bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-Cost Vibration Chamber for Landslide Sensory and Alarm System
Authors: Binti Ismail Eliza Sabira , Habaebi Mohamed Hadi , Ibrahimy Muhammad , Islam Md Rafiqul 
Published: January 2019

<p>Many previous research works published in the open literature aimed at designing a system that could detect landslide in early stage before the landslide becomes catastrophic. This paper presents a work-in-progress landslide early warning system for Malaysian environment. The aim of this paper is to develop the most effecienctly reliable cost-effective system in which slight earth movements are monitored continuously. The challenge this work aims at is to work with a low budget system that produce efficient performance. Hence, the material used is of-the-shelf. Early design optimization result of the vibration sensor used is quite promising detecting the slightest faint tremors, which are amplified using the best vibration chamber available. It is shown that the choice of proper pipe length and diameter dimensions in combination to a gravel to exaggerate the produced higher sensitivity level of 5dB. Furthermore, both systematic and random vibration tests produced similar results.</p>
Availability Prediction Methods for Terrestrial Free-Space-Optical Link Under Tropical Climate
Authors: Basahel Ahmed , Islam Md Rafiqul , Habaebi Mohamed , Ahmad Suriza 
Published: January 2019

<p>Free-space optical (FSO) links provide high speed point-to-point wireless communication, but its availability can easily be affected by weather conditions. In heavy rainfall regions, FSO links are relatively sensitive to rain. Availability prediction of FSO is indispensable part, especially in tropical areas. In this paper, methods to predict FSO link availability are presented. The overall performance of FSO link is described in terms of the availability that can be achieved over anticipated link distance. The availability prediction methods demonstrated for an FSO link ranges up to 5 km. The availability prediction methods are based on long-term statistics of atmospheric attenuations and FSO link budget under tropical climate condition. In tropical regions, for a terrestrial FSO link, carrier class availability can be achieved over a few hundred meters only; whereas enterprise class availability can be achieved over a few kilometers link distances. </p>
Anomaly Detection in Log Records
Authors: Ghuli Poonam 
Published: January 2019

<p>Complex software systems are continuously generating application and server logs for the events which had occurred in the past. These logs generated and can be utilized for anomaly and intrusion detection. These log files can be used for anomaly or outlier detection. Certain types of abnormalities or exceptions such as spikes in HTTP requests, number of exceptions raised in logs, etc. All these events are logged into the log files for further analysis. These types of events are generally used for predicting the anomalies in future. The developed prototype assumes that the user inputs log records in a standard apache log format. At first the user uploads the log file for outlier detection. Next, a prototype is developed to get the number of HTTP requests for outlier detection. Then anomalies in number of HTTP requests are detected using three techniques namely InterQuartileRange method, Moving averages and Median Absolute deviation. Once the outliers are detected, these outliers are removed from the current dataset. This output is given as input to the Multilayer Perceptron model to predict the number of HTTP requests at the next timestamp</p><p> </p>
Q-switched Erbium Doped Fiber Laser Incorporating Antimony (III) Telluride in Polyvinyl Alcohol as Saturable Absorber
Authors: Ismail Ezzatul Irradah , Ashraf Zolkopli S Muhammad , Lokman Muhammad Quisar , Yahaya Hafizal , Harun Sulaiman Wadi , Ahmad Fauzan 
Published: January 2019

<span lang="EN-US">In this paper, we demonstrated a Q-switched erbium doped fiber laser (EDFL) incorporating Antimony (III) Telluride (Sb<sub>2</sub>Te<sub>3</sub>) in polyvinyl alchohol (PVA) as passive saturable absorber. The saturable absorber were fabricated by dissolving Antimony (III) Telluride powder into PVA solution and dry in the ambient temperature for 48 hours. Then, 1 mm<sup>2</sup> x 1 mm<sup>2</sup> Sb<sub>2</sub>Te<sub>3</sub>-PVA film based saturable absorber were sandwiched in between FC/PC ferrule for Q-switched laser generation. The stable and self-started Q-switched laser operates at center wavelength 1560 nm with 3 dB bandwidth of 0.23 nm. The laser operates at pump power of 29.3 mW until 84.9 mW with repetition rate of 20.99 kHz to 89.29 kHz and pulse width of 13.95 µs to 5.10 µs. At maximum pump power, the laser able to achieve pulse energy of 62.72 nJ and high signal to noise ratio of 71.4</span>
Fusion of Random Projection, Multi-Resolution Features and Distance Weighted K Nearest Neighbor for Masses Detection in Mammographic Images
Authors: Nguyen Viet Dung , Le Minh Dong 
Published: January 2019

