bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic detection of rust disease of Lentil by machine learning system using microscopic images
Authors: Singh Kuldeep , Kumar Satish , Kaur Pawan 
Published: April 2019

<p>Accurate and early detection of plant diseases will facilitate mitigate the worldwide losses experienced by the agriculture area. MATLAB image processing provides quick and non-destructive means of rust disease detection. In this paper, microscopic image data of rust disease of <em>Lentil</em> was combined with image processing with depth information and developed a machine learning system to detect rust disease at early stage infected with fungus <em>Uromyces fabae</em> (Pers) de Bary. A novel feature set was extracted from the image data using local binary pattern (LBP) and HBBP (Brightness Bi-Histogram Equalization) for image enhancement. It was observed that by combining these, the accuracy of detection of the diseased plants at microscopic level was significantly improved. In addition, we showed that our novel feature set was capable of identifying rust disease at haustorium stage without spreading of disease. </p>
Fault detection in power transformers using random neural networks
Authors: Kaur Amrinder , Brar Yadwinder Singh , G. Leena 
Published: April 2019

This paper discuss the application of artificial neural network-based algorithms to identify different types of faults in a power transformer, particularly using DGA (Dissolved Gas Analysis) test. The analysis of Random Neural Network (RNN) using Levenberg-Marquardt (LM) and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms has been done using the data of dissolved gases of power transformers collected from Punjab State Transmission Corporation Ltd.(PSTCL), Ludhiana, India. Sorting of the preprocessed data have been done using dimensionality reduction technique, i.e., principal component analysis. The sorted data is used as inputs to the Random Neural Networks (RNN) classifier. It has been seen from the results obtained that BFGS has better performance for the diagnosis of fault in transformer as compared to LM.
Proposed T-Model to cover 4S quality metrics based on empirical study of root cause of software failures
Authors: Chhillar Dheeraj , Sharma Kalpana 
Published: April 2019

<span>There are various root causes of software failures. Few years ago, software used to fail mainly due to functionality related bugs. That used to happen due to requirement misunderstanding, code issues and lack of functional testing. A lot of work has been done in past on this and software engineering has matured over time, due to which software’s hardly fail due to functionality related bugs. To understand the most recent failures, we had to understand the recent software development methodologies and technologies. In this paper we have discussed background of technologies and testing progression over time. A survey of more than 50 senior IT professionals was done to understand root cause of their software project failures. It was found that most of the softwares fail due to lack of testing of non-functional parameters these days. A lot of research was also done to find most recent and most severe software failures. Our study reveals that main reason of software failures these days is lack of testing of non-functional requirements. Security and Performance parameters mainly constitute non-functional requirements of software. It has become more challenging these days due to lots of development in the field of new technologies like Internet of things (IoT), Cloud of things (CoT), Artificial Intelligence, Machine learning, robotics and excessive use of mobile and technology in everything by masses. Finally, we proposed a software development model called as T-model to ensure breadth and depth of software is considered while designing and testing of software. </span>
A new efficient way based on special stabilizer multiplier permutations to attack the hardness of the minimum weight search problem for large BCH codes
Authors: Joundan Issam Abderrahman , Nouh Said , Azouazi Mohamed , Namir Abdelwahed 
Published: April 2019

