bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of the quality of service scheduling mechanisms in cloud
Authors: R RemeshBabu K , Samuel Philip
Published: July 2019

Cloud computing provides on demand access to a large pool of heterogeneous computational and storage resources to users over the internet. Optimal scheduling mechanisms are needed for the efficient management of these heterogeneous resources. The optimal scheduler can improve the Quality of Services (QoS) as well as maintaining efficiency and fairness among these tasks. In large scale distributed systems, the performance of these scheduling algorithms is crucial for better efficiency. Now the cloud customers are charged based upon the amount of resources they are consumed or held in reserve. Comparing these scheduling algorithms from different perspectives is needed for further improvement. This paper provides a comparative study about different resource allocation, load balancing and virtual machine consolidation algorithms in cloud computing. These algorithms have been evaluated in terms of their ability to provide QoS for the tasks and Service Level Agreement (SLA) guarantee amongst the jobs served. This study identifies current and future research directions in this area for QoS enabled cloud scheduling.
Prioritized scheduling scheme for critical and non-critical information packets
Authors: Aanandha Saravanan K , P. Suresh Dr
Published: July 2019

The process of energy saving mechanisms is been utilized by proper planning to transmit both critical clip and non-real infor-mation by reading overheads there by reducing throughput and bandwidth in large scale critical clip networks. The existing bundle sched-uling mythologies used   were based on the First -in First-out (FIFO) manner in such cases the critical information at particular instant cannot be processed quickly but proposed system is designed in such a way it consists of  three tier precedence structure .the critical in-formation  bundles are placed in the higher status prioritizing queue and processed immediately and sent to the destination node where oth-er information bundles are given less precedence on the basis of position for non critical information bundles. The proposed scheme, ener-gy efficient in reducing the number of transmission by using merger technique. The lowest precedence bundles are processed after the higher precedence bundles. The proposed algorithm proves its uniqueness based on end -to-end delay than Energy efficient wake up scheduling MAC (EEWS) and Traffic Adaptive MAC protocol (TAMAC)
Water quality analysis and model simulation for the second largest polluted lake in Egypt
Authors: SeifSeif Diaa , Nasr Mahmoud , R. Soliman Mohamed , Moustafa Medhat , Elbarki Walid
Published: July 2019

This study investigated the spatial variation in the water quality parameters of Burullus Lake using multivariate analysis and MIKE21 model. The lake was classified into zone-1 at north-east (Z1), zone-2 at south-east (Z2), zone-3 at north-middle (Z3), zone-4 at south-middle (Z4), zone-5 at north-west (Z5), zone-6 at south-west (Z6), and zone-7 at west (Z7). The obtained parameters were temperature 21.5±5.0 ºC, pH 8.2±0.6, dissolved oxygen (DO) 5.9±1.0 mg/L, biological oxygen demand (BOD) 23.9±5.7 mg/L, NH3-N 2.5±0.3 mg/L, NO2-N 1.9±0.3 mg/L, NO3-N 1.2±0.3 mg/L, PO4-P 1.9±0.3 mg/L, SiO4 3.2±0.1 mg/L, Chlorophyll-a (Chl-a) 88.2±10.8 µg/L, and salinity 3.2±1.0 g/L. Principal component analysis showed that agricultural drainage water was the key factor influencing the water quality characteristics of Burullus Lake. Water quality index (WQI) varied between “Bad” to “Medium”, suggesting that the lake wasn’t suitable for irrigation and fish growth; however, it was appropriate for some aquatic life. A MIKE21 model was developed to provide a recommendation scenario that could be used to enhance the water quality of Burullus Lake. By improving the water quality of precise drains (namely drains 7 and 8), the WQI at Z4 and Z6 modified from “Bad” to “Medium”. The period required to achieve this self-purification was 5 months.
Fitting Conventional Neural Network Time Series Models on Sand Price Indices Dataset
Authors: Azura Md Ghani Nor , Bin Ahmad Kamaruddin Saadi , Musirin Ismail , Hashim Hishamuddin
Published: July 2019

This result-based paper discusses on the best aftereffects of both fitted BPNN-NAR and BPNN-NARMA on MCCI Sand dataset regarding distinctive error measures. This exploration examine the outcomes as far as the execution of the fitted forecasting models by every arrangement of input lags and error lags utilized, the execution of the fitted anticipating models by various hidden nodes utilized, the execution of the fitted estimating models when joining both inputs and hidden nodes, the consistency of error measures utilized for the fitted determining models, and in addition the general best fitted estimating models for Malaysian sand price indices dataset. In this examination, Malaysian sand price indices monthly data from January 1980 to December 2013 were adapted. The examination of BPNN-NAR on Malaysian sand data shows that insufficient or inadequate combination of input and error lags lead to greater RMSE. Correspondingly, the number of input lags for BPNN-NAR, as well as the number of input and error lags for BPNN-NARMA really have direct effect to the models’ performances. The higher or the lesser hidden nodes to the input lags, the higher the network’s RMSE. On the other hand, the higher the input lags lead to the higher network’s RMSE.
Arithmetic and Huffman Coding using Quasi-Cyclic Low Density Parity Check Techniques with F-OFDMA for 5G System
Authors: Idris Azlina , Aini Amran Nurul , Syarhan Idris Mohd , Taib Idris , Kassim Murizah , Seroja Sarnin Suzi , Norsyafizan W Muhammad Wan , Ya’acob Norsuzila
Published: July 2019

