bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Leakage Current Waveforms Recorded in a Coastal High Voltage Substation
Authors: Pylarinos D. , Siderakis K. , Pyrgioti E. , Thalassinakis E. , Vitellas I.
Published: November 2020

Leakage current monitoring is a widely employed technique to monitor the performance of outdoor insulation. The evaluation of leakage current waveforms recorded in the field, offers significant information since insulation’s performance is strongly linked with local conditions, and the waveforms’ shape correlate to different types of surface activity. In this paper, an investigation of leakage current waveforms recorded in a 150 kV coastal Substations suffering which suffers intense marine pollution is presented. Investigation of the recorded waveforms verified the basic waveform shapes described in the literature. Further, several variations of the basic types and complex waveforms, as well as field related waveforms, are presented. The need for added categorization criteria in the case of field measurements is discussed.
Developing Activities for Teaching Cloud Computing and Virtualization
Authors: Erturk E. , Maharjan B.
Published: November 2020

Cloud computing and virtualization are new but indispensable components of computer engineering and information systems curricula for universities and higher education institutions. Learning about these topics is important for students preparing to work in the IT industry. In many companies, information technology operates under tight financial constraints. Virtualization, (for example storage, desktop, and server virtualization), reduces overall IT costs through the consolidation of systems. It also results in reduced loads and energy savings in terms of the power and cooling infrastructure. Therefore it is important to investigate the practical aspects of this topic both for industry practice and for teaching purposes. This paper demonstrates some activities undertaken recently by students at the Eastern Institute of Technology New Zealand and concludes with general recommendations for IT educators, software developers, and other IT professionals.
A GTN-like Model for Plastic Porous Materials
Authors: Siad L. , Gangloff S. C.
Published: November 2020

An extended version of the well-known Gurson-Tvergaard-Needleman (GTN) isotropic hardening model is presented in this paper. The yield function of the proposed constitutive model possesses the distinctiveness to explicitly depend upon the third stress invariant. The presented constitutive model is used to analyze the necking of a round tensile bar. As long as softening initiation of specimen is not reached, the obtained numerical results highlight similarities and good agreement with those provided by the use of the GTN model. However, discrepancy shows up as soon as specimen failure starts.
Numerical Investigation of Plastic Deformation in Two-turn Equal Channel Angular Extrusion
Authors: Mitsak A. , Aour B. , Khelil F.
Published: November 2020

There has been a number of investigations in recent years reporting on the structure and properties of materials deformed to super plastic deformation (SPD). During SPD new textures can be formed and abnormal characteristics are displayed, attracting a growing research interest.¶ Equal channel angular extrusion (ECAE) is a method often used to obtain large plastic strains. However, according to experimental results, there is a large tensile stress in the sample during deformation, which may lead in some cases, to cracking in metallic alloys and large curvature in polymeric materials. In order to overcome these drawbacks, the ECAE process can be conducted at high temperatures.  But this contributes significantly to a decreased level of plastic deformation induced in the sample. Hence, a tool with multi-pass seems to be a very appropriate solution. In this paper, a new geometry die composed of two elbows has been simulated by finite element method aiming to provide an insight into the mechanisms of deformation and to determine the optimum geometry of the tool. The numerical results show that the length and the section of the second channel play a significant role on the homogeneity of the plastic strain distribution. It has been found that good homogeneity was obtained when the second channel has the same section as that of the entrance and the exit channels and with a length equal to three times of its width.
Simulating Nonlinear Oscillations of Viscoelastically Damped Mechanical Systems
Authors: Monsia M. D. , Kpomahou Y. J. F.
Published: November 2020

The aim of this work is to propose a mathematical model in terms of an exact analytical solution that may be used in numerical simulation and prediction of oscillatory dynamics of a one-dimensional viscoelastic system experiencing large deformations response. The model is represented with the use of a mechanical oscillator consisting of an inertial body attached to a nonlinear viscoelastic spring. As a result, a second-order first-degree Painlevé equation has been obtained as a law, governing the nonlinear oscillatory dynamics of the viscoelastic system. Analytical resolution of the evolution equation predicts the existence of three solutions and hence three damping modes of free vibration well known in dynamics of viscoelastically damped oscillating systems. Following the specific values of damping strength, over-damped, critically-damped and under-damped solutions have been obtained. It is observed that the rate of decay is not only governed by the damping degree but, also by the magnitude of the stiffness nonlinearity controlling parameter. Computational simulations demonstrated that numerical solutions match analytical results very well. It is found that the developed mathematical model includes a nonlinear extension of the classical damped linear harmonic oscillator and incorporates the Lambert nonlinear oscillatory equation with well-known solutions as special case. Finally, the three damped responses of the current mathematical model devoted for representing mechanical systems undergoing large deformations and viscoelastic behavior are found to be asymptotically stable.
Durability Properties of Palm Oil Fuel Ash Self Compacting Concrete
Authors: Ofuyatan T. , Olutoge F. A. , Olowofoyeku A.
Published: November 2020

