bluuebunny/crossref_metadata_2025 huggingface dataset:
Critical Analysis and Application of Net-Metering Practice in MEPCO
Authors: Zahid Hassan , Umer Farhana , Rashid Zeeshan , Raheem Abdur , Shakoor Rabia , Hussain G. Amjad
Published: June 2020

The electrical infrastructure around the globe is expanding at a rapid rate for the sake of fulfilling power demands in the domestic, commercial and entertainment industries aiming to boost the living standards. In this regard, renewable energy sources (RES) are globally accepted potential candidates for maintaining inexhaustible, clean, and reliable electricity with a supplementary feature of economic prospect. The efficiency of power distribution at reduced cost to the consumers can be further enhanced by introducing a two-way billing system so-called net-metering which has the potential to overcome issues such as voltage regulation, power blackouts, overstressed grid and need for expensive storage systems thereby making it beneficial for the grid and the end user. This envisioning has encouraged the Government of Pakistan to install net-metering infrastructure at places which accommodate surplus renewable energy reserves. According to the Electric Power Act 1997, the National Electric Power Regulatory Authority (NEPRA) issued the net-metering rules and regulations in September 2015 by the endorsement of Federal Government which allowed the distribution companies in Pakistan to buy surplus electricity units generated by the consumers in order to partly reimburse the units imported from the utility grid. The aim behind this research work is to promote renewable energy utilization through net-metering mechanism in order to achieve maximum power. The export of units from consumer side to utility grid and vice versa can be made through bidirectional energy meter. In this paper, a solar net-metering analysis has been carried out on ETAP software to determine its benefits in a distribution network. Different scenarios have been investigated, and it is concluded that solar net-metering technique has multiple influential benefits, e.g., improvement in voltage regulation, reduction in transmission and distribution losses, increase in power availability, less billing to consumers, and reduction of loading on utility grid.
The Effect of Oxetane as Active Diluent on Cationic UV Curing System of Fluorine-Containing Epoxy Prepolymer
Authors: Chi Baihong , Wei Mengying , He Yong
Published: June 2020

A series of fluorine-containing polyacrylic epoxy (FPAE) prepolymers with different fluorine content and molecular weight are synthesized by solution free radical polymerization of hexafluorobutyl methacrylate (HFBMA), butyl acrylate (BA), and glycidyl methacrylate (GMA). The synthesized prepolymers show high conversion and low volume shrinkage. The effect of different types of active diluent for the cationic UV curing of FPAE was investigated, among which oxetane exhibits better comprehensive property than epoxy and vinyl ether. The formulations with the optimal ratio of different functionality oxetane combination show good flexibility, adhesion, hydrophobicity, and antistain property.
Chemical and Sensory Characterisation of Two Rubus rosifolius (Red Raspberry) Varieties
Authors: Rambaran Theresa F. , Bowen-Forbes Camille S.
Published: June 2020

Raspberries are economically important fruits, being highly valued for their taste and medicinal properties. Prior to our recent finding, the occurrence of different varieties of Rubus rosifolius growing in Jamaica had not been previously reported. Upon close observation of the plants, differences in various physical features pointed to the existence of two distinct plant morphotypes, which were described as Red “R” and Wine Red “WR.” With an aim to determine which variety may be more favourable for value-added food production, we undertook their physicochemical and sensory analysis. This characterisation led to the rationalisation of the differences in the perceived sensory properties of these biologically active fruits. Total phenolic content was determined using the Folin-Ciocalteu reagent assay, and the identification and quantification of anthocyanins were done via HPLC-MS and HPLC-UV, respectively. Proximate and physicochemical analyses were also carried out. The findings of the analyses were associated with those of a consumer sensory analysis. The WR fruits had a greater quantity of the deep red anthocyanin, cyanidin-3-glucoside (66.2 mg/100 g FW), and a significantly lower lightness value. They also received a significantly higher sweetness score, which is associated with their higher total sugar content (4.8 g/100 g) and maturity index (6.7). The R fruits had a higher quantity of the orange-coloured pelargonidin-3-rutinoside (17.2 mg/100 g FW) and significantly higher titratable acidity (1.3 g citric acid/100 mL), the latter being associated with its significantly more sour taste. The high total phenolic contents suggest a health-functional value of these R. rosifolius berry fruits. Our findings, which revealed that the WR variety was the preferred choice among consumers, may be used to guide future product-development endeavours of these commercially valuable fruits.
The Antler Cycle and Fecal Testosterone of Male Sambar Deer Rusa unicolor unicolor at the Horton Plains National Park in Sri Lanka
Authors: Weerasekera D. S. , Perera S. J. , Nanayakkara D. K. K. , Herath H. M. S. S. , Rathnasekara A. N. L. , Ranawana K. B.
Published: June 2020