The rising demand of the future 5th generation (5G) wireless systems has led to the development of wireless communication technologies that can provide higher user capacity. Therefore, filtered orthogonal frequency division multiple access (F-OFDMA) was introduced to accommodate large number of users. F-OFDMA has the advantage over OFDM since it is capable of overcoming the high side lobes and increasing the spectrum utilization by eliminating the out-of-band emission which can degrade the system’s performance. In this paper, a joint method between two block coding techniques (Arithmetic coding (AC) and Huffman Coding (HC)) with an error correcting code (Quasi-Cyclic Low Density Parity Check (QC-LDPC))was proposed. AC-QC-LDPC and HC-QC-LDPC schemes were compared in terms of BER performance. Based on the simulation results, AC-QC-LDPC technique has been proven to give the 44.75% BER improvement to the F-OFDMA system which outperforms the HC-QC-LDPC technique. It is clear from the results that Arithmetic coding always give better BER improvements compared to Huffman coding with QC-LDPC.
Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital
Authors: Effendi Amran Mohd , Nabil Muhtazaruddin Mohd
Published: July 2019

This paper presents an optimization solution for renewable Distributed Generation (DG), as imposed in the Green Building Rating System (GBRS) for a public hospital. Solar photovoltaic DG unit (PV-DG) is identified as a type of DG used in this paper. The proposed optimization via PV-DG coordination will improve the sustainable energy performance of the green building by power loss reduction within accepted lower losses region using Artificial Bee Colony (ABC) algorithm. The setup input data from one of Malaysian public hospitals’ power distribution system is been adopted and simulation results via MATLAB programming show that the optimization of DG forming into bigger-scale imposed system provides a better outcome in minimization of total power losses within appropriate voltage profile as compared to current PV-DG imposed in GBRS. The objective function representing total power losses which also supported by related literature give a measure that forming sufficient and optimal PV-DG assessment criteria is highly important, thus, current PV-DG assessment in GBRS is proposed to be reviewed into new parameter setting for public hospital due to its’ high energy demand and distinctive electrical load profile.
Chaotic Immune Symbiotic Organisms Search Algorithm for Solving Optimisation Problem
Authors: Khairuzzaman Mohamad Zamani Mohamad , Musirin Ismail , Izwan Suliman Saiful , Azma Syed Mustaffa Sharifah
Published: July 2019

Achieving an optimal solution is very crucial while solving a problem. To achieve the optimality required, optimisation techniques can be implemented while solving the problem. The presence of classical optimisation techniques has enabled an optimal solution to be obtained. However, as the complexity of the optimisation problem increased, classical optimisation techniques faced difficulties in providing optimal solutions. Heuristics-based algorithms were introduced to counter the problem faced by classical optimisation techniques. Good performance of these heuristics-based algorithm has been implied through various implementation in solving optimisation problems. Despite the performance of these algorithms, the flaws of these algorithms hinder them from producing high-quality results. To mitigate the problem, this paper presents the development of Chaotic Immune Symbiotic Organisms Search algorithm which was inspired by the element of diversification as well as the increased capability of exploration. The performance of the proposed algorithm has been tested by solving several benchmark test functions. A comparative study was also conducted with respect to several other existing optimisation algorithms resulted in the superiority of the proposed algorithm in providing high-quality solutions.
Evaluation of Nature-Inspired Algorithms for Battery Parame-ter Estimation in Renewable Energy Generation Systems
Authors: Shareef Hussain , Mainul Islam Md , Sasi Stephen Samantha
Published: July 2019

Batteries in renewable energy systems suffer problems that affect their service life and quality of performance. Therefore, battery management systems (BMS) are employed in battery-integrated systems to maintain optimal operating conditions by various dynamic impedance based battery models. These models require an accurate model parameter for BMS to work effectively.  In this paper, two recently developed metaheuristic optimization, namely bird mating optimizer (BMO) and lightning search algorithm (LSA) is used effectively to determine the required parameters of well-known Randle’s battery model.  Initially, electrochemical impedance spectroscopy (EIS) test for an EnerSys Cyclon lead-acid cell with a rated capacity of 2.5Ah is conducted using EZSTAT-pro Galvanostat/Potentiostat device from Nuvant systems Inc. Next, the Randle’s battery model parameters are obtained by BMO and LSA and its performances are evaluated. The results show that BMO and LSA can accurately find the model parameters. LSA obtains slightly more accurate results than BMO and converges much faster. However, for the same number of iterations, BMO takes less computation time than LSA. The optimized model can be used in BMS for fault finding and condition monitoring.
Evaluation of Pre-Trained Convolutional Neural Network Models for Object Recognition
Authors: Zabir M , Fazira N , Ibrahim Zaidah , Sabri Nurbaity
Published: July 2019