<span>BCH codes represent an important class of cyclic error-correcting codes; their minimum distances are known only for some cases and remains an open NP-Hard problem in coding theory especially for large lengths. This paper presents an efficient scheme ZSSMP (Zimmermann Special Stabilizer Multiplier Permutation) to find the true value of the minimum distance for many large BCH codes. The proposed method consists in searching a codeword having the minimum weight by Zimmermann algorithm in the sub codes fixed by special stabilizer multiplier permutations. These few sub codes had very small dimensions compared to the dimension of the considered code itself and therefore the search of a codeword of global minimum weight is simplified in terms of run time complexity. ZSSMP is validated on all BCH codes of length 255 for which it gives the exact value of the minimum distance. For BCH codes of length 511, the proposed technique passes considerably the famous known powerful scheme of Canteaut and Chabaud used to attack the public-key cryptosystems based on codes. ZSSMP is very rapid and allows catching the smallest weight codewords in few seconds. By exploiting the efficiency and the quickness of ZSSMP, the true minimum distances and consequently the error correcting capability of all the set of 165 BCH codes of length up to 1023 are determined except the two cases of the BCH(511,148) and BCH(511,259) codes. The comparison of ZSSMP with other powerful methods proves its quality for attacking the hardness of minimum weight search problem at least for the codes studied in this paper.</span>
Variable frequency drive optimization using torque ripple control and self-Tuning PI controller with PSO
Authors: Rekha Mudundi , Kumar Malligunta Kiran 
Published: April 2019

Drive’s output power must be restricted for the prevention of stresses over higher components in the input power system while utilizing a three-phase Variable Frequency Drive (VFD) which has powered from a single-phase AC source. To resolve this problem, we introduced a novel motor q-axis current (M-QAC) with torque ripple control (TRC) of an induction motor and self-tuning PI controller with particle swarm optimization (STP-PSO) for mitigating the stress over induction motor by the torque ripple elimination and controlling. Our proposed approach has an information related to the different parts stresses of the VFD which includes the terminal block and the diodes in the input side, DC bus capacitors, torque ripple, harmonics in the current and active performance for sudden changes in the speed and load. Our proposed model is simulated in MATLAB/Simulink environment. In this paper the standard dc-bus voltage ripple-based fold- back, q-axis average current fold-back and q-axis ripple current fold-back methods are utilized for the comparative analysis. Also the comparative analysis of proposed M-QAC, TRC and STP-PSO methodologies are provide with respect to steady-state values of peak-to-peak dc voltage (Vdc), peak-to-peak input current (IINPUT), input RMS current (IRMS), motor speed and the output power. Extensive simulated performance show that the STP-PSO obtained superior results over conventional standard dc-bus voltage ripple-based fold-back method, M-QAC and TRC schemes.
Emulated reactance and resistance by a SSSC incorporating energy storage device
Authors: Rao H. V. Gururaja , Prabhu Nagesh , Mala R. C. 
Published: April 2019

<p>Static Synchronous series compensator without energy storage device can exchange only reactive power with the network and can operate in limited operating range in two quadrants only. When energy storage device is connected at the DC bus of SSSC (SSSC – ES), it can also exchange real power with the network. Operating range of SSSC will be much broader and it covers all the four quadrants. However, emulated reactance and resistance by SSSC – ES is likely to affect the performance of a distance protection system. This paper presents a detailed model of an SMIB system with SSSC – ES. Injected voltage by SSSC – ES in all the four quadrants of operation is presented. Impact of operation of SSSC _ ES in different quadrants and various control strategies for SSSC – ES on impedance emulated by SSSC – ES during steady state condition and transient system disturbance is discussed. </p>
Introducing LQR-fuzzy for a dynamic multi area LFC-DR model
Authors: Devi Palakaluri Srividya , Santhi R.Vijaya 
Published: April 2019

It is well known that Load Frequency Control (LFC) model plays a vital role in electric power system design and operation. In the literature, much research works has stated on the advantages and realization of DR (Demand Response), which has proved to be an important part of the future smart grid. In an interconnected power system, if a load demand changes randomly, both frequency and tie line power varies. LFC-DR model is tuned by standard controllers like PI, PD, PID controllers, as they have constant gains. Hence, they are incapable of acquiring desirable dynamic performance for an extensive variety of operating conditions and various load changes. This paper presents the idea of introducing a DR control loop in the traditional Multi area LFC model (called LFC -DR) using LQR- Fuzzy Logic Control. The effect of DR-CDL i.e. (Demand Response Communication Delay Latency) in the design is also considered and is linearized using Padé approximation. Simulation results shows that the addition of DR control loop with proposed controller guarantees stability of the overall closed-loop LFC-DR system which effectively improves the system dynamic performance and is superior over a classical controller at different operating scenarios.
Transient stability enhancement using thyristor controlled series compensator
Authors: Salkuti Surender Reddy 
Published: April 2019

