bluuebunny/crossref_metadata_2025 huggingface dataset:
Pengaruh Suplementasi Madu Trigona terhadap Parameter Fungsi Hati dan Ginjal Tikus Albino (Rattus norvegicus) yang Diberikan Simvastatin
Authors: Mamada Sukamto Salang , Usmar Usmar , Aliyah Aliyah , Aminullah Aminullah , Rahayu Ayu Indah , Hidayat Khaldun , Salampe Mirnawati
Published: May 2018

Simvastatin is a drug acting on 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase enzyme leading to decrease of lipid level in plasma. Simvastatin is associated with pleiotropic effects such as cardioprotective, hepatoprotective, and nephroprotective effect. This study aimed to observe effect of supplementation of trigona honey on parameters of liver function (SGPT and SGOT) and kidney function (urea) in albino rats (Rattus norvegicus) given 40 mg/kg simvastatin. Twenty-four male albino rats were divided into 6 groups (n=4). Each group was administered different treatments for 15 days orally. Group I was put as health control without any treatment, group II was given sodium carboxymethylcellulose (1% b/v) as negative control, group III was given simvastatin at the dose of 40 mg/kg, group IV was administered simvastatin (40 mg/kg) and trigona honey (6.5% v/v), while group V and VI were administered simvastatin (40 mg/kg) and ubiquinone (1.43 mg/kg); and simvastatin (40 mg/kg), trigona honey (6.5% v/v), and ubiquinone (1.43 mg/kg), respectively. Upon the treatments, level of SGOT, SGPT, and ureum was determined. The data were analyzed by using Analysis of Variance (ANOVA) and Least Significant Difference tests (p=0.05). According to the analysis, it was concluded that supplementation of trigona honey in rats administered simvastatin showed significantly lower level of all parameters than groups of simvastatin and controls.
Carcinoma indiferenciado linfoepitelioma-like de nasofaringe: tumor raro iniciado quadro com otite média secretora
Authors: Gignon Vinicius De Faria , Flório Junior Luiz Eduardo , Tsuchiya Daniela Sayumi , Kawano Letícia Sano
Published: May 2018

A região nasofaríngea apresenta diferentes tipos de tecido e epitélios, podendo apresentar uma significativa diversidade de neoplasias. O tumor maligno originado a partir de células epiteliais denomina-se carcinoma. O carcinoma indiferenciado linfoepitelioma-like é raro, mas com boa resposta ao tratamento radioterápico. O objetivo deste relato é alertar para o diagnóstico de tumores de nasofaringe iniciando quadro com Otite Média Secretora. Neste caso, trata-se de um tumor raro cujo diagnóstico precoce foi crucial para a cura da doença antes de acometer estruturas vitais pelo seu crescimento.
IMPLEMENTASI 7 KEBIASAAN DALAM MENGHADAPI GLOBALISASI FAKULTAS ILMU KOMPUTER UNIVERSITAS DIAN NUSWANTORO SEMARANG
Authors: Hendriyanto Novi
Published: May 2018

Dalam perkembangan teknologi, ada pertumbuhan yang tidak kalah penting, yaitu karakter dan kebiasaan. Kebiasaan merupakan hal yang dapat membentuk karakter di masa depan dan hal ini akan sangat berpengaruh pada dihasilkannya sumber daya manusia yang handal. Pada riset ini akan diperlihatkan bahwa dengan melatih 7 kebiasaan yang sangat efektif dari Stephen R.Covey, maka akan dihasilkan sebuah bentuk manusia baru yang sangat berkualitas tinggi, dimana manusia yang dihasilkan adalah  manusia  yang  mempunyai  inovasi,  kreatifitas  dan  dapat  menghasilkan produk-produk  yang berguna buat komunitasnya dan memiliki kebiasaan, karakter, dan sikap yang dapat diandalkan sebagai seorang innovator, pemimpin dan staff. Inilah yang dinamakan dengan pertumbuhan secara aksi dan bukan pertumbuhan scientific. Memang perlu diakui konsep daripada suatu pengetahuan memang penting karena merupakan dasar dari kemampuan yang harus dikuasai, tetapi perlu sejalan dengan pertumbuhan kebiasaan. Lebih jauh lagi,  riset ini  akan  menjelaskan hubungannya dengan universitas, dosen dan mahasiswa lebih mendalam.
IMPLEMENTASI METODE FUZZY DALAM PERANCANGAN SISTEM PENDUKUNG KEPUTUSAN PENDISTRIBUSIAN BERAS BERSUBSIDI
Authors: Sahfitri Vivi , Nasir Muhammad , Kurniawan Kurniawan
Published: May 2018