This paper aims to evaluate the accuracy performance of pre-trained Convolutional Neural Network (CNN) models, namely AlexNet and GoogLeNet accompanied by one custom CNN. AlexNet and GoogLeNet have been proven for their good capabilities as these network models had entered ImageNet Large Scale Visual Recognition Challenge (ILSVRC) and produce relatively good results. The evaluation results in this research are based on the accuracy, loss and time taken of the training and validation processes. The dataset used is Caltech101 by California Institute of Technology (Caltech) that contains 101 object categories. The result reveals that custom CNN architecture produces 91.05% accuracy whereas AlexNet and GoogLeNet achieve similar accuracy which is 99.65%. GoogLeNet consistency arrives at an early training stage and provides minimum error function compared to the other two models.
Simulation of Energy Dump Converter Topology for Switched Reluctance Motors
Authors: Ayob A , Abd Halim S , Yusof Y
Published: July 2019

The switched reluctance machine (SRM) is the least expensive machine to produce yet it is very reliable.  An SRM drive system has to be designed so that there is integration between the machine and the converter-controller configuration. This paper focuses on the resistor dump converter topology where most of the energy from the windings is dissipated in a resistor. A detailed analysis and simulation of the converter has been conducted and a design guideline for the proposed converter is laid out.  The resistor dump converter has a low component count and this enables it to achieve a low cost converter.  Simulation results show that for the resistor dump converter additional snubbers are required.  This leads to an increase in complexity of the controller as more parameters need to be considered.  Also, the addition of the passive components of the snubber makes the circuit less reliable and costly. For the purpose of just looking into detail on the behaviour of the converter, it is sufficient to look at the results of the simulation using a static inductor to model the SP-SRM.  If cost is to be the priority, the most economical choice must be made but within limits of the application.
Support Vector Machine Performance with Optimal Parameters Identification in Recognising Asphyxiated Infant Cry
Authors: Sahak R , Mansor W , Y. Lee Khuan , Zabidi A
Published: July 2019

Detection of asphyxia in infant at an early stage is crucial to reduce the rate of infant morbidity. The information regarding asphyxia can be extracted from infant cry signals using support vector machine (SVM) combined with effective feature selection methods such as principal component analysis (PCA) or orthogonal least square (OLS). The performance of SVM in recognizing infant cry with asphyxia after undergone comprehensive identification of optimal parameters at the feature extraction and classification stages has not been     reported. This paper describes the two stages of optimal parameter identification; at Mel-frequency Cepstral coefficient (MFCC) analysis stage, SVM with and without employing the PCA and OLS stages, and the performance of the SVM in recognizing infant cry with asphyxia resulted from all levels of optimal parameters identification. The SVM was first optimized after performing MFCC analysis to find the optimum parameters. Two types of kernels were used, the polynomial and RBF kernels. The subsequent SVM optimizations were conducted after PCA and OLS were employed. In the PCA, the significant features were selected using eigenvalue-one-criterion (EOC), cumulative percentage variance (CPV) and the Scree test (SCREE). The SVM performance was evaluated based on classification accuracy and computation time. The experimental results have shown that the optimized SVM was able to recognize the asphyxiated infant cry with an accuracy of 94.84% and computation time of 1.98s using PCA with EOC and RBF kernel.
Instruction Task for Malay Phrase Boundary Annotation
Authors: Mohamed Hanum Haslizatul , Atiqah Sia Abdullah Nur , Abu Bakar Zainab
Published: July 2019

The paper presents a refined instruction task to assist evaluation of prosodic phrase (PPh) boundaries by naive listeners. The results from the perceptual experiments were compared to the boundaries produced by online automatic tagger. The Kappa evaluation shows the average of 85% on inter-rater agreement. More than 60% of the boundaries which are detected by the automatic tagger matched the reference boundaries, showing that the refined instruction task can be used to evaluate perception on phrase boundaries on continuous speech.
Risks and Threats Posed to a Company’s Economic Security
Authors: Valeryevich Bank Sergey , Dmitriyevich Sekerin Vladimir , Evgenievna Gorokhova Anna , Ivanovich Nikolaykin Nikolay , Gennadievich Shcherbakov Anton
Published: July 2019

This paper examines some of the major types of risks and threats that may be posed to the economic security of national enterprises. Its purpose is to terminologically fine-tune the categories ‘threats’ and ‘risk’, analyze and classify risks from the standpoint of the multicriteria approach, as well as fine-tune existing methods for assessing risks faced by a firm’s economic security system. Based on the findings from their analysis of relevant materials, the authors have formulated the following conclusions:•an event that does not yield itself to assessment from the standpoint of quantitative and qualitative parameters is regarded as a threat. In this context, it becomes virtually impossible to come up with efficient preventive activities, as it is problematic to conduct quantitative assessments of this kind of event. Reducing the extent of a threat requires identifying and classifying relevant risks;•a modern enterprise is a backbone element in the national economy. Managing risks and threats posed to economic security at the microlevel is a part of the national strategy for social/economic development in the Russian Federation. This is why threats that emerge at the level of interaction among business entities are strategic risks;•assessing risk implies not only identifying the intensity of negative impact factors but constructing its specific forms as well. Assessment procedures are based on detecting negative impact factors, establishing the degree of their impact on a firm’s economic security system, and forecasting the potential reactions of the firm’s subsystems. The most frequently used assessment methods are expert and mathematical methods.
Statistical Toolkit for Assessing the Financial Security of Regions
Authors: Vladimirovich Dianov Dmitry , Evgen'evich Suglobov Alexander , Ivanovna Kuznetsova Elena , Viktorovna Rusavskaya Alevtina , Vladimiro Andrey
Published: July 2019

