bluuebunny/crossref_metadata_2025 huggingface dataset:
Glaucoma detection of retinal images based on boundary segmentation
Authors: Alia Zainudin Noraina , Nazari Ain , Marzuki Mustafa Mohd , Wan Zakaria Wan NurShazwani , Surayahani Suriani Nor , Hafsha Wan Kairuddin Wan Nur
Published: February 2020

The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morphological processing and adaptive thresholding method is used to extract out optic disc and optic cup from fundus image. The proposed method is tested on two publicly available online databases: RIM-ONE and DRIONS-DB. On RIM-ONE database, the average PSNR value acquired is 0.01891 and MSE is 65.62625. Meanwhile, for DRIONS-DB database, the best PSNR is 64.0928 and the MSE is 0.02647. In conclusion, the proposed method can successfully filter out any unwanted noise in the image and are able to help clearer optic disc and optic cup segmentation to be performed.
Swarm intelligent hyperdization biometric
Authors: Alhamdani Israa Mohammed , Ibrahim Yahya Ismail
Published: February 2020

At the last decade the importance of biometrics has been clearly configured due to its important in the daily life that starts from civil applications with security and recently terrorizing. A Footprint recognition is one of the effective personal identifications based on biometric measures. The aim of this research is to design a proper and reliable left human footprint biometrics system addressed (LFBS). In addition, to create a human footprint database which it is very helpful for numerous use such as during authentication. The existing footprint databases were very rare and limited. This paper presents a sturdy combined technique which merges between Image Processing with Artificial Intelligent technique via Bird Swarm Optimization Algorithm (BSA) to recognize the human footprint. The use of (BSA) enhance the performance and the quality of the results in the biometric system through feature selection. The selected features was treated as the optimal feature set in standings of feature set size. The visual database was constructed by capturing life RGB footprint images from nine person with ten images per person. The visual dataset images was pre-processed by successive operations. Chain Code is used with footprint binary image, then statistical features which represent the footprint features. These features were extracted from each image and stored in Excel file to be entered into the Bird Swarm Algorithm. The experimental results show that the proposed algorithm estimates, excellent results with a smaller feature set in comparison with other algorithms. Experimental outcomes show that our algorithm achieves well-organized and accurate result about 100% accuracy in relation with other papers on the same field.
An edge detection mechanism using L*A*B color-based contrast enhancement for underwater images
Authors: Sudhakara M , Meena M Janaki
Published: February 2020

In Ocean investigations, particularly those deployed by the Autonomous Underwater Vehicles, underwater object detection and recognition is an essential task. Edge detection places a key role and considered one of the pre-processing techniques for several deep learning applications. In an underwater environment, the illumination of light, turbulence in the water, suspended particles present in the seafloor are challenging issues to acquire the quality image. The two major problems in underwater imaging are light scattering and color change. In the former case, the vision sensors connected to the underwater vehicles or dive lights used by the divers themselves cause light dispersion and shadows in the seafloor. In the latter case, the occurrence of color distortion is mainly due to the attenuation of the light, hence the images are having dominant colors in the latter case. The conventional techniques are failed to detect the quality edges in the case of underwater images. Our mechanism focused, instead of applying the edge detection algorithm on the input image directly, it is better to apply edge detection algorithm after color correction and contrast enhancement using L*A*B model. Qualitative and quantitative test results demonstrate that the proposed mechanism is giving better results compared with state-of-the-art methods.
A multi-levels RNG permutation
Authors: Abdulsadah Ammar Khaleel , Aziz Lafta Abdullah , Dosh Mohammad
Published: February 2020

The paper proposes a new general method for producing a multilevel permutation functioning as an m-tree traversal. It is composed of two basic steps: a random number generator of period length equal m to determine which child to traverse, and recursive permutation in which permutated the subtree if found. The test results proved that the suggested method of permutation is successful depending on the correlation measure.
New algorithm for multi targets detection in clutter edge radar environments
Authors: Kamal Mustafa Subhi , Abdullah Jiwa
Published: February 2020

This paper deals with the problem of multi target detection that appears inside clutter cloud which represent the worst radar environments by using constant false alarm rate CFAR algorithm, in order to achieve maximum probability of detection with constant false alarm rate, to detect target in such environments it need to construct robust constant false alarm CFAR algorithm that excise the target spikes from CFAR window and deal with clutter edges in order to give best possible estimation to the noise background. Modified cell averaged (CA-CFAR) is analyzed and compared with Two important algorithms which are cell averaged (CA-CFAR) and ordered statistics (OS-CFAR) algorithms in additional to the modified CA-CFAR algorithm. All these algorithms were simulated with mat lab and applied them to matlab clutter test model that represent different radar environment cases. Tradeoff among these algorithms depending on their responses.
Solving wireless sensor network coverage problem using LAEDA
Authors: Khezri Shirin , Nazaari A Mahdi
Published: February 2020

