bluuebunny/crossref_metadata_2025 huggingface dataset:
DEPRESSÃO E QUALIDADE DE VIDA EM PACIENTES DIALÍTICOS
Authors: Faria Uveda Júlia , Vaz Kochhann Elisangela , Ázara Oliveira Ênio , Henrique Ferracioli Alvarenga Gabriel , Caroline Barbosa Remigio Gabriella , Leite de Andrade João Pedro , Oliveira Borges Luíza , Cardoso Vilela Faria Marina , Mendonça Rocha Carollayne , Gonçalves Cherain Luiz Gabriel
Published: February 2022

Introdução: A doença renal crônica (DRC) é caracterizada pela diminuição da função renal com duração de três meses, ou mais. Mudanças psicossociais e biológicas relacionadas ao tratamento dialítico aumentam o risco de desenvolver depressão em pacientes com DRC, além de perda de qualidade de vida. Esse estudo tem como objetivo organizar as principais informações acerca da qualidade de vida e sintomas depressivos em pacientes com DRC em hemodiálise. Metodologia: Refere-se a uma revisão integrativa da literatura sobre qualidade de vida e depressão em pacientes renais crônicos submetidos à hemodiálise. A busca ocorreu em bases de dados confiáveis (PubMed, Scielo e Google Scholar), através das palavras-chave “hemodiálise”, “doença renal crônica”, “depressão” e “saúde mental”, combinadas entre si pelos operadores booleanos AND e OR. Resultados e discussão: Pacientes dialíticos tendem a ter pior qualidade de vida e maior prevalência de depressão e ansiedade. A abordagem a esses indivíduos deve ser multidisciplinar, tanto para a promoção de saúde física quanto mental, por terapia e exercícios físicos intradialíticos, realizados no próprio ambiente hospitalar. Considerações finais: Portanto, conclui-se que a hemodiálise afeta fisicamente e psicologicamente os pacientes, principalmente a longo prazo. Medidas de promoção de saúde devem ser implementadas com o intuito de promover qualidade de vida a esses indivíduos
AUTOMAÇÃO DE TESTES UTILIZANDO A FERRAMENTA CUCUMBER
Authors: Curti Felipe Malheiros , Dallilo Felipe Diniz
Published: February 2022

Este artigo apresenta um estudo por meio da criação de cenários de testes de automação realizados com a ferramenta Cucumber. Adotou-se a metodologia descritiva de cunho quali-quantitativa e teve como ponto de partida um referencial bibliográfico. Na qual foi realizada com auxílio de livros, artigos, teses de mestrado e doutorado e com auxílio da internet. O levantamento dos dados teve base de investigação em bases de consulta como SCIELO (A Scientific Electronic Library Online), Revistas online: CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) USP (Universidade de São Paulo) FGV, (Fundação Getúlio Vargas).  Onde foi possível concluir dizendo que, o teste de automação com o Cucumber oferece uma camada de comunicação real sobre um framework de teste e que no desenvolvimento do teste verificou-se que o processo de automação pode reduzir o tempo que um analista de testes empreende em uma tarefa quando comparado com o processo manual.
A MODELAGEM EM SÉRIES TEMPORAIS PARA ESTIMATIVA DE PRECIPITAÇÃO MÁXIMA DIÁRIA NO MUNICÍPIO DE SANTO BENTO DO UNA (PERNAMBUCO-BRASIL)
Authors: Cunha Filho Moacyr , Portella Corrêa de Oliveira Fábio Henrique , Kazue Sakugawa Shinohara Neide , Casimiro Piscoya Victor , Mainar de Medeiros Raimundo , Vieira de França Manoel , Rocha Moreira Guilherme , Morant de Holanda Romildo
Published: February 2022

Este trabalho tem como objetivo propor uma modelagem em séries temporais para estimativa da precipitação máxima diária em um município do interior de Pernambuco. Objetiva-se, ainda, estimar a precipitação máxima diária para a região nos tempos de retorno de 2, 5, 10, 50, 100 e 1000 anos. O trabalho foi desenvolvido no município de São Bento do Una (Pernambuco, Brasil). Para as modelagens, foram utilizados dados pluviométricos extraídos da plataforma de dados do Instituto de Meterologia, que foram ajustados nas funções de distribuição de probabilidade normal, log-normal, gama, Weibull e Gumbel. Para avaliar se avaliar as distribuições calculadas se ajustam às funções de distribuição de probabilidades testadas, foi realizado o teste de Kolmogorv-Smirnov. Para estimativa da precipitação máxima diária considerando diferentes tempos de retorno, foram empregadas equações reconhecidas na literatura. Os resultados mostram que as distribuições Weibull e Gumbel proporcionaram melhor ajuste do que a normal, log-normal e gama. A diferença em termos de período de retorno e precipitação relacionada é notável para cada uma das cinco distribuições testadas e maiores valores de precipitação máxima diária são observados nos períodos de retorno mais longos, especialmente na distribuição log-normal.
Quantitative ABCD Analysis of Online Food Delivery Services
Authors: Prima Frederick Dsouza , S. Ganesh Bhat
Published: February 2022