Salah satu program pemerintah dalam usaha menurunkan angka kemiskinan terutama dalam hal kecukupan pangan adalah dengan memberikan bantuan beras bersubsidi. Selama ini proses yang terjadi dalam pendistribusian beras  bersubsidi menemui banyak permasalahan. Permasalahan yang paling sering adalah  distribusi  beras  bersubsidi  yang  tidak  tepat  sasaran.  Distribusi    beras  bersubsidi  ya ng  telah dilakukan oleh Pemerintah saat ini belum tepat sasaran sesuai dengan tujuan yang ingin dicapai dalam Program Pemerintah ini. Hal ini terjadi karena kurangnya pengawasan dalam pendistribusiannya. Progam Pemerintah yang bertujuan untuk memperkuat ketahanan pangan Rumah Tangga Miskin dapat dicapai jika pendistribusian beras bersubsidi tepat sasaran yaitu  diberikan pada  Rumah Tangga Miskin. Proses yang berjalan dalam pendistribusian beras bersubsidi saat ini belum memanfaatkan perkembangan teknologi informasi,    hanya dilakukan  melalui catatan survey yang  diberikan dari perangkat  daerah terendah ke perangkat daerah tingkat yang lebih tinggi.  Penelitian ini bertujuan untuk merancang suatu sistem yang dapat membantu mendistribusikan beras bersubsidi sehingga tepat sasaran serta mensimulasikan perhitungan dalam menentukan penerima beras bersubsidi  dengan menggunakan metode Fuzzy  Simple  Additive  Weighting  (SAW)  yaitu  salah  satu  Metode  Penunjang  Keputusan  dengan melakukan Penjumlahan Terbobot. Metode SAW membutuhkan proses normalisasi matrik keputusan ke suatu skala yang dapat diperbandingkan dengan semua rating alternatif yang ada. Hasil dari perancangan sistem penunjang keputusan dan simulasi perhitungan dalam pendistribusian beras bersubsidi ini menjadi dasar bagi pihak terkait untuk menentukan penerima beras bersubsidi.
OPTIMASI ALGORITMA LEARNING VECTOR QUANTIZATION (LVQ) DALAM PENGKLASIFIKASIAN CITRA DAGING SAPI DAN DAGING BABI BERBASIS GLCM DAN HSV
Authors: Sudibyo Usman , Kusumaningrum Desi Purwanti , Rachmawanto Eko Hari , Sari Christy Atika
Published: May 2018

Meningkatnya kebutuhan daging sapi, berdampak pada harga daging sapi. Harga daging sapi yang terus menerus mengalami kenaikan, tentunya menyebabkan penurunan penjualan daging sapi. Untuk mengantisipasi hal tersebut, maka beberapa pedagang mencampurkan daging sapi dengan daging babi. Dipilihnya daging babi, karena harga daging babi lebih murah dan warna serta tekstur daging babi yang mirip dengan daging sapi. Secara kasat mata daging sapi dan daging babi sulit untuk dibedakan bagi orang awam. Oleh karena itu, perlu adanya sistem yang dapat membedakan kedua daging. Penelitian ini menggunakan metode klasifikasi untuk membedakan kedua daging. Metode klasifikasi menggunakan algoritma Learning Vector Quantization. Dan penelitian ini memiliki tiga tahapan utama seperti preprocessing, segmentasi warna, ekstraksi fitur, dan klasifikasi. Preprocessing digunakan untuk mendapatkan Region of Interest (ROI) dengan memotong citra dan mengubah ukuran citra. Segmentasi warna menggunakan metode HSV untuk mendapatkan kedalaman warna citra dan ekstraksi fitur mengguakan Gray Level Co-occurrence Matrix (GLCM) untuk mendapatkan fitur dari kontras, korelasi, energi, dan homogenitas. Hasil klasifikasi dengan algoritma LVQ mendapatkan akurasi tertinggi 76,25%. Algoritma telah diuji dengan MSE untuk mengetahui minimum error dan PSNR digunakan sebagai pengukuran kualitas citra pengolahan.
KOMPARASI MODEL E-COMMERCE UKM BANGKA BELITUNG DENGAN ANALYTICAL HIERARCHY PROCESS (AHP)
Authors: Magdalena Hilyah
Published: May 2018

Usaha Kecil dan Menengah (UKM) adalah penggerak ekonomi yang paling tahan terhadap krisis ekonomi di Indonesia. Secara nasional saat ini UKM telah mempunyai peta jalan sistem perdagangan nasional berbasis elektronik (Road Map E-Commerce) 2017 – 2019. Bagi sebagian pelaku bisnis UKM di Bangka Belitung memutuskan untuk merubah pola transaksi dari transaksi konvensional menjadi transaksi elektronik. Proses mengambil keputusan untuk merubah transaksi bisnis UKM menjadi berbasis elektronik (e-commerce) sangat dipengaruhi oleh banyak faktor. Dengan demikian proses pengambilan keputusan untuk menggunakan e-commerce bagi UKM hal menjadi pengambilan multikriteria faktor. Untuk mendukung pengambilan multikriteria faktor ini maka penelitian ini menggunakan metode Analytical Hierarchy Process (AHP). Multi kriteria faktor tersebut adalah adalah keunggulan teknologi sebesar 22,6%, keunggulan desain web 21%, keunggulan pembayaran 13,6%, keunggulan promosi 11,7%, keunggulan konsumen 10,9%, keunggulan promosi 7,8%, keunggulan, resiko 6,7%, dan kelemahan 5,7%. Sedangkan jenis e-commerce yang paling tinggi B2C sebesar 24,2%. Hasil ini memberikan informasi untuk Dinas Perindustrian dan Perdagangan Bangka Belitung yang bekerja sama dengan Dinas Koperasi, Usaha Kecil dan Menengah Bangka Belitung untuk lebih fokus meningkatkan pelatihan dan pendampingan UKM untuk menguasai teknologi pemasaran berbasis internet.Kata kunci: MCDM, AHP, E-Commerce, UKM.
RANCANG BANGUN PROTOTYPE ALAT PENJEMUR PAKAIAN OTOMATIS BERBASIS ARDUINO UNO
Authors: Darusman Alhen Dwi , Dahlan Mohammad , Hilyana F. Shoufika
Published: May 2018

