bluuebunny/crossref_metadata_2025 huggingface dataset:
Parametric Optimization of Laser Additive Manufacturing of Inconel 625 Using Taguchi Method and Grey Relational Analysis
Authors: Yang Bo , Lai Youbin , Yue Xiang , Wang Dongyang , Zhao Yuhui
Published: June 2020

In order to improve the forming quality of the Inconel 625 cladding layer and make it to be more widely used. This paper addresses an experimental investigation on the influence of major process parameters like laser power, scanning speed, powder feed rate, and overlapping rate along with their interactions on surface roughness and width error of laser additive manufacturing process for forming Inconel 625 samples. Taguchi method and grey relational analysis were used to optimize the selected parameters, and the verification tests were carried out. The change of microhardness and microstructure in the overlapping zone and nonoverlapping zone of the cladding layer were studied by microhardness tester and scanning electron microscopy (SEM). The results show that the most significant effect in processing parameters on surface roughness and width error are both overlapping rate, and the optimal levels of laser power, scanning speed, powder feeder rate, and overlapping rate are 1800 W, 8 mm/s, 10 g/min, and 30%, respectively. Analysis of microstructure and composition showed that the content of Cr was high both in the Laves phase and matrix, the content of Nb in the Laves phase increased significantly and reached up to 24.48 wt%, and the Laves in the nonoverlapping zone was more compact than the overlapping zone.
On Efficient Monitoring of Weibull Lifetimes Using Censored Median Hybrid DEWMA Chart
Authors: Raza Syed Muhammad Muslim , Ali Sajid , Shah Ismail , Wang Lichen , Yue Zhen
Published: June 2020

A control chart named as the hybrid double exponentially weighted moving average (HDEWMA) to monitor the mean of Weibull distribution in the presence of type-I censored data is proposed in this study. In particular, the focus of this study is to use the conditional median (CM) for the imputation of censored observations. The control chart performance is assessed by the average run length (ARL). A comparison between CM-DEWMA control chart and CM-based HDEWMA control chart is also presented in this article. Assuming different shift sizes and censoring rates, it is observed that the proposed control chart outperforms the CM-DEWMA chart. The effect of estimation, particularly the scale parameter estimation, on ARL is also a part of this study. Finally, a practical example is provided to understand the application and to investigate the performance of the proposal in practical scenarios.
Bioinformatical Analysis of miRNA‐mRNA Interaction Network Underlying Macrophage Aging and Cholesterol‐Responsive Difference between Young and Aged Macrophages
Authors: Li Jianqing , Yin Xue , Zhang Bingyu , Li Chen , Lu Peirong
Published: June 2020

Purpose. Macrophage aging is involved with the occurrence and progression of age‐related macular degeneration (AMD). The purpose of this study was to identify the specific microRNAs (miRNA), mRNAs, and their interactions underlying macrophage aging and response to cholesterol through bioinformatical analysis in order to get a better understanding of the mechanism of AMD. Methods. The microarray data were obtained from Gene Expression Omnibus (accession GSE111304 and GSE111382). The age‐related differentially expressed genes in macrophages were identified using R software. Further miRNA‐mRNA interactions were analyzed through miRWalk, mirTarBase, starBase, and then produced by Cytoscape. The functional annotations including Gene Ontology and KEGG pathways of the miRNA target genes were performed by the DAVID and the STRING database. In addition, protein‐protein interaction network was constructed to identify the key genes in response to exogenous cholesterol. Results. When comparing aged and young macrophages, a total of 14 miRNAs and 101 mRNAs were detected as differentially expressed. Besides, 19 validated and 544 predicted miRNA‐mRNA interactions were detected. Lipid metabolic process was found to be associated with macrophage aging through functional annotations of the miRNA targets. After being treated with oxidized and acetylated low‐density lipoprotein, miR‐714 and 16 mRNAs differentially expressed in response to both kinds of cholesterol between aged and young macrophages. Among them, 6 miRNA‐mRNA predicted pairs were detected. The functional annotations were mainly related to lipid metabolism process and farnesyl diphosphate farnesyl transferase 1 (FDFT1) was identified to be the key gene in the difference of response to cholesterol between aged and young macrophages. Conclusions. Lipid metabolic process was critical in both macrophage aging and response to cholesterol thus was regarded to be associated with the occurrence and progression of AMD. Moreover, miR‐714‐FDFT1 may modulate cholesterol homeostasis in aged macrophages and have the potential to be a novel therapeutic target for AMD.
Composite Clustering Sampling Strategy for Multiscale Spectral-Spatial Classification of Hyperspectral Images
Authors: Li Chenming , Qu Xiaoyu , Yang Yao , Yao Dan , Gao Hongmin , Hua Zaijun
Published: June 2020

