bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Capacitor Placement in Radial Distribution System Using Moth Flame Optimization Algorithm
Authors: Salman Ihsan , Mohammed Khalid , Shaker Khalid , Shaker Hothefa
Published: August 2019

The environment friendly designing and running of electricity distribution structures are becoming vaster with the conjunction of renewable electricity options into power distribution systems. This study presents Moth Flame Optimization (MFO) approach to minimize total losses kW and energy cost and maximize net savings with solving the voltage deviation problem through optimal site and size of capacitor banks in electrical radial distribution networks. Two various load profiles are utilized to take a look at the modified algorithm on IEEE 123-, and 13-bus check networks. The OpenDSS software is utilized to resolve the power flowing via MATLAB programming interface. The results obtained are compared with IEEE normal state and other two heuristic approaches in same study, namely, imperialist competitive algorithm and particle swarm optimization. The proposed algorithm is more effective to minimise the total power losses and total cost and maximise net savings and to enhance the voltage profile for various distribution systems.
Student’s Success Prediction Model Based on Artificial Neural Networks (ANN) and A Combination of Feature Selection Methods
Authors: Hamoud Alaa Khalaf , Humadi Aqeel Majeed
Published: August 2019

The improvements in educational data mining (EDM) and machine learning motivated the academic staff to implement educational models to predict the performance of students and find the factors that increase their success. EDM faced many approaches for classifying, analyzing and predicting a student’s academic performance. This paper presents a model of prediction based on an artificial neural network (ANN) by implementing feature selection (FS). A questionnaire is built to collect students’ answers using LimeSurvey and google forms. The questionnaire holds a combination of 61 questions that cover many fields such as sports, health, residence, academic activities, social and managerial information. 161 students participated in the survey from two departments (Computer Science Department and Computer Information Systems Department), college of Computer Science and Information Technology, University of Basra. The data set is combined from two sources applications and is pre-processed by removing the uncompleted answers to produce 151 answers used in the model. Apart from the model, the FS approach is implemented to find the top correlated questions that affect the final class (Grade). The aim of FS is to eliminate the unimportant questions and find those which are important, besides improving the accuracy of the model. A combination of Four FS methods (Info Gain, Correlation, SVM and PCA) are tested and the average rank of these algorithms is obtained to find the top 30 questions out of 61 questions of the questionnaire. Artificial Neural Network is implemented to predict the grade (Pass (P) or Failed (F)). The model performance is compared with three previous models to prove its optimality.
Digital Transformation of Market Institutions
Authors: Abdullaev Farkhod Ozodovich , Khamraev Kuvvat Iskandarovich , Arzuova Shargul Ansatbayevna , Abdukayumov Abdumalik Nizomjonovich
Published: August 2019

This article shows how the increasing prevalence of digital technologies into various spheres of human life has necessitated change in a number of institutions. First, it grapples with economic institutions that ensure the functioning of a market economy. In addition, the definition of digital economy, the concept of digital economy, the technological developments specific to digital economy, the share of Information and Communication Technology (ICT) in the gross national product of a country, and the analysis of certain indicators of communication and information are also covered in the article.
A Study of Societal Flow of Phosphorus and Its Effect on Environmental Sustainability In Landfill Sites Terengganu, Malaysia
Authors: Ghani Latifah Abdul , Saputra Jumadil , Muhammad Zikri , Zulkarnaen Iskandar , Alfiady Teuku
Published: August 2019

Phosphorus (P) in the waste at Terengganu can be identified by the heterogeneity of waste sources present at the waste disposal collected, the technology used, location of disposal and the management depends on microbial waste decomposition operations. The diversion of phosphorus out of the waste disposal sites is associated with the presence of low phosphorus inflows due to reduction, recycling and waste recovery activities outside of the landfill system. This finding motivates the socioeconomic characterization of the actors (players) and the identification of management strategies developed by the stakeholders. Thus, the purpose of this study was to identify the nutrient element of phosphorus in the waste disposal site and investigate whether stakeholders were aware of phosphorus and phosphorus credit related to local economic circulars and to examine possible ways of managing phosphorus in the waste source by small waste players in Terengganu. The design of this study was qualitative, involving face-to-face interviews with the stakeholders and a corresponding analysis of their responses. The findings revealed lack of knowledge and awareness by actors regarding the element phosphorus, the causes and sources of phosphorus generation as well as the effects of phosphorus on environmental sustainability. This study highlights useful factors to guide future management decisions and educational programs as well as further research, to disseminate information concerning phosphorus recovery among actors involved in waste management at Terengganu.
IoT Based Multitasking Games and Entertainment Arcade Station using Raspberry-Pi
Authors: Hassan Iman Mohsin , Al-Mashhadi Haider M. , Hassan Kareem Radhi , Jawad Hayder M.
Published: August 2019