<p>Breast cancer is the top cancer in women both in the developed and the developing world. For early detection of the disease, mammography is still the most effective method beside ultrasound and magnetic resonance imaging. Computer Aided Detection systems have been developed to aid radiologists in diagnosing breast cancer. Different methods were proposed to overcome the main drawback of producing large number of False Positives. In this paper, we presented a novel method for masses detection in mammograms. To describe masses, multi-resolution features were utilized. In feature extraction step, we calculated multi-resolution Block Difference Inverse Probability features and multi-resolution statistical features. Once the descriptors were extracted, we deployed random projection and distance weighted K Nearest Neighbor to classify the detected masses. The result is quite sanguine with sensitivity, false positive reduction and time for carrying out the algorithm</p>
Optimization of PV Systems Using Data Mining and Regression Learner MPPT Techniques
Authors: Farayola Adedayo M. , Hasan Ali N , Ali Ahmed 
Published: January 2019

<span>Supervised machine learning techniques such as artificial neural network (ANN) and ANFIS are powerful tools used to track the maximum power point (MPPT) in photovoltaic systems. However, these offline MPPT techniques still require large and accurate training data sets for successful tracking. This paper presents an innovative use of rational quadratic gaussian process regression (RQGPR) technique to generate the large and very accurate training data required for MPPT task. To confirm the effectiveness of the RQGPR technique, the combination of ANN and RQGPR as ANN-RQGPR technique results were compared with the conventional ANN technique results, and that of combined ANN and linear support vector machine regression as ANN-LSVM technique results under different weather conditions. Results show that ANN-RQGPR technique produced the overall best result and with an improved performance. </span>
Enhanced Fertigation Control System towards Higher Water Saving Irrigation
Authors: Abd Rahman Muhammad Khairie Idham , Zainal Abidin Mohamad Shukri , Buyamin Salinda , Azimi Mahmud Mohd Saiful 
Published: January 2019

<span>Water saving in agriculture is increasingly important due to critical issues of water and climatic crisis. The focus of agricultural researches nowadays is to minimize the water consumption and at the same time increasing the agricultural yield. This paper presents the three-types of automatic fertigation controller for irrigation system with different application tools. A weather station, soil moisture and timer based system were used to determine the volume of water supply needed by plants to calculate an accurate irrigation operation timing. The experiment was conducted by supplying water for capsicum annum test crop located in a greenhouse. The plant water demand parameter was calculated and compared for each application tools and the best application tool was chosen to be implemented in controlling the irrigation system.</span>
Feasibility Study of Grid-Connected Solar Photovoltaic (PV) System for Primary School in Johor
Authors: Jumaat Siti Amely , Majid Adhwa Amsyar Syazwan Ab , Gan Chin Kim , Abdullah Mohd Noor , Radzi Nur Hanis , Hamdan Rohaiza , Salimin Suriana 
Published: January 2019

This project aims to determine the potential of grid connected solar Photovoltaic (PV) implementation and project planning of solar PV System in school. Generally, the educational institution used huge amount of electricity to operate so their monthly bills is expensive. Therefore, the project planning is necessary to determine the potential of solar PV system implementation. The project planning consists of the current electricity consumed by the school and the amount of 120W Monocrystalline PV module needed by them. The cost of project are determines to identify the initial cost of this project implementation. Lastly, analysis on the profit collected by SK Pintas Raya after 20 years of solar PV system implementation proved the importance of this project.
Security Authentication for Student Cards’ Biometric Recognition Using Viola-Jones Algorithm
Authors: Ibrahim S. , Jamaluddin K.R. , Samah K.A.F.A. 
Published: January 2019