In recent years, many high-performance spectral-spatial classification methods were proposed in the field of hyperspectral image classification. At present, a great quantity of studies has focused on developing methods to improve classification accuracy. However, some research has shown that the widely adopted pixel-based random sampling strategy is not suitable for spectral-spatial hyperspectral image classification algorithms. Therefore, a composite clustering sampling strategy is proposed, which can greatly reduce the overlap between the training set and the test set, while making sample points in the training set sufficiently representative in the spectral domain. At the same time, in order to solve problems of a three-dimensional Convolutional Neural Network which is commonly used in spectral-spatial hyperspectral image classification methods, such as long training time and large computing resource requirements, a multiscale spectral-spatial hyperspectral image classification model based on a two-dimensional Convolutional Neural Network is proposed, which effectively reduces the training time and computing resource requirements.
A probabilistic multi-objective approach for FACTS devices allocation with different levels of wind penetration under uncertainties and load correlation
Authors: EL-Azab M. , Omran W. A. , Mekhamer S. F. , Talaat H. E. A.
Published: June 2020

This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the Multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30-bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
The maximum power point tracking based-control system for small-scale wind turbine using fuzzy logic
Authors: Ngo Quang-Vi , Yi Chai , Nguyen Trong-Thang
Published: June 2020

This paper presents the research on small-scale wind turbine systems based on the Maximum Power Point Tracking (MPPT) algorithm. Then propose a new structure of a small-scale wind turbine system to simplify the structure of the system, making the system highly practical. This paper also presented an MPPT-Fuzzy controller design and proposed a control system using the wind speed sensor for small-scale wind turbines. Systems are simulated using Matlab/Simulink software to evaluate the feasibility of the proposed controller. As a result, the system with the MPPT-Fuzzy controller has much better quality than the traditional control system.
The impact of high temperature and irradiance source on the efficiency of polycrystalline photovoltaic panel in a controlled environment
Authors: Ogbulezie Julie C. , Njok Armstrong O. , Panjwani Manoj Kumar , Panjwani Suresh K.
Published: June 2020

Solar cells are highly sensitive to temperature, which affects its operating parameters. The study has its aim in accessing the impact of temperature (in excess above the maximum operating cell temperature) and irradiance source on the efficiency of polycrystalline photovoltaic (PV) solar panels in an environment where the temperature and irradiance level can be fully controlled. For the study to achieve its aim, a solar box and tungsten light bulbs were used to create an environment where the irradiance level and the temperature can be controlled. The solar panel was placed inside the solar box facing the light source while the irradiance level and temperature were measured and held constant. Results show a steady decrease in voltage with increasing temperature while the performance ratio and efficiency of the photovoltaic module followed a similar trend as that of voltage once the temperature exceeds the maximum operating cell temperature. Results also show the output voltage of the photovoltaic to be higher under the tungsten light than the sun, but the efficiency achieved by the photovoltaic under the sun far exceeds that obtained under the tungsten light.
Source current harmonic mitigation of distorted voltage source by using shunt active power filter
Authors: Mahmoud Muhammad Ossama , Mamdouh Wael , Khalil Hamdy
Published: June 2020

In this paper, three-phase, four-wire shunt active power filter (SAPF) is utilized to mitigate system harmonics of distorted voltage source for unbalanced and nonlinear loads. Basically, the source voltage should be pure sinusoidal waveform to get a good mitigation of source current harmonics. In this under study system, the source voltage is assumed to be harmonic distortion non-sinusoidal voltage source. The phase locked loop (PLL) control circuit is wielded for extracting the fundamental component of the distorted source voltage to use it as an input signal to the SAPF control. Another input signal to the SAPF is the distorted load current. The SAPF control system uses (p-q) theory to calculate the optimum instantaneous current to be injected by the SAPF to mitigate the source current harmonics even the source voltage is harmonic distorted. MATLAB/SIMULINK software package is utilized to simulate the system under study. The effect of SAPF is tested when it’s used with and without the PLL control circuit. The simulation results show that, the THD of source current when using the PLL control circuit is improved to comply with the harmonic limits given in the IEEE 519-1992 and IEC 61000-4-7 standards.
DC performance analysis of a 20nm gate lenght n-type silicon GAA junctionless (Si JL-GAA) transistor
Authors: Merad Faiza , Guen-Bouazza Ahlam
Published: June 2020

