bluuebunny/crossref_metadata_2025 huggingface dataset:
Causes of Change Orders in Construction Projects
Authors: Khalifa W. M. A. , Mahamid I.
Published: November 2020

Change orders are usually issued to cover variations in the scope of work, material quantities, design errors, and unit rate changes. This study discusses variations in public construction projects in Saudi Arabia by investigating their causes, studying their effects on the project, identifying the beneficial parties, and suggesting remedies to alleviate the related problems. Tasks included conducting a field survey via a questionnaire. It was determined that the top five causes of change orders from contractors’ view are: owner’s additional works, errors, and omissions in design, lack of coordination between construction parties, defective workmanship, and owner financial difficulties.
Real-Time Investigation of an Adaptive Fuzzy Synergetic Controller for a DC-DC Buck Converter
Authors: Behih K. , Benmahammed K. , Bouchama Z. , Harmas M. N.
Published: November 2020

In this paper, an adaptive fuzzy synergetic controller (AFSC) for a DC-DC converter is introduced. Two robust control techniques, synergetic control combined with fuzzy logic control, are utilized to produce a reliable DC-DC power supply. This is-realized by an indirect adaptive control of a DC-DC buck converter. To further enhance robustness, a nonlinear constraint, the equivalent of the sliding surface, is used to guarantee performance and stability for any operating condition. To ensure overall strength, closed-loop signals are bounded and the stability is guaranteed using the Lyapunov theory. Control parameters are optimized using a PSO algorithm to further enhance performances. The proposed controller (AFSC) is designed through a dSpace based experimental setup to provide robust DC-DC buck converter voltage control.
Evaluating Pressure in Deepwater Gas Pipeline for the Prediction of Natural Gas Hydrate Formation
Authors: Abbasi A. , Mohd Hashim F.
Published: November 2020

This paper proposes the prediction of hydrate formation pressure in deepwater pipeline with an approach of intelligent optimization. The proposed novel correlation of hydrate formation is using the function of ordinary differential equation. The developed optimization prediction model was founded on the constant coefficients which were examined by a multiple set of experimental data of methane (CH4), ethane (C2H6), propane (C3H8), iso-butane (iC4), nitrogen (N), Carbon Dioxide (CO2) and hydrogen sulfide (H2S) hydrates. The consequences of this research are highly optimistic for the natural gas production industry.
An Effective Method for Maximizing Social Welfare in Electricity Market via Optimal TCSC Installation
Authors: Long D. T. , Nguyen T. T. , Nguyen N. A. , Nguyen L. A. T.
Published: November 2020

The evolving electricity market has increased power demand and has brought many social benefits. Meanwhile, the transmission systems are not developed to the same extent because building new lines is difficult for environmental and political reasons. Hence, the systems are driven close to their limits resulting in congestions and critical situations endangering the system’s security. Due to this, the study of enhancing the transfer capability of existing power networks to satisfy the increased power demand, maximum social welfare, and ensure its secure operation has become one of the challenges the Independent System Operator faces in the electricity market. In order to solve this problem without building more transmission lines, the installation of FACTS devices can be a better alternative. Among FACTS devices, thyristor-controlled series compensator (TCSC) is one that can redistribute power flow in the network to improve the transfer capability of the existing system effectively. However, it is very difficult to implement. This paper presents the implementation of the Cuckoo Optimization Algorithm (COA) to solve the OPF problem which is formulated as a nonlinear optimization problem with equality and inequality constraints in a power system for social welfare maximization via the optimal installation of TCSC devices. As Cuckoo Search Algorithm (CSA), the COA also starts with an initial population-based metaheuristic optimization inspired by the nature of brood parasitism of some cuckoo species. However, unlike CSA, COA uses the cuckoo’s style for egg-laying to optimize the local search instead of using Lévy flights. This model is tested in IEEE 14 and IEEE 30 bus systems. Simulations results are compared with GA and GWO and show that the COA is one useful method for TCSC installation to maximize social welfare.
High Speed Mobility Management Performance in a Real LTE Scenario
Authors: Abuelgasim A. A. M. K. , Yusof K. M.
Published: November 2020

This paper discusses the mobility management for high-speed users, which is a crucial challenge for all mobile operators, especially when users are moving vertically across different network technologies. Mobility, also known as seamless connectivity, is directly influencing the quality of service (QoS). Mobility management-Handover (HO) performance was evaluated by field measurements of a Long Term Evolution (LTE) network of a mobile operator in the Middle East. Drive test measurements were used to analyze the results of different high-speed scenarios. User Equipment (UE) with high speed of 80-140km/h causes a high risk of failure of seamless connectivity as the HO procedure timing is longer than for UE with smaller speed. HO failure and call drop may occur when UE is moving with high speed across two adjacent cells in highways. During measurements, HO failure occurred when UE speed was 140km/h, and HO preparation timing increased when UE speed increased.
Experimental Study of Electric and Dielectric Behavior of PVC Composites
Authors: Madani L. , Belkhir K. S. , Belkhiat S.
Published: November 2020