Purpose: The core idea of the study is to understand the development of ABCD framework for analysing Online Food Delivery Services and to identify and evaluate the determinant issues and key attributes affecting the factors such as Advantages, Benefits, Constraints, and Disadvantages from stakeholders’ point of view and to find the major affecting factor in respect to Online Food Delivery Services.
Design: The study has systematically reviewed the published paper related to the ABCD analysis framework from 2016 to 2021. The study employed quantitative analysis through focus group interaction by allotting appropriate weightage to key attributes to find the major affecting factors and critical constituent elements for Online Food Delivery Services.
Findings: ABCD analysis framework is the technique used to analyse and evaluate a business model, concept, product, strategy or system. This technique is used by many researchers in different fields for the analysis of their research studies. Quantitative ABCD analysis of Online Food Delivery Services found that Advantages factors affect majorly for the success of the business. The result of ABCD analysis supports the concept/ ideas effectiveness of Online Food Delivery Services.
Originality: The paper gives insights on the determinant issues, key attributes, major affecting factors and critical constituent component elements as per the ABCD analysis framework for Online Food Delivery Services.
Type of Paper: Empirical Analysis
Study of Plant Adaptation to the Arid Zone of Uzbekistan based on System Analysis
Authors: Allaberdiev Rustamjon , Rakhimova Tura , Komilova Nilufar , Kamalova Manzura , Kuchkarov Nurbek
Published: February 2022

Studying the ecological and biological features and water regime of plants of the mountainous semidesert of Uzbekistan to determine their stability in these conditions, we concluded to use an integrated approach to solve the problem of adaptation. Functional, structural or other biological features can equally determine the resistance of a species to extreme factors, such as, for example, the rhythm of development. The purpose of the work is to identify a complex of elements of plant adaptation to arid zone to xerothermic conditions and to characterize ecological groups by the generality of adaptation systems. Based on the system analysis, the biological and structural-functional adaptive features of plants were analyzed, and the studied species were classified into ecological groups as adaptive systems and according to the generality of adaptations to the experience of the dry period. The original data obtained, which relate to the characteristics of the elements of biomorphological adaptation and adaptation of the water regime, the remaining adaptive elements were identified based on the analysis of literary data. Along with structural and behavioral signs, we focus on those features of the water regime that ensure a positive water balance among representatives of various environmental groups. Each of the selected ecological groups of plants is characterized by a certain combination of adaptive features of a physiological and biomorphological plan. With a variety of adaptive features in different plant species to drought and the absence of an integral indicator of drought resistance, it is impossible to focus on any one of them, of course, it is necessary to take into account the whole complex of signs. The complex of features will allow determining more accurately the nature of a particular combination of biomorphological and functional features peculiar to a particular ecological group
Infrastructural Support of Socio-Economic Development of Rural Territories of Ukraine
Authors: Kravchuk Nataliia , Kilnitska Olena , Lavrynenko Svitlana , Yaremova Maryna
Published: February 2022

Rural territories of Ukraine are locked in a “circle of decline” by two mutually reinforcing trends: firstly, the lack of jobs and sustainable business activity, and secondly, the lack of positive changes in the service sector for the rural population. This is often conditioned upon the low development of infrastructural facilities. This causes the need to finance modern, efficient and environmentally friendly rural infrastructure, which will increase the comfort and quality of living, stop the outflow of the working-age population to cities, improve the demographic situation in rural areas, and contribute to the development of the rural economy. Therefore, the research is aimed at diagnosing the current state of infrastructure support for rural areas and finding effective tools to eliminate the causes of their socio-economic decline. The research methodology is based on the use of such general scientific research methods as economic analysis and synthesis in the interpretation of statistical data sets, comparison in determining dynamic changes in the socio-demographic characteristics of rural areas, logical method in making generalisations and conclusions, graphical and computational-constructive for constructing a Lorentz curve, etc. The essence, definition and types of infrastructure are established. The current level of socio-economic development of rural areas of Ukraine is clarified and its interdependence with infrastructure support is discovered. The level of transport, housing and communal services, medical, cultural and educational, trade, and business infrastructure development is described. The paper highlights the experience of stimulating rural development in the EU countries, in particular, outlines financial instruments and the scope of support and comprehensive assistance to rural businesses, environmental protection, competitiveness, and social integration. European investment funds and their role in the development of EU rural infrastructure are described
Evaluation of the Effect of Tightening Torque on Single-lap Bolted Joints
Authors: Boualamallah D. , Ghazi A. , Miloudi A. , Merzoug M.
Published: February 2022

In this experimental research, a set of tests was conducted on single-lap bolted joints in terms of choosing between two types of bolts and exploiting the optimal solution for connecting samples. Then the effect of the tightening torque on the mechanical behavior of single-lap joints was evaluated. Six simple tensile tests were performed with different values of torque and the results are reported.
Critical Factors Influencing the Bid / No-Bid Decision in the Palestinian Construction Industry
Authors: Mahamid I.
Published: February 2022