With integrated circuit scales in the 22-nm regime, conventional planar MOSFETs have approached the limit of their potential performance. To overcome short channel effects 'SCEs' that appears for deeply scaled MOSFETs beyond 10nm technology node many new device structures and channel materials have been proposed. Among these devices such as Gate-all-around FET. Recentely, junctionless GAA MOSFETs JL-GAA MOSFETs have attracted much attention since the junctionless MOSFET has been presented. In this paper, DC characteristics of an n-type JL-GAA MOSFET are presented using a 3-D quantum transport model .This new generation device is conceived with the same doping concentration level in its channel source/drain allowing to reduce fabrication complexity . The performance of our 3D JL-GAA structure with a 20nm gate length and a rectangular cross section have been obtained using SILVACO TCAD tools allowing also to study short channel effects. Our device reveals a favorable on/off current ratio and better SCE characteristics compared to an inversion-mode GAA transistor. Our device reveals a threshold voltage of 0.55 V, a sub-threshold slope of 63mV / decade which approaches the ideal value, an Ion / Ioff ratio of 10e + 10 value and a drain induced barrier lowring (DIBL) value of 98mV / V.
Artificial neural network based unity power factor corrector for single phase DC-DC converters
Authors: Attia Hussain
Published: June 2020

Due to the negative effects of the non-linear semiconductor devices and the passive electrical components (inductor and capacitor) in the converter circuits, and that are deteriorating the power factor (PF) and total harmonics distortion (THD) of grid current, this study proposes a novel unity PF correction controller based on a new algorithm of neural network to improve the performance of a single phase boost DC-DC converter with respect to the mentioned concerns. The controller guarantees stable load voltage. The PF corrector, firstly measures the phase shift between grid voltage and grid current waveforms, then through a new artificial neural network (ANN) algorithm, a suitable duty cycle is predicted to guide and control the converter to reduce the phase shift between grid voltage and grid current as possible to have maximum PF which is unity PF, and to improve the THD level of grid current. The proposed system is simulated and evaluated via Simulink of MATLAB, the simulation results are collected at constant duty cycle and at controlled duty cycle through the proposed PF controller using different loads. The presented PF controller guarantees the unity power factor, and enhances the grid alternating current THD.
Internet service providers responsibilities in botnet mitigation: a Nigerian perspective
Authors: Okesola Julius Olatunji , Adebiyi Marion , Osi-Okeke Tochukwu , Adewale Adeyinka , Adebiyi Ayodele
Published: June 2020

Botnet-based attack is dangerous and extremely difficult to overcome as all the primary mitigation methods are passive and limited in focus. A combine efforts of Internet Service Providers (ISPs) are better guides since they can monitor the traffic that traverse through their networks. However, ISPs are not legally banded to this role and may not view security as a primary concern. Towards understudying the involvement of ISPs in Botnet mitigation in Nigeria, this study elicited and summarized mitigation measures from scientific literatures to create a reference model which was validated by structured interview. Although, ISPs role is seen to be voluntary and poorly incentivized, the providers still take customers security very serious but concentrate more on preventive and notification measures.
The effect of recovery satisfaction on citizens loyalty perception: a case study of mobile government services
Authors: Almarashdeh Ibrahim
Published: June 2020

Use of mobile services is an integral part of today’s life. Organizations, government agencies as well as service providers in the market employ mobile services or application in reaching their citizens or users worldwide. Notably, service failure issues might frustrate users in using mobile service, but usually, service providers would employ the strategy of recovery as solution. Recovery strategy aims to sustain the relationship with users following service failure. Somehow, the factors that might impact recovery process are unclear. It is also unclear if users will use the service again following the completion of recovery process. Hence, in this study, a survey on 743 adults was carried out, and the data were analyzed using SEM to determine the factors that impact users’ recovery satisfaction the most and the impact of recovery satisfaction on citizens loyalty to use mobile government in the future. The finding of this study illustrated that expect of self-efficacy, all factors proposed in the research model found to has a significant impact on recovery satisfaction. Among all the supported hypothesis, the highest impact on recovery satisfaction comes from perceived trust in government as the initial predictor to use the service
Feature selection for multiple water quality status: Integrated bootstrapping and SMOTE approach in imbalance classes
Authors: Uyun Shofwatul , Sulistyowati Eka
Published: June 2020

STORET is one method to determine the river water quality into four classes (very good , good, medium and bad) based on the data of water for each attribute or feature. The success of the formation of pattern recognition model much depends on the quality of data. There are two issues as the concern of this research as follows: the data having disproportionate amount among the classes (imbalance class) and the finding of noise on its attribute. Therefore, this research integrates the SMOTE Technique and bootstrapping to handle the problem of imbalance class. While an experiment is conducted to eliminate the noise on the attribute by using some feature selection algorithms with filter approach (information gain, rule, derivation, correlation and chi square). This research has some stages as follows: data understanding, pre-processing, imbalance class, feature selection, classification and performance evaluation. Based on the result of testing using 10-fold cross validation, it shows that the use of the SMOTE-bootstrapping technique is able to increase the accurate value from 83.3% to be 98.8%. While the process of noise elimination on the data attribute is also able to increase the accuracy to be 99.5% (the use of feature subset produced by the information gain algorithm and the decision tree classification algorithm).
Random forest application on cognitive level classification of E-learning content
Authors: Thomas Benny , J. Chandra
Published: June 2020