The world lives in a technology revolution that started from invention the computer system, the Internet and now in the Internet of Things (IoT) or Internet of every things (IoE). This revolution impacted the human life strongly, by depending on this technology to enhance our life and inventing new products depending on information technology like social media, mobile applications, video games and so on. This research will present the simplest, yet efficient way to build a classic Arcade Machine by using a Raspberry Pi development board, also this research will highlight how to build and install all related components, such as body structure, buttons and joysticks, programming the Raspberry Pi and adding the video game files. Later, the research will explain how to connect the Arcade Machine to the Internet for remote operation by using MCU ESP8266, relays, and the Wi-Fi function on the Raspberry Pi itself. Beside the video games, the machine can behave as an ordinary computer for the Internet browsing, music listening, image processing, documenting or doing some programing tasks, as the Raspbian operating system has python programming apps and it is possible to install any other programing language needed to execute tasks on Raspberry Pi microcontroller.
A Multi-Objective Particle Swarm Optimization for Pavement Maintenance with Chaos and Discrete
Authors: Ahmed Kawther , Al-Khateeb Belal , Mahmood Maher
Published: August 2019

Particle Swarm Optimization (PSO) is a very common algorithm in swarm intelligence algorithms. PSO has been used to solve a lot of problems with one or more goals. Actuality, the multi-objectives improvement issues in all real life are combinatorial in nature. Therefore, PSO has been improved to be able to handle very large number of decision variables and reduce or decrease computational complexity. In this work, a chaos multi objective PSO algorithm is improved for solving discrete (binary) optimization issues with crossover operation. The developed Chaos Discrete Multi Objective PSO (CDMOPSO) algorithm is applied to pavement management problem for flexible pavement to get optimal maintenance and rehabilitation plan. The results shown that there is significant improvement in the solutions satisfying pavement conditions and maintenance cost goals. It is required to a very short time of execution by the improved algorithm to reach a very good solution. Also, comparing the convergence of solutions with the rest of the PSO algorithms, it has found that the suggested algorithm is better.
Effectiveness of Cinnamon (Cinnamomum burmannii) Ethanol Extract Against Staphylococcus aureus Growth
Authors: Huda Nurul , Dwiyanti Ratih Dewi , Thuraidah Anny
Published: August 2019

Cinnamon (Cinnamomum burmannii) is widely used by the public as a food ingredient and contains chemical compounds such as alkaloids, flavonoids, polyphenols, saponins, and terpenoids which function as an antibacterial against Staphylococcus aureus. This study aims to determine the Minimum Inhibitory Concentration and Minimum Bactericidal Concentration of cinnamon ethanol extract on Staphyloccocus aureus. This research is experimental with posttest only control group design through the tube dilution method. The results of the Minimum Inhibitory Concentration (MIC) study showed no clarity at concentrations of 30% and 40%. The results of the Minimum Bactericidal Concentration (MBC) obtained the number of colonies at a level of 10% by 51 CFU / plate, 20% by 27 CFU / plate, 30% by 6 CFU / plate and 40% by 0 CFU / plate. Based on the results of this study concluded that MIC cinnamon ethanol extract was 30%, and MBC cinnamon ethanol extract was 40%.
Circumcision With Plastic Clamb in Newborn Infants
Authors: Baltrak Yusuf Atakan
Published: August 2019

Various devices were used to carry circumcision operation out. It noted that these devices, especially the Plastic Clamp method, significantly decrease complications as long as basic surgical rules, are followed. This study aims to examine the application of Plastic Clamp circumcision in infants. Children whose physical examinations revealed circumcision contradictions excluded from the study. During the study period, a total of 485 children was circumcised using the plastic clamp method under sedated anesthesia and by a single pediatric surgeon. Measurements take before operations and plastic clamps with diameters ranging from 1.2 to 1.6 cm used. The duration of the surgical procedure, early and late period post-operative complications, the separation duration of the plastic clamp, and problems evaluated. Study Results, the average length of the surgical operation was determined to be 5.5 minutes. The average hospital stay duration of the patients was 2 hours. During the follow-ups, edemas were observed in mucosal areas of 24 (4.9%) patients, 48 hours after the clamp placed and edema and swelling recovered seven days after the circumcision at the latest. On average, it observed that plastic clamp separated on its own in 7.1 days. It noted that in 4 (0.8%) patients, the plastic clamp separated prematurely during 6 hours following the operation due to pulling. Conclusion study plastic Clamp (Alisklamp) is starting to gain popularity because it falls off on its own and that it can be applied quickly under local anesthesia
Application of Dbaf Technique for Tannery Industry Wastewater Treatment
Authors:   Professor of Sanitary & Environmental Eng., Faculty of Eng., ASU, Cairo,, Nadi El , Sergany El ,   F.A.R., Associate Professor of Environmental Eng., HIT, 10th of Ramadan,, Hosseiny El ,   O.M., Assistant professor of Environmental eng., CIC, New Cairo,
Published: August 2019

