?q=planning" title=" planning"> planning</a> </p> <a href="https://publications.waset.org/abstracts/111693/construction-project-planning-using-fuzzy-critical-path-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/111693.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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5111</span> Graphical Theoretical Construction of Discrete time Share Price Paths from Matroid</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Min%20Wang">Min Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergey%20Utev"> Sergey Utev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The lessons from the 2007-09 global financial crisis have driven scientific research, which considers the design of new methodologies and financial models in the global market. The quantum mechanics approach was introduced in the unpredictable stock market modeling. One famous quantum tool is Feynman path integral method, which was used to model insurance risk by Tamturk and Utev and adapted to formalize the path-dependent option pricing by Hao and Utev. The research is based on the path-dependent calculation method, which is motivated by the Feynman path integral method. The path calculation can be studied in two ways, one way is to label, and the other is computational. Labeling is a part of the representation of objects, and generating functions can provide many different ways of representing share price paths. In this paper, the recent works on graphical theoretical construction of individual share price path via matroid is presented. Firstly, a study is done on the knowledge of matroid, relationship between lattice path matroid and Tutte polynomials and ways to connect points in the lattice path matroid and Tutte polynomials is suggested. Secondly, It is found that a general binary tree can be validly constructed from a connected lattice path matroid rather than general lattice path matroid. Lastly, it is suggested that there is a way to represent share price paths via a general binary tree, and an algorithm is developed to construct share price paths from general binary trees. A relationship is also provided between lattice integer points and Tutte polynomials of a transversal matroid. Use this way of connection together with the algorithm, a share price path can be constructed from a given connected lattice path matroid. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=combinatorial%20construction" title="combinatorial construction">combinatorial construction</a>, <a href="https://publications.waset.org/abstracts/search?q=graphical%20representation" title=" graphical representation"> graphical representation</a>, <a href="https://publications.waset.org/abstracts/search?q=matroid" title=" matroid"> matroid</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20calculation" title=" path calculation"> path calculation</a>, <a href="https://publications.waset.org/abstracts/search?q=share%20price" title=" share price"> share price</a>, <a href="https://publications.waset.org/abstracts/search?q=Tutte%20polynomial" title=" Tutte polynomial "> Tutte polynomial </a> </p> <a href="https://publications.waset.org/abstracts/118431/graphical-theoretical-construction-of-discrete-time-share-price-paths-from-matroid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118431.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">138</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">5110</span> Retraction Free Motion Approach and Its Application in Automated Robotic Edge Finishing and Inspection Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Nemer">M. Nemer</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20I.%20Konukseven"> E. I. Konukseven</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a motion generation algorithm for a six Degrees of Freedom (DoF) robotic hand in a static environment is presented. The purpose of developing this method is to be used in the path generation of the end-effector for edge finishing and inspection processes by utilizing the CAD model of the considered workpiece. Nonetheless, the proposed algorithm may be extended to be applicable for other similar manufacturing processes. A software package programmed in the application programming interface (API) of SolidWorks generates tool path data for the robot. The proposed method significantly simplifies the given problem, resulting in a reduction in the CPU time needed to generate the path, and offers an efficient overall solution. The ABB IRB2000 robot is chosen for executing the generated tool path. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CAD-based%20tools" title="CAD-based tools">CAD-based tools</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20deburring" title=" edge deburring"> edge deburring</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20scanning" title=" edge scanning"> edge scanning</a>, <a href="https://publications.waset.org/abstracts/search?q=offline%20programming" title=" offline programming"> offline programming</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20generation" title=" path generation"> path generation</a> </p> <a href="https://publications.waset.org/abstracts/57270/retraction-free-motion-approach-and-its-application-in-automated-robotic-edge-finishing-and-inspection-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57270.