The e-learning is the primary method of learning for most learners after the regular academics studies. The knowledge delivery through e-learning technologies increased exponentially over the years because of the advancement in internet and e-learning technologies. Knowledge delivery to some people would never have been possible without the e-learning technologies. Most of the working professional do focused studies for carrier advancement, promotion or to improve the domain knowledge. These learner can find many free e-learning web sites from the internet easily in the domain of interest. However it is quite difficult to find the best e-learning content suitable for their learning based on their domain knowledge level. User spent most of the time figuring out the right content from a plethora of available content and end up learning nothing. An intelligent framework using machine learning algorithms with Random Forest Classifier is proposed to address this issue, which classifies the e-learning content based on its difficulty levels and provide the learner the best content suitable based on the knowledge level .The frame work is trained with the data set collected from multiple popular e-learning web sites. The model is tested with real time e-learning web sites links and found that the e-contents in the web sites are recommended to the user based on its difficulty levels as beginner level, intermediate level and advanced level.
Integral sliding-mode controller for maximum power point tracking in the grid-connected photovoltaic systems
Authors: Tariba Nour-Eddine , Ikken Naima , Haddou Ahmed , Bouknadel Abdelhadi , El Omari Hafsa , El Omari Hamid
Published: June 2020

The output power generated in the photovoltaic modules depends both on the solar radiation and the temperature of the solar cells. To maximize the efficiency of the system, it is required to monitor the maximum power point of the photovoltaic system. For this purpose, monitoring the maximum power point (MPPT) of photovoltaic systems should be as quick and accurately as possible for increasing energy production, which ultimately increases the cost-efficiency of the photovoltaic system. This paper proposes a new approach for MPPT) using the concept of the integral sliding mode controller (ISMC) to ensure fast and precise monitoring of the peak power. The performance of the ISMC is significantly influenced by the choice of the sliding surface. To assess the reliability ISMC control, the results have been compared with those of a PI controller. The results obtained are used to evaluate the performance of the ISMC strategy under different climatic conditions. Finally, the effectiveness of the proposed solution is confirmed using simulations in PSIM tools and experimental results were used to evaluate the effectiveness of the proposed approach.
Multicast routing strategy for SDN-cluster based MANET
Authors: Naser Jaber Ibrahim , Kadhim Ahmed Jawad
Published: June 2020

The energy limitation and frequent movement of the mobile Ad hoc network (MANET) nodes (i.e., devices) make the routing process very difficult. The multicast routing problem is one of the NP-complete problems. Therefore, the need for a new power-aware approach to select an optimum multicast path with minimum power consumption that can enhance the performance and increase the lifetime of MANET has become urgent. Software defined network (SDN) is a new technique that can solve many problems of the traditional networks by dividing the architecture into data part and control part. This paper presents three power-aware multicast routing strategies for MANET. First one called a Reactive Multicast routing strategy for cluster based MANET by using SDN (RMCMS), second one called proactive multicast routing strategy for cluster based MANET by using SDN (PMCMS) and third one represents modification of PMCMS called M-PMCMS. Moreover, it produces a new mathematical model to build a multicast tree with minimum power consumption and takes into account the remaining power in each node. All proposed multicast strategies operate based on this mathematical model and aim to maximize the MANET lifetime by exploiting the advantages of SDN and clustering concepts. They consider the multicast tree with minimum power consumption as an optimal one. The simulation results illustrated that RMCMS is better than PMCMS, M-PMCMS, and MAODV in terms of power consumption and network overhead while M-PMCMS is the best one in terms of dropped packets ratio (DPR) and average end to end (E2E) delay.
Assessment of off-shore wind turbines for application in Saudi Arabia
Authors: Sundaram Arunachalam , Mas’ud Abdullahi Abubakar , Al Garni Hassan Z. , Adewusi Surajudeen
Published: June 2020

This paper presents models and economic analysis of ten different wind turbines for the region of Yanbu, Saudi Arabia using the hybrid optimization models for energy resources (HOMER) software. This study serves as a guide for decision makers to choose the most suitable wind turbine for Yanbu to meet the target of 58.7GW of renewable energy as part of Saudi Vision 2030. The analysis was carried out based on the turbines initial capital cost, operating cost, net present cost (NPC) and the levelized cost of energy (LCOE). Additionally, the wind turbines were compared based on their electricity production, excess energy and the size of the storage devices required. The results show that Enercon E-126 EP4 wind turbine has the least LCOE (0.0885 $/kWh) and NPC ($23.8), while WES 30 has the highest LCOE (0.142 $/kWh) and NPC ($38.3) for a typical load profile of a village in Yanbu.
Determining optimal location and size of capacitors in radial distribution networks using moth swarm algorithm
Authors: Duong Thanh Long , Nguyen Thuan Thanh , Phan Van-Duc , Nguyen Thang Trung 
Published: June 2020