Dalam penelitian yang berjudul prototype alat jemuran otomatis menggunakan sensor LDR dan sensor hujan berbasis Arduino Uno bertujuan untuk memudahkan pekerjaan manusia dalam masalah menjemur pakaian, karena apabila musim hujan tiba dimana ada pakaian yang dijemur dan lantas turun hujan pengguna tidak perlu khawatir karena alat penjemur pakaian otomatis ini akan secara otomatis bergerak menuju ke dalam ruangan. Metode yang digunakan adalah rancang bangun, yang diawali dari pembuatan prototype jemuran otomatis, membuat sistem kendali intensitas cahaya dan tetes air hujan sesuai dengan kebutuhan pada proses penjemur pakaian. Proses deteksi menggunakan sensor hujan dan LDR (Light Dependent Resistor), untuk indikator menggunakan LED. Pengendali yang akan digunakan berbasis Arduino Uno dengan Mikrokontroller ATmega 328 dengan bahasa pemrogaman, yaitu bahasa C. Dari hasil perancangan diketahui bahwa rangkaian dapat bekerja dengan baik yaitu ketika cuaca cerah jemuran pakaian berapa diluar ruangan dan ketika cuaca mendung atau hujan jemuran pakaian bergerak masuk ke dalam ruangan tertutup. Hal ini terlihat dari sensor dapat bekerja dan outputnya seperti LED dan kipas angin berfungsi (aktif). Pada saat pengambilan data, memakai cahaya ruangan untuk menstabilkan nilai multimeter.
ROLE OF NORMATIVE PRESSURES TO ADOPT GREEN SUPPLY CHAIN MANAGEMENT PRACTICES AND THEIR IMPACT ON ENVIRONMENTAL AND ECONOMIC PERFORMANCE
Authors: Saeed Amer , Priyankara H.P. Rasika , Naotunna N.P.G.S.I.
Published: May 2018

Businesses around the globe are facing tremendous pressures to improve their manufacturing practices to minimize their harmful effects on the environment. These pressures are being exerted from different stakeholders but in developing countries mostly there are powerful suppliers and customers, which can change the choices of decision makers in the local industry. According to institutional theory these pressures combined are called normative pressures. By using path modeling this study attempted to find out the role of normative pressures to adopt green supply chain management (GSCM) practices and the impact of those adopted practices on environmental and economic performance of those companies through partial least square (PLS) structural equation modeling (SEM). Data was collected from 134 manufacturing companies in Pakistan through a questionnaire. Path analysis results confirmed that normative pressures have positive and significant impact on adopting the GSCM practices and subsequently these practices improve the environmental performance of the companies in Pakistan. Results also confirmed many existing studies that GSCM practices directly do not improve economic performance but environmental performance does have a significant positive effect on the economic performance
LEAN SIX SIGMA: MULTIPLE CASE STUDY
Authors: Da Silva Orlando Roque , Marco Rosini Alessandro , Guevara Arnoldo J H , Palmisano Angelo , Venanzi Delvio
Published: May 2018

Lean Six Sigma is a management focused on quality and productive performance in operating systems. This article discusses the foundations of this methodology through of two different conceptions of management, Lean Manufacturing and Six Sigma. First of the article explain the DMAIC (define measure, analyze, improve and control) and their respective phases, after the Lean philosophy with the sipoc and value stream mapping techniques. The article aims to show integration of these two conception and their results. The methodology consisted in a theory was based on a literature search an exploratory research which consisted of three case studies in differences companies located in Sorocaba, São Paulo. In this article studies the applying of Lean Six Sigma and its results.
ONLINE HOTEL RESERVATION AND MANAGEMENT SYSTEM FOR THE COLLEGE OF INTERNATIONAL TOURISM AND HOSPITALITY MANAGEMENT (CITHM)
Authors: Delizo Glenda A. , Esguerra Mischelle A.
Published: May 2018

This study aims to develop and design an on-line hotel reservation and management system for the College of International Tourism and Hospitality Management of the Lyceum of the Philippines University, Batangas Campus. It presents user-friendly features that will familiarize CITHM students on the online hotel reservation system, evaluate it and highlight the benefits it can provide to the college and staff. In addition, it will purvey supplement material in their front desk operation course. The researchers used the System Development Life Cycle and Microsoft Web Developer 2008 as the programming language.Â  The developed software served as a tool for the students of CITHM to familiarize them on how to operate an online hotel reservation system. The developed software was an effective aid for the instructors in teaching the basic operations of hotel reservation system to their students. It also provided online security to protect privacy and financial information of clients.Â
Homology modeling and Molecular docking studies of AS1 (Anthranilate synthase component I (TrpE)) model of Mycobacterium tuberculos
Authors: Kumar K Naresh , Kumar C Suresh , Rao D Subba
Published: May 2018