With the interest in environmental protection the interest in industrial wastewater treatment had increased especially with enlargement in industry and the increase of the treatment cost that affect the products prices. This study aimed to investigate the suitability of applying the Dual Biological Aerated Filter (DBAF) as new low cost technique system for biological treatment preceded by a chemical precipitation to treat industrial wastewater of tannery industry. This new technology decreases construction costs, O&M costs and safe land required with high efficiency. The research made on a plant erected in Shahien tannery in Alexandria operated for five months. Where studied the factors affect the plant efficiency under all operation conditions due to operation program, chemicals used, rates and the effects on plant loads to obtain its suitability for such type of wastewater. The study proved the applicability of the system for such wastewater. The removal ratios for BOD, COD & Cr were 88.05%, 85.5%, 98.85% respectively .Which are high values for treatment efficiency of such type of wastewater and a good efficiency for TSS removal achieved. Also the system did not affected by sudden variations in loads or the non uniformity in tannery operation. The economic comparison with other treatments previously used approved the economy of this system.
Machine Learning Centric Product Endorsement on Flipkart Database
Authors:   Assistant Professor, Department of CSE, G.Pullaiah College of Engineering and Technology, Kurnool., Lakshmi* M.Sri , Kumar Dr.S Prem ,   Professor & Dean , Department of CSE, G.Pullaiah College of Engineering and Technology, Kurnool., Janardhan M. ,   Associate Professor, Department of CSE, G.Pullaiah College of Engineering and Technology, Kurnool.
Published: August 2019

The growing need for individual mining information from text leads to analyzing sentiment and viewpoints. Retailers, E-commerce companies, product companies, media houses, real estate firms, and whom all have recognized that sentiment analysis is the key to success. They perform sentiment analysis necessary to get customer information related to feelings; attitudes, reactions, and opinions of existing and potential buyers towards their product or services. In this context, evaluating an individual's viewpoint or humor from a piece of text is challenging. In recent years the need for this analysis has increased due to the benefits obtained from it. In this paper, we conduct sentiment analysis on Flipkart product reviews using machine learning techniques to address the above challenge.
The Technology of Preventing Ecological and Economic Damage Caused by Echinococcosis
Authors:   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan., Aubakirov* Marat Zhaksylykovich , Domatsky Vladimir Nikolaevich ,   Federal State Budgetary Educational Institution of Higher Education “Northern Trans-Ural State Agriculture University”, Tyumen, Russia., Mustafin Muafik Kametaevich ,   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan., Selunskaya Lyubov Stepanovna ,   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan., Khassanova Madina Asylkhanovna ,   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan., Murzakayeva Gulmira ,   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan., Erenko Evgenia Nikolaevna ,   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan., Khairov Gaziz Khametrashidovich ,   The Ministry of Education and Science of the Republic of Kazakhstan, Republican State Enterprise, A. Baitursynov Kostanay State University, Kostanay, Kazakhstan
Published: August 2019

The article presents the data about the mechanism of transmitting echinococcosis from the source of infection to a susceptible animal. It has been found that the main sources of infection are sick dogs, and, more rarely, wild animals. The factors that promote the spread of echinococcosis are home-slaughtering cattle, feeding the viscera of slaughtered animals to dogs, failure to observe the deadlines and the methods of dogs dehelminthization, poor dogs dehelminthization scale, and unordered dog keeping. The article also presents the results of the studies for comparative assessment of various methods of coproovoscopic diagnosing helminthoses in dogs.
Design and Simulation of Hybrid System using Cuckoo MPPT Technique
Authors:   Assistant Professor Department of EEE, Aditya Institute of Technology and Management, Tekkali, AP., Rao* B. Srinivasa , Kumar K. Kiran ,   Professor Department of EEE, Aditya Institute of Technology and Management, Tekkali, AP., Kumar D. Vijaya ,   Professor, Head of the Department of EEE, Aditya Institute of Technology and Management, Tekkali, AP.
Published: August 2019

In contrast to present scenario, the renewable energy sources are accessible at no expense and produce power environmental friendly. Around early afternoon the WPS fulfills its heap and gives extra energy to the capacity or to the grid. On location energy generation is without a doubt went with minimization of ecological contamination, decrease of misfortunes in power system transmission and distribution. The main theme of this paper is to propose a demonstrating and planning of grid interfaced hybrid solar-wind energy system. This is an issue particularly in little powerful system because of the limitation on the inverter markets. Inverters which are used in these sorts of energy systems work on grid or off grid. In this investigation, a novel power the board methodology has been created by structuring a wind-PV mixture system to work both as a self-ruling system and as a grid-associated system. The structured Power Management Unit performs estimation from different focuses in the system and as per this estimation; it gives a compelling energy exchange to burdens and grid. The steadiness of the smaller scale grid, power quality and voltage direction is checked by Matlab and test results. This paper also presents a concept for effective utilization of Distribution Generation systems as a part of smart grid environment, to improve the system reliability by providing effective generation under islanding mode, and also to provide controlling services in the grid-tied mode. To meet this limitations, this proposed flexible system is implemented a control technique with power-voltage-current parameters.
End to End System for Pneumonia and Lung Cancer Detection using Deep Learning
Authors:   Research Scholar, Acharya Nagarjuna University, Nagarjuna Nagar, Guntur, Andhra Pradesh, India., Ponnada* Venkata Tulasiramu , Srinivasu Dr. S.V.Naga ,   Professor, Computer science and engineering, Narasaraopeta Engineering College, Narasaraopet, Andhra Pradesh, India.
Published: August 2019