This study is aimed at evaluating the relationship between endogenous testosterone levels and antler development in male sambar deer (Rusa unicolor unicolor) inhabiting the Horton Plains National Park, Sri Lanka. Seven antler growth stages of sambar were documented based on phenotypic observations for the first time in Sri Lanka as (a) cast, (b) growing 1—single spike, (c) growing 2—antler fork into a Y as the second tine appears, (d) growing 3—velvet begins to harden as the third tine appears, (e) growth completed—velvet shedding begins, (f) hard antler, and (g) casting. Fecal samples were collected every month for a period of eighteen months from male sambar deer in different stages of the antler growth cycle, feeding in the wet patana grasslands of the park, and the fecal testosterone level was estimated by radioimmunoassay. Ten animals were randomly selected from each antler stage for the experiment. The results disclose that the highest concentrations of testosterone were recorded in the hard antler stage. Velvet shedding was preceded by an increase in the testosterone level, and it is the sudden drop in the testosterone concentration which triggers the antler casting. The casting stage corresponded with the lowest mean testosterone concentration. Although the study was able to conclude a clear relationship between the fecal testosterone levels of the male sambar deer in the Horton Plains National Park and their antler stages, there is no clear seasonality for the antler cycle.
Validation of Parkinson’s Disease-Related Questionnaires in South Africa
Authors: Nelson Gill , Ndlovu Ntombizodwa , Christofides Nicola , Hlungwani Tintswalo M. , Faust Irene , Racette Brad A.
Published: June 2020

Background. There are very few epidemiological studies investigating Parkinson’s disease (PD) in Africa. The hundreds of local languages and dialects make traditional screening and clinical evaluation tools difficult to use. Objective. The objective of the study was to validate two commonly used PD questionnaires in an African population. Methods. The PD Screening Questionnaire (PDSQ) and Parkinson’s Disease Questionnaire (PDQ-39) were modified and translated into Afrikaans, Setswana, and isiZulu and administered to a sample of healthy local residents. We assessed the internal consistencies and cluster characteristics of the questionnaires, using a Cronbach’s alpha test and exploratory factor analysis. The questionnaires were then administered to a population-based sample of 416 research participants. We evaluated the correlations between the questionnaires and both a timed motor task and the Unified Parkinson’s Disease Rating Scale motor subsection 3 (UPDRS3), using locally weighted scatterplot smoothing (LOWESS) regression analysis and Spearman’s rank correlation. Results. Both questionnaires had high overall internal consistency (Cronbach’s alpha = 0.86 and 0.95, respectively). The modified PDQ-39 had evidence of five subscales, with Factor 1 explaining 57% and Factor 2 explaining 14%, of the variance in responses. The PDSQ and PDQ-39 scores were correlated with the UPDRS3 score (ρ = 0.35, P<0.001; and ρ = 0.28, P<0.001, respectively). Conclusion. The translated PDSQ and PDQ-39 questionnaires demonstrated high internal consistency and correlations with clinical severity of parkinsonism and a timed motor task, suggesting that they are valid tools for field-based epidemiological studies.
Abnormal User Detection Based on the Correlation Probabilistic Model
Authors: Yang Xiaohui , Sun Ying
Published: June 2020

As an important part of the new generation of information technology, the Internet of Things (IoT), which is developing rapidly, requires high user security. However, malicious nodes located in an IoT network can influence user security. Abnormal user detection and correlation probability analysis are fundamental and challenging problems. In this paper, the probabilistic model of the correlation between abnormal users (PMCAU) is proposed. First, the concept of user behavior correlation degree is proposed, which is defined as two parts: user attribute similarity degree and behavior interaction degree; the attribute similarity measurement algorithm and behavior correlation measurement algorithm are constructed, respectively, and the spontaneous and interactive behaviors of users were analyzed to determine the abnormal correlated users. Second, first-order logic grammar is used to express the before and after connection of user behavior and to deduce the probabilistic of occurrence of the correlation of behavior and determine the abnormal user groups. Experimental results show that, compared with the traditional anomaly detection algorithm and Markov logic network, this model can identify the users correlated with anomalies, make probabilistic inferences on the possible associations, and identify the potential abnormal user groups, thus achieving higher accuracy and predictability in the IoT.
Damage Localization of Piles Based on Complex Continuous Wavelet Transform: Numerical Example and Experimental Verification
Authors: Zheng Wenting , Wang Sifan , Lin Chengxu , Yu Xianying , Liu Jingliang
Published: June 2020

A new signal processing method called complex continuous wavelet transform (CCWT) is introduced in this paper to localize pile damage because it clearly reveals inherent characteristics of response signals. In this method, CCWT is first performed on the response signal to obtain the wavelet coefficient matrix. The resultant coefficients are then employed to calculate phase angles at different frequency bands with an aim of pile damage localization. However, the CCWT method is only demonstrated via laboratory tests on pile specimens, and its application on actual piles has not been examined. Moreover, various factors such as pile-soil interaction need to be considered when the CCWT method is applied on actual piles. To address these issues, a numerical example of 3D finite element pile model followed by a parameter analysis and an experimental verification on an actual pile are investigated. The results demonstrate that the CCWT method is capable of localizing pile damage under different damage scenarios. However, there are still some interference points in the grayscale images of phase angles and the reduction of interference points needs to be addressed by mutual verification with other pile damage detection methods and engineering experience.
Using Bluetooth Low Energy Advertisements for the Detection of People Temporal Proximity Patterns
Authors: Garcia-Alonso Jose , Berrocal Javier , Pérez-Vereda Alejandro , Galán-Jiménez Jaime , Canal Carlos , Murillo Juan M.
Published: June 2020