The emergence of multi-drug resistant (MDR) strains of Mycobacterium tuberculosis is the main reason why tuberculosis (TB) continues to be a major health problem worldwide. It is urgent to discover novel anti-mycobacterial agents based on new drug targets for the treatment of TB, especially MDR-TB. Tryptophan biosynthetic pathway, which is essential for the survival of M. tuberculosis and meanwhile absent in mammals, provides potential anti-TB drug targets. One of the promising drug targets in this pathway is anthranilate synthase component I (TrpE), whose role is to catalyze the conversion of chorismate to anthranilate using ammonia as amino source. Anthranilate synthase is an interesting target enzyme for antimicrobial activity due to its presence in microorganisms for the synthesis of the essential amino acid tryptophan.Â  In the present study three compounds Cannabigerolic acid, cannabinolic acid and adhumulone from Cannabis sativa have been used for insilio docking studies.Â  Inhibitory studies (invitro) of these compounds against Microorganism have reported earlier.Â  Our approach is to find out the compounds inhibiting the AS1 of MTB by insilico docking and also find out compounds having similar pharmacophore characters from ZINC database so that those compounds can be procured of synthesized in laboratory and used for AS1 inhibitor studies.Â  This study shows that AS can be used as a target enzyme to investigate the mode of action of our compounds in MTB.
PERFORMANCE AND ANALYSIS OF REED-SOLOMAN CODES FOR EFFICIENT COMMUNICATION SYSTE
Authors: Chouksey Sagar , Ghadle Mayur , Rasheed Abdul , Mohd Murtaza Shaikh Khursheed
Published: May 2018

In wireless communication systems reducing bit/frame/symbol error rate is critical. If bit error rates are high then in wireless communication system our aim is to minimize error by employing various coding methods on the data transferred. Various channel coding for error detection and correction helps the communication system designers to reduce the effects of a noisy data transmission channel. In this paper our focus is to study and analysis of the performance of Reed-Solomon code that is used to encode the data stream in digital communication. The performances were evaluated by applying to different phase sift keying (PSK) modulation scheme in Noisy channel. Reed-Solomon codes are one of the best for correcting burst errors and find wide range of applications in digital communications and data storage. Reed-Solomon codes are good coding technique for error correcting, in which redundant information is added to data so that it can be recovered reliably despite errors in transmission or retrieval. The error correction system used is based on a Reed-Solomon code. These codes are also used on satellite and other communications systems.Â
Machine Learning Algorithm Evaluate the maintainability
Authors: Pal Dhaka Dr.Vijay , Agrawal Swati
Published: May 2018

Maintainability is an important quality attribute and a difficult concept as it involves a number of measurements. Quality estimation means estimating maintainability of software. Maintainability is a set of attribute that bear on the effort needed to make specified modification. The main goal of this paper is to propose use of few machine learning algorithms with an objective to predict software maintainability and evaluate them. The propose models are Gaussian process regression networks (GPRN), probably approximately correct learning (PAC), Genetic algorithm (GA). This paper predicts the maintenance effort. The QUES (Quality evaluation system) dataset are used in this study. The QUES datasets contains 71 classes. To measure the maintainability, number of “CHANGE” is observed over a period of few years. We can define CHANGE as the number of lines of code which were added, deleted or modified during few year maintenance periods. After this study these machine learning algorithm was compared with few models such as GRNN (General regression neural network) model, RT (Regression tree), MARS (Multiple adaptive regression

splines), SVM (Support vector machine), MLR (Multiple linear regression) models. Based on experiments, it was

found that GPRN can be predicting the maintainability more accurately and precisely than prevailing models. We also include object oriented software metric to measure the software maintainability. The use of machine learning algorithms to establish the relationship between metrics and maintainability would be much better approach as these are based on quantity as well as quality.
Genetic algorithm based approach to solve travelling salesman problem with one point crossover operator:
Authors: Roy Sharadindu
Published: May 2018

In this paper, the travelling salesman problem using genetic algorithm has been attempted. In this practical paper solution is easy and we can easily apply genetic operator in this type of problem. Complexity is both in time and space, provided size of the problem an as integer (count is infinite). The solution of the traveling salesman problem is global optimum. There are cities and given distances between them. Traveling salesman has to visit all of them. TSP main objective is to find traveling sequence of cities to minimize the traveling distance.* traverse one time*initially we select parent1 & parent2 by Roulette wheel concept. Apply one point crossover operator on parents and produce the offspring. Again we apply the mutation operator on offspring and created child. But the no. of bits (cities) will be inverted by the mutation operator, that is depended on mutation probability (pm). So one generation contain 6 individual. Then count fitness of the individuals in each generation. For the next generation (for parent1 & parent2) two individuals will be selected whose fitness is best in generation. Here we see crossover between two good solution may not always yield a better or as good a solution. Since parents are good, so the probability of the child being good is high. Every time we have to do, identity the good solution in the population and make multiple copies of the good solution.
Hajj and Umra smart mobile Application: Culture and Usability Study
Authors: Omar Firas , Alhmiedat Tareq , Hassouna Mohammad
Published: May 2018

Mobile technology is becoming more popular around the world. The importance of such technology relates to its capability of allowing the user of performing many different daily basis tasks. Despite the progress made in the mobile application field, there are still some boundaries and limitations in using it. Some of these difficulties are connected directly to the Culture. Other difficulties are related to the experience in using such technology. This research aims to find out the main restrictions and obstacles which limit the use of mobile handsets as an Islamic smart Hajj and Umra Application. The research aim extends to studying the effect of cultural issues on peoples use of the internet on a mobile phone. The research reported here is based on participants from the Hashemite Kingdome of Jordan.
Evaluation of Detection System of Fault Attacks based on Neural Network into a Java Virtual Machine
Authors: El farissi Ilhame , AZIZI Mostafa , Lanet Jean-Louis , Moussaoui Mimoun
Published: May 2018

