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classification</title> <meta name="description" content="Search results for: species classification"> <meta name="keywords" content="species classification"> <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 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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="species classification"> <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> 5258</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: species classification</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5198</span> Diversity and Distribution of Benthic Invertebrates in the West Port, Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyedeh%20Belin%20Tavakoly%20Sany">Seyedeh Belin Tavakoly Sany</a>, <a href="https://publications.waset.org/abstracts/search?q=Rosli%20Hashim"> Rosli Hashim</a>, <a href="https://publications.waset.org/abstracts/search?q=Majid%20Rezayi"> Majid Rezayi</a>, <a href="https://publications.waset.org/abstracts/search?q=Aishah%20Salleh"> Aishah Salleh</a>, <a href="https://publications.waset.org/abstracts/search?q=Omid%20Safari"> Omid Safari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this paper is to describe the main characteristics of macroinvertebrate species in response to environmental forcing factors. Overall, 23 species of Mollusca, 4 species of Arthropods, 3 species of Echinodermata and 3 species of Annelida were identified at the 9 sampling stations during four sampling periods. Individual species of Mollusca constituted 36.4% of the total abundance, followed by Arthropods (27.01%), Annelida (34.3%) and Echinodermata (2.4%). The results of Kruskal-Wallis test indicated that a significant difference (p <0.05) in the abundance, richness and diversity of the macro-benthic community in different stations. The correlation analysis revealed that anthropogenic pollution and natural variability caused by these variations in spatial scales. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=benthic%20invertebrates" title="benthic invertebrates">benthic invertebrates</a>, <a href="https://publications.waset.org/abstracts/search?q=diversity" title=" diversity"> diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=abundance" title=" abundance"> abundance</a>, <a href="https://publications.waset.org/abstracts/search?q=West%20Port" title=" West Port"> West Port</a> </p> <a href="https://publications.waset.org/abstracts/6112/diversity-and-distribution-of-benthic-invertebrates-in-the-west-port-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6112.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">442</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">5197</span> Performance Analysis of Artificial Neural Network Based Land Cover Classification </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Najam%20Aziz">Najam Aziz</a>, <a href="https://publications.waset.org/abstracts/search?q=Nasru%20Minallah"> Nasru Minallah</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Junaid"> Ahmad Junaid</a>, <a href="https://publications.waset.org/abstracts/search?q=Kashaf%20Gul"> Kashaf Gul </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landcover%20classification" title="landcover classification">landcover classification</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title=" artificial neural network"> artificial neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=SPOT%205" title=" SPOT 5"> SPOT 5</a> </p> <a href="https://publications.waset.org/abstracts/61063/performance-analysis-of-artificial-neural-network-based-land-cover-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61063.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">546</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">5196</span> Optimizing Perennial Plants Image Classification by Fine-Tuning Deep Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khairani%20Binti%20Supyan">Khairani Binti Supyan</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatimah%20Khalid"> Fatimah Khalid</a>, <a href="https://publications.waset.org/abstracts/search?q=Mas%20Rina%20Mustaffa"> Mas Rina Mustaffa</a>, <a href="https://publications.waset.org/abstracts/search?q=Azreen%20Bin%20Azman"> Azreen Bin Azman</a>, <a href="https://publications.waset.org/abstracts/search?q=Amirul%20Azuani%20Romle"> Amirul Azuani Romle</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=perennial%20plants" title="perennial plants">perennial plants</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20classification" title=" image classification"> image classification</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20networks" title=" deep neural networks"> deep neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=fine-tuning" title=" fine-tuning"> fine-tuning</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer%20learning" title=" transfer learning"> transfer learning</a>, <a href="https://publications.waset.org/abstracts/search?q=VGG16" title=" VGG16"> VGG16</a>, <a href="https://publications.waset.org/abstracts/search?q=ResNet50" title=" ResNet50"> ResNet50</a>, <a href="https://publications.waset.org/abstracts/search?q=InceptionV3" title=" InceptionV3"> InceptionV3</a> </p> <a href="https://publications.waset.org/abstracts/182850/optimizing-perennial-plants-image-classification-by-fine-tuning-deep-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/182850.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">66</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">5195</span> Scene Classification Using Hierarchy Neural Network, Directed Acyclic Graph Structure, and Label Relations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Po-Jen%20Chen">Po-Jen Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Jian-Jiun%20Ding"> Jian-Jiun Ding</a>, <a href="https://publications.waset.org/abstracts/search?q=Hung-Wei%20Hsu"> Hung-Wei Hsu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chien-Yao%20Wang"> Chien-Yao Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jia-Ching%20Wang"> Jia-Ching Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20network" title="convolutional neural network">convolutional neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=label%20relation" title=" label relation"> label relation</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchy%20neural%20network" title=" hierarchy neural network"> hierarchy neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=scene%20classification" title=" scene classification"> scene classification</a> </p> <a href="https://publications.waset.org/abstracts/66516/scene-classification-using-hierarchy-neural-network-directed-acyclic-graph-structure-and-label-relations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66516.