Self Compacting Concrete (SCC) is a new innovation in technology that can flow readily into place under its own self weight and fill corner areas of reinforcement structures without the need to vibrate and without segregation of its constitute. The problem of durability of concrete structures due to inadequate compaction by skilled workers has become a source of concern globally. The shortage of skilled manpower, noise and vibration of equipment on construction sites has led to the development of self compacting concrete. This paper presents an experimental study on the durability properties of Self Compacting Concrete with partial placement of Palm Oil Fuel Ash (POFA). Twelve POFA self-compacting concretes of various strength grades were designed at varying percentages of 0, 5, 10, 15, 20, 25 and 30%. The concrete with no placement of ash served as control. Conplast SP432MS was used as superplasticiser in the mix. The experiments are carried out by adopting a water-powder ratio of 0.36. Workability of the fresh concrete is determined by using tests such as: slump flow, T50, V-funnel and L-Box tests. The durability of concrete is tested by acid resistance, sulphate attack and saturated water absorption at the age of 14, 28, 56 and 90 days.
Using Neural Networks to Predict the Hardness of Aluminum Alloys
Authors: Zahran B.
Published: November 2020

Aluminum alloys have gained significant industrial importance being involved in many of the light and heavy industries and especially in aerospace engineering. The mechanical properties of aluminum alloys are defined by a number of principal microstructural features. Conventional mathematical models of these properties are sometimes very complex to be analytically calculated. In this paper, a neural network model is used to predict the correlations between the hardness of aluminum alloys in relation to certain alloying elements. A backpropagation neural network is trained using a thorough dataset. The impact of certain elements is documented and an optimum structure is proposed
Comparative Investigation of Pollution Accumulation and Natural Cleaning for Different HV Insulators
Authors: Dimitropoulou M. , Pylarinos D. , Siderakis K. , Thalassinakis E. , Danikas M.
Published: November 2020

High Voltage insulators are scattered throughout any HV network and a single insulator fault may cause an excessive outage. Reliability is a key issue for electric power systems and fault-free performance of insulators greatly reflects on the reliability of the system. Environmental influence is rather important for the optimum selection of outdoor insulators and, therefore, field measurements provide valuable information. Utilities perform such measurements in order to decide upon the location/route of new HV installations (substations, lines etc) and also to optimize the selection, maintenance and replacement of already installed insulators. A rather interesting case in Greek territory is the island of Crete, due to the coastal development of the network and the local weather conditions. The Greek utility has employed a variety of remedies to cope with the pollution problem. Following the positive feedback after the installation on certain tower in the past, a large project to replace all ceramic insulators with new polymer ones of hydrophobic surface is now in progress. Polymer coatings have also been extensively applied on substations and also on certain areas/towers of the transmission network in the past. In order to investigate the pollution accumulation and the impact of natural washing on different insulator types, a series of periodical ESDD and NSDD pollution measurements were conducted in HEDNO’s TALOS High Voltage Test Station for a 3-months period. Multiple measurements were performed on each insulator every month in order to collect additional data. Five different insulators were selected based on the types historically used in the Cretan Network. Along with the standard glass disc profile, two strings of glass fog profile (the one coated with RTV) and two long-rod composite insulators of different shed profile and material were used. Results are presented and discussed in this paper.
Development of the Contiguous-cells Transportation Problem
Authors: Charles-Owaba O. E. , Oladokun V. , Okunade O.
Published: November 2020

The issue of scheduling a long string of multi-period activities which have to be completed without interruption has always been an industrial challenge. The existing production/maintenance scheduling algorithms can only handle situations where activities can be split into two or more sets of activities carried out in non-contiguous sets of work periods. This study proposes a contiguous-periods production/maintenance scheduling approach using the Transportation Model. Relevant variables and parameters of contiguous-cells scheduling problem were taken from the literature. A scheduling optimization problem was defined and solved using a contiguous-cells transportation algorithm (CCTA) which was applied in order to determine the optimal maintenance schedule of a fleet of ships at a dockyard in South-Western Nigeria. Fifteen different problems were solved. It is concluded that the contiguous-cells transportation approach to production/ maintenance scheduling is feasible. The model will be a useful decision support tool for scheduling maintenance operations.
Preventive Maintenance Interval Prediction: a Spare Parts Inventory Cost and Lost Earning Based Model
Authors: Adebimpe O. A. , Oladokun V. , Charles-Owaba O. E.
Published: November 2020