Each stage of the statistical research of economic and financial security requires the use of another extensive block of statistical toolkit represented by methods of general theory of statistics and mathematical statistics, including multidimensional groupings – cluster analysis, correlation and regression methods. This scientific article is devoted to such a statistical toolkit and analytical capabilities for its application in the research into the financial security of the region, where the financial security of the Moscow region, described by a range of financial and economic indicators, is the subject of statistical research.
Information Security and the Internet
Authors: Shamiloglu Kurbanov Aiden , Romanovna Lenkovskaya Renata , Viktorovna Lutovinova Natalya , Efratovna Zolotareva Alla , Valerievich Zhesterov Pavel
Published: July 2019

The article analyzes problems of poor legal regulation of relationships in the Internet when the network is used as a mean of information dissemination. The article focuses on the analysis of judgements in cases involving organizations that distribute software designed for maintenance of the companies’ paper flow, when such cases reveal evidences of non-licensed use of information. Gaps are identified in possibility to use civil methods of information protection traditional for the Russian system of justice. The authors found some inefficient information protection methods considering the level of processes and technology development, such as watermarks on the images, information depositing in Web-depository. The articles draw special attention to the requirements that an author and owner may put forward to information protection in the Internet.
Mediatization of Politics as an Element of Noopolitics
Authors: Borisovich Nikonov Sergey , Sergeevich Labush Nikolai , Stepanovich Puiy Anatoli , Savova Georgieva Elena , Sergeevich Lukin Stanislav
Published: July 2019

The work deals with the study of information strategy, namely noopolitics. In the course of the work, it has been revealed that one of the elements of the information strategy formation is the need to mediatize political processes. The understanding of political processes mediatization is considered in the part devoted to the scientific research outcomes. The work also considers a phenomenon such as rumours. This is not fake news, which is so often mentioned by politicians, but political reality, which is also an element of noopolitics. The main part of the work deals with the results of the implementation of the noopolitics when preparing and carrying out presidential elections in 2018, and the role of foreign states and politicians in strengthening power in Russia.
Problems of the Topical Field “Art” in Modern School
Authors: Pavlovich Roshchin Sergey , Maratovna Nizamutdinova Svetlana , Pavlovna Shipovskaya Lyudmila , Chinchorovich Bartsitz Rauf
Published: July 2019

The paper presents key factors of the “Art” topical area within school education in modern Russian Federation. The “Art” topical area is central to the entire process of molding a creative, harmoniously developed personality. Teaching musical, artistic, spiritual, and moral components is essential for high-quality education. The authors of the paper have reasonably substantiated the need for the active introduction of art to school curricula. The authors also manifested the importance of revealing students’ creative potential and the development of their constructive skills. Of much importance is the fact that specific ways of improving the quality of school musical and artistic education emerge from the research results.
A Factor Analysis of Models for Regional Development
Authors: Kadyrbechevna Еshugova Svetlana , . .
Published: July 2019

This paper explores some of the key regional characteristics of the formation of market relationships that influence the overall economic situation in the country. The author examines regional units characterized by there being latent sources of cumulative growth within a multilevel stratified unit that incorporates a group of business entities engaged in a homogeneous type of economic activity which may initiate a multiplicative effect based on the capacity for systemic or developmental innovations, as well as a group of business entities associated with a propulsive sector through the “input/output” relationship, which ensures the translation of a multiplicative effect in the direction from higher territorial establishments to lower ones. The paper discusses the activity of key organizations within a recipient region with a view to identifying potential growth areas that could become the basis for the development of import substitution at the mesolevel, which are engaged in activity within the framework of traditional spheres of economic activity.
Trust based secure de-forestation and timber theft alert in wireless sensor networks
Authors: N. Renjith P
Published: July 2019

Deforestation is the permanent destruction of trees for timber and land. Deforestation and timber theft ends up with obliteration of entire forest in the earth. Deforestation has increased exponentially increase in this decade. It is well known that Deforestation is a prime reason for global warming, less tropical rainfalls and affects atmospheric oxygen level. In this paper, a novel query-based method has been intro-duced to alert deforestation to forest official. Trust analysis and data aggregation has been incorporated to improve security and fast trans-mission of information to the base station. Query based technique is used to evaluate the intrusion has been implemented. Simulation result proven that the ST-alert able to detect the trespasser and stop them from deforestation.
Integrated-reservoir-model-based critical oil rate correlation for vertical wells in thin oil rim reservoirs in the Niger Delta
Authors: Ndarake Okon Anietie , Appah Dulu
Published: July 2019