Coverage improvement is one of the main problems in wireless sensor networks. Given a finite number of sensors, improvement of the sensor deployment will provide sufficient sensor coverage and save cost of sensors for locating in grid points. For achieving good coverage, the sensors should be placed in adequate places. In this article, estimation of distribution algorithm based on learning automata is presented for solving the sensor placement (LAEDA-SP) in distributed sensor networks by considering two factors: 1) the complete coverage and 2) the minimum costs. The proposed algorithm is a model based on search optimization method that uses a set of learning automata as a probabilistic model of high-quality solutions seen in the search process. It is applied in a various area with different size. The results not only confirmed the successes of using the new method in sensor replacement but also they showed that the proposed method performs more efficiently compared to the state-of-the-art methods such as simulated annealing (SA) and population-based incremental learning algorithms (PBIL).
Radial basis function neural network for 2 satisfiability programming
Authors: Alzaeemi Shehab , Mansor Mohd. Asyraf , Kasihmuddin Mohd Shareduwan Mohd , Sathasivam Saratha , Mamat Mustafa
Published: February 2020

Radial Basis Function Neural Network (RBFNN) is very prominent in data processing. However, improving this technique is vital for the NN training process. This paper presents an integrated 2 Satisfiability in radial basis function neural network (RBFNN-2SAT). There are two different types of training in RBFNN, namely no-training technique and half-training technique. The performance of the solutions via Genetic Algorithm (GA) training was investigated by comparing the Radial Basis Function Neural Network No-Training Technique (RBFNN- 2SATNT) and Radial Basis Function Neural Network Half-Training Technique (RBFNN- 2SATHT). The comparison of both techniques was examined on 2 Satisfiability problem by using a C# software that was developed for this experiment. The performance of the RBFNN-2SATNT and RBFNN-2SATHT in performing 2SAT is discussed in terms of root mean squared error (RMSE), sum squared error (SSE), mean absolute percentage error (MAPE), mean absolute error (MAE), number of the hidden neurons and CPU time. Results obtained from a computer simulation showed that RBFNN-2SATHT outperformed RBFNN-2SATNT.
Diacritic segmentation technique for arabic handwritten using region-based
Authors: Shiekh Ahmed Abdalla , Azmi Mohd Sanusi , Aziz Maslita Abd , Al-Mhiqani Mohammed Nasser , Bafjaish Salem Saleh
Published: February 2020

Arabic is a broadly utilized alphabetic composition framework on the planet, and it has 28 essential letters. The letters in order was first used to compose messages in Arabic, most prominently the Qur'an the holy book of Islam. However, Arabic language has diacritics in the word or letters which are not something extra or discretionary to the language, rather they are a vital piece of it. By changing some diacritics may change both the syntax and semantics of a word by turning a word into another. However, the current researches address the foreground image and consider the diacritics as noises or secondary images. Thus, it is not suitable for Arabic handwritten. The diacritics will be removed from the image and this will lead to losing some good features.   Furthermore, to extract the diacritics, the region-based segmentation technique is used. The image will be measured based on the region properties by first finding the connected component in binary image, and then we will determine the best area range measurement in that region for each image. The proposed technique region based has been tested in nine different images with different handwritten style, and successfully extracted secondary foreground images (diacritics) for each image.
A new hand gestures recognition system
Authors: Hamed AlSaedi Ahmed Kadem , AlAsadi Abbas H. Hassin
Published: February 2020

Talking about gestures makes us return to the historical beginning of human communication, because, in fact, there is no language completely free of gestures. People cannot communicate without gestures. Any action or movement without gestures is free of real feelings and cannot express the thoughts. The purpose from any hand gestures recognition system is to recognizes the hand gesture and used it to transfer a certain meaning or for computer control or and device. Our paper introduced a low cost system to recognize the hand gesture in real-time. Generally, the system divided into five steps, one to image acquisition, second to pre-processing the image, third for detection and segmentation of hand region, four to features extraction and five to count the numbers of fingers and gestures recognition. The system has coded by Python language, PyAutoGUI library, OS Module of Python and the OpenCV library.
Foreign exchange prediction based on indices and commodities price using convolutional neural network
Authors: Rassetiadi Rian , Suharjito Suharjito
Published: February 2020