Polyvinyl chloride (PVC) is usually used as insulation in electrical engineering, mainly as cable insulation sheaths. A method for improving PVC’s dielectric properties, reducing the effects of UV aging, is the use of PVC films doped in alumina and titanium dioxide. This research investigated the influence of alumina and titanium dioxide (Al2O3/TiO2) on the dielectric properties of PVC. Four PVC samples were examined using an RLC impedance analyzer. Fourier Transform Infrared (FTIR) spectroscopy was utilized on the sample’s surfaces, exploring the chemical stability of the tested materials. In addition, the volume resistivity and average breakdown voltage of each sample were examined. Doping Al2O3/TiO2 into PVC improved its dielectric properties and volume resistivity while adding more ceramic decreased volume resistivity. Furthermore, the addition of Al2O3/TiO2 caused a significant enhancement in voltage breakdown strength.
Design and Implementation of a Statistical Testing Framework for a Lightweight Stream Cipher
Authors: Alamer A. , Soh B.
Published: November 2020

The Shrinking Generator (SG) is a popular synchronous, lightweight stream cipher that uses minimal computing power. However, its strengths and weaknesses have not been studied in detail. This paper proposes a statistical testing framework to assess attacks on the SG. The framework consists of a d-monomial test that is adapted to SG by applying the algebraic normal form (ANF) representation of Boolean functions, a test that uses the maximal degree monomial test to determine whether the ANF follows the proper mixing of bit values, and a proposed unique window size (UWS) scheme to test the randomness properties of the keystream. The proposed framework shows significant weaknesses in the SG output in terms of dependence between the controlling linear-feedback shift register (LFSR) and non-linearity of the resulting keystream. The maximal degree monomial test provides a better understanding of the optimal points of SG, demonstrating when it is at its best and worst according to the first couple of results. This paper uses UWS to illustrate the effect of the LFSR choice on possibly distinguishing attacks on the SG. The results confirm that the proposed UWS scheme is a viable measure of the cryptographic strength of a stream cipher. Due to the importance of predictability and effective tools, we used neural network models to simulate the input data for the pseudo-random binary sequences. Through the calculation of UWS, we obtained solid results for the predictions.
Aging Effect on Microstructure and Machinability of Corrax Steel
Authors: Guldibi A. S. , Demir H.
Published: November 2020

In this paper, the influence of the aging process on the microstructure and machinability of Corrax Steel was investigated for four samples: a solution heat-treated (A0) and three samples aged at 400ºC (A4), 525ºC (A5.25) and 600ºC (A6) for four hours. The effect of aging temperature on hardness was examined. Machining tests were carried out using a CNC lathe with a multi-layer coated PVD (AlTiN) cutting tool, at various cutting speeds (50, 100, 150, 200, 250, 300, 350m/min) with constant feed rate (0.1mm/rev) and 1mm constant cutting depth. The microstructure was investigated using an optical microscope and EDS attached SEM. The effect of aging on reverted austenite formation was also evaluated. In order to understand the changes in surface topology, cutting forces and vibrations were measured. With increasing aging temperature, the lath martensite was transformed to plate martensite because of the formation of precipitates and reverted austenite. Aging at different temperatures increased hardness up to 58%, cutting forces up to 117% and surface roughness up to 450%. The results describe the effect of the aging treatment on cutting forces, surface topology, tool wear and vibrations.
Seismic Amplification by Deep Subsurface and Proposal of a New Proxy
Authors: Nagao T.
Published: November 2020

Codes of practice and ground motion prediction equations involve ground structure proxies to account for seismic amplification. Although the ground consists of both shallow and deep subsurface, proxies are mainly related to the shallow subsurface as it is shallow subsurface information that is mostly available. However, as deep subsurface seismic amplification is not negligible, it may not be appropriate to use shallow subsurface proxies. In this study, the relationship between shallow and deep subsurface seismic amplification factors is discussed on the basis of S-wave velocity profile data from Japanese KiK-net strong-motion observation system stations. The correlation between typical proxies such as the average S-wave velocity of the top 30m of the ground surface and the seismic amplification factor was examined. Although there was a negative correlation between the two, the degree of the correlation was weak. A new proxy showing stronger correlations with the seismic amplification factor is proposed and its effectiveness is demonstrated.
Refining Student Marks based on Enrolled Modules’ Assessment Methods using Data Mining Techniques
Authors: Alsuwaiket M. , Blasi A. H. , Altarawneh K.
Published: November 2020