The pervasive presence of smartphones has emerged as one of the key elements for sensing people contextual information. Their sensors and communication capabilities can be used to gather a huge amount of data. Such capabilities have made it possible to compose profiles of people by relating different parameters such as time and location. This paper contributes in this sense by providing the basis for the composition of temporal proximity patterns—when and whom people share their time with each other. For this purpose, the Bluetooth Low Energy (BLE) advertisement protocol was used. The contribution of this work departs from that of those who use BLE technology focused on measuring the intensity of the signals to, for example, determine distances. In this field, a huge amount of work has been already done with very interesting results. Instead, in this work, BLE is used to emit and sense the presence of people. A set of algorithms are then used inside the smartphones to analyse the data gathered and to detect proximity patterns between people. This scenario avoids the difficulties that appear in other works—like those focused on people positioning—derived from the lack of precision of the sensors and the differences between BLE chipsets. Tests to evaluate the consumption, precision, and reliability of using this technology, together with the proposed algorithms, confirmed the feasibility of the approach. In addition, the proposal has proved very useful for the automatic construction of social networks based on physical closeness of people.
Mechanical Properties and Drying Shrinkage Investigation of Alkali‐Activated Mortar Using Waste Glass Powder
Authors: Gong Jianqing , Qu Zhigang
Published: June 2020

Alkali‐activated mortar (AAM) is one of the products of waste glass recycling that exhibits promising potential for wide engineering applications such as the construction industry. In this study, recycled waste glass powder‐based additives, namely, Silica Fume (SF) and Nano‐SiO2 (NS), were investigated for their potential to enhance the mechanical properties (strength) and drying‐shrinkage resistance of AAM. The results indicated that 5.0% and 1.5% were the optimum SF and NS dosages, respectively, for optimizing AAM performance in terms of the compressive strength, flexural strength, and drying‐shrinkage resistance. A prediction model, based on backpropagation (BP) neural network analysis, was also satisfactorily formulated and preliminarily validated for predicting the drying shrinkage of AAM containing SF or NS.
Promotion of Hair Growth by Conditioned Medium from Extracellular Matrix/Stromal Vascular Fraction Gel in C57BL/6 Mice
Authors: Xiao Shune , Deng Yurong , Mo Xiaojin , Liu Zhiyuan , Wang Dali , Deng Chengliang , Wei Zairong
Published: June 2020

Adipose-derived stem cell- (ADSC-) based regenerative medicine has expanded to include the treatment of hair loss. However, stem cell therapy remains a relatively recent technique, and reports of its use for treating alopecia are rare. ADSCs exert biological functions via the paracrine actions of various growth factors and cytokines. Conditioned medium from ADSCs (ADSCs-CM) is a cell-free suspension rich in growth factors and cytokines that has demonstrated a significant role in stimulating hair growth, with encouraging outcomes in terms of hair regeneration and hair growth. Extracellular matrix/stromal vascular fraction gel (ECM/SVF-gel) is an ADSC- and adipose native extracellular matrix-enriched product for cytotherapy. In this study, we compared the effects of CM from ECM/SVF-gel (ECM/SVF-CM) and from stem cells (SVF-CM) on hair growth in mice. ECM/SVF-CM stimulated hair growth more than SVF-CM, through promoting the proliferation of dermal papilla cells and cells in the bulge, neovascularization, and anagen induction. ECM/SVF-CM might, thus, provide an effective and improved strategy for promoting hair growth. These data provide a theoretical foundation for the clinical administration of ECM/SVF-CM for the treatment of hair loss.
UL16‐Binding Protein 1 Induced HTR‐8/SVneo Autophagy via NF‐κB Suppression Mediated by TNF‐α Secreted through uNK Cells
Authors: Liu Jing , Song Guang , Meng Tao , Zhao Ge
Published: June 2020

UL16‐binding protein 1(ULBP1) has been reported to inhibit trophoblast invasion through the modification of secretion functions of uNK cells in the previous study, but its mechanisms remain unclear. In this study, we investigated the related mechanism by which upregulated ULBP1 expression impaired trophoblast invasion. We found that conditioned media with ULBP1 increased autophagy in HTR‐8/SVneo, and anti‐TNF‐α‐neutralizing antibody rescued the autophagy caused by the conditioned medium. We further found TNF‐α induced autophagy in trophoblast cells in a dose‐dependent way and accompanied by a decreased activity of nuclear factor‐kappa B (NF‐κB). Inhibition of NF‐κB activation by chemical inhibitor augmented these autophagic responses to TNF‐α in the cells. In addition, interruption NF‐κB caused a significant decrease in HTR‐8/SVneo invasion and enhanced the inhibition effect of TNF‐α on HTR‐8/SVneo invasion. Taken together, these findings suggest that TNF‐α is able to regulate autophagic activity via suppressing NF‐κB, which might be the mechanism related to ULBP1 in preeclampsia pathogenesis.
Acute Kidney Injury in the 2019 Novel Coronavirus Disease
Authors: Qian Jing-Yi , Wang Bin , Liu Bi-Cheng
Published: June 2020