In this paper, some preventive maintenance parameters in manufacturing firms were identified and used to develop cost based functions in terms of machine preventive maintenance. The proposed cost based model considers system’s reliability, cost of keeping spare parts inventory and lost earnings in deriving optimal maintenance interval. A case of a manufacturing firm in Nigeria was observed and the data was used to evaluate the model.
Pollution Maintenance Techniques in Coastal High Voltage Installations
Authors: Siderakis K. , Pylarinos D. , Thalassinakis E. , Vitellas I. , Pyrgioti E.
Published: November 2020

Pollution of outdoor high voltage insulators is a common problem for utilities, with a considerable impact to power system reliability. In an effort to prevent possible flashovers due to pollution, many methods have been applied, aiming to improve the insulation performance, either by suppressing the formation of surface conductivity or by increasing the possible insulation level. In the case of substations, the selection of the appropriate technique is complex due to certain issues correlated to the nature of the installation. In this paper, several techniques usually implemented by utilities, are investigated based on the experienced gained in the case of Crete, a Greek island in southern Europe, where due to the coastal development of the power system, the majority of high voltage installations are exposed to intense marine pollution. The technique of coating insulators with Room Temperature Vulcanized Silicone Rubber (RTV SIR) has proved rather efficient and therefore is presented extendedly. Correlation of the material behaviour with environmental conditions is discussed and results from long term monitoring, including environmental parameters and leakage current measurements, in a 150 kV Substation are presented. It is shown that RTV SIR coatings have remarkably suppressed surface activity and that porcelain insulators exhibit different activity period when coated.
Modeling and Control of a DFIG-Based Wind Turbine During a Grid Voltage Drop
Authors: Babaie Lajimi A. , Asghar Gholamian S. , Shahabi M.
Published: November 2020

Doubly-fed induction generators (DFIG) are widely used in wind energy generation systems. During a grid voltage drop, performance is degraded with rotor over current deteriorating the fault-ride through (FRT) capability of the DFIG wind-energy generation system. In this paper, a complete mathematical DFIG model is proposed. The rotor is considered fed by a voltage source converter whereas the stator is connected to the grid directly. Output power and electromagnetic torque are controlled using field-oriented control (FOC). Simulation results show the efficiency of the controller in exploiting the maximum power of wind.
Developing Situation of Tea Harvesting Machines in Taiwan
Authors: Wu C. C.
Published: November 2020

In recent years rapid social change and industrial and commercial development in Taiwan has lead to migration of rural labor, population ageing, high wages and labor shortages, which resulted in significant problems for the tea industry. Thus, mechanization in the tea industry emerges as the direction for the future. According to a survey, tea harvesting and tea manufacturing use 87% and 5% of available labor, so the mechanization of tea harvesting is a priority. The application and development of tea harvesting machines worldwide and especially in Taiwan in recent years is investigated in this paper. Recommendations are made for the implementation of tea harvesting machinery in Taiwan in the future. This report may also used as a reference for the use of mechanical harvesting.
Modeling Photovoltaic Power
Authors: Mavromatakis F. , Franghiadakis Y. , Vignola F.
Published: November 2020

A robust and reliable model describing the power produced by a photovoltaic system is needed in order to be able to detect module failures, inverter malfunction, shadowing effects and other factors that may result to energy losses. In addition, a reliable model enables an investor to perform accurate estimates of the system energy production, payback times etc. The model utilizes the global irradiance reaching the plane of the photovoltaic modules since in almost all Photovoltaic (PV) facilities the beam and the diffuse solar irradiances are not recorded. The airmass, the angle of incidence and the efficiency drop due to low values of solar irradiance are taken into account. Currently, the model is validated through the use of high quality data available from the National Renewable Energy Laboratory (USA). The data were acquired with IV tracers while the meteorological conditions were also recorded. Several modules of different technologies were deployed but here we present results from a single crystalline module. The performance of the model is acceptable at a level of 5% despite the assumptions made. The dependence of the residuals upon solar irradiance temperature, airmass and angle of incidence is also explored and future work is described.
Design and Simulation of a Decentralized Railway Traffic Control System
Authors: Kara T. , Cengiz Savas M.
Published: November 2020

With the increasing use of railway transportation, various methods have been developed for the control and management of train traffic. Train traffic control systems that are currently in use are overwhelmingly centralized systems. In this study, the development of the general structure of railway traffic control techniques is examined, centralized and decentralized control systems are investigated, and an alternative train traffic control system, the Decentralized Train Traffic Management System (DTMS), is suggested. Simulation results on the possible application of the proposed method to a railway line in South-East Turkey are employed to evaluate the performance of the developed system.
Torque Ripple Minimization and Performance Investigation of an In-Wheel Permanent Magnet Motor
Authors: Mansouri A. , Hafedh T.
Published: November 2020