Choosing the right and effective way to assess students is one of the most important tasks of higher education. Many studies have shown that students tend to receive higher scores during their studies when assessed by different study methods - which include units that are fully assessed by varying the duration of study or a combination of courses and exams - than by exams alone. Many Educational Data Mining (EDM) studies process data in advance through traditional data extraction, including the data preparation process. In this paper, we propose a different data preparation process by investigating more than 230,000 student records for the preparation of scores. The data have been processed through diverse stages in order to extract a categorical factor through which students’ module marks are refined during the data preparation stage. The results of this work show that students’ final marks should not be isolated from the nature of the enrolled module’s assessment methods. They must rather be investigated thoroughly and considered during EDM’s data pre-processing stage. More generally, educational data should not be prepared in the same way normal data are due to the differences in data sources, applications, and error types. The effect of Module Assessment Index (MAI) on the prediction process using Random Forest and Naive Bayes classification techniques were investigated. It was shown that considering MAI as attribute increases the accuracy of predicting students’ second year averages based on their first-year averages.
Study of a New Design of the Planar Inverted-F Antenna for Mobile Phone Handset Applications
Authors: Ghnimi S. , Nasri A. , Gharsallah A.
Published: November 2020

This paper suggests a new design of the PIFA antenna for mobile phone handset applications. In this context, we are interested in the development of new techniques based on the creation of slot matching for the improvement and miniaturization of a dual-band PIFA antenna operating at 900MHz and 1800MHz. Analysis of antenna parameters such as return loss (S11), radiation pattern, Voltage Standing Wave Ratio (VSWR), current distributions, gain, and the relation between them are performed in CST software. There is a good agreement between the results of simulation by CST and HFSS and those of measurement for the proposed antenna.
Openings Effect on the Performance of Reinforced Concrete Beams Loaded in Bending and Shear
Authors: El Ame F. , Mwero J. N. , Kabubo C. K.
Published: November 2020

Transverse openings are often provided to reinforced concrete beams to accommodate utility ducts and pipes. This technique is usually adopted to avoid the creation of dead space in structures caused by extended dropped ceilings and leads to significant cost saving. On the other hand, the provision of openings through a beam creates a reduction in its strength and affects serviceability. In this study, ten reinforced concrete beams were cast using C30 concrete. Material characterization and engineering properties tests were carried out to ensure compliance with the requirements provided by the codes of practice. The effect of vertical positioning and size of openings was investigated through subjecting the beams to a four-point bending test after 28 days of curing. Maximum load capacity, first cracking load, and deflections at mid-span were recorded and crack pattern and failure mode were evaluated. Test data showed that openings of depth greater than 0.4d significantly affect the beams’ strength and lead to earlier cracking, while the failure mode remains essentially the same, a diagonal tension crack through the opening except for opening of 0.5d size where the failure occurred by a sudden formation of two independent shear cracks above and below the opening. When holes were located above the centroid of the section, the beams exhibited a lesser deflection characterized by the absence of plastic deformation. Furthermore, a significant reduction in strength was recorded compared to cases where the positioning of openings was in tension chords. This was validated using equations from the ACI code of reinforced concrete design.
Critical Factors Influencing the Behavioral Intention of Consumers towards Mobile Banking in Malaysia
Authors: Rehman Z. U. , Shaikh F. A.
Published: November 2020

Mobile banking services are widely adopted in developed and developing countries, while their adoption by Malaysian consumers is relatively low. The effective adoption of mobile banking mostly depends on consumers. This study’s objective was to examine the factors that influence Malaysian customers’ behavioral intention toward mobile banking. A detailed literature review was conducted in order to identify the critical factors that affect mobile banking users. The research model was based on the Technology Acceptance Model, investigating the additionally perceived risk. Primary data were collected from 384 generation Y bank customers. Structure equation modeling through Smart-PLS was used for data analysis. Results revealed that consumers’ behavioral intention was significantly and positively influenced by perceived usefulness and ease of use, while a significant negative relationship was found between consumers’ behavioral intention and perceived risk. The findings also revealed a mediating relationship of attitude between perceived usefulness, ease of use and risk, and behavioral intention to use mobile banking. The study provides appropriate guidelines to Malaysian banks and mobile banking application developers for the effective implementation and design of mobile banking services.
Contractor’s Selection Criteria in Construction Works in Pakistan
Authors: Soomro N. U. I. , Memon A. H. , Memon N. A. , Memon K. R.
Published: November 2020

The contractor is the primary stakeholder in materializing a project concept. For the successful completion of any project, it is compulsory for the contractor to have relevant experience. The selection of the appropriate contractor depends on various criteria. This study aims to study these selection criteria. Based on 71 questionnaire forms received from representatives of contractor, consultant and client firms involved in execution works of construction activities it is found that quality, bid amount, technical capability, financial stability, and experience are five commonly adopted criteria for contractor selection in construction works in Pakistan. On the other hand, quality, technical capability, financial stability, equipment availability, and management capability are reported as the top five effective criteria for appropriate contractor selection for any construction project.
Dynamic Behavior and Force Analysis of the Full Vehicle Model using Newmark Average Acceleration Method
Authors: Yildirim E. , Esen I.
Published: November 2020

In this study, the dynamic interaction between road and vehicle is modeled. For this purpose, a full vehicle model with eight degrees of freedom is considered. The equations of motion of the whole system are derived by the D’Alambert method and numerical solutions are obtained by the Newmark average acceleration method. Due to varying road roughness, the forces affecting the driver and the vehicle-components are analyzed in detail. Also, vertical and rotational displacements, velocities, and accelerations are examined, and results graphs are given. Two different pre-defined road profiles, created as non-random road excitation, and five different vehicle speeds are presented and analyzed.
Panic Detection in Crowded Scenes
Authors: Altamimi A. B. , Ullah H.
Published: November 2020