Background: The 2019 novel coronavirus disease (CO­VID-19) is a newly defined serious infectious disease caused by the SARS-CoV-2 virus. The epidemic started in Wuhan, China, in December of 2019 and quickly spread to over 200 countries. It has affected 4,258,666 people, with 294,190 deaths worldwide by May 15, 2020. COVID-19 is characterized by acute respiratory disease, with 80% of patients presenting mild like flu-like symptoms; however, 20% of patients may have a severe or critical clinical presentation, which likely causes multiple organ injuries (e.g., kidney, heart, blood, and nervous system). Among them, acute kidney injury (AKI) is a critical complication due to its high incidence and mortality rate. Here we present a review of the current understanding of AKI in COVID-19. Summary: CO­VID-19 is a catastrophic contagious disease caused by the coronavirus, and the AKI induced by COVID-19 significantly increases the mortality rate. In this review, we summarize the clinical characteristics of COVID-19 induced AKI by focusing on its epidemiology, pathogenesis, clinical diagnosis, and treatment. Key Messages: Multiple studies have shown that COVID-19 may involve the kidneys and cause AKI. This article reviews the characteristics of COVID-19-induced AKI largely based on up-to-date studies in the hope that it will be helpful in the current global fight against and treatment of COVID-19.
Unit vector template generator applied to a new control algorithm for an UPQC with instantaneous power tensor formulation, a simulation case study
Authors: Garcés Gómez Yeison Alberto , Toro García Nicolás , Hoyos Fredy Edimer
Published: June 2020

In this paper we present a new algorithm to generate the reference signals to control the series and parallel power inverters in an unified power quality conditioner “UPQC” to enhance power quality. The algorithm is based in the instantaneous power tensor formulation which it is obtained by the dyadic product between the instantaneous vectors of voltage and current in n-phase systems. The perfect harmonic cancelation algorithm “PHC” to estimate the current reference in a shunt active power filter was modified to make it hardy to voltage sags through unit vector template generation “UVGT” while from the same algorithm it extracts the voltage reference for series active power filter. The model was validated by mean of simulations in Matlab-Simulink®.
Improved particle swarm optimization algorithms for economic load dispatch considering electric market
Authors: Phan Tan Minh , Ha Phu Trieu , Duong Thanh Long , Nguyen Thang Trung 
Published: June 2020

Economic load dispatch problem under the competitive electric market (ELDCEM) is becoming a hot problem that receives a big interest from researchers. A lot of measures are proposed to deal with the problem. In this paper, three versions of PSO method such as conventional particle swarm optimization (PSO), PSO with inertia weight (IWPSO) and PSO with constriction factor (CFPSO) are applied for handling ELDCEM problem. The core duty of the PSO methods is to determine the most optimal power output of generators to obtain total profit as much as possible for generation companies without violation of constraints. These methods are tested on three and ten-unit systems considering payment model for power delivered and different constraints. Results obtained from the PSO methods are compared with each other to evaluate the effectiveness and robustness. As results, IWPSO method is superior to other methods. Besides, comparing the PSO methods with other reported methods also gives a conclusion that IWPSO method is a very strong tool for solving ELDCEM problem because it can obtain the highest profit, fast converge speed and simulation time.
Maximum voltage sag compensation using direct converter by modulating the carrier signal
Authors: Rahman S. Abdul , Teshome Gebrie
Published: June 2020

The aim of this paper is to achieve maximum voltage sag compensation of 52% using direct converter based DVR. The DVR topology has only two switches. The DVR is designed to compensate the voltage sag in a phase by taking power from the same phase. A direct converter is connected between the series transformer and the line in which sag compensation is to be achieved. If the actual amplitude of the error signal is used and the amplitude of carrier signal is kept at 1 unit, it is possible to achieve only 22% of sag compensation. If the amplitude of the carrier signal is modulated according to the percentage of existing sag, 52% of the sag is compensated through ordinary PWM technique with the THD less than 5%. Matlab Simulation results are presented for the validating the analysis.
The quality of data and the accuracy of energy generation forecast by artificial neural networks
Authors: Kwiatkowski Bogdan , Bartman Jacek , Mazur Damian
Published: June 2020

The paper presents the issues related to predicting the amount of energy generation, in a particular wind power plant comprising five generators located in south-eastern Poland. The location of wind power plant, the distribution and type of applied generators, and topographical conditions were given and the correlation between selected weather parameters and the volume of energy generation was discussed. The primary objective of the paper was to select learning data and perform forecasts using artificial neural networks. For comparison, conservative forecasts were also presented. Forecasts results obtained shaw that Artificial Neural Networks are more universal than conservative method. However their forecast accuracy of forecasts strongly depends on the selection of explanatory data
Advanced energy management system with the incorporation of novel security features
Authors: Muzzammel Raheel , Arshad Rabia , Mehmood Saba , Khan Danista
Published: June 2020