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">459</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">5194</span> Classification Using Worldview-2 Imagery of Giant Panda Habitat in Wolong, Sichuan Province, China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yunwei%20Tang">Yunwei Tang</a>, <a href="https://publications.waset.org/abstracts/search?q=Linhai%20Jing"> Linhai Jing</a>, <a href="https://publications.waset.org/abstracts/search?q=Hui%20Li"> Hui Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Qingjie%20Liu"> Qingjie Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiuxia%20Li"> Xiuxia Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Qi%20Yan"> Qi Yan</a>, <a href="https://publications.waset.org/abstracts/search?q=Haifeng%20Ding"> Haifeng Ding</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bamboo%20mapping" title="bamboo mapping">bamboo mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=geostatistics" title=" geostatistics"> geostatistics</a>, <a href="https://publications.waset.org/abstracts/search?q=k-NN" title=" k-NN"> k-NN</a>, <a href="https://publications.waset.org/abstracts/search?q=worldview-2" title=" worldview-2"> worldview-2</a> </p> <a href="https://publications.waset.org/abstracts/30407/classification-using-worldview-2-imagery-of-giant-panda-habitat-in-wolong-sichuan-province-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30407.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">313</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">5193</span> Effective Parameter Selection for Audio-Based Music Mood Classification for Christian Kokborok Song: A Regression-Based Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanchali%20Das">Sanchali Das</a>, <a href="https://publications.waset.org/abstracts/search?q=Swapan%20Debbarma"> Swapan Debbarma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christian%20Kokborok%20song" title="Christian Kokborok song">Christian Kokborok song</a>, <a href="https://publications.waset.org/abstracts/search?q=mood%20classification" title=" mood classification"> mood classification</a>, <a href="https://publications.waset.org/abstracts/search?q=music%20information%20retrieval" title=" music information retrieval"> music information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a> </p> <a href="https://publications.waset.org/abstracts/97113/effective-parameter-selection-for-audio-based-music-mood-classification-for-christian-kokborok-song-a-regression-based-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97113.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">5192</span> Species Diversity and Relative Abundance of Migratory Waterbirds in Abijata Lake, Central Rift Valley, Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Teklebrhan%20Kidane">Teklebrhan Kidane </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study is to investigate the species diversity and relative abundance of migratory waterbirds in Abijata Lake, an Important Bird Area and potential Ramsar site located in the Central Rift Valley of Ethiopia. The study was carried out, using line transect method along the shoreline and open area of the Lake. The data was analyzed with different diversity indices; t-Test and descriptive statistics. Thirty-two migratory waterbird species grouped into twelve families consisting of globally threatened birds were identified and recorded. Family Scolopacidae (12 species) had the highest number of species. The lowest number of species was observed under the families Ciconidae, Accipitridae, Laridae and Falconidae with one species each. The recorded bird species comprised 19 Palearctic, 5 Intra-African, 2 local migrants as well as 6 resident Palearctic migratory waterbird species. The dry season had higher species diversity (H'=1.01) compared to the wet season (H'=0.76). The highest and lowest diversity of migratory waterbirds were recorded during January (H'= 1.28) and June (H'= 0.52), respectively. However, the highest evenness (E) of bird species was recorded during wet season (E=0.21) and lower during the dry season (E=0.09). The computed seasonal effect reveals that there is significant effect of seasons on species diversity (t=2.80, P < 0.05), but the effect of seasons on individuals of migratory bird species was not significant (t=1.42, P > 0.05). Even though Lake Abijata is the sanctuary of several migratory waterbirds, anthropogenic activities are rigorously threatening their survival. Therefore, it needs an urgent conservation concern. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=migration" title="migration">migration</a>, <a href="https://publications.waset.org/abstracts/search?q=important%20bird%20area" title=" important bird area"> important bird area</a>, <a href="https://publications.waset.org/abstracts/search?q=species%20diversity" title=" species diversity"> species diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=wetland%20birds" title=" wetland birds "> wetland birds </a> </p> <a href="https://publications.waset.org/abstracts/96761/species-diversity-and-relative-abundance-of-migratory-waterbirds-in-abijata-lake-central-rift-valley-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96761.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">5191</span> The Efficiency of Cytochrome Oxidase Subunit 1 Gene (cox1) in Reconstruction of Phylogenetic Relations among Some Crustacean Species</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yasser%20M.%20Saad">Yasser M. Saad</a>, <a href="https://publications.waset.org/abstracts/search?q=Heba%20El-Sebaie%20Abd%20El-Sadek"> Heba El-Sebaie Abd El-Sadek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Some <em>Metapenaeus monoceros</em><em> cox1</em> gene fragments were isolated, purified, sequenced, and comparatively analyzed with some other Crustacean <em>Cox1</em> gene sequences (obtained from National Center for Biotechnology Information). This work was designed for testing the efficiency of this system in reconstruction of phylogenetic relations among some Crustacean species belonging to four genera (Metapenaeus, Artemia, Daphnia and Calanus)<em>.</em> The single nucleotide polymorphism and haplotype diversity were calculated for all estimated mt-DNA fragments. The genetic distance values were 0.292, 0.015, 0.151, and 0.09 within <em>Metapenaeus </em>species<em>, Calanus</em> species<em>, Artemia</em> species, and<em> Daphnia</em> species, respectively<em>. </em>The reconstructed phylogenetic tree is clustered into some unique clades. Cytochrome oxidase subunit 1 gene (<em>cox1</em>) was a powerful system in reconstruction of phylogenetic relations among evaluated crustacean species. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=crustaceans" title="crustaceans">crustaceans</a>, <a href="https://publications.waset.org/abstracts/search?q=genetics" title=" genetics"> genetics</a>, <a href="https://publications.waset.org/abstracts/search?q=Cox1" title=" Cox1"> Cox1</a>, <a href="https://publications.waset.org/abstracts/search?q=phylogeny" title=" phylogeny"> phylogeny</a> </p> <a href="https://publications.waset.org/abstracts/73884/the-efficiency-of-cytochrome-oxidase-subunit-1-gene-cox1-in-reconstruction-of-phylogenetic-relations-among-some-crustacean-species" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73884.