The Deep learning solutions for medical image analysis are offered a promising alternative solution to self-learning problem-specific features and gave a new facet for computer vision challenges. The early detection of pneumonia and lung cancer plays big role in saving the life. Any method or system contributing to early disease detection is likely to reduce the dearth rate of diseases. Our previous work [3] proposed an efficient CNN (EFFI-CNN) for Lung cancer detection. This paper presents a system to detect the pneumonia and lung cancer using deep leaning techniques (ESPLDUDL). The system leverages the EFFI-CNN, Raspberry Pi and Tensor processing Unit (TPU). The system configuration raises the bar in detection results and technology front.
Improved Logarithmic Search for Efficient Video Compression
Authors:   Department of Computer Science & Engineering, National Institute of Technology, Silchar, Assam, India., Choudhury* Hussain Ahmed , Sinha Nidul ,   Department of Electrical Engineering National Institute of Technology, Silchar, Assam, India.
Published: August 2019

For efficient video compression, the BMAs should be designed and implemented in such a way that that the Motion Estimation takes very less time and will have lesser complexity. In this paper, two new algorithms namely Improved Logarithmic Search (ILS) and Zero motion predicted ILS (ZMILS) are proposed which are based on the basic idea of Three Steps Search (TSS) algorithm. In these BMA, the search pattern of proposed algorithms changes the efficiency both in terms of complications required for each macro block (MB) and quality of the compensated images. We improved the TSS and NTSS by changing the searching pattern of locations in reference frame and by adding no movement early prediction case with these algorithms we further reduced the computations. The computations required by the new developed algorithm are lesser per macro block and even 50% of few existing techniques while retaining the quality of the reconstructed image.
An Effectual Ga Based Association Rule Generation and Fuzzy Svm Classification Algorithm for Predicting Students Performance
Authors:   Professor, Department Of Computer Application, Nehru College of Management, Coimbatore,, Blessie* E.Chandra , Vineetha K R ,   PhD Research Scholar, Nehru College of Management, Coimbatore,
Published: August 2019

This investigation provides outcome of utilizing educational data mining [EDM] to design academic performance of students from real time and online dataset collected from colleges. Data mining is determined to examine non-academic and academic data; this model utilizes a classification approach termed as Fuzzy SVM classification with Genetic algorithm to attain effectual understanding of association rule in enrolment and to evaluate data quality for classification, which is identified as prediction task of performance and academic status based on low academic performance. This model attempts to predict student’s performance in grading system. Academic and student records attained from process were considered to train models estimated using cross-validation and formerly records from complete academic performance. Simulation was performed in MATLAB environment and show that academic status prediction is enhanced while hybrid dataset are added. The accuracy was compared with the existing models and shows better trade off than those methods.
Automatic Lung Cancer Detection using Sobel & Morphological Operations
Authors:   Electronics & Communication, University Institute of Technology, RGPV Bhopal, Madhya Pradesh, India., Soni* Akanksha , Rai Dr. Avinash ,   Electronics & Communication, University Institute of Technology, RGPV Bhopal, Madhya Pradesh, India., Shivhare Ekta ,   Electronics & Communication, University Institute of Technology, RGPV Bhopal, Madhya Pradesh, India.
Published: August 2019

Cancer is the most dangerous disease that may cause death and lung cancer is one of them which is more common among all. There are various imaging techniques through which organs can be scanned for diagnosis. Lung cancer is a disease that may be caused by unrestrained cell growth in lung. Lung cancer is the most common and most dangerous cancer. CT scan can obtain the lung images, but still it has been recognized manually. Manual lung cancer detection is a challenging task because false error rate may lead you to compromise with human’s life. There are lots of researches that has been done in this field but still failed to obtain high precision with minimal error rate. Here the system proposes automatic lung cancer detection using Sobel & Morphological operations that can acquire good precision along with cancer area detection. Sobel is a gradient edge detection technique through which absolute gradient magnitude is computed in the reference of 2D input lung image that is later dilated with morphological operator. The obtained result is liable to attain high precision with less false alarm rate.
Thermal Performance of Micro-Pulsating Heat Pipe
Authors:   Mechanical Engineering Department, National Institute of Technology - Calicut, Kozhikode, Kerala, India., Lachireddi* Gangadhara Kiran Kumar
Published: August 2019

