272 research outputs found
Wireless Mesh Networks
No full textThe rapid advancements of low-cost small-size devices for wireless communications with their international standards and broadband backbone networks using optical fibers accelerate the deployment of wireless networks around the world.
The wireless mesh network has emerged as the generalization of the conventional wireless network. However, wireless mesh network has several problems to be solved before being deployed as the fundamental network infrastructure for daily use. The book is edited to specify some problems that come from the disadvantages in wireless mesh network and give their solutions with challenges. The contents of this book consist of two parts: Part I covers the fundamental technical issues in wireless mesh network, and Part II the administrative technical issues in wireless mesh network,. This book can be useful as a reference for researchers, engineers, students and educators who have some backgrounds in computer networks, and who have interest in wireless mesh network. It is a collective work of excellent contributions by experts in wireless mesh network
Performance Improvement of Decision Trees for Diagnosis of Coronary Artery Disease Using Multi Filtering Approach
No full textThe heart is one of the strongest muscular organs in the human body. Every year, this disease can kill many people in the world. Coronary artery disease (CAD) is named as the most common type of heart disease. Four well-known decision trees (DTs) are applied on the Z-Alizadeh Sani CAD dataset, which consists of J48, BF tree, REP tree, and NB tree. A multi filtering approach, named MFA, was used to modify the weight of attributes to improve the performance of DTs in this study. The model was applied on three main coronary arteries including the Left Anterior Descending (LAD), Left Circumflex (LCX), and Right Coronary Artery (RCA). The obtained results show that data balancing has a valuable impact on the performance of DTs. The comparison results show that this study provides the best results applied on the Z-Alizadeh Sani dataset compared to previous studies. The proposed MFA could improve the performance of the classic DTs algorithms significantly, with the highest accuracies obtained by NB tree for LAD, LCX, and RCA are 94.90%, 92.97% and 93.43%, respectively.</p
A Joint Deep Neural Network Model for Pain Recognition from Face
No full textPain is a primary symptom of diseases and an indicator of a patients’ health status. Effective management of pain is important for patient treatment and well-being. There are some traditional self-reported methods for pain assessment, and automatic pain detection systems using facial expressions are developing rapidly; these offer the potential for more efficient, convenient and cost-effective pain management. In this paper, a joint deep neural network model is proposed to classify pain intensity in four categories from facial images. This study used two different Recurrent Neural Networks (RNN), which were pre-trained with Visual Geometric Group Face Convolutional Neural Network (VGGFace CNN) and then joined together as a network to estimate pain intensity levels. The UNBC-McMaster Shoulder Pain database was used to train and test the proposed algorithm. As a contribution to knowledge, this paper provides new information regarding the performance of a hybrid, joint deep learning algorithm for pain multi-classification in facial images.</p
Access-Point Allocation Algorithms for Scalable Wireless Internet-Access Mesh Networks
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A design-aware test code approach for code writing problem in Java programming learning assistant system
No full textTo advance Java programming educations, we have developed the web-based Java programming learning assistant system (JPLAS) that provides the code writing problem. This problem asks a student to write a source code for a given assignment, where the correctness is verified by running the test code on JUnit. In this paper, we propose a design-aware test code approach for the code writing problem. The design-aware test code tests any important method in the model source code that has the advisable design for the assignment. Thus, by writing a code that can pass it, a student is expected to implement the code with the proper classes/methods in the model code. In evaluations of the proposal, all the students could complete highly qualitative codes for five graph algorithms using the design-aware test codes, where the code quality metrics were measured by metrics plugin for Eclipse
Verifier-Local Revocation Group Signature Schemes with Backward Unlinkability from Bilinear Maps
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A Proposal of Statement Fill-in-Blank Problem in Java Programming Learning Assistant System
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