The purpose of this study is to identify and rank the factors influencing the bid/no-bid decision according to their relative importance from the perspective of the contractors in the West Bank in Palestine. To achieve the study objectives, a questionnaire survey was conducted. The survey covered a randomly selected sample of 64 contractors involved in the construction industry in the West Bank. The questionnaire’s structure is based on the related literature, the pilot study, and the feedback from local experts in the construction industry. A total of 32 factors that might influence the bid/no-bid decision were identified and considered. Then, the targeted population was asked to rank these factors according to their relative importance. The results indicate that the top five factors affecting a contractor’s decision to bid or not include the financial stability of the client, the identity and reputation of the client in the industry, the promptness of the client in the payment process, the expected profitability, and the project’s source of funding. On the other hand, the least affecting factors are the type of the project, client’s requirements, taxes, laws and government regulations, and weather conditions. The paper provides a comprehensive understanding of the factors affecting the bidding decision. Construction parties and researchers could benefit from the results of this study.
Understanding the Seepage Behavior of Nai Gaj Dam through Numerical Analysis
Authors: Bashir A. , Chaudhry R. , Qureshi A. L. , Memon U. , Bheel N.
Published: February 2022

This study presents the seepage patterns of earth-fill dams, using critical situations by employing the finite element approach. The Nai Gaj dam is 65km northwest of Dadu city in Sindh Province, Pakistan. In this study, the seepage through the main dam body and foundation is computed and simulated for different scenarios, i.e. maximum, normal, and minimum reservoir level. Seepage analysis was conducted by using the SEEP/W sub-program of GEO-SLOPE software. Dam design parameters and dam geometry data were used as input data to compute the unknown seepage. The seepage behavior of the Nai Gaj dam is shown in terms of net flow which consists of equipotential lines, streamlines, velocity vectors, and phreatic lines. The results show the seepage flux, maximum seepage, and exit gradient at different reservoir levels. The results show that the average flow rate at normal, maximum, and minimum reservoir levels are 1.49×10-7cumec/m, 3.38×10-7cumec/m, and 2.108×10-8cumec/m respectively. In addition, the overall stability of the side slope of the dam is discussed.
A Tri-band Planar Inverted-F Antenna with Complementary Split Ring Resonator and Reactive Impedance Surface for Wireless Application
Authors: Jadhav T. , Deshpande S.
Published: February 2022

In this paper, a compact, tri-band Planar Inverted-F Antenna (PIFA) using Complementary Split Ring Resonator (CSRR) and Reactive Impedance Surface (RIS) is presented for multiband application. The structure of the PIFA consists of a metallic CSRR and 5×6 periodic unit RIS cells, which accomplishes miniaturization and improves bandwidth and multiband. The RIS metamaterial plane lies between two substrates and acts as a loading function, reducing the volume of the antenna. The measured and simulated results are consistent for a manufactured prototype. The overall size of the antenna is 22.71×3.451×1mm. The PIFA shows a tri-band with an S11 < −10dB bandwidth of approximately 17.08% (2.26-2.67GHz), 5.14% (6.85-7.21GHz) and 19.44% (7.44-9.19GHz) under measurement. The antenna radiates a wave in a preset direction with realized gains ranging from 3.21 to 8.1dbi. The CSRR and RIS improve the performance of the antenna for WLAN, C-band, and X-band applications.
A Neural Network-Based Multi-Label Classifier for Protein Function Prediction
Authors: Tahzeeb S. , Hasan S.
Published: February 2022

Knowledge of the functions of proteins plays a vital role in gaining a deep insight into many biological studies. However, wet lab determination of protein function is prohibitively laborious, time-consuming, and costly. These challenges have created opportunities for automated prediction of protein functions, and many computational techniques have been explored. These techniques entail excessive computational resources and turnaround times. The current study compares the performance of various neural networks on predicting protein function. These networks were trained and tested on a large dataset of reviewed protein entries from nine bacterial phyla, obtained from the Universal Protein Resource Knowledgebase (UniProtKB). Each protein instance was associated with multiple terms of the molecular function of Gene Ontology (GO), making the problem a multilabel classification one. The results in this dataset showed the superior performance of single-layer neural networks having a modest number of neurons. Moreover, a useful set of features that can be deployed for efficient protein function prediction was discovered.
Deadline Verification for Web Services Using Timed Automata
Authors: El Touati Y.
Published: February 2022

Many computation tasks are made today on remote cloud platforms using web services. Beyond the advantages provided by such services, many new challenges arise. One of the challenging problems is ensuring that web services respect critical deadlines. This is a critical issue, especially for real-time systems that use remote web services. This paper aims to propose a framework for deadline verification using Timed Automata (TA).
An Inclusive Study on the Effect of Strain Rate on the Stress-Strain Behavior and the Undrained Shear Strength of Clay Soils in Kombolcha, Ethiopia
Authors: Mohammed S. , Dirate D. D. , Dasho D. K. , Verma R. K. , Pampana V. R. , Sangalang R. B. , Koshuma A. E. , Ayalew A. T.
Published: February 2022