Stability is an important issue which determines the stable operation of power system. At present, the most practical available method of transient stability analysis is time domain simulation, in which the non-linear differential equations are solved by step by step method or network reduction techniques. In this paper, FACTS devices are used in the existing system for effective utilization of existing transmission resources. In this paper, the studies have been carried out in order to improve the transient stability of 5 bus system, and Western System Coordinating Council (WSCC) 9 bus system with fixed compensation on various lines, and the optimal location has been investigated for better results. To improve the transient stability margin further, a Thyristor Controlled Series Compensator (TCSC) has been used, and the results shows the effectiveness of the application of TCSC in improving the transient stability of power system.
Crosstalk in misaligned free space optical interconnects: modelling and simulation
Authors: Al-Ababneh Nedal 
Published: April 2019

<p>We introduce convenient model and an optimization scheme to optimize the signal-to-crosstalk ratio (SCR) in a free space optical interconnects (FSOIs) system that uses microlenses with finite circular apertures. In this model, we consider both the stray light crosstalk and the crosstalk due to the diffraction at the microlens apertures to evaluate the SCR. Using cylindrical form of Collins diffraction integral and the Laguerre–Gaussian (LG) beam model, we derive an approximate closed form formula for the optical field of a multimode LG beam propagating through circular apertured FSOIs by expanding the hard edge circular aperture function of the microlens in terms of complex Gaussian functions. The analyses indicate that the size of the detector is an important factor to optimize the SCR for both the apertured and the unapertured misaligned FSOIs system. The effect of higher order mode of the laser source on the SCR is also considered. </p>
Measurement of digital video broadcasting-second generation terestrial (DVB-T2) signal in Kuala Lumpur, Malaysia
Authors: Ya’acob Norsuzila , Tajudin Noraisyah , Zamiri Mashira Meri @ Mohamad , Yusof Azita Laily , Sarnin Suzi Seroja , Idris Azlina 
Published: April 2019

<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">DVB-T2 (Digital Video Broadcasting – Second Generation Terrestrial) is one of the latest technical standards being developed by the DVB Project for DTT (Digital Terrestrial Television). It is also known as digital broadcasting trough terrestrial system since 2006 and is an extension of the DVB-T system as a second generation program to improve efficiency of the total system. It is important to perform a research on the performance of DVB-T2 because Malaysia has launched the free-to-air digital TV project since 2016 hence there is a need to know how well the signal is being received by viewers. This research focuses on a DVB-T2 transmission process which involve the transmission from Menara Kuala Lumpur transmitter to receivers located at 100 different locations. The performance of DVB-T2 can be determined by measuring the field strength, MER (Module Error Ratio) and BERaLDPC (Bit Error Rate after Low Density Parity Check decoder), and then a comparison between DVB-T and DVB-T2 systems can be made. Equipments involved in the measurement are indoor antenna, distribution amplifier, waveform monitor, field strength meter, DVB-T2 decoder and TV set as the receiver. Results are recorded in Microsoft Excel and analyzed using MATLAB software. The result of the measurement shows92% of the test points had higher reading than the baseline value which means better reception of digital TV signal is delivered to the location.Comparison between DVB-T and DVB-T2 performance shows that field strength of the DVB-T2 system is slightly higher by 1.5 % – 3.8 % from DVB-T</span><p class="MsoNormal"><span style="font-size: 16.0pt; line-height: 107%; mso-bidi-font-style: italic;">Measurement of digital video broadcasting-second generation terestrial (DVB-T2) signal in Kuala Lumpur, Malaysia</span></p>
Investigation of the static current gain for InP/InGaAs single heterojunction bipolar transistor
Authors: Ouchrif Jihane , Baghdad Abdennaceur , Sshel Aicha , Badri Abdelmajid , Ballouk Abdelhakim 
Published: April 2019

