Proceedings of the 4th International Conference on Bioinformatics Research and Applications最新文献

A Framework for Identifying Excessive Sadness in Students through Twitter and Facebook in the Philippines 菲律宾通过Twitter和Facebook识别学生过度悲伤的框架

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175600

Hussain D. Zuorba, Celine Louise O. Olan, A. Cantara

{"title":"A Framework for Identifying Excessive Sadness in Students through Twitter and Facebook in the Philippines","authors":"Hussain D. Zuorba, Celine Louise O. Olan, A. Cantara","doi":"10.1145/3175587.3175600","DOIUrl":"https://doi.org/10.1145/3175587.3175600","url":null,"abstract":"Natural Language Processing (NLP) can be used to identify a person's sentiments or emotions. Depression is one sentiment that researchers have tried to identify through Natural Language Processing with little success. Depression is an episode of sadness or apathy, along with other symptoms, that lasts for at least two consecutive weeks. Depression is especially bad with students due to the amount of stress and anxiety they have to go through. While depression is very difficult to identify and treat, excessive sadness, one of the symptoms that may lead to depression can be identified early and appropriate action can be taken. The Philippines is known to have the highest depression count in Southeast Asia. Data Mining was performed on Twitter and Facebook, and with the use of Natural Language Processing (NLP) and Sentiment Analysis, a logistics regression model was devised with the use of emotion Lexicons to identify the user's state. The Latent Dirichlet Allocation (LDA) was then used to identify important topics of each user and cluster the data and make sense out of each user's excessive sadness.","PeriodicalId":371308,"journal":{"name":"Proceedings of the 4th International Conference on Bioinformatics Research and Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115536415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

A Wavelet-Neural Network for the Estimation of Chlorophyll-a Concentration in Caspian Sea 里海叶绿素- A浓度估算的小波神经网络

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175599

M. Haghparast, M. Mokhtarzade, M. Gholamalifard

{"title":"A Wavelet-Neural Network for the Estimation of Chlorophyll-a Concentration in Caspian Sea","authors":"M. Haghparast, M. Mokhtarzade, M. Gholamalifard","doi":"10.1145/3175587.3175599","DOIUrl":"https://doi.org/10.1145/3175587.3175599","url":null,"abstract":"Monitoring of vast water bodies, including internal and external waters, is an important issue which is commonly performed by remote sensing as the most economical technology. In this field, the concentration of chlorophyll-a, as a critical water quality index, has attracted most research attentions. In this paper, wavelet neural network are proposed for the estimation of chlorophyll-a concentration in Caspian Sea from multi-date MODIS product MYDOCGA.These networks are evaluated from both aspects of estimation accuracy as well as response stability and are also compared to the classical perceptron neural networks (PNN). In addition, different features are examined as the network input parameters including all the 9 MODIS product MYDOCGA bands, different subsets of these bands and also PCA(Principal Component Analysis) bands in different number. The results, which are obtained and validated based to 55 filed observed samples, proves the effectiveness of WNN (Wavelet Neural Network) in comparison to classical neural networks. The best RMSE=0.07 of these networks reveals that remote sensing can accurately replace field observations to produce thematic maps of water quality parameters provided that appropriate processing techniques are applied.","PeriodicalId":371308,"journal":{"name":"Proceedings of the 4th International Conference on Bioinformatics Research and Applications","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127657855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Exploration of Epitope-Based Vaccine Design with Broad Protection Against Influenza A (H3) Viral Strains Using Computational Biology 利用计算生物学探索基于表位的疫苗设计对甲型流感(H3)病毒株具有广泛保护作用

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175595

Y. Zou

{"title":"An Exploration of Epitope-Based Vaccine Design with Broad Protection Against Influenza A (H3) Viral Strains Using Computational Biology","authors":"Y. Zou","doi":"10.1145/3175587.3175595","DOIUrl":"https://doi.org/10.1145/3175587.3175595","url":null,"abstract":"Influenza is a highly contagious disease due to its frequently mutating viral Hemaglutinin (HA) and Neuraminidase (NA) proteins.[1] WHO reports that 250,000-500,000 people worldwide die of seasonal influenza every year.[2]This necessitates the search for universal vaccines, or broadly protective influenza vaccines. This research explored the feasibility of epitope-based broad-spectrum influenza H3 vaccine design based on common linear epitopes. Given the previously prepared broadly neutralizing antibody 4E3 that recognizes multiple H3 strains by NIDVD, three epitope candidates were selected using computer-simulated antigen-antibody docking. The three epitopes were then evaluated in vitro using molecular cloning, protein expression and immunoassay technologies. EPI-3 (amino acid sequence: WGVHHPVTDNDQIFLYAQA) was successfully cloned, expressed, and evaluated using Western Blot. The positive WB result proved the methodological validity of epitope-based broad-spectrum vaccine design using computational biology. Further work using this method is expected from the scientific community.","PeriodicalId":371308,"journal":{"name":"Proceedings of the 4th International Conference on Bioinformatics Research and Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116432056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated Newborn Pain Assessment Framework Using Computer Vision Techniques 使用计算机视觉技术的新生儿疼痛自动评估框架