Recently, electric vehicle motoring has become a topic of interest, due to the several problems caused by thermal engines such as pollution and high oil prices. Thus, electric motors are increasingly applied in vehicle’ applications and relevant research about these motors and their applications has been performed. Of particular interest are the improvements regarding torque production capability, the minimization of torque ripple and iron losses. The present work deals with the optimum design and the performance investigation of an outer rotor permanent magnet motor for in-wheel electric vehicle application. At first, and in order to find the optimum motor design, a new based particle-swarm multi-objective optimization procedure is applied. Three objective functions are used: efficiency maximization, weight and ripple torque minimization. Secondly, the effects of the permanent magnets segmentation, the stator slots opening, and the separation of adjacent magnets by air are outlined. The aim of the paper is the design of a topology with smooth output torque, low ripple torque, low iron losses and mechanical robustness.
A Novel Efficient Sine Wave Inverter with Custom Programmed PWM and Intelligent Control
Authors: Haider A. S. , Naz A. , Akhter F. , Azhar W. , Mehmood R.
Published: November 2020

This article presents an efficient design of a pure sine wave inverter which results in an electronic design with reduced losses. The proposed design incorporates the generation of custom programmed pulse width modulation (CPPWM) waveforms; the gate drive signals that are customized for the harmonic elimination from the output voltage, maximizing the fundamental component and resulting in an efficient electronic circuit design as compared to the traditional techniques in terms of the switching losses and the filtering energy losses. The CPPWM signals are digitally programmed in a micro-controller. The inverter realization is followed by an intelligent compensator design for the regulation of output voltage amplitude. The proposed algorithm self-adjusts its parameters in response to the load current and voltage amplitude variations hence resulting in an improved performance. The simulation results of the control algorithm are presented. The experimental validation of the theoretically investigated controller is also presented by implementing a discrete time realization of the control algorithm using digital controller interfaced in real time with MATLAB®/Simulink®. The hardware results are elucidated. The feasibility of the proposed controller is theoretically and experimentally verified by its efficiency compared to the classical techniques, the available tunable parameters in the controller structure and the immense flexibility in the attainable closed loop dynamics.
Steganography and Hiding Data with Indicators-based LSB Using a Secret Key
Authors: Saqer W. , Barhoom T.
Published: November 2020

Steganography is the field of science concerned with hiding secret data inside other innocent-looking data, called the container, carrier or cover, in a way that no one apart from the meant parties can suspect the existence of the secret data. There are many algorithms and techniques of concealing data. Each of which has its own way of hiding and its own advantages and limitations. In our research we introduce a new algorithm of hiding data. The algorithm uses the same technique used by the Least Significant Bit (LSB) algorithm which is embedding secret data in the least significant bit(s) of the bytes of the carrier. It differs from the LSB algorithm in that it does not embed the bytes of the cover data sequentially but it embeds into one bit or two bits at once. Actually it depends on indicators to determine where and how many bits to embed at a time. These indicators are two bits of each cover byte after the least two significant bits. The advantage of this algorithm over the LSB algorithm is the randomness used to confuse intruders as it does not use fixed sequential bytes and it does not always embed one bit at a time. This aims to increase the security of the technique. Also, the amount of cover data consumed is less because it sometimes embeds two bits at once.
Brittleness and Packing Density Effects on Blast-hole Cuttings Yield of Selected Rocks
Authors: Adebayo B.
Published: November 2020

This paper evaluates brittleness and packing density to analysis their effects on blast-hole cutting yield for three selected rocks in Nigeria. Brittleness test (S20) was carried out in accordance with Norwegian Soil and Rock Engineering and the Brittleness Index (BI) for the selected rocks were estimated. The packing density determined from the photomicrograph of the rock samples. The grain size of 45 blast-holes drill cuttings collected from three selected while drilling of these rocks were determined using standard method of America Society for Testing and Materials (ASTM) D 2487. The brittleness values are 50%, 44% and 42% for micro granite, porphyritic granite and medium biotite granite respectively. The result of BI varied from 10.32 – 11.59 and they are rated as moderately brittle rocks. The values of packing density varied from 92.20 – 94.55%, 91.00 -92.96% and 92.92 – 94.96% for all the rocks. The maximum weights of blast-hole particle size retained at 75 µm are 106.00g, 103.28 g and 99.76 g for medium biotite granite, micro granite and porhyritic granite respectively. Packing density values have correlation to some extent with (S20) values hence, this influence the yield of blast-hole cuttings as drilling progresses. The minimum weight of blast-hole cuttings particle size retained at 150 µm agrees with brittleness index classification for micro granite.
Investigation of the Behavior of Steel Shear Walls Using Finite Elements Analysis
Authors: Abubakri K. , Veladi H.
Published: November 2020