This research aims to study the effect of strain rate on the stress-strain association and shear strength of clay soils in Kombolcha, Ethiopia. Field and laboratory experimentations were conducted on 3 soil samples collected at 4.5m depth, considering the physical and engineering properties of the soil. Unconsolidated, undrained triaxial compression tests were performed under confining pressure on the specimens that were axially loaded at a rate of strain varying from 0.38mm/min to 1.14mm/min by taking 2 points above and below 1% of the specimen height. Stress-strain relations were developed under the stated different rates of strains to describe their effect. It was revealed that the strain rate effect was observed. By increasing the strain rate shifts the stress-strain curve upward, and the corresponding shear strength of the soil also increased under effective stress. Accordingly, the strain rate increased the shear parameters. The average angle of friction increased by 13.43%, 15.08%, 13.18%, and 14.33% when the rate of strain changed from 0.38 to 0.57mm/min, 0.57 to 0.76mm/min, 0.76 to 0.95mm/min, and 0.95 to 1.14mm/min respectively, while the average cohesion increased by 17.67%, 19.52%, 14.87%, and 16.48%. The failure at strain rate 1%/min of sample height (0.76mm/min) was uniformly distributed and there was uniform pore pressure distribution throughout the sample height. The effect is slightly more when the shear strength increased at the left side than at the right side. Average shear strength parameters such as cohesion and angle friction were recorded for strain rates from 0.57mm/min to 1.25mm/min specifically for the clay soils found in Kombolcha town, Ethiopia.
A Review on the Use of Machine Learning Against the Covid-19 Pandemic
Authors: Biabani S. A. A. , Tayyib N. A.
Published: February 2022

Coronavirus-2019 disease (Covid-19) is a contagious respiratory disease that emerged in late 2019 and has been recognized by the World Health Organization (WHO) as a global pandemic in early 2020. Since then, researchers have been exploring various strategies and techniques to fight against this outbreak. The point when the pandemic appeared was also a period in which Machine Learning (ML) and Deep Learning (DL) algorithms were competing with traditional technologies, leading to significant findings in diverse domains. Consequently, many researchers employed ML/DL to speed up Covid-19 detection, prevention, and treatment. This paper reviews the state-of-the-art ML/DL tools used, thoroughly evaluating these techniques and their impact on the battle against Covid-19. This article aims to provide valuable insight to the researchers to assess the use of ML against the Covid-19 pandemic.
The Effect of Different Curing Temperatures on the Properties of Geopolymer Reinforced with Micro Steel Fibers
Authors: Amouri M. S. , Fawzi N. M.
Published: February 2022

In this study, geopolymer mortar was designed in various experimental combinations employing 1% micro steel fibers and was subjected to different temperatures, according to the prior works of other researchers. The geopolymer mortar was developed using a variety of sustainable material proportions (fly ash and slag) to examine the influence of fibers on its strength. The fly ash weight percentage was 50%, 60%, and 70% by slag weight to study its effect on the geopolymer mortar's properties. The optimal ratio produced the most significant results when mixed at a 50:50 ratio of fly ash and slag with 1% micro steel fibers at curing temperature 240oC for 4 hours through two days. The compressive strength of the geopolymer mortar increased by 11%, 11.5%, and 14% after 3, 7, and 28 days when utilizing fibers. The result shows that fly ash with a ratio of 50% by weight of slag improved the compressive strength of the mixture. It was discovered that a combination with 50% of the weight of fly ash with micro steel fibers, when treated at 240oC for curing age of 3, 7, and 28 days, had a flexural resistance rate of 28%, 30%, 33% higher than a mixture without fibers.
A Distributed Control Approach for Demand Response in Smart Grids
Authors: El Gharbi A.
Published: February 2022

The smart grid is a new concept that has been developed during recent years to improve the intelligence and efficiency of electric power system management. Traditional electricity systems are combined and integrated with information technology, communication technology, and intelligent control technology in the smart grid. Demand Response (DR) refers to the changes in consumers' electricity consumption behavior in response to dynamic pricing or financial incentives. Based on the control manner, DR methods are classified as centralized or distributed. In distributed techniques, customers communicate with the other consumers and provide data to the power utility about the overall use. In this paper, we focus on the distributed approach of DR using the shifting method for a short-term horizon. To be more specific, three well-known solutions were studied: the Resource Allocation with Legitimate Claims, the Constrained Fair-Splitting Dispatch, and Real-Time Pricing. Finally, we compare the different techniques of DR distributed approaches based on the control mechanism.
Using Google My Maps as a Geospatial Ticket Management System for Scheduling and Monitoring Power Distribution Network Works
Authors: Pylarinos D.
Published: February 2022