The Java Card technology provides a secure environment for developing smart card application based on Java while also respecting some constraints such as the limited memory and processing card. In addition to the security and cryptography APIs offered by the Java Card technology, the smart card is protected against some threats. But, the fault attacks based on the variation of the physical parameters are able to disrupt its operation. In order to enhance the smart card security, we thought to add an intelligent component able to distinguish between the smooth functioning and the attack. This component is a Neural Network that we developed in C language and integrated in open source Virtual Machine (Avian) in order to simulate the attack effect and the network behavior. In this context, the detection rate of the attacks is 96% with no false positive.
Intuitionistic fuzzy optimization: Usage of hesitation index
Authors: Garai Arindam , Roy Tapan Kumar
Published: May 2018

This paper presents the concept of usage of hesitation index in optimization problem under uncertainty. Our technique is an extension of idea of intuitionistic fuzzy optimization technique, proposed by Plamen P. Angelov in 1997, which is widely considered as a successful intuitionistic fuzzy optimization tool by researchers all over the world. It is well known that the advantages of the intuitionistic fuzzy optimization problems are twofold: firstly, they give the richest apparatus for formulation of optimization problems and on the other hand, the solution of intuitionistic fuzzy optimization problems can satisfy the objective(s) with bigger degree of satisfaction than the analogous fuzzy optimization problem and the crisp one. Angelovâ€™s approach is an application of the intuitionistic fuzzy (IF) set concept to optimization problems. In his approach, the degree of acceptance is maximized while the degree of rejection is minimized. In our approach, not only the degree of acceptance is maximized and the degree of rejection is minimized but also the degree of hesitation is minimized. For the sake simplicity alone, the same problem, as studied by Angelov, is considered. Varied importance (and hence weights) to each of the degree of acceptance and the degree of rejection and the degree of hesitation have been given. Tables with these results are formulated and compared among.
AUTOMATIC ROAD DETECTION OF SATELLITE IMAGES USING IMPROVED EDGE DETECTION
Authors: Kaur Supreet , Baghla Seema
Published: May 2018

Road networks play an important role in a number of geospatial applications, such as cartographic, infrastructure planning and traffic routing software. Automatic and semi-automatic road network extraction techniques have significantly increased the extraction rate of road networks. The road detection performance is a critically affected by the noise or low frequency images. Road edge detection plays an significant role to detect the direction of the road and the specific location of obstacles, size and speed of obstacles in the road. In this paper, several road detection techniques are theoretically analyzed, and a new road detection technique is proposed using median filter. By comparing it with some well known techniques it is found that there exist many gaps in the techniques proposed so far. Â By comparing the proposed algorithm with proposed it is proved that the proposed algorithm does not provide artifacts was quite more in old tewchniques.
AUTOMATIC ENERGY SAVING (AES) MODELTO BOOST UBIQUITOUS WIRELESS SENSOR NETWORKS (WSNs)
Authors: Razaque Abdul , Elleithy Khaled
Published: May 2018

We deploy BT node (sensor) that offers passive and active sensing capability to save energy. BT node works in passive mode for outdoor communication and active for indoor communication. The BT node is supported with novel automatic energy saving (AES) mathematical model to decide either modes. It provides robust and faster communication with less energy consumption. To validate this approach, we use two types of simulations: Test bed simulation is performed to automate the server through mobile phone using AES model. Ns2 simulation is done to simulate the behavior of network with supporting mathematical model. The main objective of this research is to access remotely available several types of servers, laptops, desktops and other static and moving objects. This prototype is initially deployed to control MSCS [13] & [14] from remote place through mobile device. The prototype can further be implemented to handle several objects simultaneously in university and other organizations consuming less energy and resources.
A Survey of multimedia videoconferencing system and a proposal for a novel hybrid cloud and P2P architecture
Authors: Debbabi Imen , Kammoun Wafa , Bouallegue Ridha
Published: May 2018

Technological advances of the Internet and network technology have allowed the development and deployment of new services as multipoint multimedia applications: long-distance education, IPTV, distributed games and videoconferencing systems. In this paper, we focus on videoconferencing systems, which represents the most complex type of video communication. These systems have been used for several of years in business, and more recently in everyday life and they allow interactive communications and facilitate the joint work among users regardless of their geographical location. In this paper, we describe a variety of proposed videoconferencing solutions and classify them according to characteristics such as network architectures and video coding technologies and we propose a novel hybrid cloud and P2P architecture with introduction a function for QoS Adaptation.
DESIGN AND DEVELOPMENT OF AN ONLINE EXAM MAKER AND CHECKER
Authors: M. Ramos Maria Cristina , Velasquez Janice E.
Published: May 2018