Thin oil rim reservoirs are mostly characterized by development and production challenges; one of which is early water coning tendency. In the Niger Delta, most developed critical oil rate correlations to avert coning focused on conventional bottom-water drive reservoirs, while thin oil rim reservoirs received limited attention. Available correlations to estimate critical oil rate of thin oil rim reservoirs in Niger Delta are based on generic reservoir models, which does not consider the reservoir heterogeneity. Hence, it leaves these available correlations’ predictions in doubt, considering the sensitive nature of developing thin oil rim reservoirs. Thus, a correlation for critical oil rate (qc) based on integrated reservoir model in the Niger Delta was develop for thin oil rim reservoirs using multivariable numerical optimization approach. The obtained result indicated that the developed correlation predicted 226.05 bbl/day compared to the actual Oilfield critical oil rate of 226.11 bbl/day. Furthermore, sensitivity study indicated that the developed correlation and the integrated reservoir model predictions of fractional well penetration (hp/h) and height below perforation - oil column (hbp/h) on critical oil rate (qc) were close and resulted in coefficient of determination (R2) of 0.9266 and 0.9525, Chi square (X2) of 0.539 and 0.655, and RMSE of 4.336 and 4.357. Additionally, the results depict that critical oil rate depends indirectly on fractional well penetration and directly on height above perforation for vertical wells. Therefore, to delay water-coning tendency in thin oil rim reservoirs these completion parameters are consideration in vertical wells to establish optimum critical oil rate during hydrocarbons production. Also, the developed correlation can be used as a quick tool to estimate critical oil rate of thin oil rim reservoirs in the Niger Delta.
Emotional Arousal Substrate in Relation to Eysenck Theory of Extraversion
Authors: Yusoff Nasir , NurAzhani Anuar Nik , Nor Arifin Wan , Begum Tahamina , Reza Faruque
Published: July 2019

Background: Eysenck theory posits that extraverts possess a trait of personality that is associated with personal enjoyment. Objectives: This study aims to examine the combination effect of extraversion and arousal intensity on the neural process of emotional arousal. Methods: This study was implemented in two parts – (1) Validation of Extraversion-Five Factor Non Verbal Personality Questionnaire (E-FF-NPQ) for personality screening, and (2) Event Related Potential (ERP)/electroencephalograph (EEG) recording session. In part one, the E-FF-NPQ was validated by 153 respondents, recruited from Universiti Sains Malaysia. In part two, after having their personality trait screened, electroencephalogram was recorded in 90 participants (N=30 for each personality) during the Event Related Potential session. Emotional arousal pictures that were taken randomly from the International Affective Picture System (IAPS) were used as visual stimuli and divided into three categories (high, moderate, low) based on the normative mean values of IAPS. Results: Interaction effect of the extraversion trait and emotional arousal intensity was detected in the frontal region as indicated by the latency of N200. Conclusion: The Theory of Eysenck on the connection between extraversion and well-being is almost supported.
Chemical Composition, pH Value, and Points of Zero Charge of High Calcium and High Iron Electric Arc Furnace Slag
Authors: Zu Nurain Ahmad Siti , R Hamdan , Afnizan Wan Mohamed Wan , Othman N , Shaylinda Mohd Zin Nur
Published: July 2019

Electric arc furnace (EAF) slag as filter media has been extensively used nowadays for wastewater treatment technology. Steel slag was produced as byproduct from steelmaking processes. However, different batches of steel slag production produce different composition. Thus, this study determined the chemical composition, pH value and points of zero charge (PZC) of two different samples of electric arc furnace (EAF) slag; high iron EAF slag (Slag HFe) and high calcium EAF slag (Slag HCa). The steel slag were characterized using X-ray Fluorescence Spectroscopy (XRF) analysis for the chemical composition, extraction with boiling water for pH value, and salt addition method for PZC. Slag HFe was mainly consisted of 38.2% ferric oxide and 20.4% calcium oxide, 10.20 pH value and pH 10.55 for PZC. While for Slag HCa, they were composed of 1.64% ferric oxide and 49.5% calcium oxide of pH value of 11.11 and pH 11.75 for PZC. Therefore, Slag HCa was considered as a more basic species compared to Slag HFe.
Methane Potential from the Digestion of Food Waste in a Batch Reactor
Authors: Seswoya Roslinda , Tarmizi Abdul Karim Ahmad , Aiza Darnak Nur , Fahmi Abd Rahman Muhammad
Published: July 2019