In this study, the problem of optimal capacitor location and size determination (OCLSD) in radial distribution networks for reducing losses is unraveled by moth swarm algorithm (MSA). MSA is one of the most powerful meta-heuristic algorithm that is taken from the inspiration of the food source finding behavior of moths. Four study cases of installing different numbers of capacitors in the 15-bus radial distribution test system including two, three, four and five capacitors areemployed to run the applied MSA for an investigation of behavior and assessment of performances. Power loss and the improvement of voltage profile obtained by MSA are compared with those fromother methods. As a result, it can be concluded that MSA can give a good truthful and effective solution method for OCLSD problem.
Islanded microgrid congestion control by load prioritization and shedding using ABC algorithm
Authors: Mogaka L. O. , Nyakoe G. N. , Saulo Michael J.
Published: June 2020

The continued growth in load demand and the gradual change of generation sources to smaller distributed plants utilizing renewable energy sources (RESs), which supply power intermittently, is likely to strain existing power systems and cause congestion. Congestion management still remains a challenging issue in open access transmission and distribution systems. Conventionally, this is achieved by load shedding and generator rescheduling. In this study, the control of the system congestion on an islanded micro grid (MG) supplied by RESs is analyzed using artificial bee colony (ABC) algorithm. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time during islanding mode operation. This is to ensure as minimal load as possible is shed during a contingency that leads to loss of mains and ensure a congestion free microgrid operation. This is tested and verified on a modified IEEE 30-bus distribution systems on MATLAB platform. The results are compared with other algorithms to prove the applicability of this approach.
The optimal control system of the ship based on the linear quadratic regular algorithm
Authors: Nguyen Manh-Cuong , Vuong Duc-Phuc
Published: June 2020

In this paper, the authors propose an optimal controller for the ship motion. Firstly, the model and dynamic equations of the ship motion are presented. Based on the model of the ship motion, the authors build the linear quadratic regular algorithm-based control system of ship motion to minimize the error between the desired trajectory and the response trajectory. The task of the controller is to control the trajectory of the ship to coincide with the desired trajectory. The ship model and controller are built to investigate the system quality through Matlab-Simulink software. The results show that the quality of the hold control system is very high. The trajectory of a ship always follows the desired trajectory with very small errors.
Framework for propagating stress control message using heartbeat based IoT remote monitoring analytics
Authors: Akanksha Eisha
Published: June 2020

Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study.
The effectiveness of MgCeAl11O19:Tb3+ phosphor in enhancing the luminous efficacy and color quality of multi-chip white LEDs
Authors: Thi Phuong Loan Nguyen , Anh Nguyen Doan Quoc
Published: June 2020

In this research paper, we introduced yellow-green MgCeAl11O19:Tb3+ asa new phosphor ingredient to adapt to the quality requirements onthe chromatic homogeneity and emitted luminous flux of modern multi-chip white LED lights (MCW-LEDs). The results from experiments and simulation show that employing MgCeAl11O19:Tb3+ phosphor can lead to much better optical properties and therefore is a perfect supporting material to achieve the goals of the research. When the MgCeAl11O19:Tb3+ phosphor is added into the phosphorus composite which already contains YAG: Ce3+ particles, and the silicone glue, it affects the optical properties significantly. In other words, the concentration of this phosphor can determine the efficiency of lumen output and chromatic homogeneity of WLEDs. In specific, as the concentration of MgCeAl11O19:Tb3+ go up, the luminous yield will increase accordingly, though there is an insignificant decrease in CQS. Moreover, if the MgCeAl11O19:Tb3+ concentration reduce a little bit, it is possible to better the correlated color temperature uniformity and lumen efficacy of LED packages. In addition, the Mie scattering theory, Monte Carlo simulation and LightTools 8.3.2 software are employed to analyze and simulate the LED packages’ structure as well as the phosphor compound.
Design and analysis of optimized CORDIC based GMSK system on FPGA platform
Authors: Kajur Renuka , V. Prasad K.
Published: June 2020