In this study, thermal performance of MPHP is investigated computationally. A case with 0.7mm hydraulic diameter with 7 turns is considered for the study. Simulation is carried out using ANSYS-FLUENT® software by considering water as working fluid with the help of VOF model. Computational study shows the oscillation of fluid inside and formation of new vapor slugs. The heat input is varied from 1.2 W to 4.8 W in the step of 1.2. Flow circulation inside the MPHP is not unidirectional and frequently changes with the pressure disturbance created in the channels. The temperature profile from computational study shows the startup condition is changing with heat input. Thermal resistance of the MPHP decreases with increase in heat input and the corresponding thermal resistance found to be varied from 3.94 to 3.65 K/W.
Hiding an Image in Its Small Segment by Mixing the Segments
Authors:   M.phil Research Scholar Department of Computer Science Alagappa University, Karaikudi, (Tamil Nadu) India., Rahul* B. , Dhenakaran Dr. S.S. ,   Professor, Department of Computer Science, Alagappa University, (Tamil Nadu) India.
Published: August 2019

Blending mechanism and segmentation procedures are used for the hiding process. By blending the segments of an image forms a single segment. The whole image is hiding in this single segment. The proposed work attempted to split an image into eight segments and mixing the segments by performing arithmetic operations between the segments. The original image is hiding in the one of eight segment of the image. By the reverse process, the original image can be extracted.
A Persuasive Resource-Aware Allocation Scheduler for Enhancing Task Scheduling
Authors:   Research Scholar A.V.V.M Sri Pushpam College, Poondi, Thanjavur, India., Rengasamy* R. , Chidambaram M. ,   Department of Computer Science, Rajah Serfoji Government College,Thanjavur, India.
Published: August 2019

The deployment of Map Reduce has been built to grant enhancements to total system objectives such as job throughput. Hence, the support for user-specific objectives and resource allocation management has been least regarded and addressed. Schedulers enable users to assign jobs to queues that fulfil shared of specific resource. Existing work mainly focus on scheduling glitch occurring on the master’s side where the scheduler on the master node tries to allocate same work across all the worker nodes. The proposed scheduler focus on enhancing resource allocation when various kinds of workloads execute on the clusters. In order to evaluate the performance on the proposed scheduler which enhances resource utilization, an accomplishing time goal with each job is created.
Intellectual Acute Lymphoblastic Leukemia (ALL) Detection Model for Diagnosis of Blood Cancer from microscopic images using Hybrid Convolutional Neural Network
Authors:   Ph. D from Career Point University, Kota (Rajasthan)., Sharma* Mr. Anuj , Buksh Dr. Bala ,   Ph. D. (Comp. Sc.) - Birmingham, United Kingdom.
Published: August 2019

Blood cell malignantly growth has been accounted for to be one of the most transcendent types of disease maladies. ALL (Acute Lymphoblastic Leukaemias) is the malignant types of blood cancer and their detection and classification in earlier stage is biggest issue. Automatic detection and classification of ALL from microscopic images is a challenging and intellectual assignment in medical science. Existing techniques for ALL detection and classification are an understandable alternative for real-time dermoscopic data analysis. Existing microscopic image processing approaches are unable to analyze the ALL data with non-stationary nature. In this perspective, the focus of this research is to design hybrid Convolutional Neural Network (CNN) architecture by utilizing Firefly Optimization Algorithm (FOA/FFA) to detect the ALL from microscopic images of human blood cell into malignant or normal blood cell. Methods: For training and testing of proposed ALL Detection and Classification (ALL-DC) Model, Standard ALL-IDB (Acute-Lymphoblastic-Leukaemias Image Database for Image Processing) is used with hybrid CNN architecture based on the FOA. Here, Histogram of Oriented Gradients (HOG) descriptor with FOA is used as feature extraction and selection mechanism from the Region of Blood Cell (ROBC).Feature extraction approach plays an important responsibility to classify lots of blood diseases. On the way to achieve this goal, we proposed ALL-DC model that combines recent developments in deep learning with fuzzy based CNN structure and for ROBC segmentation, hybridization of K-means segmentation algorithm with FOA that are capable to segment the accurate blood cell region from microscopic images. Using k-means segmentation technique, the foreground and background component is separated into two regions and after that to improve the segmentation results; FOA is used with the novel concept of image enhancement approach. Results: The proposed ALL-DC system is evaluated using the largest publicly accessible standard ALL-IDB dataset, containing 600 training and 400 testing microscopic images. When the evaluation parameters of proposed work is compared with a number of other state-of-art schemes, the proposed scheme achieves the most excellent performance of 98.5% in terms of accuracy which also known as area under the curve (AUC) in differentiating ALL from benign cell using only the extracted and optimized HOG feature. Conclusion: When the proposed model is tested on different microscopic images, evaluation parameters is calculated and compared with a few other state-of-art methods and we obtained the proposed method achieves the best performance in terms of classification accuracy. ALL-DC model is implemented and constructed using the concept of Image Processing and Neural Network Toolbox within MATLAB Software.
Noise Immune Pseudo-Stacked-wide keeper Domino technique for Ultra Deep Submicron Technology
Authors:   Department of Electronics and Communication Engineering, NERIST, NIRJULI, INDIA., Ghimiray* Sapna Rani , Meher Preetisudha ,   Department of Electronics and Communication Engineering, NIT Arunachal Pradesh, YUPIA, INDIA, Dutta Pranab Kishore ,   Department of Electronics and Communication Engineering, NERIST, NIRJULI, INDIA
Published: August 2019