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">362</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">5190</span> Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thanh%20Nguyen">Thanh Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrei%20Doncescu"> Andrei Doncescu</a>, <a href="https://publications.waset.org/abstracts/search?q=Pierre%20Siegel"> Pierre Siegel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=spam%20filtering" title=" spam filtering"> spam filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=naive%20bayes" title=" naive bayes"> naive bayes</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree" title=" decision tree"> decision tree</a> </p> <a href="https://publications.waset.org/abstracts/50531/performance-comparison-of-adtree-and-naive-bayes-algorithms-for-spam-filtering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50531.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">5189</span> An Investigation into Fraud Detection in Financial Reporting Using Sugeno Fuzzy Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Sarchami">Mohammad Sarchami</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohsen%20Zeinalkhani"> Mohsen Zeinalkhani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fraud" title="fraud">fraud</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20reporting" title=" financial reporting"> financial reporting</a>, <a href="https://publications.waset.org/abstracts/search?q=Sugeno%20fuzzy%20classification" title=" Sugeno fuzzy classification"> Sugeno fuzzy classification</a>, <a href="https://publications.waset.org/abstracts/search?q=firm" title=" firm"> firm</a> </p> <a href="https://publications.waset.org/abstracts/82712/an-investigation-into-fraud-detection-in-financial-reporting-using-sugeno-fuzzy-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82712.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">248</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">5188</span> Effect of Personality Traits on Classification of Political Orientation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vesile%20Evrim">Vesile Evrim</a>, <a href="https://publications.waset.org/abstracts/search?q=Aliyu%20Awwal"> Aliyu Awwal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Today as in the other domains, there are an enormous number of political transcripts available in the Web which is waiting to be mined and used for various purposes such as statistics and recommendations. Therefore, automatically determining the political orientation on these transcripts becomes crucial. The methodologies used by machine learning algorithms to do the automatic classification are based on different features such as Linguistic. Considering the ideology differences between Liberals and Conservatives, in this paper, the effect of Personality Traits on political orientation classification is studied. This is done by considering the correlation between LIWC features and the BIG Five Personality Traits. Several experiments are conducted on Convote U.S. Congressional-Speech dataset with seven benchmark classification algorithms. The different methodologies are applied on selecting different feature sets that constituted by 8 to 64 varying number of features. While Neuroticism is obtained to be the most differentiating personality trait on classification of political polarity, when its top 10 representative features are combined with several classification algorithms, it outperformed the results presented in previous research. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=politics" title="politics">politics</a>, <a href="https://publications.waset.org/abstracts/search?q=personality%20traits" title=" personality traits"> personality traits</a>, <a href="https://publications.waset.org/abstracts/search?q=LIWC" title=" LIWC"> LIWC</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/27676/effect-of-personality-traits-on-classification-of-political-orientation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27676.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">495</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">5187</span> Rapid Inventory of Terrestrial Ferns and Lycopods in Center for Ecological Development and Recreation (Cedar), Impalutao, Impasug-Ong Bukidnon, Philippines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diobein%20Flores">Diobein Flores</a>, <a href="https://publications.waset.org/abstracts/search?q=Venus%20Buagas"> Venus Buagas</a>, <a href="https://publications.waset.org/abstracts/search?q=Virgie%20Darunday"> Virgie Darunday</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study inventoried the species composition of terrestrial ferns and lycopods in Center for Ecological Development and Recreation (CEDAR) Impalutao, Impasug-ong, Bukidnon. Specifically, it aimed to determine and describe the species composition, and diagnostic characters of the ferns and lycopods in the study site. Transect walk method was employed in the inventory of the species. Each species were classified, identified and described according to its diagnostic characters. Results of the study revealed a total of 20 species of ferns and lycopods. Of these, 18 species were ferns and 2 species were lycopods. Eleven (11) families and fifteen (15) genera for ferns and one (1) family and one (1) genera for lycopods. Psomiocarpa apifolia is Philippine endemic and said to be vulnerable or threatened. Taxonomic characters based on habit, rhizome, leaf arrangement and orientation, stem structure and circinate vernation were used to identify the terrestrial pteridophtyes into families, genera and species. The species collected and assessment in CEDAR should be further investigated and monitor their conservation status. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alpha%20taxonomy" title="alpha taxonomy">alpha taxonomy</a>, <a href="https://publications.waset.org/abstracts/search?q=conservation" title=" conservation"> conservation</a>, <a href="https://publications.waset.org/abstracts/search?q=habit" title=" habit"> habit</a>, <a href="https://publications.waset.org/abstracts/search?q=taxonomic%20characters" title=" taxonomic characters"> taxonomic characters</a> </p> <a href="https://publications.waset.org/abstracts/56000/rapid-inventory-of-terrestrial-ferns-and-lycopods-in-center-for-ecological-development-and-recreation-cedar-impalutao-impasug-ong-bukidnon-philippines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56000.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">223</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">5186</span> Plant Species Composition and Frequency Distribution Along a Disturbance Gradient in Kano Metropolis Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamisu%20Jibril">Hamisu Jibril</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study explores changes in plant species composition along disturbance gradient in urban areas in Nigeria at Bayero University Kano campuses. The aim is to assess changes in plant species composition and distribution within a degraded dryland environment in Kano Metropolis, Nigeria. Vegetation sampling was conducted using plots quadrat and transect methods, and different plant species were identified in the three study sites. Data were analyzed using ANOVA, t-tests and conventional indices to compare species richness, evenness and diversity. The study found no significant differences in species frequency among sites or sampling methods but observed higher species richness, evenness and diversity values in grasses species compared to trees. The study addressed changes in plant species composition along