The Gaussian minimum shift keying (GMSK) is one of the best suited digital modulation schemes in the global system for mobile communication (GSM) because of its constant envelop and spectral efficiency characteristics. Most of the conventional GMSK approaches failed to balance the digital modulation with efficient usage of spectrum. In this article, the hardware architecture of the optimized CORDIC-based GMSK system is designed, which includes GMSK Modulation with the channel and GMSK Demodulation. The modulation consists of non-return zero (NRZ) encoder, an integrator followed by Gaussian filtering and frequency modulation (FM). The GMSK demodulation consists of FM demodulator, followed by differentiation and NRZ decoder. The FM Modulation and demodulation use the optimized CORDIC model for an In-phase (I) and quadrature (Q) phase generation. The optimized CORDIC is designed by using quadrant mapping and pipelined structure to improve the hardware and computational complexity in GMSK systems. The GMSK system is designed on the Xilinx platform and implemented on Artix-7 and Spartan-3EFPGA. The hardware constraints like area, power, and timing utilization are summarized. The comparison of the optimized CORDIC model with similar CORDIC approaches is tabulated with improvements.
Algorithm of detection, classification and gripping of occluded objects by CNN techniques and Haar classifiers
Authors: Useche Paula , Jimenez-Moreno Robinson , Martinez Baquero Javier
Published: June 2020

The following paper presents the development of an algorithm, in charge of detecting, classifying and grabbing occluded objects, using artificial intelligence techniques, machine vision for the recognition of the environment, an anthropomorphic manipulator for the manipulation of the elements. 5 types of tools were used for their detection and classification, where the user selects one of them, so that the program searches for it in the work environment and delivers it in a specific area, overcoming difficulties such as occlusions of up to 70%. These tools were classified using two CNN (convolutional neural network) type networks, a fast R-CNN (fast region-based CNN) for the detection and classification of occlusions, and a DAG-CNN (directed acyclic graph-CNN) for the classification tools. Furthermore, a Haar classifier was trained in order to compare its ability to recognize occlusions with respect to the fast R-CNN. Fast R-CNN and DAG-CNN achieved 70.9% and 96.2% accuracy, respectively, Haar classifiers with about 50% accuracy, and an accuracy of grip and delivery of occluded objects of 90% in the application, was achieved.
Glioblastomas brain tumour segmentation based on convolutional neural networks
Authors: Al-Hadidi Moh'd Rasoul , AlSaaidah Bayan , Al-Gawagzeh Mohammed
Published: June 2020

Brain tumour segmentation can improve diagnostics efficiency, rise the prediction rate and treatment planning. This will help the doctors and experts in their work. Where many types of brain tumour may be classified easily, the gliomas tumour is challenging to be segmented because of the diffusion between the tumour and the surrounding edema. Another important challenge with this type of brain tumour is that the tumour may grow anywhere in the brain with different shape and size. Brain cancer presents one of the most famous diseases over the world, which encourage the researchers to find a high-throughput system for tumour detection and classification. Several approaches have been proposed to design automatic detection and classification systems. This paper presents an integrated framework to segment the gliomas brain tumour automatically using pixel clustering for the MRI images foreground and background and classify its type based on deep learning mechanism, which is the convolutional neural network. In this work, a novel segmentation and classification system is proposed to detect the tumour cells and classify the brain image if it is healthy or not. After collecting data for healthy and non-healthy brain images, satisfactory results are found and registered using computer vision approaches. This approach can be used as a part of a bigger diagnosis system for breast tumour detection and manipulation.
Determining damages in ceramic plates by using discrete wavelet packet transform and support vector machine
Authors: Yumurtaci Mehmet , Gokmen Gokhan , Akinci Tahir Cetin
Published: June 2020

In this study, an analysis was conducted by using discrete wavelet packet transform (DWPT) and support vector machine (SVM) methods to determine undamaged and cracked plates. The pendulum was used to land equal impacts on plates in this experimental study. Sounds, which emerge from plates as a result of the impacts applied to undamaged and cracked plates, are sound signals used in the analysis and DWPT of these sound signals were obtained with 128 decompositions for feature extraction. The first four components, reflecting the characteristics of undamaged and cracked plates within these 128 components, were selected for enhancing the performance of the classifier and energy values were used as feature vectors. In the study, the SVM model was created by selecting appropriate C and γ parameters for the classifier. Undamaged and cracked plates were seen to be successfully identified by an analysis of the training and testing phases. Undamaged and cracked statuses of the plates that are undamaged and have the analysis had identified different cracks. The biggest advantage of this analysis method used is that it is high-precision, is relatively low in cost regarding experimental equipment and requires hardware.
A new perspective of refractive error calculation with mobile application
Authors: Brata Komang Candra , Hidayatulloh Mukhammad Sharif , Fanani Lutfi , Brata Adam Hendra
Published: June 2020