The anaerobic digestibility of a targeted substrate, measured as methane yield is conducted via biochemical methane potential (BMP). In this study, the batch BMP test was conducted using Automatic Methane Potential Test System (AMPTS II) for 25 days and focused on the methane production from the digestion of food waste (FW, in the form of raw and diluted) at inoculum to substrate ratio (I/S) ratio of 2:0 and under mesophilic temperature.  The results showed that solids (TS and VS) concentration reduced significantly due to the       dilution. The ultimate methane yields from the digestion of raw FW and diluted FW were 1891.91ml CH4/gVS and 1983.96 ml CH4/gVS respectively. This showed that the dilution significantly improved the methane yield. In addition, the lag phase of the methane yield curve for both BMP tests was less than one (1) day, showing the good biodegradability of FW. The kinetic methane production from laboratory data and Modified Gompertz modelling fitted well. However, the kinetic equation parameters such as Mo, Rm and l from the model were slightly lower based on the observation of the laboratory data.
Analysis of the Potential Hazard Identification and Risk Assessment (HIRA) and Hazard Operability Study (HAZOP): Case Study
Authors: Suhardi Bambang , Widyo Laksono Pringgo , Ayu V.E Andhika , Mohd.Rohani Jafri , Shy Ching Tan
Published: July 2019

This study aims to investigate the potential hazards and accidents that might occur at batik printing PT. Batik Merak Manis and recommends practical solutions to enhance safety and health at the workplace. This research adopts Hazard Identification Risk Assessment (HIRA) and Hazard and Operability Studies (HAZOP) to perform risk identification and assessment in the workplace. There are 17 findings of potential hazards in the production areas of batik printing which can be categorized into five types of hazards including: workers attitude, work posture, work procedure, workstation, and physical work environment. Of the risk assessment, the obtained value of 34% in the category of extreme hazard, 24% hazard in the high and medium category respectively, and 18% lower hazard category. Proposed improvements are made based HAZOP analysis worksheet. The proposed practical solutions include improvements in work attitude, work posture, and physical work environment.
Factors Related to Safety Climate in Production Line Workers of Food Manufacturing
Authors: Yangok Abdullbasis , Choosong Thitiworn
Published: July 2019

Developing and encouraging a safety culture is an important factor to achieve a safe workplace with low injury rates. Safety climate can be an indicator of the status of an occupational health and safety management system in an organization. It can provide a snapshot of the safety culture. The Thai version of Nordic Occupational Safety Climate Questionnaire is used to evaluate the safety climate in the food manufacturing industry in Songkhla, Thailand. The results can also be used as a guideline in the development and safety management in the future. The response rate was great. The employees who participated were 14.7% male and 85.3% were female. Most subjects were 41-50 years-old and most had a 1- to 5-year working experience. The highest safety climate score of the workers was the dimension of “workers’ trust in the efficacy of safety systems” (3.29) while the lowest score was the dimension of “workers' safety priority and risk non-acceptance” (2.89). For the leaders, the highest safety climate score was the dimension of “workers’ safety commitment” (3.44) and the lowest score was the dimension of “management safety empowerment” (3.10). The factors related to accident occurrence were the differences in the organizations and the mean score of the safety climate dimension of “worker’s safety priority and risk non-acceptance”.
Ultrafine Particles Measurement in Printing Industry Across West Malaysia
Authors: Jamen Shahrulnizam , Makmom Abdullah Ahmad
Published: July 2019

Ultrafine particles (UFPs) emission generated from devices such as printer and photocopy machines are known as potential risks to human health. However, limited information is available to study UFPs exposure generate from larger printer. Thus, this study aimed to determine the concentration of UFPs such as particle number (PN) and lung deposited surface area (LDSA) and investigates the influence of physical environment factors on UFPs in two types of offset lithographic printing rooms such as monochrome and color, across West Malaysia. The measurements of PN and LDSA were taken by using a condensation particle counter and the diffusion charger dosimeter during the printing activities. The mean values for PN and LDSA are 22215 particles/cm3 and 43 µm2/cm3, respectively. The exposure of UFPs from the monochrome room was found to be significantly higher than the color room (p < 0.001 for PN; p < 0.001 for LDSA) due to variation in the ventilation system. Based on correlation analysis, the physical environment factors, such as relative humidity, temperature, and air movement, were observed to influence the UFPs concentrations in printing room.  The findings imply that a good selection of the ventilation system is important to minimize worker’s exposure to UFPs emission.
Maintenance Management Model: an Identification of Key Elements for Value-Based Maintenance Management by Local Authority
Authors: Gala Mong Sylvia , Fikri Mohamed Sarajul , Mohd. Saidin Misnan Mohd.
Published: July 2019

Maintenance management is a crucial element which governs the economic value of the organization itself. The maintenance management portrays the practice of leading and turning the organization through the deployment and handling of available resources such as financial, human, material, knowledgeable and technology. Consequently, the maintenance management needs to be emphasized by any means of planning, directing, implementing and controlling and several improving methods to achieve economic aspects of the organization. This paper covers part of the study to examine the current practices of the local authorities in Malaysia in maintenance management of public facilities. A systematic literature review has been carried out to identify the existing models and frameworks related to maintenance strategies formulation, selection and its implementation. The literature support for all the key elements needed to achieve value-based maintenance management. Few models of maintenance management were examined to acquire the essential elements before proposing the maintenance management model for local authorities. By analyzing the models, it characterizes the innovations introduced by every author and compares the elements based on maintenance standard requirement for maintenance processes. Also, the discussion is made on the key elements to be included and improved to support organization needs and its application.
Evaluation of Structure and Accessibility of Public Space Network in Kano Central Area with the Bid to Promote Urban Cohesion and Sustainability
Authors: Muktar Muhammad , S. Ahmed Abdulaziz
Published: July 2019