Currently, steel shear walls are considered by engineers as an economic method against lateral loads imposed by wind and earthquake in tall structures. Accordingly, there is a growing need to develop accurate methods alongside approximation methods to estimate the behavior of these structural elements. The finite element technique is one of the strongest numerical methods in analysis of solid mechanics problems. Finite element analysis however requires high technical knowledge of the behavioral models of materials. Therefore, it is less used by designers for certain structural elements such as steel shear walls. This study examines the failure mechanism of steel shear walls using finite elements analysis and validates this modeling by comparing the results with experimental studies.
Exploitation of Nanoindentation and Statistical Tools to Investigate the Behavior of Materials
Authors: Aminallah L. , Habibi S.
Published: November 2020

The determination of the performance of materials requires the characterization of materials at scales: macro, micro and nanoscale. Among the most common experimental methods one can find the instrumented indentation test for determining the contact stiffness and contact depth and analyzing the characteristic curve by nanoindentation load on the penetration of the indentor. Through statistical processing of the experimental results, the rigidity of contact on the contact depth is investigated, depending on the indentation load, for bronze, brass and copper. A mathematical model is adopted to describe the polynomial regression by the method of least squares growth rigidity with one or more geometric parameters representative of the size of the footprint. This study allows us to identify factors that influence the rigidity of the materials examined and the sensitivity of the used indenters.
On-line Handwriting Signature Verification Based on Using Extreme Points Extraction
Authors: Zneit R. S. A.
Published: November 2020

This paper presents a method for on-line Handwriting Signature Verification (HSV) using Extreme Points Matching (EPM). EPM does not use direct computation of curve’s curvature thus it does not expect smoothness in the analyzing process of the trajectory. In the proposed method the curve’s form is described by a small set of extreme points and the method thus seems more precise. Furthermore, it provides an effective preprocessing of the curve and can be utilized in one-to-many pattern matching in a restricted access systems.
A Comparative Analysis Between Optimized and Baseline High Pressure Compressor Stages Using Tridimensional Computational Fluid Dynamics
Authors: Dragan V. , Malael I. , Gherman B.
Published: November 2020

Re-vamping of industrial turbo-machinery is commonplace in the oil and gas industry in applications where subterranean combustion is used for oil extraction. The current case study refers to such an industrial compressor re-vamping, using a state of the art 3D fully viscous CFD methodology coupled with artificial neural networks (ANNs) and genetic algorithms (GA). The ANN is used to establish correlations within a database of CFD simulations of geometrical variations of the original rotor and the GA uses those correlations to estimate an optimum. The estimate is then tested with the same CFD method and the results are fed back into the database, increasing the accuracy of the ANN correlations. The process is reiterated until the optimum estimated by the GA is confirmed with the CFD simulations. The resulting geometry is superior to the original in terms of efficiency and pressure ratio as well as the range of stabile operation, as confirmed by the successful implementation in the field. In this paper we present an analysis of why the optimized geometry achieves superior performances to the original one. Further work will present comparison between the detailed experimental data and CFD.
A Novel Hybrid Algorithm for Software Cost Estimation Based on Cuckoo Optimization and K-Nearest Neighbors Algorithms
Authors: Miandoab E. E. , Gharehchopogh F. S.
Published: November 2020

The inherent uncertainty to factors such as technology and creativity in evolving software development is a major challenge for the management of software projects. To address these challenges the project manager, in addition to examining the project progress, may cope with problems such as increased operating costs, lack of resources, and lack of implementation of key activities to better plan the project. Software Cost Estimation (SCE) models do not fully cover new approaches. And this lack of coverage is causing problems in the consumer and producer ends. In order to avoid these problems, many methods have already been proposed. Model-based methods are the most familiar solving technique. But it should be noted that model-based methods use a single formula and constant values, and these methods are not responsive to the increasing developments in the field of software engineering. Accordingly, researchers have tried to solve the problem of SCE using machine learning algorithms, data mining algorithms, and artificial neural networks. In this paper, a hybrid algorithm that combines COA-Cuckoo optimization and K-Nearest Neighbors (KNN) algorithms is used. The so-called composition algorithm runs on six different data sets and is evaluated based on eight evaluation criteria. The results show an improved accuracy of estimated cost.
A Genetic-Firefly Hybrid Algorithm to Find the Best Data Location in a Data Cube
Authors: Faridi Masouleh M. , Afshar Kazemi M. A. , Alborzi M. , Toloie Eshlaghy A.
Published: November 2020

Decision-based programs include large-scale complex database queries. If the response time is short, query optimization is critical. Users usually observe data as a multi-dimensional data cube. Each data cube cell displays data as an aggregation in which the number of cells depends on the number of other cells in the cube. At any given time, a powerful query optimization method can visualize part of the cells instead of calculating results from raw data. Business systems use different approaches and positioning of data in the data cube. In the present study, the data is trained by a neural network and a genetic-firefly hybrid algorithm is proposed for finding the best position for the data in the cube.
Identifying The Effective Factors for Cost Overrun and Time Delay in Water Construction Projects
Authors: Mirzai Matin D.
Published: November 2020