In many situations, not standardized and limited access to eye health care in several regions of Indonesia becomes the main challenge for myopia patients to measure and monitor their current refractive error condition. Many apps were proposed to provide low-cost alternative measurement tools rather than expensive tools such as Phoropter with Snellen chart and Retinoscopy, but still, those apps need an Internet connection and manually complex steps to operate. These conditions make myopia patients reluctant to use this kind of service. In this regard, we propose an intuitive diopter level measurement app based on mobile application setup, which implements the concept of measure the user face to smartphone screen distance for the rapid diopter calculation processes and at the same time provides a low-cost alternative refractive measurement tool. This paper highlights our experiences when developing a mobile application that can help patients with myopia measuring their blur line distances and evaluate their diopter levels independently. We conduct a number of human trials with the device on a controlled environment to demonstrate the ability of the proposed app to measure the diopter level. The experimental results show that the proposed app is quite successful in measuring the diopter level of myopia patients with a relatively small range of calculation errors compared to optometrist measurement results.
Development and testing of a thai website accessibility evaluation tool
Authors: Angkananon Kewalin , Wald Mike , Ploadaksorn Piyabud
Published: June 2020

This paper deals with the important problem that there is no help with the accessibility evaluations of Thailand’s web by developing and evaluating a new method and tool online, WebThai2Access, with experts, developers, and users with disabilities. This tool was evaluated by 30 developers, 30 hearing impaired people, 30 visually impaired people, and 30 elderly people. The developers evaluated the websites whereas experimental tasks were given to each disabled group based on the problems they had accessing web information. The developers found WebThai2Access very usable and the 15 test criteria were reliable for evaluating websites. The lower and upper 95% limits for confidence ratings of developers were minus or plus 10% for YouTube and Pantip websites and minus or plus 3% with the blind association website. The 95% lower and upper limits of confidence were minus or plus 5% for hearing impaired users, minus or plus 2% for elderly users and minus or plus 0% for visually impaired users. The results therefore showed WebThai2Access was reliable and accessible for developers whose evaluations reasonably well predicted website accessibility for users with disabilities.
Earlier stage for straggler detection and handling using combined CPU test and LATE methodology
Authors: Katrawi Anwar H. , Abdullah Rosni , Anbar Mohammed , Abasi Ammar Kamal
Published: June 2020

Using MapReduce in Hadoop helps in lowering the execution time and power consumption for large scale data. However, there can be a delay in job processing in circumstances where tasks are assigned to bad or congested machines called "straggler tasks"; which increases the time, power consumptions and therefore increasing the costs and leading to a poor performance of computing systems. This research proposes a hybrid MapReduce framework referred to as the combinatory late-machine (CLM) framework. Implementation of this framework will facilitate early and timely detection and identification of stragglers thereby facilitating prompt appropriate and effective actions.
Power quality improvement based on hybrid coordinated design of renewable energy sources for DC link channel DSTATCOM
Authors: Hussain Ali Nasser , Ali Ahmed Jadaan , Ahmed Firas Saaduldeen
Published: June 2020

This paper presents a comprehensive analysis of power quality for static synchronous compensator on the distribution power system (DSTATCOM) when a different types of energy sources are used to supply the dc link channel of DSTATCOM. These types of power supplies have a different effect on the compensation of DSTATCOM due to operation nature of these sources. The dynamic response of the DSTATCOM has been investigated that produced by individual and hybrid energy sources to evaluate the influence of these sources in terms of time response, compensation process and reduce the harmonics of current for source. Three cases have been considered in this study. First the photovoltaic (PV) cells alone second the battery storage alone and third a hybrid coordinated design between (PV cells with battery storage) is used. A boost Dc-Dc circuit has been connected to a photovoltaic cell with Maximum Power Point Tracking (MPPT) while a Dc-Dc buck-boost circuit is used with a battery. High coordination between PV and battery circuits in the hybrid system is used in order to improve the performance. A synchronous reference frame (SRF) with unit vector has been used to control the STATCOM circuit. The simulation results show that the hybrid design has the superiority response compared to the individual sources.
Y2O3:Ho3+ and ZnO:Bi3+: a selection for enhancing color quality and luminous flux of WLEDs
Authors: Phuong Loan Nguyen Thi , Quoc Anh Nguyen Doan
Published: June 2020

As the luminescence industry develops, the white light light-emitting diode (LED) package with a single chip and a single phosphor although produces good luminous flux but has a poor color rendering index (CRI) can no longer fulfill the requirements of modern lighting applications. Therefore, this research is conducted to response to the urgent demands of improving other lighting qualities of WLED while maintaining high luminous efficiency. To achieve this target, we applied the new WLED package, which contains multi-chips and multi-phosphor layers, and have obtained outstanding results in both CRI and luminous efficacy. Two types of phosphor used in the WLED package are Y2O3:Ho3+ and ZnO:Bi3+. A color configuration model is also developed to adjust the shading of the white-light LED module. The results of this research show that the triple-layer phosphorhas the best performance when applied in a white-light LED package, which is demonstrated through better color quality, CRI and luminous efficacy, The manufacturers can rely on this research to produce the optimal-quality WLED, or WLED that is appropriate to their quality demands.
Computer aided diagnosis for breast cancer based on the gabor filter technique
Authors: Kamil Mohammed Y.
Published: June 2020