The unauthorized access to the university entrance could be gained by only flashing a student card. This unsecure situation shows the loophole of security authentication in a university. In order to overcome this, a biometric recognition could be the most suitable candidate as it varies uniquely from one person to another. A study on student cards’ biometric recognition using Viola-Jones algorithm is presented as it is proven as a powerful algorithm in terms of superb detection rates and speed. It is done by comparing the facial structures and features between the student card’s image and the card holder image, thus determining the similarity. The recognition performance is evaluated based on the percentage of similarity using 100 testing images of 50 students. The observation on results obtained the effectiveness of the Viola-Jones features in student cards’ biometric recognition rate.
Comparison of Swarm Intelligence Algorithms for High Dimensional Optimization Problem
Authors: Bashath Samar , Ismail Amelia Ritahani 
Published: January 2019

<p>High dimensional optimization considers being one of the most challenges that face the algorithms for finding an optimal solution for real-world problems. These problems have been appeared in diverse practical fields including business and industries. Within a huge number of algorithms, selecting one algorithm among others for solving the high dimensional optimization problem is not an easily accomplished task. This paper presents a comprehensive study of two swarm intelligence based algorithms: 1-particle swarm optimization (PSO), 2-cuckoo search (CS).The two algorithms are analyzed and compared for problems consisting of high dimensions in respect of solution accuracy, and runtime performance by various classes of benchmark functions.</p><p> </p>
Pattern Analysis of Goals Scored in Malaysia Super League 2015
Authors: Razali Nazim , Mustapha Aida , Clemente Filipe Manuel , Ahmad Md Fauzi , Salamat Mohamad Aizi 
Published: January 2019

This paper is set to study the pattern of goals scored across 132 matches in 2015 Malaysian Super League (MSL). Despite of well-known researches in European football, no information in Malaysian football teams has been done consistently. To identify the patterns, this research focuses on goals scored based on timing that includes scoring frequency, the impact of first goal achieved by team towards the final match outcome, as well as the impact of having home advantage for matches during MSL 2015. The findings of this paper will provide useful information on MSL besides helping coaches with fresh insight for creating effective training and tactical plan as the time progressed during match. At the same time, players will also be more prepared for a consistent performance especially when training for matches as the visiting teams.
Performance Enhancement of Bidirectional NOC Router With and Without Contention for Reconfigurable Coarse Grained Architecture
Authors: Sougoumar Yazhinian , Sadasivam Tamilselvan 
Published: January 2019

<p>Network on Chip (NoC) router plays a vital role in System on Chip (SoC) applications. Routing operation is difficult to perform inside the SoC chip. Because it contains millions of chips in one single Integrated Circuit (IC), in which every chip consists of millions of transistors. Hence NoC router is designed to enable efficient routing operation in the SoC board. NoC router consists of Network Interconnects (NI), Crossbar Switches, arbiters, a routing logic and buffers. Conventional unidirectional router is designed by priority based Round Robin Arbiter (RRA). It produces more delay to find the priority, which comes from various input channels and more area is consumed in unidirectional router. Also if any path failure occurs, it cannot route the data through other output channel. To overcome this problem, a novel bidirectional NoC router with and without contention is proposed, which offers less area and high speed than the existing unidirectional router. A novel bidirectional NoC router consists of round robin arbiter, Static RAM, switch allocator, virtual channel allocator and crossbar switch. The proposed bidirectional router can route the data from any input channel to each and every output channel. So it avoids conflict situation and path failure problems. If any path fails, immediately it will take the alternative path through the switch allocator. The proposed routing scheme is applied into the coarse grained architecture for improving the speed of the interconnection link between two processing elements. Simulation is performed by ModelSim6.3c and synthesis is carried out by Xilinx10.1.</p>
Advanced Optimal For Three Phase Rectifier in Power Electronic System
Authors: Shneen Salam Waley 
Published: January 2019