The study is an online, computer aided tool that was designed primarily for the conduct of online examination. The system was created using PHP, a web based scripting language, and MySQL as the database software. The system focuses on the automation of students' examinations; preparation, scheduling, checking and grading. A database is provided for the storage of exam questions, answers to questions and students' records. The system allows instructors to create an exam by entering questions with its corresponding answers into the database. Instructors are provided with three options on the type of exam; these include, True or False, Multiple Choice and Fill in the Blanks.There are three account types based on the intended users. One is the Administrator Account; this can be used to create instructor accounts. It can also be used to delete or suspend other accounts based on activity status.Â  The Instructor Account allows teachers to create student accounts and enroll the same. This account can be used also to create, activate, edit, delete exams and monitor students' performances. The Student Account is for the officially enrolled students where they can take exams and view scores even from previous examinations.This software allows instructors to keep track of students' performances from all exams since the results will be stored in a database linked to an online system.Â  While taking the online exam, students can choose the number of exam questions that will be displayed on the screen at a given time.A student can take the exam only on the specified date and time set by the instructor. Ideally, a particular exam should be taken only once. In cases of retakes due to valid reasons and special exam considerations, the instructor is given the option to administer the previously activated exam, edit or create a new set of questions.One limitation though, this online system is not to be used to compute for the class performance for the final grade since this requires other components such as seat works, graded recitations, laboratory activities, etc. This only computes and shows the scores from previous exams and the average.
IMPLEMENTATION OF SVM USING SEQUENTIAL MINIMAL OPTIMIZATION FOR POWER TRANSFORMER FAULT ANALYSIS USING DGA
Authors: Gomathy V. , Sumathi Dr.S.
Published: May 2018

Reliable operations of power transformers are necessary for effective transmission and distribution of power supply. During normal functions of the power transformer, distinct types of faults occurs due to insulation failure, oil aging products, overheating of windings, etc., affect the continuity of power supply thus leading to serious economic losses. To avoid interruptions in the power supply, various software fault diagnosis approaches are developed to detect faults in the power transformer and eliminate the impacts. SVM and SVM-SMO are the software fault diagnostic techniques developed in this paper for the continuous monitoring and analysis of faults in the power transformer. The SVM algorithm is faster, conceptually simple and easy to implement with better scaling properties for few training samples. The performances of SVM for large training samples are complex, subtle and difficult to implement. In order to obtain better fault diagnosis of large training data, SVM is optimized with SMO technique to achieve high interpretation accuracy in fault analysis of power transformer. The proposed methods use Dissolved Gas-in-oil Analysis (DGA) data set obtained from 500 KV main transformers of Pingguo Substation in South China Electric Power Company. DGA is an important tool for diagnosis and detection of incipient faults in the power transformers. The Gas Chromatograph (GC) is one of the traditional methods of DGA, utilized to choose the most appropriate gas signatures dissolved in transformer oil to detect types of faults in the transformer. The simulations are carried out in MATLAB software with an Intel core 3 processor with speed of 3 GHZ and 2 GB RAM PC. The results obtained by optimized SVM and SVM-SMO are compared with the existing SVM classification techniques. The test results indicate that the SVM-SMO approach significantly improve the classification accuracy and computational time for power transformer fault classification.
Offline Signature Verification System with Gaussian Mixture Models (GMM)
Authors: Jain Charu , Singh Priti , Rana Preeti
Published: May 2018

Gaussian Mixture Models (GMMs) has been proposed for off-line signature verification. The individual Gaussian components are shown to represent some global features such as skewness, kurtosis, etc. that characterize various aspects of a signature, and are effective for modeling its specificity. The learning phase involves the use of Gaussian Mixture Model (GMM) technique to build a reference model for each signature sample of a particular user. The verification phase uses three layers of statistical techniques. The first layer involves computation of GMM-based log-likelihood probability match score, Â second layer performs the mapping of this score into soft boundary ranges of acceptance or rejection through the use of z-score analysis and normalization function, thirdly, threshold is used to arrive at the final decision of accepting or rejecting a given signature sample. The focus of this work is on faster detection of authenticated signature as no vector analysis is done in GMM. From the experimental results, the new features proved to be more robust than other related features used in the earlier systems. The FAR (False Acceptance Rate) and FRR (False Rejection Rate) for the genuine samples is 0.15 and 0.19 respectively.
Computer Aided Diagnosis of Melanoma Skin Cancer using Clinical Photographic Images
Authors: Mabrouk Mai S. , Sheha Mariam , Sharawy Amr A.
Published: May 2018

Melanoma is considered as one of the most malignant, metastatic and dangerous form of skin cancer that may cause death. The curability and survival of this type of skin cancer depends directly on the diagnosis and removal of melanoma in its early stages. The accuracy of the clinical diagnosis of melanoma with the unaided eye is only about 60% depending only on the knowledge and experience that each doctor has accumulated. The need to the Computer-Aided Diagnosis system (CAD) is increased to be used as a non-invasive supporting tool for physicians as a second opinion to increase the accuracy of detection, as well contributing information about the essential optical characteristics for identifying them. The ultimate aim of this research is to design an automated low cost computer aided diagnosis system of melanoma skin cancer to increase system flexibility, availability. Also, investigate to what extent melanoma diagnosis can be impacted using clinical photographic images instead of using dermoscopic ones, regarding that both are applied upon the same automatic diagnosis system. Texture features was extracted from 140 pigmented skin lesion (PSL) based on Grey level Co-occurrence matrix (GLCM), effective features are selected by fisher score ranking and then classified using Artificial Neural Network (ANN), the whole system is processed through an interactive Graphical User Interface (GUI) to achieve simplicity. Results revealed the high performance of the proposed CAD system to discriminate melanoma from melanocytic skin tumors using texture analysis when applied on clinical photographic images with prediction accuracy of 100 % for the training phase and 91 % for the testing phase. Also, results indicated that using this type of images provides high prediction accuracy for melanoma diagnosis relevant to dermoscopic images considering that photographic clinical images are acquired using less expensive consumer which exhibit a certain degree of accuracy toward the edges of our field of view.
Performance Analysis of IEEE 802.15.4 Based Wireless Sensor Networks using LAR protocol for CBR and ZIGBEE Traffic Applications
Authors: P. Samundiswary , R Surender
Published: May 2018