The most prominent reason for the death of women all over the world is breast cancer. Early detection of cancer helps to lower the death rate. Mammography scans determine breast tumors in the first stage. As the mammograms have slight contrast, thus, it is a blur to the radiologist to recognize micro growths. A computer-aided diagnostic system is a powerful tool for understanding mammograms. Also, the specialist helps determine the presence of the breast lesion and distinguish between the normal area and the mass. In this paper, the Gabor filter is presented as a key step in building a diagnostic system. It is considered a sufficient method to extract the features. That helps us to avoid tumor classification difficulties and false-positive reduction. The linear support vector machine technique is used in this system for results classification. To improve the results, adaptive histogram equalization pre-processing procedure is employed. Mini-MIAS database utilized to evaluate this method. The highest accuracy, sensitivity, and specificity achieved are 98.7%, 98%, 99%, respectively, at the region of interest (30×30). The results have demonstrated the efficacy and accuracy of the proposed method of helping the radiologist on diagnosing breast cancer.
A study of remotely booking slot for vehicle using Internet of Things
Authors: Florence S. Metilda , Uma M. , Fancy C. , Saranya G.
Published: June 2020

Internet Of Things (IoT) is a continually growing area which aids us to unite diverse objects. The proposed system exhibits the universal notion of utilizing cloud-based intellectual automotive car parking facilities in smart cities as a notable implementation of the IoT. Such services demonstrate to be a noteworthy part of the IoT and thus serving users in no small amount due to its pure commerce positioned qualities. Electromagnetic fields are being used by RFID to detect and track tags ascribed to objects automatically. The RFID technology is used in this system along with suitable IoT protocols to evade human interference, which reduces the cost. Information is bartered using readers and tags. RFID and IoT technologies are mainly used to automate the guide systems and make them strong and more accurate. Open Service Gateways can be effectively used for this module. This system established on the consequence of IoT and the purposes are solving the chaos, bewilderment, and extensive backlogs in parking spaces like malls and business parks that are customary as a consequence of the increased use of automobiles. The proposed work aims to solve these problems and offer car drivers a hassle-free and instantaneous car parking experience. While a number of nodes are positioned depends on topographical restrictions, positioning of prominent anchor sensor nodes in the smart parking is a primary factor against which the efficiency and cost of the parking system hang. A Raspberry Pi would act as a mini-computer in our system. A suitable smallest path methodology would be cast-off to obtain the shortest distance between the user and every car park in the system. Hence, the pausing time of the user is decreased. This work furthermore includes the practice of remotely booking of a slot with the collaboration of android application exercising smartphones for the communication between the Smart Parking system and the user.
Influence of various application types on the performance of LTE mobile networks
Authors: Agamy Adel , Mohamed Ahmed M.
Published: June 2020

Modern mobile internet networks are becoming heavier and denser. Also it is not regularly planned, and becoming more heterogeneous. The explosive growth in the usage of smartphones poses numerous challenges for LTE cellular networks design and implementation. The performance of LTE networks with bursty and self-similar trafﬁc has become a major challenge. Accurate modeling of the data generated by each connected wireless device is important for properly investigating the performance of LTE networks. This paper presents a mathematical model for LTE networks using queuing theory considering the inﬂuence of various application types. Using sporadic source trafﬁc feeding to the queue of the evolved node B and with the exponential service time assumption, we construct a queuing model to estimate the performance of LTE networks. We use the performance model presented in this paper to study the inﬂuence of various application categories on the performance of LTE cellular networks. Also we validate our model with simulation using NS3 simulator with different scenarios.
An enhanced energy-efﬁcient routing protocol for wireless sensor network
Authors: Daanoune Ikram , Baghdad Abdennaceur , Ballouk Abdelhakim
Published: June 2020

Recent few years, Wireless Sensor Network (WSN) has been an increasingly important technology that has been applied in almost all domains, even in complex environments where human activity is impossible. In WSN, various factors are impacted energy consumption, such as communication protocols, packet data transmission, and limited battery. So, the lifespan of the WSNs is limited. In this context, energy efficiency is the factor most attracted by many researchers. In this paper, we proposed a new improved LEACH routing protocol. This proposed protocol based on the current energy to select cluster-heads, and it uses a root cluster-head with more current energy and low distance to the sink to gather all data, then sends it to the sink. The simulation results in MATLAB confirmed that the proposed algorithm performed better than the conventional LEACH protocol, and increased the network lifetime in WSN.