The need to ensure the long-term ability of power distribution systems to meet demands means that upgrades and alterations/expansions, as well as inspection and maintenance works, are constantly necessary. This paper presents an approach to use custom Google Maps as a ticket management system for scheduling and monitoring such works. A geospatial representation is rather useful in networks that are great in length and follow irregular routes (which is typically the case for power distribution networks). However, acquiring a representation of such networks, especially for the Low Voltage side, is an enormous task. This paper presents a cost-free and easy-to-implement approach that can be used in the absence of a full geospatial representation of the network. This approach utilizes an assign-to-the-feeding-transformer (for all Low Voltage issues) and assign-one-indicating-point (for each Middle Voltage issue) scheme, thus, requiring a minimum amount of data easily retrieved from the network. This approach provides a georeferenced ticket management system that can be employed for improved monitoring and scheduling through a user-friendly and free-to-use web-based application which use requires no additional costs or training. The presented approach has been applied in the area of Patras, Greece and initial results, showing a significant improvement in productivity, ranging from 10% to 42%, along with background information are further presented and discussed in this paper.
DFT Investigation of the Structual and Optoelectronic Properties of Alkali Metal Hydrides MH (M=Li, Na)
Authors: Iliass T. , Ziani H. , Gueddim A. , Guibadj A. D.
Published: February 2022

This paper presents ab initio calculations within the Density Functional Theory (DFT) for the structural and optoelectronic properties of the alkali metal hydrides LiH and NaH in rocksalt structure (B1). This study used the Generalized Gradient Approximation (GGA) of Wu-Cohen to consider the electronic exchange and correlation interactions. In addition, the Tran-Blaha modified Becke-Johnson exchange potential was used with the GGA approach (GGA-TBmBJ) to calculate the band structure with high accuracy. The structural properties, namely the lattice parameter, the bulk modulus, and the pressure derivative of the bulk modulus were determined and found to be generally in good agreement with other research findings. Furthermore, the energy band gaps, the Density Of States (DOS), the static and high-frequency dielectric constant, along the refractive index were addressed and analyzed. These results could be useful for hydrogen storage purposes.
Challenges in the Numerical Analysis of Centrifugal Pumps¨: Energetic, Cavitation and Dynamic Characteristics
Authors: Lipej A.
Published: February 2022

Pumps are energetic devices that are present in a wide range of industries. Their installed power varies from a few tens of watts up to hundreds of megawatts. As the energy consumption is connected with global warming and climate change, the development of pumps that have good characteristics is very important. Theoretical and experimental methods have long been utilized in the development of pumps, but recently much research has been carried out with the help of Computational Fluid Dynamics (CFD) analysis. Certain numerical analyses can be of high quality and accurate, but special operational phenomena still occur, where special attention is required when performing analysis. This category includes operating regimes outside the Best Efficiency Point (BEP), the formation of inlet recirculation, cavitation, and the influence of wall roughness on all the above characteristics. The current paper presents the main problems that developers face when numerically analyzing the above-mentioned special operating regimes. Both numerical and experimental results are considered.
Stability Analysis of Boundary Layer Flow and Heat Transfer of Fe2O3 and Fe-Water Base Nanofluid οver a Stretching/Shrinking Sheet with Radiation Effect
Authors: Lanjwani H. B. , Chandio M. S. , Malik K. , Shaikh M. M.
Published: February 2022

In this paper, the radiation and slip effects are investigated on the boundary layer flow and heat transfer of Fe2O3 and Fe-water base nanofluids over a porous stretching/shrinking sheet. A similarity transformation is used to convert the system of governing partial differential equations into ordinary differential equations, which are then numerically solved in Maple software with the help of the shooting technique. At different ranges of the applied parameters, dual solutions are found. The effects of the different physical factors such as radiation, nanoparticle volumetric fractions, suction, and slip parameters are determined and discussed. The skin-friction coefficient and local Nusselt number are influenced significantly by the applied parameters. In the boundary layer regime, the increase in nanoparticle volume fractions and radiation parameters enhance the temperature and boundary-layer thicknesses, while increasing Prandtl number, suction, and thermal slip parameters decrease the temperature and reduce thermal boundary-layer thicknesses. The suspension of iron nanoparticles shows more enhancement in skin friction and Nusselt number than the iron oxide nanoparticles in base fluid water.
Prestressing Effects on Full Scale Deep Beams with Large Web Openings¨: An Experimental and Numerical Study
Authors: Abbas R. , Hussein I.
Published: February 2022

Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and behavior. A total of seven deep beam specimens with identical shear span-to-depth ratio, compressive strength of concrete, and amount of horizontal and vertical web reinforcement ratios have been tested under mid-span concentrated load applied monotonically until failure. The main variables studied were the effects of depth of the web openings and the prestressing location on deep beam performance. The test results showed that the enlargement in the size of web openings substantially reduces the element’s shear capacities while prestressing strands location above the web openings has more effect at increasing the element’s shear capacities. The numerical study considered three-dimensional finite element models that have been developed in Abaqus software to simulate and predict the performance of prestressed deep beams. The results of numerical simulations were in good agreement with the experimental ones.
A Non-Parametric Empirical Method for Nonlinear and Non-Stationary Signal Analysis
Authors: Berrouche Y.
Published: February 2022