The level of accuracy in predicting is the key in conducting forex trading activities in gaining profits. Some predictions are made only by using historical currency data to be predicted, this makes predictions less accurate because they do not consider external influences. This study examines external factors that can influence the results of predictions, by looking for the relationship between the value of indices such as NTFSE and S & P 500 and the value of commodities such as gold and silver to the prediction process of EUR / USD. Prediction carried out using a deep learning algorithm with the Convolutional Neural Network method uses 2 1-dimensional convolution layers with ReL activation. The data used is the value of Open, High, Low and Close prices on forex, indices and commodities which are combined into one with the close forex value target for the next 5 days. Testing of EUR / USD test data only gets MSE results of 0.00081894. While the results of testing of the combined test data between EUR / USD, indices and commodities producing MSE vary between 0.00068717 to 0.0109606 where the best combination is a combination of FTSE 100 and Natural Gas values. So it can be concluded that other factors included in predicting have an influence on the results obtained.
Investigating dengue outbreak in Tamil Nadu, India
Authors: Komal Kumar N , Tulasi R. Lakshmi , Vigneswari D.
Published: February 2020

Dengue has been indigenous to India in last decade. There was a major outbreak in the state of Tamil Nadu in 2017. Here, we investigate the dengue outbreak in parts of Tamil Nadu, India. Dengue case data were obtained from the hospital records in the Chennai district of Tamil Nadu. The data were analyzed using statistical approaches such as correlation and regression. The result shows that the dengue outbreak in Tamil Nadu during 2017 was due to the population, water stagnation, and sewage, whereas the human activity weren’t the cause of the dengue outbreak which caused 65 deaths. Male constitutes 54.71% whereas female accounted for 45.29% of dengue incidence in Tamil Nadu, majority deaths were children aged less than 10 years due to the outbreak of Dengue Hemorrhagic Fever (DHF). This investigation was evaluated using mathematical regressions, Geographically Weighted Regression (GWR) regression outperformed Ordinary Least Square (OLS) regression model in detecting dengue incidence. This investigation can be strengthened by implementing a surveillance system in parts of Tamil Nadu before an outbreak.
A new modification nonlinear conjugate gradient method with strong wolf-powell line search
Authors: Ahmed Chergui , Tahar Bouali
Published: February 2020

The conjugate gradient method has played a special role in   solving large-scale unconstrained Optimization problems. In this paper, we propose a new family of CG coefficients that   possess    sufficient descent conditions and global convergence properties this CG method is similar to (Wei et al) [7].  Global convergence   result is established under Strong Wolf-Powell line search. Numerical results to find  the  optimum solution of some test  functions show the   new proposed formula has the best result in CPU time and the number of iterations, and the number of gradient evaluations when it comparing with FR, PRP, DY, and WYL 
Identification of language in a cross linguistic environment
Authors: Thomas Merin , C A Dr Latha , Puthussery Antony
Published: February 2020

World has become very small due to software internationationalism. Applications of machine translations are increasing day by day. Using multiple languages in the social media text is an developing trend. .Availability of   fonts in the native language enhanced the usage of native text in internet communications. Usage of   transliterations of language   has become quite common. In Indian scenario current generations are   familiar to talk in native language but not to read and write in the native language, hence they started using English representation of native language in textual messages. This paper describes the   identification of the transliterated text in cross lingual environment .In this paper a Neural network model   identifies the prominent language in the text and hence the same can be used to identify the meaning of the text in the concerned language. The model is based upon Recurrent Neural Networks that found to be the most efficient in machine translations. Language identification can serve as a base for many applications in multi linguistic environment. Currently the South Indian Languages Malayalam, Tamil are identified from given text. An algorithmic approach of Stop words based model is depicted in this paper. Model can be also enhanced to address all the Indian Languages that are in use.
Modification of speed and current limiting performance of BLDC motor based on harmony search optimization method
Authors: Abbas Mohammed Qasim , Yassin Yaser Atta
Published: February 2020

The brushless DC (BLDC) motor is a multi-variable and non-linear system so that it's required more advanced explaining and controlling set. In this work, an algorithm is proposed based on the harmony search algorithm (HAS) method. HSA mimics music improvisation process to find the optimal solution. In BLDC motor, many constraints are required; speed performance and current limiting control are dominated. HAS is proposed to find the optimal PID parameters for the two speed and current-limiting controllers that are proposed in the drive. By Matlab/Simulink results, a good performance is shown compared with the classical method that absence current-limiting controller.
Data mining, fuzzy AHP and TOPSIS for optimizing taxpayer supervision
Authors: Jupri M. , Sarno Riyanarto
Published: February 2020