Water construction projects in Iran frequently face problems which cause cost overrun and time delay, the two most common issues in construction projects in general. The objective of this survey is to identify and quantify these problems and thus help in avoiding them. This survey represents a collection of the most significant problems found in the literature, classified into 11 groups according to their source. The questionnaire form used contains 84 questions which were answered by random engineers who work in water construction projects. The Relative Importance Weight (RIW) method is used to weight the importance of each one of the 84 problems. The focus of this survey is on overall top ten issues which are: bureaucracy in bidding method, inflation, economical condition of the government, not enough information gathered and surveys done before design, monthly payment difficulties, material cost changes, law changes by the government, financial difficulties, mode of financing and payment for completed work and changes made by the owner. A section for each of these issues provides additional information about them. In the full text of this survey the same weighting method is used to classify the main groups, and the results show that issues related to the groups of government, owner and consultant has the most significant impact. The last part of this survey describes the point of view of the engineers who took part in this survey and the recommendations they made.
A Novel Image Stream Cipher Based On Dynamic Substitution
Authors: Elsharkawi A. , El-Sagheer R. M. , Akah H. , Taha H.
Published: November 2020

Recently, many chaos-based stream cipher algorithms have been developed. Traditional chaos stream cipher is based on XORing a generated secure random number sequence based on chaotic maps (e.g. logistic map, Bernoulli Map, Tent Map etc.) with the original image to get the encrypted image, This type of stream cipher seems to be vulnerable to chosen plaintext attacks. This paper introduces a new stream cipher algorithm based on dynamic substitution box. The new algorithm uses one substitution box (S-box) and a chaotic shuffling process. Each byte in the plain image vector is substituted using a different S-box to get the cipher image vector. This algorithm is designed to be invulnerable to chosen plaintext attacks. In addition, this algorithm is more secured compared to conventional stream cipher.
Introducing A Hybrid Data Mining Model to Evaluate Customer Loyalty
Authors: Alizadeh H. , Minaei Bidgoli B.
Published: November 2020

The main aim of this study was introducing a comprehensive model of bank customers᾽ loyalty evaluation based on the assessment and comparison of different clustering methods᾽ performance. This study also pursues the following specific objectives: a) using different clustering methods and comparing them for customer classification, b) finding the effective variables in determining the customer loyalty, and c) using different collective classification methods to increase the modeling accuracy and comparing the results with the basic methods. Since loyal customers generate more profit, this study aims at introducing a two-step model for classification of customers and their loyalty. For this purpose, various methods of clustering such as K-medoids, X-means and K-means were used, the last of which outperformed the other two through comparing with Davis-Bouldin index. Customers were clustered by using K-means and members of these four clusters were analyzed and labeled. Then, a predictive model was run based on demographic variables of customers using various classification methods such as DT (Decision Tree), ANN (Artificial Neural Networks), NB (Naive Bayes), KNN (K-Nearest Neighbors) and SVM (Support Vector Machine), as well as their bagging and boosting to predict the class of loyal customers. The results showed that the bagging-ANN was the most accurate method in predicting loyal customers. This two-stage model can be used in banks and financial institutions with similar data to identify the type of future customers.
Forecasting Wastewater Treatment Results with an ANFIS Intelligent System
Authors: Mahshidnia M. , Jafarian A.
Published: November 2020

Wastewaters caused by industrial and manufacturing production containing pollutants which beside degradation and depletion of natural resources, impose excessive pressure on the Earth's ecosystems and exacerbate water shortages. One of the pollutants is a toxic substance named Malachite Green (MG). Wastewater treatment means to obtain usable water by separating contaminants of contaminated water. One of its main purposes is the recovery and re-use of wastewater for a variety of uses including agriculture and aquaculture, especially in arid and semi-arid countries, as well as providing environmental protection. The main purpose of the present study was to investigate MG separation efficiency by nano composite materials. Poly-aniline was covered on Wheat Husk Ash in order to prepare this type of nano composite. The material was analyzed by X-ray radiation and scanned by an electron microscope. The level of separation depends on the initial value of wheat husk ash and poly-aniline and the initial concentration of MG and the intensity of ultraviolet radiation and radiation time. The effect of these parameters was investigated and optimum operating conditions were obtained. An adaptive neural fuzzy intelligent system was used to forecast the results of the MG separation process. The comparison between the results forecasted by the designed model and experimental data strengthens the validity of the process.
Effect of Pre-gelatinized Wheat Starch on Physical and Rheological Properties of Shortened Cake Batter and Cake Texture
Authors: Ebrahimi F. , Tarzi B. G. , Asghari M.
Published: November 2020