A Non-parametric Ensemble Empirical Mode Decomposition (NCEEMD) method is a novel technique for nonlinear and non-stationary signal analysis to detect a gearbox fault. The NCEEMD method was based on the CEEMD, but the Gaussian white noise was replaced by the fractional Gaussian noise. The NCEEMD method does not need to choose the appropriate SNR and the number of ensemble trials before signal processing, which makes it a non-parametric method. This new approach was evaluated using a simulated malfunction signal representing two typical faults in gearbox systems: modulation and rub-impact. Its performance was evaluated in terms of MSE and computation time. A comparative study between the EMD, EEMD, CEEMD, and NCEEMD methods showed that the latter performed better by improving the computation time and accuracy of CEEMD. The proposed method is a non-parametric method that provides a powerful tool in extracting the modulation and the rub-impact features from a vibration signal. The NCEEMD method helps to track down the gearbox faults and resolve this crucial problem in mechanical machines.
Load Shedding in Microgrids with Dual Neural Networks and AHP Algorithm
Authors: Nhung L. T. H. , Phung T. T. , Nguyen H. M. V. , Le T. N. , Nguyen T. A. , Vo T. D.
Published: February 2022

This paper proposes a new load shedding method based on the application of a Dual Neural Network (NN). The combination of a Back-Propagation Neural Network (BPNN) and of Particle Swarm Optimization (PSO) aims to quickly predict and propose a load shedding strategy when a fault occurs in the microgrid (MG) system. The PSO algorithm has the ability to search and compare multiple points, so the proposed NN training method helps determine the link weights faster and stronger. As a result, the proposed method saves training time and achieves higher accuracy. The Analytic Hierarchy Process (AHP) algorithm is applied to rank the loads based on their importance factor. The results of the ratings of the loads serve as a basis for constructing the load shedding strategies of a NN combined with the PSO algorithm (ANN-PSO). The proposed load shedding method is tested on an IEEE 25-bus 8-generator MG power system. The simulation results show that the frequency recovery of the power system is positive. The proposed neural network adapts well to the simulated data of the system and achieves high performance in fault prediction.
An Intelligent Detoxification Function of Liver Algorithm-Partial Transmit Sequence (IDFLA-PTS) for the Reduction of Peak to Average Power Ratio in Underwater Acoustic OFDM Communication
Authors: Ali A. , Chen B. , Raza W. , Ali A. , Li H.
Published: February 2022

Intelligent algorithms in artificial intelligence have brought several benefits to digital signal processing. The boom in machine learning and intelligent systems provides new perspectives and methods to solve many research problems in Underwater Acoustic (UWA) Orthogonal Frequency Divisional Multiplexing (OFDM) communication. Partial transmit sequence is a tremendous technique for the mitigation of high Peak-to-Average Power Ratio (PAPR) in OFDM communication systems, but finding the optimum phase factors has still a few problems. In this paper, a Partial Transmit Sequence (PTS) based on an Intelligent Detoxification Function of Liver Algorithm-Partial Transmit Sequence (IDFLA-PTS) is proposed for the mitigation of PAPR in the UWA OFDM communication systems. This algorithm reduces the PAPR and the complexity of the proposed UWA OFDM model. The IDFLA-PTS is also compared with the Genetic Algorithm-Partial Transmit Sequence (GA-PTS). Besides this, the Bit Error Rate (BER) performance of the IDFLA-PTS is shown when a High Power Ampliﬁer (HPA) is used for the BELLHOP channel model. The experimental results of the proposed IDFLA-PTS method achieved nearly optimum results with fair complexity as compared to GA-PTS and boosted the BER performance.
Evaluating the Efficiency of Finance Methods in Residential Complex Projects in Iraq
Authors: Khameesa A. S. , Altaay M. R.
Published: February 2022

Financial funding of a construction firm plays an important role in all aspects of the process development. It has been noted that financial crises have a direct impact on the construction industry. The Iraqi government, whether locally or globally, has faced a severe shortage of financing which has resulted in incomplete projects. Due to the financial crisis that Iraq went through which led to the suspension of many residential complex projects and the difficulty of the use of public financing methods, we researched the private financing (public-private partnership) methods instead of public financing methods in residential complex projects implementation. This study verified the financial problems and the factors that relate to the possibility of their occurrence with the use of a questionnaire that was designed and distributed to professionals in the field. Arbitration of the questionnaire, pilot study, questionnaire distribution, and statistical tests were conducted. The T-test (paired samples T-test) was used to find out if there are differences between the public and private financing methods. The results showed that the private financing (public-private partnership) methods, under the current conditions in Iraq, are better than the public financing methods.
Designing an IoT Agriculture Monitoring System for Improving Farmer’s Acceptance of Using IoT Technology
Authors: Anas S. A. B. , Singh R. S. S. , Kamarudin N. A. B.
Published: February 2022