The achievement of accepting optimal tax need effective and efficient tax supervision can be achieved by classifying taxpayer compliance to tax regulations. Considering this issue, this paper proposes the classification of taxpayer compliance using data mining algorithms; i.e. C4.5, Support Vector Machine, K-Nearest Neighbor, Naive Bayes, and Multilayer Perceptron based on the compliance of taxpayer data. The taxpayer compliance can be classified into four classes, which are (1) formal and material compliant taxpayers, (2) formal compliant taxpayers, (3) material compliant taxpayers, and (4) formal and material non-compliant taxpayers. Furthermore, the results of data mining algorithms are compared by using Fuzzy AHP and TOPSIS to determine the best performance classification based on the criteria of Accuracy, F-Score, and Time required. Selection of the taxpayer's priority for more detailed supervision at each level of taxpayer compliance is ranked using Fuzzy AHP and TOPSIS based on criteria of dataset variables. The results show that C4.5 is the best performance classification and achieves preference value of 0.998; whereas the MLP algorithm results from the lowest preference value of 0.131. Alternative taxpayer A233 is the top priority taxpayer with a preference value of 0.433; whereas alternative taxpayer A051 is the lowest priority taxpayer with a preference value of 0.036.
Performance analysis of wireless sensor network with load balancing for data transmission using xbee zb module
Authors: Ardiansyah Ahmad Yusuf , Sarno Riyanarto
Published: February 2020

In general, research in the field of wireless sensor network (WSN) has never discussed the reliability aspect of network routing with router devices that can find new routes when damage occurs. To date, overloaded routers will be ignored without any response that gives control which can reduce the quality of network performance. Therefore, we propose research using the AODV routing, and Mesh routing algorithm to find other routes as an alternative when problems occur and using the Round Robbin based xbee algorithm on providing load balance control carried out by the router. The experiments on the performance of non-balancing networks and balancing were conducted. Both trials used quality of service (QoS) parameters as a guarantee of performance to be more effective and in line with expectations. Measurements performed by testing the parameters of packet loss, delay, throughput, and fault tolerance. The network performance in finding other alternative routes has been successfully carried out by transmitting 100 packets from the end device node to the coordinator node via the router based on distance variations from 0 to 100 meters. The recovery time required by the dead router to find another route was 10 seconds, this was related to the parameter delay, and fault tolerance. The experimental results of the non-balancing system showed an average 20 % packet loss in one transmission, meanwhile the packet loss was smaller than the previous experiment by 37%. Therefore, the WSN with balancing system was proven to be more effective that could improve QoS performance by 17%.
Illumination-robust face recognition based on deep convolutional neural networks architectures
Authors: Bendjillali Ridha Ilyas , Beladgham Mohammed , Merit Khaled , Taleb-Ahmed Abdelmalik
Published: February 2020

In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology. In this research paper, we present a Face Recognition (FR) system divided into three steps: The Viola-Jones face detection algorithm, facial image enhancement using Modified Contrast Limited Adaptive Histogram Equalization algorithm (M-CLAHE), and feature learning for classiﬁcation. For learning the features followed by classiﬁcation we used VGG16, ResNet50 and Inception-v3 Convolutional Neural Networks (CNN) architectures for the proposed system. Our experimental work was performed on the Extended Yale B database and CMU PIE face database. Finally, the comparison with the other methods on both databases shows the robustness and effectiveness of the proposed approach. Where the Inception-v3 architecture has achieved a rate of 99, 44% and 99, 89% respectively.
New symmetric key cipher capable of digraph to single letter conversion utilizing binary system
Authors: Kako Najdavan Abduljawad , Sadeeq Haval Tariq , Abrahim Araz Rajab
Published: February 2020

In this paper, a new Playfair cipher built on bits level symmetric key cryptographic was proposed for the purpose of converting pairs of letters (digraphs) into single letters. The proposed algorithm is capable to overcome many of the shortcoming and vulnerabilities that exist in the current classical version of Playfair algorithm. The Playfair cipher is exceedingly complex than a classical substitution cipher, but still simple to hack using automated tactics. It is famous as a digraph cipher because two letters are exchanged by other two letters. This destroys any solo letter occurrence statistics, but the digraph statistics still unaffected (frequencies of two letters). Unluckily letter pairs have a flatter distribution than the one letter frequencies, so this intricacy matters for solving the code using pen and paper procedures. The suggested encryption process is conducted as follows; letters are first arranged in a spiral manner in Polybius square, afterwards, each pair will be replaced utilizing before-after technique if we are arranging pairs horizontally and down-up technique (vertically). The former process produces pairs of Plaintext that will be converted to binary bit stream then will be divided over blocks with stable sizes. Bits of these blocks are taken from pairs then fit them into square matrix of suitable order to put the concept of row-wise and revers row-wise matrix. Bits of this matrix are split into 2x2 square matrixes. The sub-matrixes are formed 8 bits. Here the XNOR operation is taken into consideration for bitwise operation to generate the keys for decryption and produce the cipher-text.
An enhanced hybrid genetic algorithm for solving traveling salesman problem
Authors: Ali Zeravan Arif , Rasheed Subhi Ahmed , Ali Nabeel No’man
Published: February 2020

Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Salesman Problem (TSP), promoting the skillful algorithms to get the solution of TSP have been the burden for several scholars. For inquiring global optimal solution, the presented algorithm hybridizes genetic and local search algorithm to take out the uplifted quality results. The genetic algorithm gives the best individual of population by enhancing both cross over and mutation operators while local search gives the best local solutions by testing all neighbor solution. By comparing with the conventional genetic algorithm, the numerical outcomes acts that the presented algorithm is more adequate to attain optimal or very near to it. Problems arrested from the TSP library strongly trial the algorithm and shows that the proposed algorithm can reap outcomes within reach optimal. For more details, please download TEMPLATE HELP FILE from the website.
Enhancement of overall equipment effectiveness (OEE) data by using simulation as decision making tools for line balancing
Authors: Abd Rahman M. S. , Mohamad E. , Abdul Rahman A. A.
Published: February 2020

Nowadays, the digitalization of the production-based industries is driven by emerging technologies tools. The concept of lean manufacturing (LM) towards Industry 4.0 was developed where data analytics of engineering processes are analyzed and connected to reduce wastes. Many authors discuss about the benefits of extending data analytics as a method to support decision. However, the absence of comprehensive framework on how to embed LM and IT tools has existed as a new challenge. The aim of the research is to initiate a framework of model driven decision support system (MD-DSS) where data simulation and communication technologies are accompanied for manufacturing process improvement. In this research, Overall Equipment Effectiveness (OEE) data was captured through internet networking system and simulate to predict the improvement output. The main information flow route within MD-DSS are demonstrated in detail to show how decision-making process. To illustrate the applicability of the MD-DSS, it has been applied at food industry in Malaysia. The results show that the MD-DSS can easily be adopted in factories facilited with internet network to support decision-making of improvement plan activities.
A novel scheme for energy-efficient bridge layer in sensor-cloud
Authors: Saleh Almurisi Nasr Musaed , Srinivasulu Tadisetty
Published: February 2020

Recently, Sensor-Cloud has been widely utilized in various domains, providing real-time monitoring and remote observations. The sensory data is collected from different heterogeneous WSNs, uploaded to the cloud, virtualized, and served for many user applications. However, the survivability of the physical sensors is a challenge, where the nodes are battery-powered and must be utilized wisely. The need is to extend their lifetime and, thus, ensuring cloud functionality and user satisfaction. In this paper, we address the energy-efficiency of the physical sensors in the Sensor-Cloud paradigm. We propose a new scheme based on layered architecture, in which data transmitted to the cloud through a multi-hop routing. The new scheme introduces a novel algorithm to define a set of nodes called the bridge layer, receiving data from the cluster-head-layer and forwards to the sink node layer. Nodes in the bridge layer are selected according to their final score defined based on their energy-efficiency and distance-efficiency as given by the algorithm. Thus, ensuring a robust layer that helps in reducing the transmission energy and extending overall network lifetime. Our simulation results show an improved performance of our scheme over the scenario without the bridge layer, in terms of several parameters we considered.
Implementation of optical flow: good feature definition for tracking of heart cavity
Authors: Anwar Anwar , Sigit Riyanto , Basuki Achmad , Gunawan I Putu Adi Surya
Published: February 2020

Echocardiography is a method of examination using high-frequency sound waves to capture images of the heart organ structure. Echocardiography video is used by a doctor to analyze heart wall cavity movements and identify heart disease. Several points of view including the long axis, the two and four cavities in the left ventricle can be used in the examination of heart function. Cardiac assessment is still performed conventionally, which requires a level of thoroughness. This research proposes a method for tracking the movement of the heart wall. In this method, the good feature was defined only in the first frame. Furthermore, the whole frame will be processed by the optical flow method. Good feature definition consists of image enhancement, segmentation and tracking processes using the optical flow. Furthermore, the calculation of contour similarity from the proposed method by forming contour manually using 24 point initialization to draw the heart cavity. The proposed method shows the calculation results with a sensitivity of 90% and an accuracy of 87.451%.
Efficient method for breast cancer classification based on ensemble hoffeding tree and naïve Bayes
Authors: Alhayali Royida A. Ibrahem , Ahmed Munef Abdullah , Mohialden Yasmin Makki , Ali Ahmed H.
Published: February 2020