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">5109</span> Path-Spin to Spin-Spin Hybrid Quantum Entanglement: A Conversion Protocol</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Indranil%20Bayal">Indranil Bayal</a>, <a href="https://publications.waset.org/abstracts/search?q=Pradipta%20Panchadhyayee"> Pradipta Panchadhyayee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Path-spin hybrid entanglement generated and confined in a single spin-1/2 particle is converted to spin-spin hybrid interparticle entanglement, which finds its important applications in quantum information processing. This protocol uses beam splitter, spin flipper, spin measurement, classical channel, unitary transformations, etc., and requires no collective operation on the pair of particles whose spin variables share complete entanglement after the accomplishment of the protocol. The specialty of the protocol lies in the fact that the path-spin entanglement is transferred between spin degrees of freedom of two separate particles initially possessed by a single party. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=entanglement" title="entanglement">entanglement</a>, <a href="https://publications.waset.org/abstracts/search?q=path-spin%20entanglement" title=" path-spin entanglement"> path-spin entanglement</a>, <a href="https://publications.waset.org/abstracts/search?q=spin-spin%20entanglement" title=" spin-spin entanglement"> spin-spin entanglement</a>, <a href="https://publications.waset.org/abstracts/search?q=CNOT%20operation" title=" CNOT operation"> CNOT operation</a> </p> <a href="https://publications.waset.org/abstracts/142538/path-spin-to-spin-spin-hybrid-quantum-entanglement-a-conversion-protocol" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142538.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">198</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">5108</span> The Effect of Critical Activity on Critical Path and Project Duration in Precedence Diagram Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20Nisar">J. Nisar</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Halim"> S. Halim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activity in Precedence Diagram Method (PDM) provides a more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in the PDM network will have an anomalous effect on the critical path and the project completion date. In this study, we classified the critical activities in two groups i.e., 1. activity on single critical path and 2. activity on multi-critical paths, and six classes i.e., normal, reverse, neutral, perverse, decrease-reverse and increase-normal, based on their effects on project duration in PDM. Furthermore, we determined the maximum float of time by which the duration each type of critical activities can be changed without effecting the project duration. This study would help the project manager to clearly understand the behavior of each critical activity on critical path, and he/she would be able to change the project duration by shortening or lengthening activities based on project budget and project deadline. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=construction%20management" title="construction management">construction management</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20path%20method" title=" critical path method"> critical path method</a>, <a href="https://publications.waset.org/abstracts/search?q=project%20scheduling%20network" title=" project scheduling network"> project scheduling network</a>, <a href="https://publications.waset.org/abstracts/search?q=precedence%20diagram%20method" title=" precedence diagram method"> precedence diagram method</a> </p> <a href="https://publications.waset.org/abstracts/97001/the-effect-of-critical-activity-on-critical-path-and-project-duration-in-precedence-diagram-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97001.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">222</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">5107</span> Integer Programming Model for the Network Design Problem with Facility Dependent Shortest Path Routing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Taehan%20Lee">Taehan Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We consider a network design problem which has shortest routing restriction based on the values determined by the installed facilities on each arc. In conventional multicommodity network design problem, a commodity can be routed through any possible path when the capacity is available. But, we consider a problem in which the commodity between two nodes must be routed on a path which has shortest metric value and the link metric value is determined by the installed facilities on the link. By this routing restriction, the problem has a distinct characteristic. We present an integer programming formulation containing the primal-dual optimality conditions to the shortest path routing. We give some computational results for the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=integer%20programming" title="integer programming">integer programming</a>, <a href="https://publications.waset.org/abstracts/search?q=multicommodity%20network%20design" title=" multicommodity network design"> multicommodity network design</a>, <a href="https://publications.waset.org/abstracts/search?q=routing" title=" routing"> routing</a>, <a href="https://publications.waset.org/abstracts/search?q=shortest%20path" title=" shortest path"> shortest path</a> </p> <a href="https://publications.waset.org/abstracts/51447/integer-programming-model-for-the-network-design-problem-with-facility-dependent-shortest-path-routing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51447.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right 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