This paper describes Agri-Snaps, an Internet of Things (IoT) agriculture monitoring system designed to improve farmers’ acceptance of using IoT technology in their farm field. Agri-Snaps consists of four dedicated sensor circuit modules that integrate magnetic pogo pin connectors for easier assembly with the controller circuit module. This work investigated how such a design can enable the farmers to understand how 1) to assemble, 2) self-troubleshoot, and 3) maintain the monitoring system independently without requiring expertise on the farm site. User-experience testing was conducted with ten participants to validate Agri-Snaps’s viability. The results showed that those participants positively rated Agri-Snaps as attractive, easy to understand and assemble, exciting, and innovative compared to the typical agriculture monitoring systems.
Efficient Hybrid Algorithm Solution for Optimal Reactive Power Flow Using the Sensitive Bus Approach
Authors: Sahli Z. , Hamouda A. , Sayah S. , Trentesaux D. , Bekrar A.
Published: February 2022

This paper presents the design and application of an efficient hybrid algorithm for solving the Optimal Reactive Power Flow (ORPF) problem. The ORPF is formulated as a nonlinear constrained optimization problem where the active power losses must be minimized. The proposed approach is based on the hybridization of Particle Swarm Optimization (PSO) and Tabu-Search (TS) technique. The proposed PSO-TS approach is used to find the settings of the control variables (i.e. generation bus voltages, transformer taps, and shunt capacitor sizes) which minimize transmission active power losses. The bus locations of the shunt capacitors are identified according to sensitive buses. To show the effectiveness of the proposed method, it is applied to the IEEE 30 bus benchmark test system and is compared with PSO and TS without hybridization, along with some other published approaches. The obtained results reveal the effectiveness of the proposed method in dealing with the highly nonlinear constrained nature of the ORPF problem.
A Novel Approach for the Modeling of Electromagnetic Forces in Air-Gap Shunt Reactors
Authors: Duc H. B. , Minh T. P. , Anh T. P. , Quoc V. D.
Published: February 2022

Shunt reactors are usually used in electrical systems to imbibe reactive powers created by capacitive powers on the lines when the system is operating on low or no loads. Moreover, they are also used to balance reactive powers and maintain the stability of a specified voltage. In general, the air gaps of a magnetic circuit shunt reactor are arranged along the iron core to reduce the influence of fringing and leakage fluxes. Therefore, non-magnetic materials made of ceramics or marbles are often used in air gaps to separate the iron core packets. The direction of the fringing flux is perpendicular to the laminations, so the core packets of the shunt reactor are generally made from radially laminated silicon steels. Due to the alternating electromagnetic field through the core, a periodically altered electromagnetic force is produced between the core packets, tending to compress the ceramic spacers. This electromagnetic force causes vibration and noise in the core. In this research, a finite element approach based on the Maxwell stress tensor was developed to compute the magnetic flux density and the electromagnetic forces appearing in a shunt reactor.
Assessment of Groundwater Quality Using Water Quality Indices: A Case Study of Paliganj Distributary, Bihar, India
Authors: Praveen K. , Roy L. B.
Published: February 2022

Groundwater quality evaluation in the command area of Paliganj distributary of the Sone irrigation scheme in India was carried out during two different seasons in the year 2020, namely pre-monsoon, i.e. during March, and post-monsoon, i.e. during October. Forty groundwater samples were obtained from hand pumps and dug wells in the study area during the pre- and post-monsoon seasons. The chemical characteristics of groundwater samples were determined according to American Public Health Association approved process. Twelve parameters, namely, pH, EC, TDS, Ca, Mg, Na, F, SO4, K, Cl, and HCO3 were used to compute the water quality based on the weighted arithmetic water quality index method. In the study area, Ca2+-Mg+-HCO3−, and Ca2+-Mg+-Na+-HCO3- were the dominant hydro-chemical facies. All the samples were found to belong to the excellent to good category for drinking purposes during the pre-monsoon period. However, during the post-monsoon season, only 75% of the samples fell into the excellent to good group, while the remaining 25% fell into the poor for drinking purposes category. By analyzing through the irrigation quality index, 80% of the samples are considered highly suitable for irrigation and the remaining 20% come under the medium category. Thus, it was seen that the majority of groundwater samples are suitable for drinking and irrigation purposes, although groundwater in some portions of the area had high salinity and the Sodium Adsorption Ratio (SAR), showing that it is unsuitable for irrigation and requires adequate drainage.
Circuit Modeling and Analysis of Wearable Antennas on the Effect of Bending for Various Feeds
Authors: Mallavarapu S. , Lokam A.
Published: February 2022

The promising utilization of wearable antennas has experienced gigantic growth during the last decade. An antenna is one of the most significant and crucial components of wireless wearable devices. They need to be particularly designed to work while worn on and off the body. The wearable antenna embedded into clothing finds its use in wireless communications including tracking and navigation, mobile and wearable computing, and public safety and security. For user accessibility, there is a growing requirement for incorporating antennas on or in clothing. Determining the dielectric characteristics of the flexible substrates utilized in the design of the wearable antenna is also essential. In this paper, a Microstrip Ring Resonator (MRR) is employed to determine the dielectric properties of fabric substrates followed by state-of-the-art designs of wearable antennas and their bending effects at ISM band frequencies. An electrical equivalent model is designed to realize the potentials inside the geometry of an antenna under bending environment. This is followed by observing the effect of bending for different feeding methods on the wearable antenna's parameters when bending on a certain radius. The robustness of the proposed wearable antenna is examined by measuring the antenna under various bending curvatures for return loss, gain, and efficiencies. This will disclose the various contemplations for designing a wearable antenna from different feeding mechanisms with different materials and exemplifying the antenna's outcomes to dynamic moments of the human body. The performance of the proposed wearable antenna is acceptable even in a deformation environment, and there is a good agreement between the measured and the simulation results.
Illegal Construction Imposed by the Private Lands in Peripheral Urban Areas of M’sila, Algeria
Authors: Benkhaled E. , Mili M. , Oudina F.
Published: February 2022