A crowd is a gathering of a huge number of individuals in a confined area. Early identification and detection of unusual behaviors in terms of panic occurring in crowded scenes are very important. Panic detection comprises of formulating normal scene behaviors and detecting and identifying non-matching behaviors. However, panic detection and recognition is a very difficult problem, especially when considering diverse scenes. Many methods proposed to cope with these problems have limited robustness as the density of the crowd varies. In order to handle this challenge, this paper proposes the integration of different features into a unified model. Discriminant binary patterns and neighborhood information are used to model complex and unique motion patterns in order to characterize different levels of features for diverse types of crowd scenes, focusing in particular on the detection of panic and non-pedestrian entities. The proposed method was evaluated considering two benchmark datasets and outperformed five existing methods.
Factors Influencing the Intention to Continue using B2B e-Commerce in Manufacturing SMEs
Authors: Hussein L. A. , Baharudin A. S. , Kiumarsi S. , Hilmi M. F.
Published: November 2020

Business-to-Business (B2B) electronic commerce plays a tremendous role in nurturing the growth of Small and Medium Enterprises (SMEs) in developed and developing countries. However, the growth of B2B e-commerce in developing nations remains at the early adoption stage. The purpose of this paper is to examine the factors that influence B2B e-commerce adoption in SMEs in a developing country. The current study employs the questionnaire survey technique to gather information from 245 manufacturing SMEs in Jordan. It uses Structural Equation Modeling (SEM) to investigate the different factors that affect the intention to adopt or continue using B2B e-commerce. The study reveals that compatibility and outsourcing IT support have significant effects on the intention to continue using B2B e-commerce in Jordanian manufacturing SMEs. The implications of the findings are discussed.
Use of Marble Powder and Tile Powder as Cementitious Materials in Concrete
Authors: Bheel N. , Kalhoro K. A. , Memon T. A. , Lashari Z. U. Z. , Soomro M. A. , Memon U. A.
Published: November 2020

The use of agricultural and industrial waste products as raw materials in the construction industry is investigated extensively. These products are inexpensive and help in environmental sustainability, as environmental pollution is thus reduced. This study focused in investigating the properties of fresh, physical and hardened concrete blended with marble (MP) and tile powder (TP) of several proportions, such as 0%, 5% (2.5%MP + 2.5%TP), 10% (5%MP + 5%TP), 15% (7.5%MP + 7.5%TP), and 20% (10%MP + 10%TP) by weight. A total of 60 concrete cylinders were cast with 0.45 water/cement ratio, 1:1.96:2.14 mix ratio, and were cured for 7 and 28 days. These cylinders were used for checking the compressive and splitting tensile strength of concrete. The experimental results showed that compressive and splitting tensile strengths were increased by 8.90% and 8.30% respectively for the 2.5%MP + 2.5%TP sample after 28 days.
A Short Review on Green Supply Chain Management Practices: The Impact on Operational and Environmental Performance
Authors: Shaikh F. A. , Shahbaz M. S. , Odhano N.
Published: November 2020

The aspects of sustainability and ecology have gradually become matters of significant concern within supply chain management processes. The aim of this study is to investigate the impact of the green supply chain on the environment and on operational performance. This study considers environmental management practices within firms, sustainable supply chain management practices relating to suppliers and customers, and environmentally conscious product and process design, by adopting a case-study approach and focusing on four major firms. The findings of this study reveal that the companies applying green supply chain management achieve better environmental performance but at an extra cost. Meanwhile, green practices provide improved customer satisfaction and attraction for retailers, distributors, and authorities.
Torque Ripple Minimization of a Switched Reluctance Motor using a Torque Sharing Function based on the Overlap Control Technique
Authors: Maksoud H. A.
Published: November 2020

The torque ripple produced in a switched reluctance motor (SRM) can be seen as one of its major drawbacks. It occurs mainly due to the sequential switching of the motor phases and changes in the length of the air gap. The torque sharing functions (TSFs) are the more effective and favorable techniques developed to reduce the torque ripple in SRMs. However, the time responses of instantaneous torque for incoming and outgoing phases during commutation period (CP) are different. In addition, with increasing motor speed the CP decreases and the torque response of the outgoing phase oversteps it. In this paper, a modified torque sharing function based on the change of the overlap angle during the commutation process depending on the motor speed is presented. In the designed control algorithm of the TSFs, the motor speed is has become an input besides the rotor position and the torque command. The commutation time is precisely adjusted enough for the commutating process. The proposed method gives good results in a wide speed range. To deduce the magnetic characteristics of the SRM, finite element analysis (FEA) is applied and a look-up table model is derived. The effectiveness and robustness of the proposed control technique are exhibited in the simulation results.
Prestress Losses in Concrete Rafters with Openings
Authors: Alkhafaji F. J. , Izzet A. F.
Published: November 2020