<p>Heterojunction Bipolar Transistors are being used increasingly in communication systems due to their electrical performances. They are considered as excellent electronic devices. This paper presents an investigation of the static current gain β based on two technological parameters related to the device geometry for InP/InGaAs Single Heterojunction Bipolar Transistor (SHBT). These parameters are the base width and the emitter length . We used Silvaco’s TCAD tools to design the device structure, and to extract the static current gain β from I-V output characteristics figures. According to this investigation, we determined the optimal values of the examined parameters which allow obtaining the highest static current gain β.</p>
Indonesian online travel agent sentiment analysis using machine learning methods
Authors: Poernomo Abimanyu Dharma , Suharjito Suharjito 
Published: April 2019

Many companies use social media to support their business activities. Three leading online travel agent such as Traveloka, Tiket.com, and Agoda use Facebook for supporting their business as customer service tool. This study is to measure customer satisfaction of Traveloka, Tiket.com, and Agoda by analyzing Facebook posts and comments data from their fan pages. That data will be analyzed with three machine learning algorithms such as K-Nearest Neighbors (KNN), Naïve Bayes, and Support Vector Machine (SVM) to determine the sentiment. From the classification results, data will be selected with the highest f-score to be used to calculate the Net Sentiment Score used to measure customer satisfaction. The result shows that KNN result better than Naive Bayes and SVM based on f-score. Based on Net Sentiment Score shows companies that get the highest satisfaction value of Traveloka followed by Tiket.com and Agoda
Cervical cancer detection method using an improved cellular neural network (CNN) algorithm
Authors: Azamimi Abdullah Azian , Dickson Giong Aafion Fonetta , Hanin Zahri Nik Adilah 
Published: April 2019

<span>Cervical cancer is the second most common in Malaysia and the fourth frequent cancer among women in worldwide. Pap smear test is often ignored although it is actually useful, beneficial and essential as screening tool for cervical cancer. However, Pap smear images have low sensitivity as well as specificity. Therefore, it is difficult to determine whether the abnormal cells are cancerous or not. Recently, computer-based algorithms are widely used in cervical cancer screening. In this study, an improved cellular neural network (CNN) algorithm is proposed as the solution to detect the cancerous cells in real-time by undergoing the image processing of Pap smear images. A few templates are combined and modified to form an ideal CNN algorithm to detect the cancerous cells in total of 115 Pap smear images. A MATLAB based CNN is developed for an automated detection of cervix cancerous cells where the templates segmented the nucleus of the cells. From the simulation results, our proposed CNN algorithm can detect the cervix cancer cells automatically with more than 88% accuracy.</span>
Comparing bags of features, conventional convolutional neural network and AlexNet for fruit recognition
Authors: Abdul Hamid Nik Noor Akmal , Razali Rabiatul Adawiya , Ibrahim Zaidah 
Published: April 2019

This paper presents a comparative study between Bag of Features (BoF), Conventional Convolutional Neural Network (CNN) and Alexnet for fruit recognition. Automatic fruit recognition can minimize human intervention in their fruit harvesting operations, operation time and harvesting cost. On the other hand, this task is very challenging because of the similarities in shapes, colours and textures among various types of fruits. Thus, a robust technique that can produce good result is necessary. Due to the outstanding performance of deep learning like CNN and its pre-trained models like AlexNet in image recognition, this paper investigates the accuracy of conventional CNN, and Alexnet in recognizing thirty different types of fruits from a publicly available dataset. Besides that, the recognition performance of BoF is also examined since it is one of the machine learning techniques that achieves good result in object recognition. The experimental results indicate that all of these three techniques produce excellent recognition accuracy. Furthermore, conventional CNN achieves the fastest recognition result compared to BoF, and Alexnet.
Optimal sizing and location of distributed generation for loss minimization using firefly algorithm
Authors: Kamarudin Muhamad Najib , Tengku Hashim Tengku Juhana , Musa AbdulHamid 
Published: April 2019