IEEE 802.15.4 standard based wireless sensor networks (WSNs) emerges as the next generation wireless standard for low-rate wireless personal area networks. IEEE 802.15.4 standard offers low power, low data rate and short range networking for wireless battery powered devices. It has also started to demand much attention towards research. The performance of the network can be analysed by using different types of routing protocols. In this paper, the performance analysis of IEEE 802.15.4 based Wireless Sensor Networks is done by using Â Location Aided Routing (LAR) protocols for the traffic applications such as Constant Bit Rate (CBR) and Zigbee traffic application. The LAR protocol enables the routing of data between the source and destination by using directional flooding technique. The performance metrics such as throughput, delay, jitter and packets dropped of LAR for Â CBR and Zigbee traffic application is evaluated and analysed. The simulation is modelled by using QualNet.
Cascading Guided Search Cloud Service Search Engine
Authors: Arvaree Ms Thamilvaani , Atan Dr. Rodziah
Published: May 2018

Cloud computing is one contemporary technology in which the research community has recently embarked. This paradigm shifts the location of the infrastructure to the network to reduce the costs associated with the management of hardware and software resources. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. Organization adopts cloud computing services through service provider via Internet. In recent years, numbers of cloud service providers are increase.Â  However, there is no study that focuses on search engine and web portal for cloud computing for users who want to find cloud service. At the same time, â€œvendor lock inâ€ issues and the lack of common cloud standards delayed the interoperability across these providers. Thus, lead the cloud customer to face challenges and problems in selecting the right service provider who meets their needs. This research focus on meeting the user requeriment in cloud environment whereby, user requirements reflect to search query that entered by the end users and how these search queries are exactly matched with accurate cloud service. Therefore, end of the research cloud service search engine was developed as a proposed tool for meeting the user requirements.Â
Multipath Routing protocol: NCPR and QAMR
Authors: Garg Roopali , Kaur Guneet
Published: May 2018

Mobile ad hoc network is an assembly of mobile nodes with no centralized server. Due to mobility of nodes and decentralized network it is difficult to maintain the quality of service (QoS) in routing the packets from source to destination.Â  QoS can be defined in terms of various metrics like delay, bandwidth, packet loss, routing overhead, jitter. Routing can be unicast, multicast or multipath.Â  This paper presents the description about the QoS multipath routing algorithm.
The Value Of Human Resource Information Systems In Human Resource Management
Authors: Okinyi Oyoo Mark , Omieno Kelvin Kabeti , Margaret Kitone K.
Published: May 2018

In todayâ€™s organizations Human Resource Management has become one of the key resources of business organizations. The need to integrate Human Resource Management (HRM) with information systems has become a necessity as modern firms are realizing that their people and information resources are vital for their survival. This is the reason Human Resource Information Systems (HRIS) is now used extensively in all organizations irrespective of its size, tenure of establishment, complexities of operations etc. With the growing importance of human resource management and increasing size of the organizations, maintenance of employee related data and generating reports are the crucial aspects of any organization. Therefore more and more organizations are adopting computer based human resource management systems (HRMS) This paper is an attempt to highlight the value of information systems in Human Resource Management. The study is conducted through analysis of secondary data from books, journals and reviews.
Text Normalization for Telugu Text-to-Speech Synthesis
Authors: Sunitha Dr. K.V.N. , Devi P.Sunitha
Published: May 2018

Most areas related to language and speech technology, directly or indirectly, require handling of unrestricted text, and Text-to-speech systems directly need to work on real text. To build a natural sounding speech synthesis system, it is essential that the text processing component produce an appropriate sequence of phonemic units corresponding to an arbitrary input text. A novel approach is used, where the input text is tokenized, and classification is done based on token type. The token sense disambiguation is achieved by the semantic nature of the language and then the expansion rules are applied to get the normalized text. However, for Telugu language not much work is done on text normalization. In this paper we discuss our efforts for designing a rule based system to achieve text normalization in the context of building Telugu text-to-speech system.
Software Defect Prevention through Orthogonal Defect Classification (ODC)
Authors: Kumaresh Sakthi , Baskaran R
Published: May 2018

â€œQuality is never an accident; it is always the result of intelligent effortâ€ [10]. In the process of making quality software product, it is necessary to have effective defect prevention process, which will minimize the risk of making defects /errors in software deliverables. An ideal approach would involve effective software development process with an integrated defect prevention process. This paper presents a Defect Prevention Model in which Defect Prevention Process(DPP) is integrated into software development life cycle to reduce the defects at early stages itself, thereby reducing the defect arrival rate as the project progresses to the subsequent stages. Orthogonal Defect Classification (ODC) scheme involving defect trigger, defect type etc. are discussed in this work to illustrate how ODC can be used in the defect prevention process. ODC can be used to measure development progress with respect to product quality and identify process problems, which will help to come out with â€œBest Practicesâ€ to be followed to eradicate the defects in the subsequent projects.
A Fully Automated Method for Noisy cDNA Microarray Image Quantification
Authors: Fouad Islam A. , Mabrouk Mai S. , Sharawy Amr A.
Published: May 2018