There have been major concerns in the planning of both public and private spaces in Kano central area. Consequently, the entire urban fabric have been restructured due to uncontrolled developmental growth, population density, high cost of land value, unavailability of business location and poor accessibility to road network. These situations have brought about a physical and social shift in the position of Kano Central Business District (CBD) area, of which not prevented will continue to cause major urban cohesion and sustainability issue. Thus, this paper took a preemptive step to evaluate the existing problems and identify the major sustainability issues and where urban cohesion failed. A qualitative method was employed that does not only consider the study of morphological factors of the public space network in Kano CBD, but also the social, environmental and economic dynamics they generate. Thus, the data were collected through fieldwork (favoring direct contact with the territory), and analyzed using four key dimensions namely ‘Form and legibility’, ‘Access and Connections’, ‘Uses and Activities’, then ‘Sociability and Identification’. The findings revealed that the neighborhoods that make up the CBD have lot of abandoned buildings, insufficient access routes, poor drainage system, high volume of traffic that cause lot of pollution and proliferation of solid waste that makes road network impermeable, and an aesthetic eyesore. In view of these, the study recommends a set of urban intervention strategy capable of guiding the planning and redesign of public spaces in Kano CBD in order to promote urban cohesion and a sustainable environment.
Intelligent Vehicular System with Speed Limit
Authors: Laxma Reddy D , S. Arulanth T , Nehru K , Nagaraju N , Ramesh Reddy G
Published: July 2019

In the scholarly world and the car business vehicular communication is one of the important point. The point of this developing interest is to build up a compelling communication network to the Intelligent Transportation System. Here in the proposed paper we exhibited remote base station model with a great put assessment. The auto movement demonstrate and lining framework with variable solicitations are used remote to get point display. The wireless networks performance may be compact from a spread of parameters, equivalent to radio communication vary, the quantity of shoppers may vary and speed of the vehicle. Some of the parameters are analyzed and displayed.
Efficient EER-LEACH Protocol for Monitoring the Activities of Pregnant Women Using Wearable Body Sensor Network
Authors: Subalakshmi S , Murugaboopathi G , Senthilkumar D
Published: July 2019

In health care monitoring framework, it is important to always screen the patient's physiological parameters. For instance, pregnant lady parameters, like, blood pressure, uterine contraction heart rate of pregnant ladies and heart rate alongside the fetal development to detect their wellbeing condition. This paper introduces a monitoring framework that has the capacity to screen physiological changes from the pregnant ladies. In the proposed framework, controller node (CN) has connected on patient body to gather every one of the signs from the uterine contraction monitoring wearable body sensors and sends them to the base station. The appended sensors on patient's body frame a wireless body sensor network (WBSN) and they can detect the uterine constriction, heart rate, blood pressure etc. This framework can recognize the unusual conditions, issue an alert to the patient and send to the doctor. Likewise, the proposed framework comprises of a few relay nodes which are in charge of handing-off the information sent by the controller node (CN) and forward them to the base station. The principle effort of this framework is to diminish the vitality utilization to delay the system lifetime, accelerate and stretch out anticipated work is to expand the sensor execution. This framework is likewise created for multi-patient observing for hospital healthcare and contrasted with the current systems in view of coverage, energy utilization and speed.
Designing a Portable Camera Image Acquisition System Operating Within an Indoor Wi-Fi Network and Optimized for A Robotic Vehicle
Authors: Priya George Anu , Felix Joseph X
Published: July 2019

Nowadays people working in industrial sectors face lot of problem like placing a valuable objects or things in some place unknowingly and searching it. To overcome this problem we are moving into the field of Object searching and identify which assist industrial sectors and research labs. Object searching mechanism is a challenging task. Real time object search poses many difficulties in recognizing objects. We are tending to do real time image capturing as well as recognizing techniques and it will forward data through Wi-Fi used in embedded device. The proposed system makes use of computer vision techniques based on real time image processing and recognizing the object and send via internet to PC.
New Software Testing Method Based on Evolutionary Algorithm
Authors: Khosravi Samiyeh , . .
Published: July 2019

Software Testing is an important part of software development which is performed to support and enhance reliability and quality of software. It consists of estimating testing effort, selecting suitable test team, designing test cases, executing the software with those test cases and examining the results produced by these methods. This paper proposes Fuzzy Based approach for finding out the complexity weight based on requirement. Based on the weight, this paper computes the software complexity point. Fuzzy logic uses membership functions to include linguistic variables and quantifiers. Fuzzy Logic could be used in project estimation purposes efficiently by gathering size data on previously developed programs. The advantage of this model is that it is able to estimate the software complexity which in turn predicts the software requirement stability during the software development cycle.
Survey on Image Dimensionality Reduction Using Deep Learning Techniques
Authors: M. Monica K , Bindu G , Sridevi S
Published: July 2019