In this paper, experimental work was conducted to evaluate the losses in prestressing force of 13 (12 perforated and 1 solid) simply supported prestressed concrete rafters. All beams had the same dimensions and reinforcements. The tested beams were divided into four main groups and three additional subgroups were driven. These groups were classified according to size, number, and configuration of the openings, and the orientation of the posts (vertical or inclined). Regarding the prestress losses that have been affected by the cross-section properties, the provision of the codes is applicable only to prismatic solid beams, so non-prismatic or moreover perforated beams also need to be studied. This paper aims to propose a method based on the same code provisions but taking into consideration the cross-section variation along the beam length. The proposed method divides the overall length of the rafter into a number of assumed prismatic segments with heights measured at centers. Then, the overall prestress loss is found as the sum of these segments weighed by the ratios of the length of each beam segment to the overall length. The experimental results of the proposed method ranged from 84.749% to 95.607% denoting its validity.
Human Interruption Management in Workplace Environments: An Overview
Authors: Alkahtani M. , Abidi M. H. , Ahmad A. , Darmoul S. , Samman S. , Ghaleb M.
Published: November 2020

Interruptions are unexpected breaks that introduce new tasks on top of ongoing activities. In work environments, interruptions occur when operators and decision-makers have to deal simultaneously with several stimuli and information sources and have to make decisions so as to maintain the flow of activities at a satisfactory level of performance or quality of service. The causes and effects of interruptions and their subsequent management strategies in workplace environments have been researched in the past, however, only a few review articles are available to report on current advances in this area, to analyze contributions, and to highlight open research directions. This paper offers an up-to-date review and a framework for interruptions and interruption management strategies. The current approaches to identify, report, and manage interruptions in a variety of workplace environments are reviewed and a description of environmental characteristics that favor the occurrence of interruptions and influence interruption management in workplace environments is provided. Various approaches to classify and model the different types of interruptions and their cause-consequence relationships are discussed and the strategies to manage interruptions and approaches to measure human performance when dealing with interruptions are analyzed. Based on these insights, several guidelines to manage interruptions in workplace environments are provided, and future research directions are highlighted.
Cloud Job ‎Scheduling with‎ Ions Motion Optimization Algorithm
Authors: Hassan M. E. , Yousif A.
Published: November 2020

Cloud computing technology success comes from its manner of delivering information ‎technology services, how they are designed, propagated, maintained and scaled. Job Scheduling ‎on cloud computing is a crucial ‎research area and is known to be an NP-complete problem. Scheduling refers to assigning user requests to underlying resources effectively. ‎This paper proposes a new Job Scheduling mechanism for cloud computing ‎environment. The proposed mechanism is based on the Ions Motion Optimization (IMO) algorithm. IMO has two phases, liquid, and crystal. These two phases balance the algorithm behavior ‎between convergence and local optima avoidance. To evaluate the proposed mechanism, a ‎simulation with different scenarios using the CloudSim simulator is conducted. The performance of ‎the proposed algorithm is compared with two metaheuristic algorithms known as Cat Swarm ‎Optimization (CSO) and Glowworm Swarm Optimization (GSO). Furthermore, the proposed IMO ‎mechanism is compared with First Come First Served and random solution. The experimental ‎results demonstrated that the proposed mechanism outperformed both CSO ‎and GSO and produced the shortest execution time in all experimental scenarios.
A Web-based Data Visualization Tool Regarding School Dropouts and User Asssesment
Authors: Kayanda A. M. , Machuve D.
Published: November 2020

Data visualization is important for understanding the enormous amount of data generated daily. The education domain generates and owns huge amounts of data. Presentation of these data in a way that gives users quick and meaningful insights is very important. One of the biggest challenges in education is school dropouts, which is observed from basic education levels to colleges and universities. This paper presents a web-based data visualization tool for school dropouts in Tanzania targeting primary and secondary schools, together with the users’ feedback regarding the developed tool. We collected data from the United Republic of Tanzania Government Open Data Portal and the President’s Office - Regional Administration and Local Government (PO-RALG). Python was then used to preprocess the data, and finally, with JavaScript, a web-based tool was developed for data visualization. User acceptance testing was conducted and the majority agreed that data visualization is very helpful for quickly understanding data, reporting, and decision making. It was also noted that the developed tool could be useful not only in the education domain but it could also be adopted by other departments and organizations of the government.
Usability Testing of a Web Portal for Ornamental Plants and Flowers in Arusha, Tanzania
Authors: Asiimwe K. P. , Machuve D. , Dida M. A.
Published: November 2020