Nowadays, energy management is a subject of great importance and complexity. Pakistan, being in a state of developing country, generates electrical power mainly by using non-renewable sources of energy. Non-renewable entities are fossil fuels such as furnace oil, natural gas, coal, and nuclear power. Pakistan has been facing a severe shortage of production in energy sector for last two decades. This shortfall is affecting the industrial development as well as economic growth. With the growing population, the load demand is rapidly increasing and there must be a need to expand the existing ones or to build new power systems. In this paper, an autonomous management system has been proposed to enhance quality, reliability and confidence of utilization of energy between end consumers and suppliers. Such objectives can only be fulfilled by making the power supply secure for end consumers. Distributed and centralized control systems are involved for maintaining a balance between renewable energy resources and base power, so that end consumers demand can be fulfilled when required. A reliable Two-way communication system between suppliers and end consumers has been proposed by using Message Digest algorithm which ensures that there would be no energy theft. Simulations have been done in MATLAB/ Simulink environment and results have been presented to show the effectiveness of the proposed model.
Smart monitoring system of Najran dam
Authors: Almawgani A. H. M. , Alshorman M. A. , Alyami M. A. , Alhmammi H. M. , Almahri D. S. , Alkhuraym M. A. , Alwasel A. H.
Published: June 2020

Najran city faces the flood situation every year due to intensive rain and climatic disturbances. Flooding also causes loss of money, along with loss of life and property and the destruction of agriculture and livestock. Thus, this project proposes a conceptual framework with three main phases: monitoring the water level inside the dam and level in water stream before and after the dam, controlling the opening and closing of the dam gate and measuring the water pressure at the dam barrier. In the case of high water level dam is monitored through water sensors placed at the top of the dam and then these sensors give a reference to the stepper motor and the flow of the stepper motor is controlled by the dam gate. The experimental results shows that the proposed system has the capability to reliably tackle the flood water. It can accurately measure the water level and control the gate of dam as soon as the level of the water reaches to danger level and water pressure at the barrier is measured by the sensor. The developed real-time monitoring system in Najran dam will help authorities to take preventive actions to deal with flood disaster.
Dual-layer remote phosphor structure: a novel technique to enhance the color quality scale and luminous flux of WLEDs
Authors: That Phung Ton , Bui Thuc Minh , Phuong Loan Nguyen Thi , Le Phan Xuan , Quoc Anh Nguyen Doan , Tho Le Van
Published: June 2020

The effects of red light-emitting phosphor CaMgSi2O6:Eu2+,Mn2+ on the optical properties of single-layer remote phosphor structure (SRPS) and dual-layer remote phosphor structure (DRPS) are the focus of this study. The differences in color quality and luminous flux (LF) of white light-emitting diodes (WLEDs) between these two structures are also revealed and demonstrated based on the Mie theory. SRPS consists of one mixed phosphor layer betweenCaMgSi2O6:Eu2+,Mn2+ andYAG:Ce3+particles, while DRPS includes two separated layers: red phosphor layer and yellow phosphor layer. In this work, 5% SiO2 is added into the phosphor layers to increase scattering abilities. Discrepancies in structures greatly affect the optical characteristics of WLEDs. The results showed that the color rendering index (CRI) increased with the concentration in both structures with nearly equal values. Meanwhile, color quality scale (CQS) of DPRS is 74 at ACCTs ranging from 5600K to 8500K, higher than CQS of SRPS which is only 71 at 8500K. In addition, the luminous flux of DRPS is significantly higher than SRPS at 2% -14% of CaMgSi2O6:Eu2+,Mn2+. In summary, DRPS is better for color quality and lumen outputin comparison to SRPS and adding the right amount of red phosphor can enhance CQS and LF.
Methodology for detection of paroxysmal atrial fibrillation based on P-Wave, HRV and QR electrical alternans features
Authors: Castro Henry , Garcia-Racines Juan David , Bernal-Noreña Alvaro
Published: June 2020

The detection of Paroxysmal Atrial Fibrillation (PAF) is a fairly complex process performed manually by cardiologists or electrophysiologists by reading an electrocardiogram (ECG). Currently, computational techniques for automatic detection based on fast Fourier transform (FFT), Bayes optimal classifier (BOC), k-nearest neighbors (K-NNs), and artificial neural network (ANN) have been proposed. In this study, six features were obtained based on the morphology of the P-Wave, the QRS complex and the heart rate variability (HRV) of the ECG. The performance of this methodology was validated using clinical ECG signals from the Physionet arrhythmia database MIT-BIH. A feedforward neural network was used to detect the presence of PAF reaching a general accuracy of 97.4%. The results obtained show that the inclusion of the information of the P-Wave, HRV and QR Electrical alternans increases the accuracy to identify the PAF event compared to other works that use the information of only one or at most two of them.
The effects of multiple layers feed-forward neural network transfer function in digital based Ethiopian soil classification and moisture prediction
Authors: Bezabeh Belete Biazen , Mengistu Abrham Debasu
Published: June 2020