Images provide rich information. With reference to the data set which may be related or unrelated in nature, locates step by step, a wide range of application and its attributes through capturing mechanism by sensing the suitable technologies. On the other hand, it also creates a huge quantity of data which may be relevant, irrelevant or redundant in nature and it is used for detailed task of the image.  Also, Many brings a lot of problems such as increase in computational time of image, density of image and range of mapping of data, semantics of the data set and also it also there is a scope of huge amount of labeled data for the process of training to the new environment setup.  Mostly, this is not easy and costly for users to obtain sufficient training models in several application modules.  This research paper deals with these problems by exploring the more classical dimension reduction algorithms with deep knowledge for supporting communities.
Design of Conformal Microstrip Patch Antenna for Vehicle Tracking
Authors: Ebenezer Abishek B , Abdul Hashim Z , Sai Prasath Hari , Arul Stephen C , C. Kishore Kumar P
Published: July 2019

The road accidents have increased in the urban areas to the level which is alarming. The accidents cause loss of human life which can be avoided if the accident victim is rescued at the earliest and given the necessary treatment. This paper involves the designing of an antenna unit for the purpose of tracking the vehicles met with the accidents. The tracking unit placed in vehicles requires a low profile antenna to be placed on top of the roof of vehicle. The simulation study of this antenna is performed in Feko Suite and validated in CST.
Analysis to Determine the Scope and Challenging Responsibilities of Ethical Hacking Employed in Cyber Security
Authors: Vignesh R , Rohini K
Published: July 2019

This paper analyzes a variety of Challenging Roles of Ethical Hacking employed in Cyber Security. The requirement for more viable requesting data security rehearses is progressively evident with every security encroaches revealed in the media. Ethical hacking set forward a target investigation of an association's data security bearing for associations of numerous phase of security capability. Programmers must output for shortcomings, test section focuses, needs targets, and build up a procedure that best use their assets. The reason for this sort of security appraisal directly affects the estimation of the entire assessment. More finished it is recognized that electronic devices are fundamental to forestall digital culprits hacking into online systems to contain their administrations and access secret information for uncalled for purposes. Ethical Hacking is capably required where approved programmers endeavor to penetrate a business' frameworks/arranges for the benefit of the proprietors with the goal of discovering security shortcomings. It give bits of knowledge into how Ethical Hacking, as Penetration Testing utilizing free open source devices, can be utilized by associations to secure their system's administrations/activities. Utilizing Nmap, Google Hacking, Nessus, Brutus and Acunetix .Thus measures were placed in to determine these vulnerabilities and dodge the delicate information from potential digital threats.
Optimization Before Biomedical Image Compression Using CLAHE and DCS
Authors: S. Magar Satyawati , Sridharan Bhavani
Published: July 2019

In current years, improving the Compression Ratio (CR) in medical imaging is essential and becomes big challenge in the field of biomedical. In that direction we have done optimization before biomedical image compression. For the same we have used the image enhancement techniques. For the enhancement of an image we have used Contrast Limited Adaptive Histogram Equalization (CLAHE) and Decorrelation Stretch (DCS) algorithms. By optimizing an image before compression we have achieved better Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR) than existing methods of an image compression. Mainly results are compared with Oscillation Concept method of an image compression with and without optimization.
Predictive Analysis of Cryptocurrency Price Using Deep Learning
Authors: Yao Yecheng , Yi Jungho , Zhai Shengjun , Lin Yuwen , Kim Taekseung , Zhang Guihongxuan , Yoonjae Lee Leonard
Published: July 2019

The decentralization of cryptocurrencies has greatly reduced the level of central control over them, impacting international relations and trade. Further, wide fluctuations in cryptocurrency price indicate an urgent need for an accurate way to forecast this price. This paper proposes a novel method to predict cryptocurrency price by considering various factors such as market cap, volume, circulating supply, and maximum supply based on deep learning techniques such as the recurrent neural network (RNN) and the long short-term memory (LSTM),which are effective learning models for training data, with the LSTM being better at recognizing longer-term associations. The proposed approach is implemented in Python and validated for benchmark datasets. The results verify the applicability of the proposed approach for the accurate prediction of cryptocurrency price.
Smart Infotainment System for Vehicular Network
Authors: Siddharthraju K , Dhivya Devi R , Shanmugaraja T , Mithunraj S , Sophia S
Published: July 2019

On fast moving life, time management has become an important factor. Objective of this paper is to implement features of high range vehicles even in middle range vehicles through few performance metric improvements. The parametric and non-parametric analysis is applied to evaluate vibration modes. In a Vehicular Ad hoc Network (VANET), vehicles communicate with each other through Dedicated Short-Range Communication (DSRC) wireless devices. Equipped with hundreds of smart sensors, vehicles can detect their own parameters (such as braking, lane changes, and acceleration) and road conditions (such as icy roads and weather conditions).Vehicular ad hoc networks, the spontaneous creation of a wireless network for data exchanges, are used for clustering data. Quantitative data analysis is carried out for decision making.