The demand of high performance with low leakage has extensively exploited domino logics for high speed computing and microprocessor systems. But this benefit gets compromised with scaling of technology leading to increase in sub-threshold leakage and reduced noise immunity. This paper presents a new performance oriented circuit technique for higher noise immunity with ultra-low leakage and better speed design. The proposed circuit technique employs pseudo buffer along with stacking effect to reduce leakage and power dissipation. The modified keeper transistor in the proposed circuit helps to reduce circuit delay and also improve noise sensitivity. The simulation has been carried out using Cadence spectre 90nm technology with results indicating 57% to 68% less leakage and 77% less power dissipation. The Energy-Delay-Product for the proposed circuit is the lowest in comparison to other existing techniques. The high values of Average Noise Threshold Energy, Unity Noise gain and Energy Normalized Average Noise Threshold Energy proves the improvement in Noise robustness over the previous techniques.
Learning Based Resolution Enhancement of Digital Images
Authors:   Department of CSE, Karunya Institute of Technology and Sciences, Coimbatore, India., Jebadurai* Jebaveerasingh , Jebadurai Immanuel Johnraja ,   Department of CSE, Karunya Institute of Technology and Sciences, Coimbatore, India., Paulraj Getzi Jeba Leelipushpam ,   Department of CSE, Karunya Institute of Technology and Sciences, Coimbatore, India., Samuel Nancy Emymal ,   System Administrator, Sam Salt Works, Tuticorin, India.
Published: August 2019

Image super-resolution (SR), the process that improves the resolution, has been used in many real world applications. SR is the preprocessing phase of majority of these applications. The improvement in image resolution improves the performance of image analysis process. The SR of digital images take the low resolution images as inputs. In this article, a learning based digital image SR approach is proposed. The proposed approach uses Convolutional Neural Network (CNN) with leaky rectified linear unit (ReLU) for learning and generalization. The experiments with the test dataset from USC-SIPI indicate that the proposed approach increases the quality of the images in terms of the quantitative metric peak signal to noise ratio. Further, it avoided the problem of dying ReLU.
Sustainability for the Community by the Community: CSR and Community Involvement through Gamification
Authors:   Research Scholar, Dr. Shakuntala Mishra National Rehabilitation University, Lucknow, Uttar Pradesh, India., Khan Fawad Ali , Yadav Nagendra ,   Professor, Dr. Shakuntala Mishra National Rehabilitation University, Lucknow, Uttar Pradesh, India., Beena Fatima ,   Assistant Professor, Manipal Academy of Higher Education, Dubai International Academic City,Dubai, UAE, Kumar Mohit ,   Associate Professor, IILM Lucknow, Lucknow, Uttar Pradesh, India.
Published: August 2019

This paper explores the aspects of Gamifying the eight human core motivations for voluntary and continued involvement of the community in CSR activities. In these dynamic times communities are expecting diverse aspects in terms of value creation and delivery from the organizations. The organizations in turn have to devise robust CSR strategies that take sustainability as their foundation and create and implement resilient strategies that require a refurbishment of their CSR processes. Gamification is a craft where we derive all the fun and engaging elements found in games and apply the same to real world productive applications. Any process can be better implemented if we design the process for human motivation in a system as opposed to pure-efficiency designs. It should be more of a Human focusing design rather than a Functional focusing one. Sustainability is not an end game process. It is like taking a bath or brushing your teeth. It has to be worked upon every day, with the same vigor and with the objective of KAIZEN. It is not something that can be achieved, rather it is a process that can be developed and retained. This objective can only be achieved if the community voluntarily steps up and takes active and responsible steps towards a better future.
Automation of Longitudinal Time Series Data Visualization using Plot Specifications obtained from XL file
Authors:   Student, Department of Computer Science and Engineering, St. Joseph’s Institute of Technology, OMR, Chennai – 119 India., Sneha S.R. , Rohini G. ,   Professor, Department of Electronics and Communication Engineering, St. Joseph’s Institute of Technology, OMR, Chennai – 119, India., Srinivasan Kamal ,   Senior Statistical Programmer, Regeneron Pharmaceuticals, Tarrytown, New York, USA..
Published: August 2019