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175590

E. Parodi, D. Melis, L. Boulard, M. Gavelli, E. Baccaglini

{"title":"Automated Newborn Pain Assessment Framework Using Computer Vision Techniques","authors":"E. Parodi, D. Melis, L. Boulard, M. Gavelli, E. Baccaglini","doi":"10.1145/3175587.3175590","DOIUrl":"https://doi.org/10.1145/3175587.3175590","url":null,"abstract":"Pain evaluation in newborns is becoming a mandatory task in clinical practice. Currently, despite its complexity, pain assessment is entirely delegated to subjective estimates. The aim of this study is to propose an automated -- thus objective -- approach for neonatal pain evaluation focusing on facial expressions. From patients' face detection, a set of relevant parameters were extracted; both pixel-based image processing and analysis of facial landmarks led to final pain scores which were computed with respect to 3 widely adopted pain scales. The algorithm has been validated in a trial based on 15 videos acquired at the Neonatal Unit of AO Ordine Mauriziano Hospital, Turin, during heel stick procedure for blood sampling. The proposed algorithm scores have been compared to those subjectively assigned by health care professionals. The results confirm that manual pain assessment is a challenging task that often results in an elevated variance across scores between different operators, making automated evaluation highly desirable. The proposed algorithm is a first step in this direction, and despite difficulties in handling rapid facial changes, it is preparatory to the definition of an experimental protocol which merges video analysis, including the most relevant facial metrics, with audio processing for improved reliability.","PeriodicalId":371308,"journal":{"name":"Proceedings of the 4th International Conference on Bioinformatics Research and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130112733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Human Gender Recognition with Upper Body Gait Kinematics 基于上半身步态运动学的人类性别识别

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175596

Ha Tran, P. Pathirana, A. Seneviratne

{"title":"Human Gender Recognition with Upper Body Gait Kinematics","authors":"Ha Tran, P. Pathirana, A. Seneviratne","doi":"10.1145/3175587.3175596","DOIUrl":"https://doi.org/10.1145/3175587.3175596","url":null,"abstract":"Human gender recognition has captured the attention of researchers particularly in computer vision and biometric arena. These investigations based on computer vision or image processing have highlighted applications in security systems, medical applications etc. This work is primarily aimed at investigating a possible characteristic difference in upper body movement kinematics between males and females and, in the affirmative, if that kinematic information alone is sufficient to distinguish each cohort from the other. We use a Microsoft Kinect© to capture the human upper body gait kinematics to uncover gender based kinematic variations. Two groups of healthy volunteers (18 females, 16 males) were requested to walk along a linear pathway in front of the camera. Upper body movement kinematics were extracted from the male and female cohorts during walking. Principal component analysis (PCA) was employed to substantiate the differences between the two cohorts in terms of kinematic information. Finally, we use k-means clustering to classify and evaluate the performance of the classification system. Despite of the limitation of the dataset, e.g., the limited range of the Kinect© camera, the accuracy of the proposed approach reached up to 94%, indicating that upper body joint movements possess significant information content on human gender based features.","PeriodicalId":371308,"journal":{"name":"Proceedings of the 4th International Conference on Bioinformatics Research and Applications","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126132967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Virtual Screening for COX-2 Inhibitors with Random Forest Algorithm and Feature Selection 基于随机森林算法和特征选择的COX-2抑制剂虚拟筛选

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175594

Shangjie Ai, Yong Bai, Xiande Liu

引用次数: 2

Aqueous Shell Chirality Research of Varying Thickness 变厚度水壳手性研究

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175601

A. Khakhalin, O. N. Gradoboeva

引用次数: 2

Early versus Late Dimensionality Reduction of Bag-of-Words Feature Representation for Image Classification 用于图像分类的词袋特征表示的早降维与晚降维

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175598

Chih-Fong Tsai, Ya-Han Hu, Wei-Chao Lin, Ming-Chang Wang

{"title":"Early versus Late Dimensionality Reduction of Bag-of-Words Feature Representation for Image Classification","authors":"Chih-Fong Tsai, Ya-Han Hu, Wei-Chao Lin, Ming-Chang Wang","doi":"10.1145/3175587.3175598","DOIUrl":"https://doi.org/10.1145/3175587.3175598","url":null,"abstract":"Extracting the bag-of-words (BoW) feature from images has been widely used for image classification. In general, some local keypoints are first of all detected from each image and the keypoint descriptor, such as scale-invariant feature transform (SIFT), is extracted. Then, the keypoint descriptors of a given image dataset are tokenized (or clustered) to generate a visual-word vocabulary (or codebook). Next, the visual-word vector of an image contains the presence or absence information of each visual word in the image, e.g. the number of keypoints in the corresponding cluster, i.e. visual word. Consequently, images are represented by a histogram over visual words. Since the dimensionalities of the SIFT keypoint descriptor and the final BoW feature for image classification are certainly high, this paper aims at examining the effect of performing dimensionality reduction (DR) for both different features on classification accuracy. In particular, early DR is used over the SIFT descriptor and late DR for the BoW feature. The experimental results based on Caltech 101 (2-D images) and ESB (3-D images) datasets show that reducing 50% dimensionality of the SIFT descriptor by PCA can allow the SVM classifier to perform similar to the one without DR. On the other hand, late DR only works for 2-D images, but the classification performance of SVM cannot be kept if over 25% dimensionality of the BoW feature is reduced.","PeriodicalId":371308,"journal":{"name":"Proceedings of the 4th International Conference on Bioinformatics Research and Applications","volume":"19 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132242573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biophysical and Motion Features Extraction for an Effective Home-Based Rehabilitation 有效居家康复的生物物理和运动特征提取

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175597

M. Morando, S. Ponte, E. Ferrara, S. Dellepiane

引用次数: 6

Correlation Dimension Estimation from EEG Time Series for Alzheimer Disease Diagnostics 脑电时间序列相关维数估计用于阿尔茨海默病诊断

Proceedings of the 4th International Conference on Bioinformatics Research and Applications Pub Date : 2017-12-08 DOI: 10.1145/3175587.3175591

Martin Dlask, J. Kukal

引用次数: 4