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Keyword: NetworkReview of Different Methods for Optimal Placement of Phasor Measurement Unit on the Power System Network
Phasor Measurement Unit (PMU) is an integral device for tracking, protection, and regulation of the power network. PMU gives synchronised calculations of actual-time data for voltage phasor, current phasor, and the frequency. Placing PMU in every node to observe the power network is not realistic from an economic standpoint and even for big data management.…
Read MorePolarity Switch within Social Networks
It is the age of information. Social networks are the main reason why, following the increasing activity of online users. With this comes a big impact on the real world, it can be positive and highly negative as well. Therefore, research in this field is highly needed for the betterment of societal behaviors within social…
Read MoreNetwork Modeling with ANP to Determine the Appropriate Area for the Development of Dry Port in Thailand
One drawback of the Multiple Criteria Decision Making (MCDM) problem with the Analytic Network Process (ANP) is that the origin of the network cannot be clearly defined. In addition, it is not possible to specify internal relationship between criteria and sub-criteria. The application of Design Structure Matrix (DSM) with the Partitioning Reachability Matrix method resulted…
Read MoreDense Deep Neural Network Architecture for Keystroke Dynamics Authentication in Mobile Phone
The ever-growing technology in mobile smartphones has enabled users to store sensitive and private information; as a result, it required the need for an improved security system. Previous approaches heavily relied on shallow machine learning algorithms that require feature extraction which is time consuming, laborious and can cause, resulting in poor authentication. In this paper,…
Read MoreVehicle Rollover Detection in Tripped and Untripped Rollovers using Recurrent Neural Networks
Comparing to other types of vehicle accidents, fatality rate of tipped rollover accidents shows significant number. Thus, tripped rollover prevention systems are important in order to keep driver safe. In other hands, different rollover indices are defined to handle the risk. The variable unknown parameters of each index, for instance, current load of the vehicle…
Read MoreInferring Topics within Social Networking Big Data, Towards an Alternative for Socio-Political Measurement
This research sought to measure some socio-political indicators using millions of opinionated messages from social network sourced big data. Thus, and using an enhanced mixed method for sentiment analysis and a fusion model algorithm to infer topics from short text, this study attempted to demonstrate the value of computational approaches in measuring some phenomena in…
Read MoreUsing the Neural Network to Diagnose the Severity of Heart Disease in Patients Using General Specifications and ECG Signals Received from the Patients
Nowadays, heart diseases cause the maximum death in the world. Also, due to the noticeable increase of heart diseases, studying this field is one of the important matters in medical community. Therefore, this study tries to benefit using information in data base of cardiac arrhythmia and employ arterial intelligent and neural network, in order to…
Read MoreUsing Classic Networks for Classifying Remote Sensing Images: Comparative Study
This paper presents a comparative study for using the classic networks in remote sensing images classification. There are four deep convolution models that used in this comparative study; the DenseNet 196, the NASNet Mobile, the VGG 16, and the ResNet 50 models. These learning convolution models are based on the use of the ImageNet pre-trained…
Read MoreBrain Tumor Classification Using Deep Neural Network
Brain tumors are a type of tumor with a high mortality rate. Since multifocal-looking tumors in the brain can resemble multicentric gliomas or gliomatosis, accurate detection of the tumor is required during the treatment process. The similarity of neurological and radiological findings also complicates the classification of these tumors. Fast and accurate classification is important…
Read MoreContextual Word Representation and Deep Neural Networks-based Method for Arabic Question Classification
Contextual continuous word representation showed promising performances in different natural language processing tasks. It stems from the fact that these word representations consider the context in which a word appears. But until recently, very little attention was paid to the contextual representations in Arabic question classification task. In the present study, we employed a contextual…
Read MoreNewton-Raphson Algorithm as a Power Utility Tool for Network Stability
Nigerian power utility companies particularly the distribution and generation aspects were recently in the process of national power reform converted from public to private service by privatization. Prior to these development, power utility companies’ performance is low due to poor operational style that leads to inadequate revenue generation. Thus, the task before the privatized companies…
Read MoreApplicability of Generalized Metropolis-Hastings Algorithm to Estimating Aggregate Functions in Wireless Sensor Networks
Over the last decades, numerous distributed consensus-based algorithms have found a wide application as a complementary mechanism for data aggregation in wireless sensor networks. In this paper, we provide an analysis of the generalized Metropolis-Hastings algorithm for data aggregation with a fully-distributed stopping criterion. The goal of the implemented stopping criterion is to effectively bound…