a disturbance gradient in an urban environment, focusing on species richness, evenness, and diversity. The study contributes to understanding the vegetation dynamics in degraded urban environments and highlights the need for conservation efforts. The research also adds to the existing literature by confirming previous findings and suggesting re-planting efforts. The study suggests similarities in plant species composition between old and new campus areas and emphasizes the importance of further investigating factors leading to vegetation loss for conservation purposes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=species%20diversity" title="species diversity">species diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20kano" title=" urban kano"> urban kano</a>, <a href="https://publications.waset.org/abstracts/search?q=dryland%20environment" title=" dryland environment"> dryland environment</a>, <a href="https://publications.waset.org/abstracts/search?q=vegetation%20sampling" title=" vegetation sampling"> vegetation sampling</a> </p> <a href="https://publications.waset.org/abstracts/184510/plant-species-composition-and-frequency-distribution-along-a-disturbance-gradient-in-kano-metropolis-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184510.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">60</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">5185</span> Ants of the Genus Trichomyrmex Mayr, 1865 (Hymenoptera: Formicidae) in the Arabian Peninsula, with Description of Two New Species</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mostafa%20R.%20Sharaf">Mostafa R. Sharaf</a>, <a href="https://publications.waset.org/abstracts/search?q=Shehzad%20Salman"> Shehzad Salman</a>, <a href="https://publications.waset.org/abstracts/search?q=Hathal%20M.%20Al%20Dhafer"> Hathal M. Al Dhafer</a>, <a href="https://publications.waset.org/abstracts/search?q=Shahid%20A.%20Akbar"> Shahid A. Akbar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulrahman%20S.%20Aldawood"> Abdulrahman S. Aldawood</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ant genus Trichomyrmex Mayr is revised for the Arabian Peninsula based on the worker caste. Nine species are recognized and descriptions of two new species, T. almosayari sp. n. and T. shakeri sp. n. from Riyadh Province, the Kingdom of Saudi Arabia (KSA) are given. A key to species and diagnostic characters of the treated species are presented. New country records are presented, T. abyssinicus (Forel) for the KSA and T. destructor (Jerdon) and T. mayri (Forel) for the State of Qatar. New distribution records for T. destructor (Jerdon) and T. mayri (Forel) in the KSA are provided. Regional and world distributions, and distribution maps for the treated species are included. Ecological and biological data are given where known. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ants" title="ants">ants</a>, <a href="https://publications.waset.org/abstracts/search?q=Trichomyrmex" title=" Trichomyrmex"> Trichomyrmex</a>, <a href="https://publications.waset.org/abstracts/search?q=Arabian%20Peninsula" title=" Arabian Peninsula"> Arabian Peninsula</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20almosayari" title=" T. almosayari"> T. almosayari</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20shakeri" title=" T. shakeri"> T. shakeri</a> </p> <a href="https://publications.waset.org/abstracts/47451/ants-of-the-genus-trichomyrmex-mayr-1865-hymenoptera-formicidae-in-the-arabian-peninsula-with-description-of-two-new-species" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47451.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">347</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">5184</span> DNA Barcoding of Tree Endemic Campanula Species From Artvi̇n, Türki̇ye</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hayal%20Akyildirim%20Be%C4%9Fen">Hayal Akyildirim Beğen</a>, <a href="https://publications.waset.org/abstracts/search?q=%C3%96zg%C3%BCr%20Emi%CC%87na%C4%9Fao%C4%9Flu"> Özgür Emi̇nağaoğlu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> DNA barcoding is the method of description of species based on gene diversity. In current studies, registration, genetic identification and protection of especially endemic plants pecies are carried out by DNA barcoding techniques. Molecular studies are based on the amplification and sequencing of the barcode gene region by the PCR method. Endemic Campanula choruhensis Kit Tan & Sorger, Campanula troegera Damboldt and Campanula betulifolia K.Koch is widespread in Artvin, Erzurum and around Çoruh valley passing through it. Intense road and dam constructions are carried out in and around the distribution area of this species. This situation harms the habitat of the species and puts its extinction. In this study, the plastid matK barcode gene regions (650 bp) of three Campanula species were created. To make the identification of this species quickly and accurately, gene sequence compared with sequences of other Campanula L. species. As a result of phylogenetic analysis, C. choruhensis is close relative to C. betulifolia. Morphologically, these species were determined to be more similar to each other with flower and leaf characters. C. troegera formed a separate branch. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=campanula" title="campanula">campanula</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20barcoding" title=" DNA barcoding"> DNA barcoding</a>, <a href="https://publications.waset.org/abstracts/search?q=endemic" title=" endemic"> endemic</a>, <a href="https://publications.waset.org/abstracts/search?q=t%C3%BCrkiye" title=" türkiye"> türkiye</a>, <a href="https://publications.waset.org/abstracts/search?q=artvin" title=" artvin"> artvin</a> </p> <a href="https://publications.waset.org/abstracts/171316/dna-barcoding-of-tree-endemic-campanula-species-from-artvin-turkiye" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171316.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">69</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">5183</span> Effect of Signal Acquisition Procedure on Imagined Speech Classification Accuracy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.R%20Asghari%20Bejestani">M.R Asghari Bejestani</a>, <a href="https://publications.waset.org/abstracts/search?q=Gh.%20R.%20Mohammad%20Khani"> Gh. R. Mohammad Khani</a>, <a href="https://publications.waset.org/abstracts/search?q=V.R.%20Nafisi"> V.R. Nafisi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain%20computer%20interface" title="brain computer interface">brain computer interface</a>, <a href="https://publications.waset.org/abstracts/search?q=silent%20talk" title=" silent talk"> silent talk</a>, <a href="https://publications.waset.org/abstracts/search?q=imagined%20speech" title=" imagined speech"> imagined speech</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a> </p> <a href="https://publications.waset.org/abstracts/154214/effect-of-signal-acquisition-procedure-on-imagined-speech-classification-accuracy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154214.