The most dangerous type of cancer suffered by women above 35 years of age is breast cancer. Breast Cancer datasets are normally characterized by missing data, high dimensionality, non-normal distribution, class imbalance, noisy, and inconsistency. Classification is a machine learning (ML) process which has a significant role in the prediction of outcomes, and one of the outstanding supervised classification methods in data mining is Naives Bayess Classification (NBC). Naïve Bayes Classifications is good at predicting outcomes and often outperforms other classifications techniques. Ones of the reasons behind this strong performance of NBC is the assumptions of conditional Independences among the initial parameters and the predictors. However, this assumption is not always true and can cause loss of accuracy. Hoeffding trees assume the suitability of using a small sample to select the optimal splitting attribute. This study proposes a new method for improving accuracy of classification of breast cancer datasets. The method proposes the use of Hoeffding trees for normal classification and naïve Bayes for reducing data dimensionality.
Optimization model for QoS based task scheduling in cloud computing environment
Authors: Potluri Sirisha , Rao Katta Subba
Published: February 2020

Shortest job first task scheduling algorithm allocates task based on the length of the task, i.e the task that will have small execution time will be scheduled first and the longer tasks will be executed later based on system availability. Min- Min algorithm will schedule short tasks parallel and long tasks will follow them. Short tasks will be executed until the system is free to schedule and execute longer tasks. Task Particle optimization model can be used for allocating the tasks in the network of cloud computing network by applying Quality of Service (QoS) to satisfy user’s needs. The tasks are categorized into different groups. Every one group contains the tasks with attributes (types of users and tasks, size and latency of the task). Once the task is allocated to a particular group, scheduler starts assigning these tasks to accessible services. The proposed optimization model includes Resource and load balancing Optimization, Non-linear objective function, Resource allocation model, Queuing Cost Model, Cloud cost estimation model and Task Particle optimization model for task scheduling in cloud computing environement. The main objectives identified are as follows. To propose an efficient task scheduling algorithm which maps the tasks to resources by using a dynamic load based distributed queue for dependent tasks so as to reduce cost, execution and tardiness time and to improve resource utilization and fault tolerance. To develop a multi-objective optimization based VM consolidation technique by considering the precedence of tasks, load balancing and fault tolerance and to aim for efficient resource allocation and performance of data center operations. To achieve a better migration performance model to efficiently model the requirements of memory, networking and task scheduling. To propose a QoS based resource allocation model using fitness function to optimize execution cost, execution time, energy consumption and task rejection ratio and to increase the throughput. QoS parameters such as reliability, availability, degree of imbalance, performance and SLA violation and response time for cloud services can be used to deliver better cloud services.
DWDM over FSO under the effect of different atmospheric attenuations
Authors: Maraha Heyam , Ameen Kameran Ali , Mahmood Ozlam Abdulhakeem , Aldawoodi Aras
Published: February 2020

In optical networks, Dense wavelength division multiplexing (DWDM) has been considered as a promising technique to meet the increasing bandwidth demands. It has been used to increase the capacity of long-haul optical transport systems such as free-space optics (FSO) and optical fiber. However, by applying DWDM over the FSO link, different challenges affect the performance system such as clear air, haze and rain atmospheric attenuations. This paper investigates eleven-channel DWDM over FSO based on the electrical linear equalizer that will improve the performance results at the receiver. The channels operate over (1561.42 nm, 1559.79 nm, 1558.17 nm, 1558.55 nm, 1554.94 nm, 1553.33 nm, 1551.72 nm, 1550.12 nm, 1548.51 nm, 1546.92 and 1545.32 nm) wavelengths that have separated based on the traditional International Telecommunication Union (ITU) grid. In the experiments, the system transmits 110 Gbit/s for FSO distances 9500 m, 3000 m, and 2500 m in superbly clear air, haze, and heavy haze atmospheric attenuations, respectively. Over different atmospheric attenuations, we evaluated our system performance using BER, eye diagram and the quality factor (Q-Factor). 
Utility-scale photovoltaic generators: a review on trends, grid code requirements and challenges
Authors: Tan Nadia M. L. , K. Ramasamy Agileswari , K. Ramachandaramurthy Vigna , Marsadek Marayati , Othman Mohd. R. , Ariffin Ibrahim
Published: February 2020

This paper provides an overview of the global trends in utility-scale photovoltaic (PV) installed capacity. This paper also presents a comparison of grid-connection requirements of six countries in the continents of Europe, Asia, Africa, and Australia for utility-scale PV generators in normal and abnormal grid conditions. Many country-based grid codes and international standards (IEEE 1547) for interconnection of inverter-based renewable energy generators are demanding stricter grid-connection compliance from utility-scale PV generators to ensure power system safety and reliability as its penetration level increases. This paper then discusses the economic and technical impacts, and explores the preparedness of PV generation systems in meeting the grid code requirements.
Comparative performance evaluation of four photovoltaic technologies in saharan climates of Algeria: ghardaïa pilot station
Authors: Tadjer Sid Ahmed , Idir Abdelhakim , Chekired Fathia
Published: February 2020