Interest in the power electronic system which used in many applications is increasing day by day. So, many researchers have focused on the analyses, design and control of these systems. In this study, Optimal for Three Phase Rectifier in Power Electronic System control strategy has been proposed for PSO-PI fuzzy logic controller (FLC) based Three Phase Rectifier in Power Electronic System. Proposed Power Electronic System(PES) consists of input, isolation and output stages. In order to test dynamic performance of PSO-PI based PES, simulation study was carried out by MATLAB/Simulink. The results obtained from the PSO-PI based PES are not only superior in the rise time, settling time and overshoot but can prevent from voltage and has improved power quality.
Homotopy Analysis Method for the First Order Fuzzy Volterra-Fredholm Integro-differential Equations
Authors: A. Hamoud Ahmed , P. Ghadle Kirtiwant 
Published: January 2019

A fuzzy Volterra-Fredholm integro-differential equation (FVFIDE) in a parametric case is converted to its related crisp case. We use homotopy analysis method to find the approximate solution of this system and hence obtain an approximation for the fuzzy solution of the FVFIDE. This paper discusses existence and uniqueness results and convergence of the proposed method.
Performance Improvement of MIMO-OSTBC System with BCH-TURBO Code In Rayleigh Fading Channel
Authors: Naima SOFI , Debbat FATIMA , Bendimerad Fethi Tarik 
Published: January 2019

Recently, OSTBCs has become a widespread technique for signal transmission over wireless channels because of their diversity gain, but there are not designed to achieve an additional coding gain. Hence, OSTBCs must be concatenated with an external code which allows a significant coding gain.FEC (forward error correction) is a technique used for detecting and possibly correcting errors that can occur when messages are transmitted through a digital communication system, also for rendering the information more reliable. Thus, with staffing these coding techniques that are able to reach Shannon limits, in MIMO systems, better performances can be achieved by taking advantages of diversity and coding gains. The objective of this paper is to compare different FEC codes in Rayleigh fading channel and propose an appropriate code for MIMO-OSTBC systems. The simulation results reveal the performance of the proposed model
Video Quality Assessment through PSNR Estimation for Different Compression Standards
Authors: Deshpande Renuka Girish , Ragha Lata L , Sharma Satyendra Kumar 
Published: January 2019

<p align="center"><strong><em>Abstract</em></strong></p><p><em> There is a threefold increase in video traffic over internet. Due to this video compression has become important. Compression of video signals is quiet an interesting task but comes at the cost of video quality. After compression, two methods are scientifically applied to evaluate the quality of video; Subjective and objective analysis. In subjective approach the compressed video is shown to a group of viewers and their feedback is recorded Objective approach aims to set up a mathematical model which can approximate the results of subjective analysis. One such approach is based on the measurement of PSNR. When a signal is applied to the encoder for compression, too much of compression results in a signal with a smaller size but at the same time quality of the signal degrades. In this paper we will compare the quality of compressed video signals produced by H.264, Mpeg2 and Mpeg4 encoder based on the values of MSE and PSNR. Lower the value of MSE, higher will be the PSNR. Comparative plots of MSE, PSNR, SSIM and images for subjective analysis have been added at the end of this paper. </em></p>
Machine Learning with PySpark - Review
Authors: Bandi Raswitha , Amudhavel J , Karthik R 
Published: January 2019

<p>A reasonable distributed memory-based Computing system for machine learning is Apache Spark. Spark is being superior in computing when compared with Hadoop. Apache Spark is a quick, simple to use for handling big data that has worked in modules of Machine Learning, streaming SQL, and graph processing. We can apply machine learning algorithms to big data easily, which makes it simple by using Spark and its machine learning library MLlib, even this can be made simpler by using the Python API PySpark. This paper presents the study on how to develop machine learning algorithms in PySpark. </p>
Modelling of a Low Frequency Based Rectangular Shape Piezoelectric Cantilever Beam for Energy Harvesting Applications
Authors: Mohamed Ramizi , Sarker Mahidur R. , Mohamed Azah 
Published: January 2019