In the area of machine learning performance analysis is the major task in order to get a better performance both in training and testing model. In addition, performance analysis of machine learning techniques helps to identify how the machine is performing on the given input and also to find any improvements needed to make on the learning model. Feed-forward neural network (FFNN) has different area of applications, but the epoch convergences of the network differs from the usage of transfer function. In this study, to build the model for classification and moisture prediction of soil, rectified linear units (ReLU), Sigmoid, hyperbolic tangent (Tanh) and Gaussian transfer function of feed-forward neural network had been analyzed to identify an appropriate transfer function. Color, texture, shape and brisk local feature descriptor are used as a feature vector of FFNN in the input layer and 4 hidden layers were considered in this study. In each hidden layer 26 neurons are used. From the experiment, Gaussian transfer function outperforms than ReLU, sigmoid and tanh transfer function. But the convergence rate of Gaussian transfer function took more epoch than ReLU, Sigmoid and tanh.
Local feature extraction based facial emotion recognition: a survey
Authors: Slimani Khadija , Kas Mohamed , El Merabet Youssef , Ruichek Yassine , Messoussi Rochdi
Published: June 2020

Notwithstanding the recent technological advancement, the identification of facial and emotional expressions is still one of the greatest challenges scientists have ever faced. Generally, the human face is identified as a composition made up of textures arranged in micro-patterns. Currently, there has been a tremendous increase in the use of local binary pattern based texture algorithms which have invariably been identified to being essential in the completion of a variety of tasks and in the extraction of essential attributes from an image. Over the years, lots of LBP variants have been literally reviewed. However, what is left is a thorough and comprehensive analysis of their independent performance. This research work aims at filling this gap by performing a large-scale performance evaluation of 46 recent state-of-the-art LBP variants for facial expression recognition. Extensive experimental results on the well-known challenging and benchmark KDEF, JAFFE, CK and MUG databases taken under different facial expression conditions, indicate that a number of evaluated state-of-the-art LBP-like methods achieve promising results, which are better or competitive than several recent state-of-the-art facial recognition systems. Recognition rates of 100%, 98.57%, 95.92% and 100% have been reached for CK, JAFFE, KDEF and MUG databases, respectively.
Offset effect on the S-Bend structure losses and optimization of its size for integrated optics
Authors: Brik Fatima , Harize S. , Fares A. , Saouchi K.
Published: June 2020

The S-Bend structures are heavily exploited to join optical components. Reducing the power loss caused by the curve is the main objective in the design step of these components. However integrated optical circuits require S-Bend waveguide to be low loss and compact sized. In this paper, we present a contribution to link the curved structure to the straight waveguide by using the simulated bend function available in the Beam propagation tool of the Rsoft commercial software package. Simulation results confirm that this approach allows a reduction of the size of the curved structure with offset with relatively minimum of losses for photonic field.
A NURBS-optimized dRRM solution in a mono-channel condition for IEEE 802.11 entreprise Wlan networks
Authors: Guessous Mehdi , Zenkouar Lahbib
Published: June 2020

Dynamic radio resource management, RRM, is an essential design block in the functional architecture of any Wifi controller in IEEE 802.11 indoor dense enterprise Wlans. In a mono-channel condition, it helps tackle co-channel interference problem and enrich end-to-end Wifi clients experience. In this work, we present our dRRM solution: WLCx, and demonstrate its performance over related-work and vendor approaches. Our solution is built on a novel and realistic per-Beam coverage representation approach. Unlike the other RRM solutions, WLCx is dynamic: even the calculation system parameters are processed. This processing comes at price in terms of processing time. To overcome this limitation, we constructed and implemented a NURBS surface-based optimization to our RRM solution. Our NURBS optimized WLCx, N-WLCx, solution achieves almost 92.58% time reduction in comparison with basic WLCx. Furthermore, our optimization could easily be extended to enhance others, vendors and research, RRM solutions.
A comprehensive study on disease risk predictions in machine learning
Authors: Saranya G. , Pravin A.
Published: June 2020

Over recent years, multiple disease risk prediction models have been developed. These models use various patient characteristics to estimate the probability of outcomes over a certain period of time and hold the potential to improve decision making and individualize care. Discovering hidden patterns and interactions from medical databases with growing evaluation of the disease prediction model has become crucial. It needs many trials in traditional clinical findings that could complicate disease prediction. Comprehensive survey on different strategies used to predict disease is conferred in this paper. Applying these techniques to healthcare data, has improvement of risk prediction models to find out the patients who would get benefit from disease management programs to reduce hospital readmission and healthcare cost, but the results of these endeavours have been shifted.
A high security and noise immunity of speech based on double chaotic masking
Authors: Hussein Ehab AbdulRazzaq , Khashan Murtadha K. , Jawad Ameer K.
Published: June 2020