The aim of this paper is to present an evaluation of the performancerate of four different photovoltaic techniques in the Saharan environment. The purpose of this study is to investigate, analyse, discuss and illustrate the most effective of the different photovoltaic cell technologies (monocrystalline , amorphous silicon , poly-crystalline silicon  and cadmium telluridethin film  ) installed in Ghardaia which is located in southern of Algeria’s Sahara desert. In order to choose the most suitable technology in the Saharan climate conditions, the energy values produced by the plant were compared to those found by the PVSYST sizing software. The results show that thin-film and amorphous silicon panels produce low illumination, so they are the best choice for the Saharan environment.
DC inline plane test of silicone rubber samples with different filler for high-voltage insulation
Authors: Norddin Nurbahirah , Mastura Saadon Intan , Kamarudin Najwa , Rahim Norain , Abd Razak Jeefferie bin
Published: February 2020

This paper is about preparation of silicone rubber (SiR) samples with different filler for high-voltage insulation purpose. The fillers used were silica from waste glass, calcium carbonate from cockle shell, silica/calcium carbonate and wollastonite. All the fillers were crushed into powder and undergo internal mixer and hot press as a material preparation. It was expected that the combination of filler with silicone rubber would give better result when experiencing ageing process. The direct current (DC) inclined plane test was used to investigate the tracking and erosion on silicone rubber composites. The tracking length was observed between the top and bottom electrode. Comparison would then be made between the silicone rubbers with different fillers based on the result obtained from the experiment.
Green roof performance under malaysia tropical climates: a review
Authors: Fitriah Isa Nur , Kasmin Hartini , Yahya Norhaizura , Abdul Rahim Mustaqqim , Md Ghazaly Zuhayr
Published: February 2020

Green roof system is one of sustainable approach for energy consumption reduction and improving the aesthetic value of the built environment. The system has been adopted by most of developed countries; and in Malaysia, research on green roof studies are quite evolving however the implementation of the system is slow due to some perceptions and obstacles. Green roof has potential on providing benefits such as reduction on the urban heat island effect, reduces temperatures, pollution and improves the attenuation of stormwater. This paper will highlights on a preliminary review of the implementation green roof system in Malaysia and explores the performances of Malaysian green roof in order to highlight the performance of green roof under tropical climatic conditions using local configurations.
A novel approach for the fastest MPPT tracking algorithm for a PV array fed BLDC motor driven air conditioning system
Authors: Munisekhar S , Marutheswar G.V , Sujatha P , Vadivelu K R
Published: February 2020

The paper presents a modified constant voltage (MACV) maximum power tracking algorithm approach for PV array fed brushless DC (BLDC) motor drive for air conditioning application. The proposed algorithm tracks the power instantaneously for sudden changes in solar radiation. The PV power is fed to Voltage source inverter directly without conventional dc dc converter there by reducing the overall cost and high frequency switching losses and efficiency of the system is improved by reducing number of power conversion stages. The appropriateness of the voltage and current controller for PV fed BLDC motor for cooling applications is verified for dynamic changes of solar radiation. The proposed system is designed and modelled and results are verified using MATLAB/SIMULINK software. 
Energy conservation potentials of an office buildings in Northern Nigeria: A case study of Katsina secretariat complex
Authors: Rabiu Abbas Muhammad
Published: February 2020

The importance of energy conservation in our contemporary world cannot be overemphasized, efficient utilization of energy has significant impact in improving economy at all levels of human endeavour. No doubt, adequate and appropriate utilization of energy especially electrical energy boosts up any organizational developmental activities. Recently, research interest has emphasis towards efficient energy utilization and energy conservation as the effective means of reducing energy consumption in buildings thereby reducing its maintenance cost. This paper investigated and analysed the energy consumption characteristics of Katsina state secretariat complex for the period of 3 years (i.e. from 2014 to 2016) based on site surveys and analysis of the energy end users present, using the records of electricity utility bills and Automotive Gas Oil (AGO), being the two energy carriers of the complex. Records have shown that, the secretariat complex average electricity and AGO annual consumptions were found as 1045661.95 kWh and 116650.33 litres of AGO (which is equivalent to 1250491.54 kWh) respectively. The investigation revealed a distinct consumption pattern, indicating peak energy consumption during the hot months of April to August due to significant air conditioning requirements. The result of the investigation of the energy conservation potentials in the secretariat complex have shown that, energy savings of up to 6.5% of the total energy can be achieved by switching-off all security lights during the day. While turning off the air conditioners in the early morning hours of between 8am to 10am would provide a saving of up to 19% of the total energy. Furthermore, a saving of 16.5% of the total energy can be achieved when the incandescent lamps are replaced with the energy efficient ones. The energy conserving measures (ECMs) followed in this research has shown significant savings in terms of both energy and cost, and if well implemented can give way for a sustainable energy management of similar office buildings in future.
Prospective study of power generation from natural resources using hybrid system for remote area
Authors: Yaakub M. F. , Mohd Noh F. H. , I. Mohd Zali M. F. , H. Harun M.
Published: February 2020