The Information and Communication Technology (ICT) adoption has steadily advanced in the horticulture sector in Tanzania. This study aims to test and give feedback regarding the usability of a developed web portal prototype for ornamental plants and flowers in Arusha City. The stakeholders are botanists and researchers who search for plant and flower information (taxonomy), small scale farmers, herbalists, and the Arusha City Council. The assessments were organized and conducted in groups where each stakeholder was given access to the web portal for 2 days. Questionnaires were distributed to get feedback from each participant (a total of 48 participants). Multicriteria satisfaction analysis was chosen to measure user satisfaction measuring usability factors such as service quality, technical quality, information quality, and system quality. The overall obtained results had a mean score above 3.5 (70%) on a five-point scale Likert scale analysis.
SFCL-SMES Control for Power System Transient Stability Enhancement Including SCIG-based Wind Generators
Authors: Zebar A. , Madani L.
Published: November 2020

The resolution of the environment pollution depends on renewable energy sources, such as wind energy systems. These systems face transient and voltage stability issues with wind energy employing fixed-speed induction generators to be augmented with resistive type Superconducting Fault Current Limiter (SFCL) and Superconducting Magnetic Energy Storage (SMES) devices. The use of a combined model based on SFCL and SMES for promoting transient and voltage stability of a multi-machine power system considering the fixed-speed induction generators is the primary focus of this study. Our contribution is the development of a new model that combines the advantages of SFCL and SMES. The proposed model functions assure flexible control of reactive power using SMES controller while reducing fault current using superconducting technology-based SFCL. The effectiveness of the proposed combined model is tested on the IEEE11-bus test system applied to the case of a three-phase short circuit fault in one transmission line.
An Efficiency Study of the Aerodynamic Sound Generators Suitable for Acoustic Particle Agglomeration
Authors: Vekteris V. , Ozarovskis D. , Moksin V. , Turla V. , Jurkonis E.
Published: November 2020

The object of this study is the acoustic field generated by aerodynamic acoustic generators of various types and designs. Six types of aerodynamic acoustic generators were studied experimentally and theoretically to determine the parameters of their generated acoustic field. It was established that the aerodynamic Hartmann type sound generator produces the necessary for acoustic particle agglomeration acoustic field and can be used in acoustic air cleaning equipment. It was established that classical theoretical calculation methods underestimate the design features of aerodynamic acoustic generators and cannot be used to calculate their characteristics.
Effect of Sugarcane Bagasse Ash and Lime Stone Fines on the Mechanical Properties of Concrete
Authors: Bheel N. , Memon A. S. , Khaskheli I. A. , Talpur N. M. , Talpur S. M. , Khanzada M. A.
Published: November 2020

Cement production releases huge amounts of carbon dioxide having a significant impact on the environment while also having huge energy consumption demands. In addition, the disposal and recovery of natural concrete components can lead to environmental degradation. The use of waste in concrete not only reduces cement production, but it also reduces energy consumption. The aim of this study is to evaluate the properties of fresh and hardened concrete by partially replacing cement with sugarcane bagasse ash (SCBA) and limestone fines (LSF). In this investigation work the cement was replaced with SCBA ash and LSF by 0% (0% SCBA+ 0% LSF), 5% (2.5% SCBA+ 2.5% LSF), 10% (5% SCBA+ 5% LSF), 15% (7.5% SCBA+ 7.5% LSF) and 20% (10% SCBA+ 10% LSF) by weight of cement. In this regard, a total of 60 samples of concrete specimens were made with mix proportion of 1:1.5:3 with 0.56 water-cement ratio. Cube specimens were tested for compressive strength and cylindrical specimens were used for determining splitting tensile strength at 7 and 28 days respectively. The optimum result displayed that the crushing strength and split tensile strength increased by 10.33% and 10.10% while using 5% SCBA+ 5% LSF as a substitute for cement in concrete after the 28th day. The slump value of concrete declined as the content of SCBA and LSF increased.
Structural and Electrical Properties of Ca2+ Doped LaFeO3: The Effect of A-site Cation Size Mismatch
Authors: Irmak A. E.
Published: November 2020

In this study, nanosized La1-xCaxFeO3 (0.00≤x≤0.40) compounds prepared via sol-gel method followed by heat treatment at 1100oC for 24 hours are studied. Crystal structure, microstructure, surface morphology and temperature-dependent resistivity of the samples are investigated. TEM investigation reveals nanoparticles with an average size of 35nm produced from the sol-gel process. The crystal structure of the compounds belongs to an orthorhombically distorted perovskite structure with Pbnm space group. Lattice distortion and cation size mismatch increase with an increase in Ca and particle and grain growth are suppressed by Ca doping. Electrical conduction is explained via thermally activated hopping of small polarons. Unit cell volume, charge ordering temperature, and activation energy for small polarons decrease linearly with an increase in cation size mismatch. Room temperature resistivity decreases with Ca doping and gets its minimum value for 30% Ca at which the orthorhombic distortion is maximum.
A Control Model for Reinforced Concrete Work Materials on the Construction of Duta Mall 2
Authors: Daslim S. , Mursadin A.
Published: November 2020