<p>Harvesting few amount of charge from environmental ambient sources namely, wind, thermal, heat, vibration, solar utilizing micro scale energy harvesting devices, offers vast view of powering for numerous portable low power electronic devices. However, power harvesting using piezoelectric crystal from low power ambient source nowdays has increasing popularity with the advantages of low cost, long life time, stability and clean energy. Recent trends have shown that most researchers are interested in designing a low resonance frequency vibration based energy harvesting devices despite of its challenges ahead. In this paper, a low frequency based rectangular shape piezoelectric cantilever beam has been developed for energy harvesting applications. The proposed vibration based low frequency cantilever beam using piezoelectric element has been developed by finite element analysis (FEA) employing COMSOL Multiphysics platform. The main goal of the study is to analyze the outcome of geometric model of a piezoelectric cantilever beam and to calculate the resonance frequency of the structure according to its length. The material of PZT-5H, has been considered to enhance the efficiency of the low frequency based cantilever beam. Finally, the proposed result is compared with other existing works.</p>
A Simulation of Energy Recycling Concept in Automotive Application Using Hybrid Approach
Authors: Samsudin Noor Azah , Syariff Aripin Muhammad , Ahmad Khalid Shamsul Kamal , Amri Nordin Nor Amirul 
Published: January 2019

<p>This paper presents development of a simulation to demonstrate a relatively new hybrid approach in improving energy resources that is applicable in automotive industry. The existing hybrid approach in automotive industry is considerably efficient in terms of energy saving by switching between fuel and electricity for energy resources. However, both energy resources confront various challenges. While the electricity resources require recharging, the fuel resources are scarce and expensive. Therefore, in this paper we aim to propose a relatively new hybrid approach, referred to as energy recycling concept equipped with coordination algorithm. To simulate the proposed energy recycling concept, a prototype of Electrical Control Unit (ECU) car is built. Then, an algorithm that coordinates battery charging is developed and integrated with the ECU. Finally, the simulation of the proposed energy recycling concept equipped with the coordination algorithm is evaluated on the prototype of the ECU car. The results show that the proposed energy recycling concept that allows switching between two sources of energy is applicable to operate the ECU car prototype.<strong><em> </em></strong></p>
Celebrity Face Recognition using Deep Learning
Authors: Binti Mat Kasim Nur Ateqah , Binti Abd Rahman Nur Hidayah , Ibrahim Zaidah , Abu Mangshor Nur Nabilah 
Published: January 2019

Face recognition is one of the well studied problems by researchers in computer visions. Among the challenges of this task are the occurrence of different facial expressions like happy or sad, and different views of the images such as front and side views. This paper experiments a publicly available dataset that consists of 200,000 images of celebrity faces. Deep Learning technique is gaining its popularity in computer vision and this paper applies this technique for face recognition problem. One of the techniques under deep learning is Convolutional Neural Network (CNN). There is also pre-trained CNN models that are AlexNet and GoogLeNet, which produce excellent accuracy results. The experimental results indicate that AlexNet is better than basic CNN and GoogLeNet for face recognition.
Object Recognition Inspiring HVS
Authors: Akbarpour Mohammadesmaeil , Mehrshad Nasser , Razavi Seyyed-Mohammad 
Published: January 2019

<p><span>Human recognize objects in complex natural images very fast within a fraction of a second. Many computational object recognition models inspired from this powerful ability of human. The Human Visual System (HVS) recognizes object in several processing layers which we know them as hierarchically model. Due to amazing complexity of HVS and the connections in visual pathway, computational modeling of HVS directly from its physiology is not possible. So it considered as a some blocks and each block modeled separately. One models inspiring of HVS is HMAX which its main problem is selecting patches in random way. As HMAX is a hierarchical model, HMAX can enhanced with enhancing each layer separately. In this paper instead of random patch extraction, Desirable Patches for HMAX (DPHMAX) will extracted. HVS for extracting patch first selected patches with more information. For simulating this block patches with more variance will be selected. Then HVS will chose patches with more similarity in a class. For simulating this block one algorithm is used. For evaluating proposed method, Caltech 5 and Caltech101 datasets are used. Results show that the proposed method (DPMAX) provides a significant performance over HMAX and other models with the same framework.</span></p>