The focus of this study was the effect of 1.5%, 3% and 4.5% pre-gelatinized wheat starch (based on the total weight of cake batter) on improving the qualitative properties of shortened cake batter. Specific volume and viscosity of the shortened cake batter were measured for controls, 1.5%, 3% and 4.5% gelatinized starch; some important properties such as texture and sensory evaluation were examined. By increasing pre-gelatinized wheat starch used in the batter, a significant difference was observed in the rheological properties of the batter. Cake batter properties were found improved compared to the control samples. The sample with 3% pre-gelatinized starch had a lower viscosity than other treatments. The treatment with 4.5% pre-gelatinized starch had the lowest specific volume compared to other treatments. The overall results showed that the shortened cake with 3% pre-gelatinized starch was the best treatment in terms of texture and sensory evaluation factors.
Adaptable Web Prediction Framework for Disease Prediction Based on the Hybrid Case Based Reasoning Model
Authors: Trstenjak B. , Donko D. , Avdagic Z.
Published: November 2020

Nowadays, we are witnessing the rapid development of medicine and various methods that are used for early detection of diseases. In order to make quality decisions in diagnosis and prevention of disease, various decision support systems based on machine learning methods have been introduced in the medical domain. Such systems play an increasingly important role in medical practice. This paper presents a new web framework concept for disease prediction. The proposed framework is object-oriented and enables online prediction of various diseases. The framework enables online creation of different autonomous prediction models depending on the characteristics of diseases. Prediction process in the framework is based on a hybrid Case Based Reasoning classifier. The framework was evaluated on disease datasets from public repositories. Experimental evaluation shows that the proposed framework achieved high diagnosis accuracy.
An Electrical Energy Consumption Monitoring and Forecasting System
Authors: Rojas-Renteria J. L. , Espinoza-Huerta T. D. , Tovar-Pacheco F. S. , Gonzalez-Perez J. L. , Lozano-Dorantes R.
Published: November 2020

Electricity consumption is currently an issue of great interest for power companies that need an as much as accurate profile for controlling the installed systems but also for designing future expansions and alterations. Detailed monitoring has proved to be valuable for both power companies and consumers. Further, as smart grid technology is bound to result to increasingly flexible rates, an accurate forecast is bound to prove valuable in the future. In this paper, a monitoring and forecasting system is investigated. The monitoring system was installed in an actual building and the recordings were used to design and evaluate the forecasting system, based on an artificial neural network. Results show that the system can provide detailed monitoring and also an accurate forecast for a building’s consumption.
A Modular Cascaded Multilevel Inverter Based Shunt Hybrid Active Power Filter for Selective Harmonic and Reactive Power Compensation Under Distorted/Unbalanced Grid Voltage Conditions
Authors: Demirdelen T. , Kayaalp R. I. , Tumay M.
Published: November 2020

In recent years, shunt hybrid active power filters are being increasingly considered as a viable alternative to both passive filters and active power filters for compensating harmonics. In literature, their applications are restricted to balanced systems and low voltage applications and therefore not for industrial applications. This paper investigates the performance of a modular cascaded multilevel inverter based Shunt Hybrid Active Power Filter (SHAPF) for reactive power compensation and selective harmonics elimination under distorted/unbalanced grid voltage conditions in medium voltage levels. In the proposed control method, reactive power compensation is achieved successfully with a perceptible amount and the performance results of harmonic compensation are satisfactory. Theoretical analysis and simulation results are obtained from an actual industrial network model in PSCAD. The simulation results are presented for a proposed system in order to demonstrate that the harmonic compensation performance meets the IEEE-519 standard.
Analysis of IPTV Channels Watching Preferences in Bosnia and Herzegovina
Authors: Tanovic A. , Androulidakis I. , Orucevic F.
Published: November 2020

IPTV service is a new service which is today offered from almost every Telecom operator. One of the advantages of IPTV service stemming from its architecture is certainly the fact that it is very easy to measure what TV channels are the ones mostly watched. This papers desribes this measurement and analysis results in one Telecom operator in Bosnia and Herzegovina. They describe what TV channels are mostly watched in different time periods. We developed a simple weighting algorithm to order the channels by watching rate. Based on it we are providing extensive tables. This paper forms an industrial contribution with results important for marketing but also is scientific contribution because it introduces one new method of scoring TV channels based on previous measurements in their audience. We also developed IPTV Statistics model and described results from this research for a new statistics model. This paper is the continuous of previously published contributions from this area.
Reconnoitering Students' Satisfaction of an Online Based Assessment System to Improve Usability using PSO: An Examination into a Problem Solving and Programming Course
Authors: Vairamuthu S. , Margret Anouncia S.
Published: November 2020