It is known that increasing the security of the information and reducing the noise effect through public channels are two of the main priorities in developing any communication system. In this article, an efficient, secure communication system with two levels of encryption has been applied to the speech signal. The suggested security approach was implemented by using two different stages of chaotic masking on the signal; one masking was conducted by using Lorenz system and the other masking was built by using Rӧssler chaotic flow system. The main goal of developing this two-chaotic masking approach is to increase the key space and the security of the information. Also, an immunity technique has been implemented in the suggested approach to reduce the noise effect. For practical application purposes, this system was tested with additive white gaussian noise (AWGN) channel. The simulation results show that the quality of reconstructed speech signal is changeable according to the used signal to noise ratio (SNR); therefore, a proposed technique based on digital processing method (DPM) was applied to the first masked signal by converting the sampled data from the analog to the binary format. The simulation results show that an 22 dB (SNR) is sufficient to recover the speech signal with minimum noise by using the suggested approach.
On some types of slight homogeneity
Authors: Al Ghour Samer , Al Khatib Nahed
Published: June 2020

As a generalization of the concept SLH space, we introduce the concept of slightly strongly locally homogeneous (SSLH) spaces. Also, we introduce the concepts of slightly dense set as well as slightly separable space, and use them to introduce two new types of slightly countable dense homogeneous spaces. Several results, relationships, examples and counter-examples concerning these concepts are obtained.
Novel holistic architecture for analytical operation on sensory data relayed as cloud services
Authors: B. C Manujakshi , Ramesh K. B.
Published: June 2020

With increasing adoption of the sensor-based application, there is an exponential rise of the sensory data that eventually take the shape of the big data. However, the practicality of executing high end analytical operation over the resource-constrained big data has never being studied closely. After reviewing existing approaches, it is explored that there is no cost effective schemes of big data analytics over large scale sensory data processiing that can be directly used as a service. Therefore, the propsoed system introduces a holistic architecture where streamed data after performing extraction of knowedge can be offered in the form of services. Implemented in MATLAB, the proposed study uses a very simplistic approach considering energy constrained of the sensor nodes to find that proposed system offers better accuracy, reduced mining duration (i.e. faster response time), and reduced memory dependencies to prove that it offers cost effective analytical solution in contrast to existing system.
FANET optimization: a destination path flow model
Authors: Sadiq Bashir Olaniyi , Salawudeen A. T.
Published: June 2020

Closed-loop routing in flying ad hoc networks (FANET) arises as a result of the quick changes of communication links and topology. As such, causing link breakage during information dissemination. This paper proposed a destination path flow model to improve the communication link in FANET. The models utilized Smell Agent Optimization and Particle Swarm Optimization algorithms in managing link establishment between communicating nodes. The modeled scenario depicts the practical application of FANET in media and sports coverage where only one vendor is given the license for live coverage and must relay to other vendors. Three different scenarios using both optimization Algorithms were presented. From the result obtained, the SAO optimizes the bandwidth costs much better than PSO with a percentage improvement of 10.46%, 4.04% and 3.66% with respect to the 1st, 2nd and 3rd scenarios respectively. In the case of communication delay between the FANET nodes, the PSO has a much better communication delay over SAO with percentage improvement of 40.89%, 50.26% and 68.85% in the first, second and third scenarios respectively.
Texture classification of fabric defects using machine learning
Authors: Ben Salem Yassine , Abdelkrim Mohamed Naceur
Published: June 2020

In this paper, a novel algorithm for automatic fabric defect classification was proposed, based on the combination of a texture analysis method and a support vector machine SVM. Three texture methods were used and compared, GLCM, LBP, and LPQ. They were combined with SVM’s classifier. The system has been tested using TILDA database. A comparative study of the performance and the running time of the three methods was carried out. The obtained results are interesting and show that LBP is the best method for recognition and classification and it proves that the SVM is a suitable classifier for such problems. We demonstrate that some defects are easier to classify than others.
Self-checking method for fault tolerance solution in wireless sensor network
Authors: Croock Muayad Sadik , Khuder Saja Dhyaa , Hassan Zahraa Abbas
Published: June 2020

Recently, the wireless sensor network (WSN) has been considered in different application, particularly in emergency systems. Therefore, it is important to keep these networks in high reliability using software engineering techniques in the field of fault tolerance. This paper proposed a fault node detection method in WSN using the self-checking technique according to the rules of software engineering. Then, the detected faulted node is covered employing the reading of nearest neighbor nodes (sensors). In addition, the proposed method sends a message for maintenance to solve the fault. The proposed method can reduce the time between the detection and recovery of a fault to prevent the confusion of adopting wrong readings, in which the detection is making with mistake. Moreover, it guarantees the reliability of the WSN, in terms of operation and data transmission. The proposed method has been tested over different scenarios and the obtained results show the superior efficiency in terms of recovery, reliability, and continuous data transmission.
The impact of coloured filters on the performance of polycrystalline photovoltaic panel in an uncontrolled environment
Authors: Njok Armstrong O. , Iloke Joel I. , Panjwani Manoj Kumar , Hussain Mangi Fareed
Published: June 2020