Urban building lands are considered a scarce resource, which forces us to rationalize their use and assignment. They play an important role in shaping the urban space with all its components and determine its characteristics. The impact on urban space depends on the legal nature of the land, the density of buildings, and the quality of social cohesion. Like all Algerian cities, the city of M'sila has experienced, since the '90s, an increasing demand for building plots, especially in the outskirts which are mostly private properties. This situation directly contributed to the spread of illegal constructions and as a result, districts lack basic living conditions. This phenomenon appeared in the peripheral district called La Rocade. In this paper, we will attempt to identify the impact of the legal nature of land properties, particularly private ones, on the proliferation of illegal constructions in the outskirts of the city of M'sila. We will try to find solutions and alternatives to limit or stop its spread and propose urban interventions to restructure this district and integrate it into the existing urban space.
CCEPTED Automorphisms on complex simple Lie algebras of order 3
Authors:   Department of Multimedia and Game Development, Minghsin University of Science and Technology Hsinchu County, Taiwan., Hsin Ching-I
Published: February 2022

For complex simple Lie algebras, the article provides classification of all automorphisms of order 3. The method is an extension of Dynkin diagrams, so that the classification is a listing of diagrams which represent automorphisms of order 3. This work extends an earlier result on automorphisms of order 2. As an application, it shows that for automorphisms of orders 2 and 3 only, the invariant subalgebra determines the automorphism.
AN IMPROVED MULTI-OBJECT INSTANCE SEGMENTATION BASED ON DEEP LEARNING
Authors:   School of Computer Sciences Universiti Sains Malaysia,11800, Pulau Pinang, Malaysia, Funkur Alshdaifat Nawaf Farhan , Azam osman Mohd ,   School of Computer Sciences Universiti Sains Malaysia,11800, Pulau Pinang, Malaysia, Zawawi Talib Abdullah ,   School of Computer Sciences Universiti Sains Malaysia,11800, Pulau Pinang, Malaysia
Published: February 2022

Deep Learning (DL) networks have attracted growing interest and attention by researchers and scholars alike due to the growing importance of detecting and instance segmentation of objects in an image. Instance segmentation is a critical issue that requires further improvement due to the difficulties in adapting object detection and instance segmentation approaches. This paper presents an approach that overcome these issues by proposing a new approach based on the recent DL approach in addition to developing an approach for multi-object instance segmentation. The improved multi-object segmentation approach presented in this paper consists of three stages. Firstly, it improves the RestNet-101 (Residual Neural Network) backbone by connecting it to the convolution layer for each ResNet block. Secondly, the localization of multiple objects is improved by enhancing the Region Proposal Network (RPN), and thirdly, a complex instance segmentation approach is utilized. The result of this study based on a standard dataset, called the Common Object in Context (COCO) dataset (Lin et al., 2014), reveals that the suggested approach compared to other well-known segmentation approaches, has improved the instance segmentation process in terms of precision and training time.
Assessing The Challenges of Executing State Sponsored Projects in Ghana: A Case of Getfund Construction Projects in The Upper West Region
Authors: Iddrisu Abdul Ganiyu
Published: February 2022

The core mandate of GETFund is to provide funding to supplement government budgetary  allocations in the provision of educational infrastructure at all levels of education from  pre-tertiary to tertiary level as stipulated in the (GETFund Act, 2000 Act 581). The study  aims to evaluate the challenges and managerial skills adopted by GETFund contractors.  The study's objective is to examine the challenges of GETFund construction projects,  identify factors affecting GETFund projects and devise effective strategies to enhance  effective GETFund project execution in the Region. The study adopted a descriptive  survey design. Sixty-five clients, twenty-one consultants, and sixty-two contractors  totaling one hundred and forty-eight were sampled for the study. Questionnaires,  interviews, and observation were the main methods adopted for data collection. The data  were analyzed using descriptive statistics. The study revealed that the most leading  challenges affecting the efficient execution of GETFund construction projects are political  and financial. Furthermore, the most leading factors confronting efficient GETFund  construction projects execution in the Region are cost and time. In addition, the study  revealed that most of the contractors' agents executing GETFund projects do not have the  requisite technical personnel, expertise, and resources, making it difficult to  understand/interpret drawings and other specifications given to them by project  consultants. The study recommended that professional regulatory bodies such as Building  and Road Research Institute (BRRI) organize in-service training to improve the  management skills of companies.