Controlling is a crucial stage in achieving a project target, covering aspects of cost, quality, and time. In the construction industry, the cost aspect is often the main focus. The project of Duta Mall 2 (DM 2) is the development of an existing building and the cost aspect is a major concern to the owner. Dynamic internal and external factors of the DM 2 project cause the project control to be quite difficult, with the materials becoming the most dominant factor in construction cost. Cost control starts from reinforced concrete work materials, consisting of ready mixed concrete, concrete steel, wire, plywood, timber, and nails. Bad control of material purchasing can lead to cost escalation, degradation of material quality, and impact on the execution schedule of works. This research was conducted to obtain quantitative correlations between material components based on reinforced concrete works material supply data. From these data, some linear regression models can be designed to obtain a more accurate and effective prediction of material volume needs in the future. Model equations can be applied to control material demand, measure waste, reference of material volume in arranging the project cost budget, in addition to the process in the control procedure of the request for goods (materials and equipment).
Mobile-based Deep Learning Models for Banana Disease Detection
Authors: Sanga S. L. , Machuve D. , Jomanga K.
Published: November 2020

In Tanzania, smallholder farmers contribute significantly to banana production and Kagera, Mbeya, and Arusha are among the leading regions. However, pests and diseases are a threat to food security. Early detection of banana diseases is important to identify the diseases before too much damage is done on the plants. In this paper, a tool for early detection of banana diseases by using a deep learning approach is proposed. Five deep learning architectures, namely Vgg16, Resnet18, Resnet50, Resnet152 and InceptionV3 were used to develop models for banana disease detection, achieving all high accuracies, varying from 95.41% for InceptionV3 to 99.2% for Resnet152. InceptionV3 was selected for mobile deployment because it demands much less memory. The developed tool was capable of detecting diseases with a confidence of 99% of the captured leaves from the real environment. This tool will help smallholder farmers conduct early detection of banana diseases and improve their productivity.
Photonic Jet Suitable for High Precision Contact Laser Surgery Applications in Water
Authors: Azizi M. K. , Alotaibi A. A.
Published: November 2020

The use of contact probes in surgical laser technologies (SLT) allows tissue contact without damage and enables tactile feedback during operations. Among the materials suitable for the manufacturing of chirurgical contact probes, sapphire has been widely used. Indeed, the optical properties of this material allow the formation of a high energy density localized region at the front of the contact probe, when used in air. However, in water, this focusing effect is very weak. In this work, the use of a cylindrical sapphire contact probe associated with a continuous (CW) Nd: Yag laser (at 1064nm) is proposed and studied, which provides, in water, a narrow and high-intensity beam (photonic jet). With the evolution of technology, this kind of surgery can be done remotely. Based on 5G technology, medical experts can bring their skills to remote other practitioners around the world. The obtained results show a linear dependence of the focal length and a linear dependence of the beam intensity of the photonic jet to the cylinder radius while the full width at half maximum of the photonic jet beam shows exponential decay dependence. Such a system could give rise to a new kind of optical scalpel to the ultra-precise laser surgery in water.
Optimized Controller Design for an Islanded Microgrid using Non-dominated Sorting Sine Cosine Algorithm (NSSCA)
Authors: Islam Q. N. U. , Abdullah S. M. , Hossain M. A.
Published: November 2020

In order to cope with the increasing energy demand, microgrids emerged as a potential solution which allows the designer a lot of flexibility. The optimization of the controller parameters of a microgrid ensures a stable and environment friendly operation. Non-dominated Sorting Sine Cosine Algorithm (NSSCA) is a hybrid of Sine Cosine Algorithm and Non-dominated Sorting technique. This algorithm is applied to optimize the control parameters of a microgrid which incorporates both static and dynamic load. The obtained results are compared with the results of the established Non-dominated Sorting Genetic Algorithm-II (NSGA-II) in order to justify the proposal of the NSSCA. The average time needed to converge in NSSCA is 7.617s whereas NSGA-II requires an average of 10.660s. Moreover, the required number of iterations for NSSCA is 2 which is significantly less in comparison to the 12 iterations in NSGA-II.
Multiple Voltage Disturbance Compensation in Distribution Systems using DVR
Authors: Suraya S. , Irshad S. M. , Azeem M. F. , Al-Gahtani S. F. , Mahammad M. H.
Published: November 2020

The subject of power quality is gaining much interest nowadays. With the sophisticated sensitive electrical devices available in the market, power stations should ensure qualified and eminent power to the point of utilization. Bad voltage conditions in a power system can cause a malfunction at the point of utilization. Dynamic voltage restorer (DVR) is a reliable power electronic offsetting device which when engaged in the power system is effectual in the operation of compensating voltage sag/swell. In this research work, a DVR for offsetting multiple voltage disturbances in a power system is presented and a novel control strategy to trigger power switches in DVR is proposed. The proposed novel control methodology is compared with Synchronous Reference Frame (SRF) theory-controlled DVR. The simulation model is designed and the analysis with MATLAB/SIMULINK is presented
Pneumonia and Eye Disease Detection using Convolutional Neural Networks
Authors: Chakraborty P. , Tharini C.
Published: November 2020