<span>Distributed generation (DG) plays an important role in improving power quality as well as system realibility. As the incorporation of DG in the power distribution network creates several problems to the network operators, locating a suitable capacity and placement for DG will essentially help to improve the quality of power delivery to the end users. This paper presents the simulation of an application of firefly algorithm (FA) for optimally locating the most suitable placement and capacity of distributed generation (DG) in IEEE 33-bus radial distribution network. This strategy aims at minimizing losses together with improving the voltage profile in distribution network. The losses in real power and voltages at each bus are obtained using load flow analysis which was performed on an IEEE 33-bus radial distribution network using forward sweep method. The proposed method comprises of simulation of the test system with DG as well as in the absence of DG in the system. </span><span>A comparison between the Firefly Algorithm (FA) with Genetic Algorithm (GA) is also demonstrated in this paper. The results obtained have proven that the Firefly Algorithm has a better capability at improving both the voltage profile and the power losses in the system.</span>
Reduced mutual coupling multiband MIMO patch antenna with swastik type mushroom EBG
Authors: Thirupathi Maturi , Harikrishna Baranikunta 
Published: April 2019

<p>This paper presents a reduced mutual coupling 1x2 rectangular patch antenna. The major disadvantage of the MIMO is mutual coupling. When two antennas are placed nearby mutual coupling occurs. When mutual coupling occurs decrease the channel capacity. Hence the propose system which resonates at first 2.5GHz, second is resonates at 5.4GHz. Two closely spaced antenna elements are separated by a distance of λmax/8. Here Swastik type mushroom EBG is introduced. EBG is placed between the two antennas. When EBG is placed between the two antennas good coupling reduction is obtained. This design is excellent isolation of -35dB and -25dB can be observed in the simulation results.</p>
Rain attenuation statistics over 5G millimetre wave links in Malaysia
Authors: Ghanim Mustafa , Alhilali Manhal , Din Jafri , Lam Hong Yin 
Published: April 2019

<p>Millimetre wave band is a solid contender to be utilized for the future 5G wireless systems deployment. Rain-induced attenuation is a major disadvantage at these frequencies. This paper presents statistics of rain-induced attenuation and rainfall data for two years of horizontally polarized links propagating at 38 GHz and 26 GHz over a terrestrial path link of 301 meters. From the analysed datasets, a rain rate around 116 mm/h exceeded at 0.01% of the time of an average year, while the links recorded 16 and 9.5 dB at the same percentage of time for 38 and 26 GHz respectively. The study aims to identify the prediction model that deliver most reasonable predictions for 5G links operating in Malaysian tropical climate. ITU-R P.530-17, Mello’s, and Ghiani’s models were all examined. Using ITU-R model, relative error margins of around 3.8%, 30% and 49.7% alongside 22.3, 9.5, 33% were obtained in 0.1%, 0.01% and 0.001% of the time for 26 and 38 GHz respectively. Curiously, ITU-R model demonstrates better predictions to measured rain attenuation with lower error probability. This study highlights the need for new prediction models for short path-length 5G links and helps to improve the design of terrestrial links operating at millimetre wave frequencies in tropical regions.</p>
Design of on-chip temperature-based digital signal processing for customized wireless microcontroller
Authors: R. Faezal S.F. , N. Isa M. , Taking S. , N. Mohyar S. , B. Jambek A. , Harun A. 
Published: April 2019

<span>Dramatic rises in power density and die sizes inside system-on-chip (SoC) design have led to the thermal issue. High temperatures or uneven temperature distributions may result not only in reliability issues, also has become the biggest issue that can limit the system performance. This paper presents the design and simulation of a temperature-based digital signal processing unit for modern system-on-chip design using the Verilog HDL. This design provides continuous monitoring of temperature and reacts to specified conditions. The simulation of the system has been done on Synopsys Software. The result showed that temperature monitoring process is within the temperature range due to the incorporation of an interrupt-based system and with an advantage of minimum chip area required.</span>