Living in the 21st century, electricity has become a need in every society level. However, numbers of the remote area, especially in third world countries still facing difficulty to reach a grid-connected electricity due to various reasons. As such, this paper presents a prospective study of generating an electrical energy that is converted by utilizing natural resources from the sky. It is realized by implementing a hybrid solar-rainwater harvesting system. Combination of 12Vdc 3Watt solar cells and 3.7 Vdc 129mW pico-hydro implemented in the work has given a great yield reaching average 921 milliwatts of energy produced by the natural resources.
Enhancement the stability of power system using optimal location of FACTS devices
Authors: Abdullah Ali Najim , Ghadhban Ahmed Majeed , Hameed Hayder Salim , Hussein Husham Idan
Published: February 2020

This paper proposes a steady-state of the Static Var Compensator (SVC) & Thyristor Controlled Series Capacitor (TCSC) set up for enhancing the damping overall performance and growing the integral clearing time (CCT) of a power network. The indispensable clearing time is carried out through increasing the time fault interval until the gadget loses stability. Increasing the CCT can be contribute to reliability of the safety gadget, decrease the protection machine ranking and cost. In order to attain most enhancement of machine stability via optimizing location, sizing and control modes of SVC and TCSC. Models and methodology for putting and designing shunt FACT’s units SVC (injected reactive strength Q) and series FACT’s devices TCSC (chose capacitive region) are examined in a 6-bus system. Performance factors are described to show validation of SVC and TCSC on extraordinary conditions. It is proven that the SVC is better than TCSC. 
Smart grid in the context of industry 4.0: an overview of communications technologies and challenges
Authors: Qarabash Noor Ahmed , Sabry Sana Sabah , Qarabash Haneen Ahmed
Published: February 2020

The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG systems. In addition, the paper highlights challenges and issues that need to be addressed for a successful implementation of SG. Finally, we provide suggestions for future
 research directions. 
Comparative analysis of positive output super lift DC-DC luo converters
Authors: Adlakha Richa , Khosla Anita , Joshi Dheeraj
Published: February 2020

Due to the advancement in the semiconductor technologies, DC-DC converters are gaining the importance in several industrial applications. They form the core of the switched mode power supplies which are used in real time applications. The performance of the conventional converter is affected by the parasitic elements and their voltage gain is also limited. To improve upon this, Super lift converters converter were developed by Luo. Voltage lift technique increases the voltage in geometric progression .These super lift converter are classified as positive output and negative output which are further classified into different series. In this paper series of Positive output Super lift converter topologies are analyzed. The proportional –integral controller is employed to theses converter in the paper. These converters boost the voltage up to three times the input voltage and gaining importance in Electric vehicles and Solar powered applications. The simulations are carried in PSIM.
Eyelids, eyelashes detection algorithm and houghtransform method for noise removal in iris recognition
Authors: Nadia Bounegta , Abdessalam Bassou , Mohamed Beladgham
Published: February 2020

The biometric system is based on human’s behavioral and physical characteristics. Among all of these, iris has unique structure, higher accuracy and it can remain stable over a person’s life. Iris recognition is the method by which system recognize a person by their unique identical feature found in the iris. Iris recognition technology includes four subsections as, capturing of the iris image, segmentation, extraction of the needed features and matching. This paper is a detail description of eyelids; eyelashes detection technique and Hough transform method applied on iris image. 
Computer control of teaching enhancement by communication networked
Authors: Tawfeeq Nada N. , Marie Mehdi J. , Gaeid Khalaf S
Published: February 2020

Enhancement of teaching and education is crucial. This enhancement is rapidly improved through combining communication and technology resulting in various benefits (particularly the wireless Technologies (WT)). Such combination encourages lecturers to meet the worldwide demand for changing traditional teaching techniques to technology-based methods. Wireless system networks (WSNs) represent systems of smart devices that arelinked wirelessly. In addition, these devices are characterized by having a bandwidth of bounded communication, abilities of sensing and computation. For performing operations of control, this system employs a Flywheel Position Control System (FW PCS) as a plant node. This study utilizes the True Time 1.5 MATLAB/Simulink platform for simulating and implementing the WSN mathematical model with wireless networks. The simulation is carried out between plant nodes and controller using the IEEE 802.15.4 standard (also called ZigBee) via protocols of Wi-Fi. The suggested E-learning model comprises a set of properties that can encourage and enhance the level of students in various learning purposes and stages. 