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">153</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">5182</span> Evaluation of Vehicle Classification Categories: Florida Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ren%20Moses">Ren Moses</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaqueline%20Masaki"> Jaqueline Masaki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the need for accurate and updated vehicle classification system through a thorough evaluation of vehicle class categories to identify errors arising from the existing system and proposing modifications. The data collected from two permanent traffic monitoring sites in Florida were used to evaluate the performance of the existing vehicle classification table. The vehicle data were collected and classified by the automatic vehicle classifier (AVC), and a video camera was used to obtain ground truth data. The Federal Highway Administration (FHWA) vehicle classification definitions were used to define vehicle classes from the video and compare them to the data generated by AVC in order to identify the sources of misclassification. Six types of errors were identified. Modifications were made in the classification table to improve the classification accuracy. The results of this study include the development of updated vehicle classification table with a reduction in total error by 5.1%, a step by step procedure to use for evaluation of vehicle classification studies and recommendations to improve FHWA 13-category rule set. The recommendations for the FHWA 13-category rule set indicate the need for the vehicle classification definitions in this scheme to be updated to reflect the distribution of current traffic. The presented results will be of interest to States’ transportation departments and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vehicle%20classification" title="vehicle classification">vehicle classification</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20monitoring" title=" traffic monitoring"> traffic monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=pavement%20design" title=" pavement design"> pavement design</a>, <a href="https://publications.waset.org/abstracts/search?q=highway%20traffic" title=" highway traffic"> highway traffic</a> </p> <a href="https://publications.waset.org/abstracts/84802/evaluation-of-vehicle-classification-categories-florida-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84802.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">181</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">5181</span> The Role of Physically Adsorbing Species of Oxyhydryl Reagents in Flotation Aggregate Formation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20A.%20Kondratyev">S. A. Kondratyev</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20I.%20Ibragimova"> O. I. Ibragimova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The authors discuss the collecting abilities of desorbable species (DS) of saturated fatty acids. The DS species of the reagent are understood as species capable of moving from the surface of the mineral particle to the bubble at the moment of the rupture of the interlayer of liquid separating these objects of interaction. DS species of carboxylic acids (molecules and ionic-molecular complexes) have the ability to spread over the surface of the bubble. The rate of their spreading at pH 7 and 10 over the water surface is determined. The collectibility criterion of saturated fatty acids is proposed. The values of forces exerted by the spreading DS species of reagents on liquid in the interlayer and the liquid flow rate from the interlayer are determined. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=criterion%20of%20action%20of%20physically%20adsorbed%20reagent" title="criterion of action of physically adsorbed reagent">criterion of action of physically adsorbed reagent</a>, <a href="https://publications.waset.org/abstracts/search?q=flotation" title=" flotation"> flotation</a>, <a href="https://publications.waset.org/abstracts/search?q=saturated%20fatty%20acids" title=" saturated fatty acids"> saturated fatty acids</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20pressure" title=" surface pressure"> surface pressure</a> </p> <a href="https://publications.waset.org/abstracts/76153/the-role-of-physically-adsorbing-species-of-oxyhydryl-reagents-in-flotation-aggregate-formation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76153.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">5180</span> Deciphering Orangutan Drawing Behavior Using Artificial Intelligence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benjamin%20Beltzung">Benjamin Beltzung</a>, <a href="https://publications.waset.org/abstracts/search?q=Marie%20Pel%C3%A9"> Marie Pelé</a>, <a href="https://publications.waset.org/abstracts/search?q=Julien%20P.%20Renoult"> Julien P. Renoult</a>, <a href="https://publications.waset.org/abstracts/search?q=C%C3%A9dric%20Sueur"> Cédric Sueur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To this day, it is not known if drawing is specifically human behavior or if this behavior finds its origins in ancestor species. An interesting window to enlighten this question is to analyze the drawing behavior in genetically close to human species, such as non-human primate species. A good candidate for this approach is the orangutan, who shares 97% of our genes and exhibits multiple human-like behaviors. Focusing on figurative aspects may not be suitable for orangutans’ drawings, which may appear as scribbles but may have meaning. A manual feature selection would lead to an anthropocentric bias, as the features selected by humans may not match with those relevant for orangutans. In the present study, we used deep learning to analyze the drawings of a female orangutan named Molly († in 2011), who has produced 1,299 drawings in her last five years as part of a behavioral enrichment program at the Tama Zoo in Japan. We investigate multiple ways to decipher Molly’s drawings. First, we demonstrate the existence of differences between seasons by training a deep learning model to classify Molly’s drawings according to the seasons. Then, to understand and interpret these seasonal differences, we analyze how the information spreads within the network, from shallow to deep layers, where early layers encode simple local features and deep layers encode more complex and global information. More precisely, we investigate the impact of feature complexity on classification accuracy through features extraction fed to a Support Vector Machine. Last, we leverage style transfer to dissociate features associated with drawing style from those describing the representational content and analyze the relative importance of these two types of features in explaining seasonal variation. Content features were relevant for the classification, showing the presence of meaning in these non-figurative drawings and the ability of deep learning to decipher these differences. The style of the drawings was also relevant, as style features encoded enough information to have a classification better than random. The accuracy of style features was higher for deeper layers, demonstrating and highlighting the variation of style between seasons in Molly’s drawings. Through this study, we demonstrate how deep learning can help at finding meanings in non-figurative drawings and interpret these differences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognition" title="cognition">cognition</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=drawing%20behavior" title=" drawing behavior"> drawing behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=interpretability" title=" interpretability"> interpretability</a> </p> <a href="https://publications.waset.org/abstracts/152609/deciphering-orangutan-drawing-behavior-using-artificial-intelligence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152609.