End users’ computing environment has been consistently changing in recent years due to the major advancements of Information Technology. This work aimed to measure the level of users’ satisfaction and provide feedbacks for continuous improvement of a course offered in an academic institution. End users here were the students enrolled for the course and the faculty members who offered the same and also acted as an assessor for the assessments. All assessments were scheduled and conducted online. This study was conducted to focus on two different aspects: Measuring User satisfaction and investigating information systems measures to improve usability using nature inspired computing. For user satisfaction analysis, the study employed the Multicriteria Satisfaction Analysis. The course considered was a problem solving and programming course offered to the fresh students enrolled in the first year of the undergraduate degree program in the academic institution during 2015-2016. To identify the factors for improved usability, PSO was employed in this work.
Study of the Behavior of Water Droplets Under the Influence of a Uniform Electric Field on Conventional Polyethylene and on Crosslinked Polyethylene (XLPE) with MgO Nanoparticles Samples
Authors: Charalambous C. , Danikas M. , Yin Y. , Vordos N. , Nolan J. W. , Mitropoulos A.
Published: November 2020

It is well known that polyethylene (PE) and cross-linked polyethylene (XLPE) are suitable insulating materials for underground cables. Samples of PE and of XLPE with MgO nanoparticles were investigated regarding their flashover behaviour with a uniform electric field and water droplets of various conductivities. In the present paper, the effect of the mounting arrangement of the water drops on the value of the flashover voltage and the effect of the volume of dripping water on the flashover voltage were also studied. Surface damages were analyzed using Scanning Electron Microscopy (SEM) studies and the study of the nano-structure of the samples was studied using the SAXS system.
Important Non-Wood Forest Products in Turkey: An Econometric Analysis
Authors: Kurt R. , Karayilmazlar S. , Cabuk Y.
Published: November 2020

Wood resources obtained from forest and non-wood forest products (NWFP) have gained great importance recently as their economic values keeps increasing by the day. In this study, forecasting of Turkish Non-Wood Forest Products such as thyme, bay leaves, salvia and pine nut export amounts was carried out using a linear regression analysis method for the next fifteen years based on the data for the years between 1990 and 2009. Moreover, estimated import values and actual import values from the last years were compered and analyzed. Finally, predictions on future trends were made.
Design of a Mobile Agents Based Solution to Distributional Management of Computer Networks, Taking into Account the Security Mechanisms
Authors: Bahrami S.
Published: November 2020

Mobile agents (MAs) is one of the technologies considered in the recent years to perform management processes. This technology provides the ability to move code in distributed environments and to connect with other resources and agents locally which makes it an appropriate technology in the development of software applications of distributed network, especially management systems. For using mobile agent technology, an infrastructure for the management of MAs is needed. In this project, an infrastructure called MCT management is introduced for network management. In this infrastructure, some protocols like SNMP are used to get management data for the network administrator. With respect to management ability, MAs can dynamically access the database SNMP (i.e. MIB) and extract the data required by the managers. Most well-known methods are characterized by being static relative to code and location in which components cannot modify their location or code in a lifetime. However, the MAs method can dynamically increase communications, reduce costs and overcome certain limitations by changing location and components.
Evaluation of the Acoustic Properties of Wood-Plastic-Chalk Composites
Authors: Daeipour Z. , Safdari V. , Nurbakhsh A.
Published: November 2020

Wood-plastic composites are a new group of materials that can be used in construction instead of wood and plastic. They are used in various industries due to features such as sound and water absorption, among others. This article aims to study the acoustic properties of wood-plastic composites made of wood flour, low-density polyethylene, and chalk. In this study, 6 combinations were made with different material percentages. Acoustic tests were performed for frequency ranges of 125, 250, 500, 1000, and 2000 Hz. The results of this study showed that the maximum amount of sound absorption was observed at a frequency of 2000 onwards. At the frequency of 25 to 2000, no remarkable change in sound absorption was recorded. At the 2000 to upper frequencies, one of the samples displayed the maximum amount of sound absorption. In terms of water absorption, a significant variation was reported in three samples with passing time (2, 24, 48 and 72 hours).
Variable Speed Limits: Strategies to Improve Safety and Traffic Parameters for a Bottleneck
Authors: Hasanpour M. Z. , Ahadi M. R. , Moghadam A. S. , Behzadi G. A.
Published: November 2020

The primary purpose of the speed limit system is to enforce reasonable and safe speed. To reduce secondary problems such as accidents and queuing, Variable Speed Limits (VSL) has been suggested. In this paper VSL is used to better safety and traffic parameters. Traffic parameters including speed, queue length and stopping time have been pondering. For VLS, an optimization decision tree algorithm with the function of microscopic simulation was used. The results in case of sub saturated, saturated and supersaturated at a bottleneck are examined and compared with the Allaby logic tree. The results show that the proposed decision tree shows an improved performance in terms of safety and comfort along the highway. The VSL pilot project is part of the Road Safety Improvement Program included in Iran’s road safety action plan that is in the research process in the BHRC Research Institute, Road and Housing & Urban Development Research that is planned for next 10-year Transportation safety view Plan.