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Keyword: MACSpatiotemporal Traffic State Prediction Based on Discriminatively Pre-trained Deep Neural Networks
The availability of traffic data and computational advances now make it possible to build data-driven models that capture the evolution of the state of traffic along modeled stretches of road. These models are used for short-time prediction so that transportation facilities can be operated in an efficient way that guarantees a high level of service.…
Read MoreHuman Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots
In this paper, a novel approach for collision avoidance for indoor mobile robots based on human-robot interaction is realized. The main contribution of this work is a new technique for collision avoidance by engaging the human and the robot in generating new collision-free paths. In mobile robotics, collision avoidance is critical for the success of…
Read MoreImpact of PSS and SVC on the Power System Transient Stability
The Static Var Compensator (SVC) is used to improve the stability of the power system because of its role in injecting or absorbing the reactive power in the electrical transmission lines. The Power System Stabilizer (PSS) is also a control device which ensures maximum power transfer and thus the stability of the power system enhancement.…
Read MoreSelf-Organizing Map based Feature Learning in Bio-Signal Processing
Feature extraction is playing a significant role in bio-signal processing. Feature identification and selection has two approaches. The standard method is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The…
Read MoreDesign, Fabrication and Testing of a Dual-Range XY Micro-Motion Stage Driven by Voice Coil Actuators
Nowadays, compliant micro-motion stages offer high positioning accuracy and repeatability. When assembled with conventional stages, the resulting dual-range positioning systems allow for nanometer scale accuracy within a centimeter scale working area. However, such systems invoke a high cost and large footprint. This paper presents a low-cost, compact compliant XY micro-motion stage where dual-range manipulation has…
Read MorePrincipal Component Analysis Application on Flavonoids Characterization
Flavonoid is one of the bioactive compounds that are currently used in pharmaceutical and medicinal industries due to their health benefit. The focus of current research is mainly on the extraction and isolation of bioactive compounds; however non to date has explored on the identification of flavonoids classes under the Fourier Transform Infrared spectroscopy (FTIR).…
Read MoreComputational Intelligence Methods for Identifying Voltage Sag in Smart Grid
In recent years pattern recognition of power quality (PQ) disturbances in smart grids has developed into crucial topic for system equipments and end-users. Undoubtedly analyzing the PQ disturbances develop and maintain smart grids effectiveness. Voltage sags are the most common events that affect power quality. These faults are also the most costly. This paper represents…
Read MoreA Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks
A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN). Most wormhole detection schemes reported in…
Read MoreChikungunya virus; Review of Epidemiology and Outbreak in Pakistan
Chikungunya virus (CHIKV) is mosquito-borne, alpha virus. It causes acute fever and acute and chronic musculoskeletal pain in humans. CHIKV has spread to 22 countries including Pakistan resulting in hundreds of thousands of death across the world. International travel stands out as one of the major risk factors for rapid global spread of the disease.…
Read MoreMedical imbalanced data classification
In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine…
Read MoreEvaluation of Pure Aluminium Inoculated with Varying Grain Sizes of an Agro-waste based Inoculant
Pure Aluminium and its alloy are widely utilized in Engineering and Industrial applications due to certain significant properties such as softness, ductility, corrosion resistance, and high electrical conductivity which it possesses. Addition of an agro-waste based grain refiner to the melt can alter the characteristics positively or negatively. Therefore, the aim of this paper is…
Read MoreDetection of Vandalism in Wikipedia using Metadata Features – Implementation in Simple English and Albanian sections
In this paper, we evaluate a list of classifiers in order to use them in the detection of vandalism by focusing on metadata features. Our work is focused on two low resource data sets (Simple English and Albanian) from Wikipedia. The aim of this research is to prove that this form of vandalism detection applied…
Read MoreCross layers security approach via an implementation of data privacy and by authentication mechanism for mobile WSNs
To implement a new secure network with high mobility and low energy consumption, we use smart sensors. These sensors are powered by micro batteries generally non rechargeable. So, to extend their lifetime, it is necessary to implement new energy conservation techniques. Existing works separate the two features (security, energy conservation) and are interested specifically in…
Read MoreRecent Trends in ELM and MLELM: A review
Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer feed forward neural networks. Compared with the existing neural network learning algorithm it solves the slow training speed and over-fitting problems. It has been used in different fields and applications such as biomedical engineering, computer vision, remote sensing, chemical process…
Read MoreA Web-Based Decision Support System for Evaluating Soil Suitability for Cassava Cultivation
Precision agriculture in recent times had assumed a different dimension in order to improve on the poor standard of agriculture. Similarly, the upsurge in technological advancement, most especially in the aspect of machine learning and artificial intelligence, is a promising trend towards a positive solution to this problem. Therefore, this research work presents a decision…
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