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">5179</span> Comparative Analysis of Classification Methods in Determining Non-Active Student Characteristics in Indonesia Open University</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dewi%20Juliah%20Ratnaningsih">Dewi Juliah Ratnaningsih</a>, <a href="https://publications.waset.org/abstracts/search?q=Imas%20Sukaesih%20Sitanggang"> Imas Sukaesih Sitanggang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=comparative%20analysis" title="comparative analysis">comparative analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=clasiffication" title=" clasiffication"> clasiffication</a>, <a href="https://publications.waset.org/abstracts/search?q=Bagging" title=" Bagging"> Bagging</a>, <a href="https://publications.waset.org/abstracts/search?q=Na%C3%AFve%20Bayes" title=" Naïve Bayes"> Naïve Bayes</a>, <a href="https://publications.waset.org/abstracts/search?q=C.45" title=" C.45"> C.45</a>, <a href="https://publications.waset.org/abstracts/search?q=non-active%20students" title=" non-active students"> non-active students</a>, <a href="https://publications.waset.org/abstracts/search?q=Indonesia%20Open%20University" title=" Indonesia Open University"> Indonesia Open University</a> </p> <a href="https://publications.waset.org/abstracts/8231/comparative-analysis-of-classification-methods-in-determining-non-active-student-characteristics-in-indonesia-open-university" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8231.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">316</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">5178</span> Spatio-Temporal Pest Risk Analysis with ‘BioClass’</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vladimir%20A.%20Todiras">Vladimir A. Todiras</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=model" title=" model"> model</a>, <a href="https://publications.waset.org/abstracts/search?q=pest" title=" pest"> pest</a>, <a href="https://publications.waset.org/abstracts/search?q=risk" title=" risk "> risk </a> </p> <a href="https://publications.waset.org/abstracts/27954/spatio-temporal-pest-risk-analysis-with-bioclass" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27954.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">282</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">5177</span> Bioinformatics Analysis of DGAT1 Gene in Domestic Ruminnants</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sirous%20Eydivandi">Sirous Eydivandi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diacylglycerol-O-acyltransferase (DGAT1) gene encodes diacylglycerol transferase enzyme that plays an important role in glycerol lipid metabolism. DGAT1 is considered to be the key enzyme in controlling the synthesis of triglycerides in adipocytes. This enzyme catalyzes the final step of triglyceride synthesis (transform triacylglycerol (DAG) into triacylglycerol (TAG). A total of 20 DGAT1 gene sequences and corresponding amino acids belonging to 4 species include cattle, goats, sheep and yaks were analyzed, and the differentiation within and among the species was also studied. The length of the DGAT1 gene varies greatly, from 1527 to 1785 bp, due to deletion, insertion, and stop codon mutation resulting in elongation. Observed genetic diversity was higher among species than within species, and Goat had more polymorphisms than any other species. Novel amino acid variation sites were detected within several species which might be used to illustrate the functional variation. Differentiation of the DGAT1 gene was obvious among species, and the clustering result was consistent with the taxonomy in the National Center for Biotechnology Information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DGAT1gene" title="DGAT1gene">DGAT1gene</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatic" title=" bioinformatic"> bioinformatic</a>, <a href="https://publications.waset.org/abstracts/search?q=ruminnants" title=" ruminnants"> ruminnants</a>, <a href="https://publications.waset.org/abstracts/search?q=biotechnology%20information" title=" biotechnology information"> biotechnology information</a> </p> <a href="https://publications.waset.org/abstracts/29456/bioinformatics-analysis-of-dgat1-gene-in-domestic-ruminnants" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29456.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">491</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">5176</span> Traditional Knowledge on Living Fences in Andean Linear Plantations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=German%20Marino%20Rivera">German Marino Rivera</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Linear plantations are a common practice in several countries as living fences (LF) delimiting agroecosystems. They are composed of multipurpose perennial woods that provide assets, protection, and supply services. However, not much is known in some traditional communities like the Andean region, including the species composition and the social and ecological benefits of the species used. In the High Andean Colombian region, LF seems to be very typical and diverse. This study aimed to analyze the traditional knowledge about LF systems, including the species composition and their uses in rural communities of Alto Casanare, Colombia. Field measurements, interviews, guided tours, and species sampling were carried out in order to describe traditional practices and the species used in the LF systems. The use values were estimated through the Coefficient of Importance of the Species (CIS). A total of 26 farms engage in LF practices, covering an area of 9283.3 m. In these systems, 30 species were identified, belonging to 23 families. Alnus acuminata was the specie with the highest CIS. The species presented multipurpose uses for both economic and ecological purposes. The transmission of knowledge (TEK) about the used species is very heterogeneous among the farmers. Many species used were not documented, with reciprocal gaps between the literature and traditional species uses. Exchanging this information would increase the species' versatility, the socioeconomic aspects of these communities, increases the agrobiodiversity and ecological services provided by LF. The description of the TEK on LF provides a better understanding of the relationship of these communities with the natural resources, pointing out creative approaches to achieve local environment conservation in these agroecosystems and promoting socioeconomic development. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ethnobotany" title="ethnobotany">ethnobotany</a>, <a href="https://publications.waset.org/abstracts/search?q=living%20fences" title=" living fences"> living fences</a>, <a href="https://publications.waset.org/abstracts/search?q=traditional%20communities" title=" traditional communities"> traditional communities</a>, <a href="https://publications.waset.org/abstracts/search?q=agroecology" title=" agroecology"> agroecology</a> </p> <a href="https://publications.waset.org/abstracts/163444/traditional-knowledge-on-living-fences-in-andean-linear-plantations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163444.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">93</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">5175</span> Comparative Analysis of Feature Extraction and Classification Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20L.%20Ujjwal">R. L. Ujjwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Abhishek%20Jain"> Abhishek Jain</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title="computer vision">computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=age%20group" title=" age group"> age group</a>, <a href="https://publications.waset.org/abstracts/search?q=face%20detection" title=" face detection"> face detection</a> </p> <a href="https://publications.waset.org/abstracts/58670/comparative-analysis-of-feature-extraction-and-classification-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58670.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">368</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">5174</span> Selection of Appropriate Classification Technique for Lithological Mapping of Gali Jagir Area, Pakistan </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khunsa%20Fatima">Khunsa Fatima</a>, <a href="https://publications.waset.org/abstracts/search?q=Umar%20K.%20Khattak"> Umar K. Khattak</a>, <a href="https://publications.waset.org/abstracts/search?q=Allah%20Bakhsh%20Kausar"> Allah Bakhsh Kausar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Satellite images interpretation and analysis assist geologists by providing valuable information about geology and minerals of an area to be surveyed. A test site in Fatejang of district Attock has been studied using Landsat ETM+ and ASTER satellite images for lithological mapping. Five different supervised image classification techniques namely maximum likelihood, parallelepiped, minimum distance to mean, mahalanobis distance and spectral angle mapper have been performed on both satellite data images to find out the suitable classification technique for lithological mapping in the study area. Results of these five image classification techniques were compared with the geological map produced by Geological Survey of Pakistan. The result of maximum likelihood classification technique applied on ASTER satellite image has the highest correlation of 0.66 with the geological map. Field observations and XRD spectra of field samples also verified the results. A lithological map was then prepared based on the maximum likelihood classification of ASTER satellite image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ASTER" title="ASTER">ASTER</a>, <a href="https://publications.waset.org/abstracts/search?q=Landsat-ETM%2B" title=" Landsat-ETM+"> Landsat-ETM+</a>, <a href="https://publications.waset.org/abstracts/search?q=satellite" title=" satellite"> satellite</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20classification" title=" image classification"> image classification</a> </p> <a href="https://publications.waset.org/abstracts/3823/selection-of-appropriate-classification-technique-for-lithological-mapping-of-gali-jagir-area-pakistan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3823.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">394</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">5173</span> Growth and Some Physiological Properties of Three Selected Species of Bifidobacteria in Admixture of Soy Milk and Goat Milk</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Zahran">Ahmed Zahran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Bifidobacterium breve ATCC 15700, Bifidobacterium adolescents ATCC 15704 and Bifidobacterium longum ATCC 15707 were tested for their growth, acid production, bile tolerance, antibiotic resistance and adherence to columnar epithelial cells of the small intestine of goat. The growth of all studied species was determined in the MRSL medium. B.longum 15707 was the most active species in comparison with the other two species; it was also more resistant to bile acids. The adhesion of the studied species to the columnar epithelial cells was studied. All the studied species showed some degree of adhesion; however, B.longum adhered more than the other two species. This species was resistant to four types of antibiotics and was sensitive to chloramphenicol 30 µg. The activity of Bifidobacterium species in soymilk was evaluated by measuring the development of titratalle acidity. B.longum 15707 was the most active species in terms of growth and activity of soymilk. So, soymilk containing bifidobacteria could be added to goat milk to produce acceptable functional soy yogurt, using the ratio of (1:4) soy milk to goat milk. This product could be of unique health benefits, especially in the case of high cholesterol levels and replenishment of intestinal flora after antibiotic therapy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bifidobacteria%20physiological%20properties" title="bifidobacteria physiological properties">bifidobacteria physiological properties</a>, <a href="https://publications.waset.org/abstracts/search?q=soy%20milk" title=" soy milk"> soy milk</a>, <a href="https://publications.waset.org/abstracts/search?q=goat%20milk" title=" goat milk"> goat milk</a>, <a href="https://publications.waset.org/abstracts/search?q=attachment%20epithelial%20cells" title=" attachment epithelial cells"> attachment epithelial cells</a>, <a href="https://publications.waset.org/abstracts/search?q=columnar%20tissues" title=" columnar tissues"> columnar tissues</a>, <a href="https://publications.waset.org/abstracts/search?q=probiotic%20food" title=" probiotic food"> probiotic food</a> </p> <a href="https://publications.waset.org/abstracts/168851/growth-and-some-physiological-properties-of-three-selected-species-of-bifidobacteria-in-admixture-of-soy-milk-and-goat-milk" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168851.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">84</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">5172</span> Patterns in Fish Diversity and Abundance of an Abandoned Gold Mine Reservoirs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20E.%20Obayemi">O. E. Obayemi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Ayoade"> M. A. Ayoade</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20O.