Read MoreConvolutional Neural Network Based Classification of Patients with Pneumonia using X-ray Lung Images
Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID-19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing number…
Read MoreTowards Directing Convolutional Neural Networks Using Computational Geometry Algorithms: Application to Handwritten Arabic Character Recognition
Suppose we want to classify a query item Q with a classification model that consists of a large set of predefined classes L and suppose we have a knowledge that indicates to us that the target class of Q belongs to a small subset from L. Naturally, this filtering will improve the accuracy of any…
Read MoreFast Stream Cipher based Chaos Neural Network for Data Security in CAN Bus
Vehicle systems are controlled by embedded electronic devices called electronic control units (ECUs). These ECUs are connected together with network protocols. The Controller Area Network (CAN) protocol is widely implemented due to its high fault tolerance. However, the CAN is a serial broadcast bus, and it has no protection against security threats. In this paper,…
Read MoreTowards Classification of Shrimp Diseases Using Transferred Convolutional Neural Networks
Vietnam is one of the top 5 largest shrimp exporters globally, and Mekong delta of Vietnam contributes more than 80% of total national production. Along with intensive farming and growing shrimp farming area, diseases are a severe threat to productivity and sustainable development. Timely response to emerging shrimp diseases is critical. Early detection and treatment…
Read MoreFuzzy Recognition by Logic-Predicate Network
The paper presents a description and justification of the correctness of fuzzy recognition by a logic-predicate network. Such a network is designed to recognize complex structured objects that can be described by predicate formulas. The NP-hardness of such an object recognition requires to separate the learning process, leaving it exponentially hard, and the recognition process…
Read MoreCorrelation-Based Incremental Learning Network for Gas Sensors Drift Compensation Classification
A gas sensor array is used for gas analysis to aid in an inspection. The signals from the sensor array are fed into machine learning models for learning and classification. These signals are characterized by time series fluctuating according to the environment or drift. When an unseen pattern is entered, the classification may be incorrect,…
Read MoreMachine Learning for Network Intrusion Detection Based on SVM Binary Classification Model
Recently, the number of connected machines around the worldwide has become very large, generating a huge amount of data either to be stored or to be communicated. Data protection is a concern for all institutions, it is difficult to manage the masses of data that are susceptible to multiple threats. In this work, we present…
Read MoreOverview of Solar Radiation Estimation Techniques with Development of Solar Radiation Model Using Artificial Neural Network
Estimation Solar radiation is the most significant part of the optimization of solar power. This may be achieved if the solar radiation is predicted well in advance. Meteorological stations have radiation measuring devices like pyranometer, pyrheliometer, radiometer, solarimeter, etc. however, it may not be available at the location of interest for researchers. Due to this…
Read MoreNeural Network-Based Fault Diagnosis of Joints in High Voltage Electrical Lines
In this paper a classification system based on a complex-valued neural network is used to evaluate the health state of joints in high voltage overhead transmission lines. The aim of this method is to prevent breakages on the joints through the frequency response measurements obtained at the initial point of the network. The specific advantage…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreA Survey on 3D Hand Skeleton and Pose Estimation by Convolutional Neural Network
Restoring, estimating the fully 3D hand skeleton and pose from the image data of the captured sensors/cameras applied in many applications of computer vision and robotics: human-computer interaction; gesture recognition, interactive games, Computer-Aided Design (CAD), sign languages, action recognition, etc. These are applications that flourish in Virtual Reality and Augmented Reality (VR/AR) technologies. Previous survey…
Read MoreThe Design of an Experimental Model for Deploying Home Area Network in Smart Grid
In the smart power grid, designing an efficient and reliable communication architecture has an important role in improving efficiency, and maintaining the connectivity of different network components. The home area network (HAN) provides an energy management system in houses since it enables home energy control and monitoring. So, it is imperative to determine a HAN…
Read MoreEvaluation of Type A Uncertainty in a Network Analyzer From 300 kHz to 8.5 GHz
Network Analyzer is equipment widely used for the execution of radio frequency application scattering parameters. Throughout absolute reading the scattering parameter measured. An absolute reading does not include error, drift, offset, linearity, resolution, coefficient of sensitivity and several other variables that will contribute to the measured measurement dispersion. Type A evaluations of measurement uncertainty clarified…
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