Automatic disease detection systems based on Convolutional Neural Networks (CNNs) are proposed in this paper for helping the medical professionals in the detection of diseases from scan and X-ray images. CNN based classification helps decision making in a prompt manner with high precision. CNNs are a subset of deep learning which is a branch of Artificial Intelligence. The main advantage of CNNs compared to other deep learning algorithms is that they require minimal pre-processing. In the proposed disease detection system, two medical image datasets consisting of Optical Coherence Tomography (OCT) and chest X-ray images of 1-5 year-old children are considered and used as inputs. The medical images are processed and classified using CNN and various performance measuring parameters such as accuracy, loss, and training time are measured. The system is then implemented in hardware, where the testing is done using the trained models. The result shows that the validation accuracy obtained in the case of the eye dataset is around 90% whereas in the case of lung dataset it is around 63%. The proposed system aims to help medical professionals to provide a diagnosis with better accuracy thus helping in reducing infant mortality due to pneumonia and allowing finding the severity of eye disease at an earlier stage.
Application of Sunflower Optimization Algorithm for Solving the Security Constrained Optimal Power Flow Problem
Authors: Duong T. L. , Nguyen T. T.
Published: November 2020

Finding the Optimal Power Flow (OPF) which minimizes total generator cost is the answer to one of the most important problems in the electricity market operation. Independent System Operators (ISO) face many challenges while operating the system in order to obtain economic benefits and security. The solution to this problem is known as Security Constrained Optimal Power Flow (SCOPF). SCOPF is a very large-scale and nonlinear optimization problem with many complex constraints. This paper proposes the Sunflower Optimization (SFO) algorithm for solving the SCOPF problem. The proposed method is tested on the IEEE 30-bus and the IEEE 118-bus systems for both normal and outage cases. The result comparison with other known methods showed that the proposed SFO algorithm is an effective method for solving the SCOPF problem in the electricity market.
Classification of Electrical Power System Conditions with Convolutional Neural Networks
Authors: Kiruthika M. , Bindu S.
Published: November 2020

Undesirable operation of a distant relay at the occurrence of stressed conditions is a reason for blackouts. There are a few computational intelligent methods available in the literature for avoiding relay maloperations. However, because of variations in the system parameters and expansions of the network, the performance of these techniques can be degraded. To solve this issue, data mining approaches have been introduced. The existing data mining approaches need improvement in terms of accuracy and error rate while discriminating fault and stressed conditions. In this paper, a Convolutional Neural Network (CNN) based classifier is proposed for identifying various faults and differentiating fault and power swing situations. The data are collected from the IEEE-9 bus system by Phasor Measurement Units (PMU) and the proposed CNN classifier model classifies system conditions like normal, fault, and power swing. The outcome shows that the classifier has high accuracy and low error rate compared to other classification models such as Naïve Bayes, Decision Tree, and K-Nearest Neighbor. Furthermore, the proposed CNN model is validated with the use of TensorFlow framework to demonstrate its superior performance.
Simulation-based Analysis of a Dynamic Voltage Restorer under Different Voltage Sags with the Utilization of a PI Controller
Authors: Soomro A. H. , Larik A. S. , Mahar M. A. , Sahito A. A. , Sohu I. A.
Published: November 2020

Power quality problems are becoming a major issue. Every utility company consumer desires to receive steady-state voltage, i.e. a sinusoidal waveform of constant frequency as generated at power stations, but the influence of disturbances in the shape of sags and swells, interruptions, transients and harmonic distortions which affect power quality, resulting in loss of data, damaged equipment, and augmented cost. The most powerful voltage disturbance is the sag voltage. In this paper, a Dynamic Voltage Restorer (DVR) is proposed for sag voltage compensation. It is cost-effective and protects critical loads in a good manner from balanced or unbalanced sag voltage. Control strategy (such as a PI controller) is adopted with DVR topology and the performance of such a device with the proposed controller is analyzed through simulation in MATLAB/Simulink. Three types of faults are utilized, which are available in MATLAB/Simulink pack, for obtaining the sag voltage. The specific range of total harmonic distortion percentage is also discussed. After the result validation of the DVR topology in MATLAB/Simulink, it has been seen that the proposed topology is able to compensate the sag voltage of any type of fault and reduce the unbalancing and voltage distortions of the grid.
Imperfect Roll Arrangement Compensation Control based on Neural Network for Web Handling Systems
Authors: Duc D. N. , Thi L. T. , Nguyen T. L.
Published: November 2020

The speed and tension control problem of a web handling system is investigated in this paper. From the system equations of motion, we developed a backstepping-sliding mode control for web speed and tension regulation tasks. It is obvious that the designed control depends heavily on roll inertia information. Dissimilar to other researches that were based on the assumptions of rolls with perfect cylindrical form with the rotating shafts of the rolls considered properly aligned, the novelty of this paper is the presentation of a neural network to compensate the effects of imperfect roll arrangement. The neural network design is based on the Radial Basis Function (RBF) network estimating the uncertainty of roll inertia. The information on estimated inertia is fed into a backstepping-sliding mode controller that ensures tension and velocity tracking. The control design is presented in a systematical approach. Closed loop system stability is proven mathematically. The tracking performance is shown through several simulation scenarios.