%20Komolafe"> O. O. Komolafe</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fish survey was carried out for an annual cycle covering both rainy and dry seasons using cast nets, gill nets and traps at two different reservoirs. The objective was to examined the fish assemblages of the reservoirs and provide more additional information on the reservoir. The fish species in the reservoirs comprised of twelve species of six families. The results of the study also showed that five species of fish were caught in reservoir five while ten fish species were captured in reservoir six. Species such as Malapterurus electricus, Ctenopoma kingsleyae, Mormyrus rume, Parachanna obscura, Sarotherodon galilaeus, Tilapia mariae, C. guntheri, Clarias macromystax, Coptodon zilii and Clarias gariepinus were caught during the sampling period. There was a significant difference (p=0.014, t = 1.711) in the abundance of fish species in the two reservoirs. Seasonally, reservoirs five (p=0.221, t = 1.859) and six (p=0.453, t = 1.734) showed there was no significant difference in their fish populations. Also, despite being impacted with gold mining the diversity indices were high when compared to less disturbed waterbodies. The study concluded that the environments recorded low abundant fish species which suggests the influence of mining on the abundance and diversity of fish species. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Igun" title="Igun">Igun</a>, <a href="https://publications.waset.org/abstracts/search?q=fish" title=" fish"> fish</a>, <a href="https://publications.waset.org/abstracts/search?q=Shannon-Wiener%20Index" title=" Shannon-Wiener Index"> Shannon-Wiener Index</a>, <a href="https://publications.waset.org/abstracts/search?q=Simpson%20index" title=" Simpson index"> Simpson index</a>, <a href="https://publications.waset.org/abstracts/search?q=Pielou%20index" title=" Pielou index"> Pielou index</a> </p> <a href="https://publications.waset.org/abstracts/173907/patterns-in-fish-diversity-and-abundance-of-an-abandoned-gold-mine-reservoirs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173907.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">107</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">5171</span> Identification of Shark Species off The Nigerian Coast Using DNA Barcoding</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20O.%20Fola-Matthews">O. O. Fola-Matthews</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20O.%20Soyinka"> O. O. Soyinka</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20N.%20Bitalo"> D. N. Bitalo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nigeria is one of the major shark fishing nations in Africa, but its fisheries managers still record catch data in aggregates ‘sharks’ with no species-specific details. This is because most of the shark specimens look identical in morphology, and field identification of some closely related species is tricky. This study uses DNA barcoding as a method to identify shark species from five different landing areas off the Nigerian Coast. 100 dorsal fins were sampled in order to provide a Chondrichthyan sequence that would be matched to reference specimens in a DNA barcode database <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BOLD" title="BOLD">BOLD</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20barcoding" title=" DNA barcoding"> DNA barcoding</a>, <a href="https://publications.waset.org/abstracts/search?q=nigeria" title=" nigeria"> nigeria</a>, <a href="https://publications.waset.org/abstracts/search?q=sharks" title=" sharks"> sharks</a> </p> <a href="https://publications.waset.org/abstracts/143574/identification-of-shark-species-off-the-nigerian-coast-using-dna-barcoding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143574.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">168</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">5170</span> A Real-time Classification of Lying Bodies for Care Application of Elderly Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Vazquez-Santacruz">E. Vazquez-Santacruz</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Gamboa-Zuniga"> M. Gamboa-Zuniga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=real-time%20classification" title="real-time classification">real-time classification</a>, <a href="https://publications.waset.org/abstracts/search?q=sensors" title=" sensors"> sensors</a>, <a href="https://publications.waset.org/abstracts/search?q=robots" title=" robots"> robots</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20care" title=" health care"> health care</a>, <a href="https://publications.waset.org/abstracts/search?q=elderly%20patients" title=" elderly patients"> elderly patients</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence "> artificial intelligence </a> </p> <a href="https://publications.waset.org/abstracts/24235/a-real-time-classification-of-lying-bodies-for-care-application-of-elderly-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24235.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">866</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">5169</span> Evidence of Scientific-Ness of Scriptures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shyam%20Sunder%20Gupta">Shyam Sunder Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Written scriptures are created out of Words of God, revealed or inspired. This process of conversion, from revealed Words to written scriptures, happens after a long gap of time and with the involvement of a large number of persons, and unintentionally, scientific and other types of errors get into scriptures; otherwise, scriptures are, in reality, truly scientific. Description of Chronology of life in the womb (Fetal Development), Rotation of Universe, spherical shape of the earth, evolution process of non-living matter and living species, classification of species by nature of birth, etc., most convincing prove that scriptures are truly scientific. In fact, there are many facts for which, to date, science has not found answers but are available in scriptures, like the creation of singularity from which the Big Bang took place and the Universe got created innumerable universes, and the most fundamental particle Param-anu. These findings demonstrate that scriptures contain scientific knowledge that predates scientific discoveries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Big%20Bang" title="Big Bang">Big Bang</a>, <a href="https://publications.waset.org/abstracts/search?q=evolution" title=" evolution"> evolution</a>, <a href="https://publications.waset.org/abstracts/search?q=Param-anu" title=" Param-anu"> Param-anu</a>, <a href="https://publications.waset.org/abstracts/search?q=scientific" title=" scientific"> scientific</a>, <a href="https://publications.waset.org/abstracts/search?q=scriptures" title=" scriptures"> scriptures</a>, <a href="https://publications.waset.org/abstracts/search?q=singularity" title=" singularity"> singularity</a>, <a href="https://publications.waset.org/abstracts/search?q=universe" title=" universe"> universe</a> </p> <a href="https://publications.waset.org/abstracts/175588/evidence-of-scientific-ness-of-scriptures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175588.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">34</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=species%20classification&page=2" rel="prev">&lsaquo;</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=species%20classification&page=1">1</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=species%20classification&page=2">2</a></li> <li class="page-item active"><span class="page-link">3</span></li> <li class="page-item"><a class="page-link" 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