Photovoltaic modules behave extraordinarily by transforming part of the visible spectrum into electrical energy, and their efficiencies are affected by the nature of radiation (light) reaching them. When light strikes a photovoltaic cell, this light may go through the cell without been absorbed if it is too energetic or if the light possesses low energy it will be absorbed by the cell and cause the electrons to twist and vibrate in their bonds without dislodging them, hence causing the cell to heat up which ultimately leads to a decrease in its overall efficiency. This study is aimed to investigate how photovoltaics respond to different wavelengths of light. For the study to achieve its aim, colour filters were used to ensure that only a particular wavelength of light reaches the photovoltaic module at a time. In the process of collecting data from the solar panel, the solar panel was placed horizontally flat on a platform one meter above sea level facing the sun. Data was first obtained from the solar panel without the filters and after that with the filters placed one at a time and data collected accordingly. The amount of solar power and solar flux anytime a different colour filter was placed on the solar panel were measured. Among the coloured filter used yellow produced the highest efficiency, while blue produced the least efficiency. However, the solar panel was still more efficient when exposed to the natural spectrum.
An interactive approach for solar energy system: design and manufacturing
Authors: Mahdi Benbaziz Djallal Eddine , Abdelatif Hassini , Zafrane Mohammed Amine
Published: June 2020

The energy production in the word is a very complex problem with decreasing the pollution. Therefore, the aim is to find an optimal solution, this research focuses on the development and the optimization of parabolic concentrator using an interactivity approach and virtual design tools. Recently, several works have been developed in this area. In this study, a new conception, design Optimization approach has been involved in system energy design including new concept. The design strategy has been successfully applied to design problems. The optimizer tool developed for based on Heuristic: Gravitational Search Algorithm. The results of the presented in this paper are significant in the system energy design, which presents an effective approach of development by reducing the cost of installation, the time of analysis by increasing the radiation and solar flux concentrated within the parabola generating an increase in accumulated energy.
Control strategies for seamless transfer between the grid-connected and islanded modes of a microgrid system
Authors: Lavanya V. , Kumar N. Senthil
Published: June 2020

Design of control strategies for Distributed generation systems is very important to achieve smoother transition between the grid connected and islanding modes of operation. The transition between these two modes of operation should be seamless, without any severe transients during the changeover. In this paper, two different control strategies namely inverter output current control and indirect grid current control for the seamless transfer between the modes of operation has been explored for the suitability. The design and analysis of the cascaded control loops based on Proportional Integral (PI) controller has been dealt in detail for both inverter output current control and indirect grid current control strategy. Control parameters are designed using the control system toolbox in MATLAB. A 10kW grid connected microgrid system has been designed and simulated in MATLAB/Simulink and the results are presented under grid connected operation, islanding operation and the transition between the modes considering fault condition in the grid side. The simulation studies are carried out using both the control strategies and the results are presented to validate the design methodology.
Fixed-time observer-based distributed secondary voltage and frequency control of islanded AC microgrids
Authors: Ghazzali Mohamed , Haloua Mohamed , Giri Fouad
Published: June 2020

This paper deals with the problem of voltage and frequency control of distributed generators (DGs) in AC islanded microgrids. The main motivation of this work is to obviate the shortcomings of conventional centralized and distributed control of micro-grids by providing a better alternative control strategy with better control performance than state-of-the art approaches. A distributed secondary control protocol based on a novel fixed-time observer-based feedback control method is designed for fixed-time frequency and voltage reference tracking and disturbance rejection. Compared to the existing secondary microgrid controllers, the proposed control strategy ensures frequency and voltage reference tracking and disturbance rejection before the desired fixed-time despite the microgrid initial conditions, parameters uncertainties and the unknown disturbances. Also, the controllers design and tuning is simple, straightfor-ward and model-free.i.e, the knowledge of the microgrid parameters, topology, loads or transmission lines impedance are not needed in the design procedure. The use of distributed control approach enhances the reliability of the system by making the control system geographically distributed along with the power sources, by using the neighboring DGs informations instead of the DG’s local informations only and by cooperatively rejecting external disturbances and maintaining the frequency and the voltage at their reference values at any point of the microgrid. The efficiency of the proposed approach is verified by comparing its performance in reference tracking and its robustness to load power variations to some of the works in literature that addressed distributed secondary voltage and frequency control.
Standalone photovoltaic array fed induction motor driven water pumping system
Authors: Loubna Atarsia , Riad Toufouti , Salima Meziane
Published: June 2020

Due to the absence of energy transmission lines connected to the water pumping sites in remote areas, problems related to the electrical power outages and the environmental degradation caused by fossil fuel. For this one of the most conceived solutions is the photovoltaic water pumping technology which has the advantage of being sustainable and respectful of the environment to supply water to rural areas. To ensure the need of water, especially for domestic use and small communities, in this article, the photovoltaic energy system for autonomous water pumping using the induction motor was presented, particularly adapted to the isolated regions. Pumping system consists of four photovoltaic (PV) panels, boost converter, inverter, induction motor, centrifugal pump and a storage tank. In this study, the output power of a PV solar cell is fully used by proposing the P&O algorithm, where it is used to follow a maximum power point tracking (MPPT) technique. The recommended system is designed, modeled and simulated on the MATLAB/Simulink platform. The efficiency of the proposed algorithm is observed with variable solar sunshine.