Longitudinal Time Series data visualization plays important role in all sector of business decision making [9]. With enormous amount of complex data [11] from cloud and business requirement, number of graphs needed for decision making increased many folds. Generating enormous number of plots manually with more human input is tedious, time consuming and error prone. To avoid these issues, suitable visualization techniques with solid design principles become very important. We conceptualized and designed a novel method for automation of these processes. R-GGPLOT2[7] package and XL specifications file were primarily used to achieve this goal. We here show as how we can create multiple plots from time series data, plots specifications-XL file and R package GGPLOT2[7] in a single run. Since all required information are entered in XL sheet, R function can be run with no modification. Multiple plots can be generated by using enormous data available in production and service sectors such as finance, healthcare, transportation and food industries etc.
Solving the Quadratic Assignment Problem using the Swallow Swarm Optimization Problem
Authors:   Ph.D in Chouaib Doukkali University, Morocco., BOUZIDI* Safaa , BOUZIDI Morad ,   Researcher; Computer Science from Chouaib Doukkali University, Morocco., RIFFI Mohammed Essaid ,   Professor, Computer Science, Chouaib Doukkali University, Morocco.
Published: August 2019

In recent years, there is a growing interest in swarm intelligent algorithms inspired by the observation of the natural behavior of swarm to define a computational method, which may resolve the hardest combinatorial optimization problems. The Quadratic Assignment Problem is one of the well-known combinatorial problems, which simulate with the assignment problem in several domains such as the industrial domain. This paper proposes an adaptation of a recent algorithm called the swallow swarm optimization to solve the Quadratic Assignment Problem; this algorithm is characterized by a hierarchy of search who allow it to search in a totality of research space. The obtained results in solving some benchmark instances from QAPLIB are compared with those obtained from other know metaheuristics in other to evaluate the performance of the proposed adaptation.
Integritas Pendidikan Multikultural dalam Implementasi Kurikulum 2013
Authors: Watoni M Saipul
Published: August 2019

Multicultural-based education is a tiered educational process that is able to become a binder and a bridge that accommodates differences in social, ethnic, gender and religious status in multicultural societies in order to create intelligent, wise and polite personalities in dealing with diversity problems. The multicultural education paradigm is very useful for building social harmony among the diversity of ethnicity, race, religion, culture and needs among us. Considering the complexity of plurality and multiculturalism in Indonesia in terms of socio-cultural and geographical conditions that are so diverse and broad, special strategies are needed to solve these problems through various fields; social, economic, cultural and educational. In this regard, multicultural-based education has actually been integrated in the 2013 curriculum. This is reflected in being integrated in the education curriculum and learning process.
Motivasi, Bimbingan dan Perhatian Orang Tua Siswa dalam Pendidikan di MTs. Baiturrahim Kabar Kecamatan Sakra Lombok Timur
Authors: Syahdan Syahdan
Published: August 2019

The purpose of this study is to find out or obtain information or a clear picture of the forms of roles performed by parents of students in helping the success of education, especially Islamic religious education in MTs. Baiturrahim Kabar 2019/2020 Academic Year. The benefits expected in this study can provide benefits for researchers, teachers, and parents of students to create conducive learning facilities, can provide information for parents of students to be able to create a good home environment for their children to pursue and practice the lessons learned. This study was designed in the form of a qualitative study by describing data relating to the variables in this study regarding parental participation in supporting the success of Islamic education in students in MTs. Baiturrahim Kabar. While the study population was all MTs students. NW Baiturrahim Kabar, amounting to 52 students from grade VII to class IX. The instruments used to obtain data are questionnaires / questionnaires, and interviews. The results obtained are the participation of parents in Islamic religious education of their students classified as moderate. This form of parental participation consists in providing motivation, guidance, and attention. Motivation has a very important role in motivating, building the personality and intellect of students to better the future of their children based on the demands of the Islamic religion. The most visible guidance for students is giving advice, giving good ways to get along, speaking well, giving a set of dreams, giving sanctions if guilty. While participation in parents in giving attention to their students to pay attention to all the needs that support learning for their students both within the family and in the wider community.
Hubungan Minat Baca dan Penguasaan Kosakata dengan Pemahaman Bacaan Berbahasa Inggris
Authors: Jumatriadi Jumatriadi
Published: August 2019

This research is aimed at finding out the nature and strength of relationships between reading interest, vocabulary mastery with English reading comprehension, both separately and simultaneously. The research was conducted at students of first and second semester of Islamic Religion Education Department of STIT Palapa Nusantara Lombok-NTB with 50 students taken as samples using random sampling. The technique used to analyze data was the statistical technique of regression and correlation. The result of the research indicates that there are positive correlation between: (1) reading interest with English reading comprehension; (2) vocabulary mastery with English reading comprehension; and (3) reading interest and vocabulary mastery with English reading comprehension. Based on the result of the research, it can be concluded that English reading comprehension can be developed by increasing reading interest and vocabulary mastery.
Engagement and authoring platform for teacher and learner of science, Go-Lab portal for learning at school
Authors: Al-Sarray Esraa
Published: August 2019

The Global Science Labs is a European collaborative project funded jointly by the European Commission, which provides students and teachers with the opportunity to acquire laboratory experience in science through experiments using laboratory equipment managed by companies and technical staff that are competent in dealing with all scientific experiments via the Internet. And how they allow the teacher to choose his own script. In this research we will highlight how to use them in developing the educational process, and how it shortens the time and material and logistical possibilities. On this basis, proposals and recommendations were reached.
Intracranial calcifications on CT: an updated review
Authors: Saade Charbel , Najem Elie , Asmar Karl , Salman Rida , El Achkar Bassam , Naffaa Lena
Published: August 2019

Intracranial calcifications are frequently encountered in non-contrast computed tomography scan in both adult and pediatric age groups. They refer to calcifications within the brain parenchyma or vasculature and can be classified into several major categories: physiologic/age-related, dystrophic, congenital disorders/phakomatoses, infectious, vascular, neoplastic, metabolic/endocrine, inflammatory and toxic diseases. In this updated review, we present a wide spectrum of intracranial calcifications from both pediatric and adult populations focusing on their pattern, size and location.
Non-Western Epistemology and the Understanding of the Pachamama (Environment) Within the World(s) of the Aymara Identity
Authors: Apaza Huanca Yaneth Katia
Published: August 2019

The purpose of this article is to understand, from the perspective of the Bolivian Aymara identity of Bolivia, the intrinsic relation these persons have with Nature. This task is developed through the study of what they call Pachamama (sacred Mother Earth), which is part of their identity as an ‘all interrelated whole, the Suma Qamaña or Good Living’, and which can be considered a non-Western epistemology. Their worldview breaks with the Western (anthropocentric) conception of environment that informs European and Anglo-Saxon continental law, and that is currently predominant in international standards of reference. Proponents of this perspective achieved a transformation in the international treatment of Nature, recognised by the United Nations (Resolution 63/278 of 2009, promoted by the Bolivian State), gaining inspiration from the inclusion by Ecuador of Pacha Mama (Nature) as a subject of rights in its constitution (2008).
Wildlife Trafficking between the European Union and Mexico
Authors: Arroyo-Quiroz Inés , Wyatt Tanya
Published: August 2019

Illegal wildlife trade or wildlife trafficking is a global threat to all kinds of species, not just charismatic megafauna or wildlife in Africa and Asia. This paper presents the findings of an investigation of the illegal trade in native and non-native wildlife and wildlife products between the European Union and Mexico. Using literature analysis, secondary trade data and expert interviews, this study explores the nature and extent of wildlife trafficking between these two regions, including the involvement of organised crime within an eco-global criminological framework. This is important for the regions studied and for the global community more generally, as wildlife trafficking is contributing not only to species extinction, but also to instability, violence and unhealthy physical environments for humans.
Conflict, Environment and Transition: Colombia, Ecology and Tourism after Demobilisation
Authors: McClanahan Bill , Sanchez Parra Tatiana , Brisman Avi
Published: August 2019

In 2016, Colombia’s left-wing guerrilla FARC-EP (Fuerzas Armadas Revolucionarias de Colombia—Ejército del Pueblo) began demobilisation. While demobilisation and the ensuing peace accords brought renewed hope that the country could imagine different political and social relations—and new ecological and economic conditions—multinational corporations filled the ‘void’ left by FARC-EP forces. Corporate interests in Colombia’s natural resources predated the demobilisation. However, extractive processes were restricted by the dynamics of the armed conflict. In 2016, immediately following the demobilisation, deforestation in Colombia jumped 44 per cent. In the transitional demobilisation period, huge swaths of the country were opened for economic development. Thus, while the environment is often a victim in armed conflict, in Colombia, conflict contributed to the preservation of some areas. Among the forms of development that have emerged in Colombia, ‘ecotourism’ has risen quickly to the fore. While ecotourism may offer some promise, it should be viewed with caution.
Real Options Valuation in Gold Mining Projects under Multinomial Tree Approach
Authors: Zapata Quimbayo Carlos Andres , Mejía Vega Carlos Armando
Published: August 2019

Metal price, exchange rate, and operating costs are three of the most important sources of uncertainty in mining projects. In that sense, numerous research studies have been carried out to account for price uncertainty, while few others have incorporated the simultaneous effects of operating costs and price uncertainties. The purpose of this paper is to introduce the octanomial tree method to value an Australian gold mine project by adding three market uncertainties such as the gold spot price, USD/AUD exchange rate and the operative costs, under a multinomial tree approach. The proposed model combines the simplicity of the binomial tree model with the ability to deal efficiently with multiple uncertainties.
School and District Leaders Talk about Teacher Attrition
Authors: Elyashiv Rinat Arviv
Published: August 2019

Teacher attrition has become a challenge in many educational systems worldwide. Many studies have focused onteachers' perspectives, while attempting to identify the factors that motivated teachers' decision to leave theprofession. The present study aimed to explore teacher attrition from the point of view of school leaders - principalsand inspectors. Using qualitative and quantitative methods, the results indicate that school and district leadersperceived teacher attrition via two-dimensional structure, including explicit and implicit dimensions. The explicitdimension refers to the act of leaving. The participants indicated that the main reasons that motivate teachers'decision to leave the profession are related to the stressful working environment and poor job conditions. Theimplicit dimension presents a hidden attrition. Based on cost-benefit theory the study highlights the complexstructure of teacher attrition.