DNA microarray is an innovative tool for gene studies in biomedical research, and its applications can vary from cancer diagnosis to human identification. Image processing is an important aspect of microarray experiments, the primary purpose of the image analysis step is to extract numerical foreground and background intensities for the red and green channels for each spot on the microarray. The background intensities are used to correct the foreground intensities for local variation on the array surface, resulting in corrected red and green intensities for each spot that can be considered as a primary data for subsequent analysis. Most techniques divide the overall microarray image processing into three steps: gridding, segmentation, and quantification. In this paper, aÂ Â  simple automated gridding technique is developed with a great effect on noisy microarray images. A segmentation technique based on â€˜edge-detectionâ€™ is applied to identify the spots and separate the foreground from the background is known as microarray image segmentation. Finally, a quantification technique is used to calculate the gene expression level from the intensity values of the red and green components of the image. Results revealed that the developed methods can deal with various kinds of noisy microarray images, with high Â griddingaccuracy of 92.2% for low quality images and 100% for high quality images resulting in better spot quantification to getÂ  more accurate gene expression values.Â
A Survey on SmartPhone Honeypot
Authors: Ahmed Dr.Hanaa Mohsin , Hassan Dr. Nidaa Flaih , A. Fahad Assmaa
Published: May 2018

Smartphones are becomingÂ Â  a dominant form of mobile computing in the world. The Smartphone, as a platform, blends a traditional general computing platform with a specialized mobile phone platform. The general computing tradition is historically open, allowing its owners to install whatever software they choose and to add or remove hardware as they please. Also they are a vault for large amount of personal information about banking, social network, and inter-personal communication. These capabilities and information value make it an attractive target to internet miscreants.This paper presents a survey on recent researches in Smartphone honeypot. Physical and virtual honeypots have been studied in details; however, there is only little work in the field of mobile related honeypot. The survey presents the challenges while setting up a smartphone honeypot, and summarizes the researches published in this area. We clarify the methods used to build their honeypot, and the results they obtained and their recommendations.
On the Theory of NP-Complete Problems
Authors: Listrovoy S.V.
Published: May 2018

It is shown that the theory of NP -Ñomplete problems can't be used for the analysis of optimizing tasks.
Study of Image steganography using LSB, DFT and DWT
Authors: Mazumder Juned Ahmed , Hemachandran K.
Published: May 2018

In this paper we have studied and implement the color image steganography using LSB, DFT and DWT. First we have studied the various literatures of LSB, DFT and DWT and then implemented one system in which we can do steganography using these techniques, after implementation we have evaluated the results using these techniques applying various image formats against different message size. For each of the cases we have calculated Â the MSE and PSNR and presented here in a tabulated form. Our main intention is to show how MSE and PSNR changes with respect to different image formats and different message sizes using these techniques. Besides the analysis of MSE and PSNR we have also analyzed the message insertion and message extraction time for all the cases.
INTELLIGENT COMPUTING METHODS FOR THE INTERPRETATION OF NEUROPSYCHIATRIC DISEASES BASED ON RBR-CBR-ANN INTEGRATION
Authors: Gangwar Mohit , Mishra R. B. , Yadav R. S.
Published: May 2018

Neuropsychiatry is an integrative and collaborative field that brings together brain and behavior, but its diagnosis is complex and controversial due to the conflicting, overlapping and confusing nature of the multitude of symptoms, hence the need to retain cases in a case base and reuse effective previous solutions for current cases. This paper proposes a method based on the integration of Rule based reasoning (RBR), Case based reasoning (CBR) and Artificial neural network (ANN) that utilizes solutions to previous cases in assisting neuropsychiatrist in the diagnosis of neuropsychiatric disease. The system represents five neuropsychiatric diseases with 38 symptoms grouped into six categories. Integrated method improves the computational and reasoning efficiency of the problem-solving strategy. We have hierarchically structured the five neuropsychiatric diseases in terms of their physio-psycho (muscular, cognitive and psychological), EEG and neuroimagin based parameters. Cumulative confidence factor (CCF) is computed at different node form lowest to highest level of hierarchal structure in the process of diagnosis of the neuropsychiatric diseases. The basic objective of this work is to develop integrated model of RBR-CBR and RBR-CBR-ANN in which RBR is used to hierarchically correlate the sign and symptom of the disease and also to compute CCF of the diseases. CBR is used for diagnosing the neuropsychiatric diseases for absolute and relative diagnosis. In relative diagnosis CBR is also used to find the relative importance of sign and symptoms of a disease to other disease and ANN is used for matching process in CBR.
Two Modified Hager and Zhang's Conjugate Gradient Algorithms For Solving Large-Scale Optimization Problems
Authors: Yuan Gonglin , Li Yong
Published: May 2018

At present, the conjugate gradient (CG) method of Hager and Zhang (Hager and Zhang, SIAM Journal on Optimization, 16(2005)) is regarded as one of the most effective CG methods for optimization problems. In order to further study the CG method, we develop the Hager and Zhang's CG method and present two modified CG formulas, where the given formulas possess the value information of not only the gradient but also the function. Moreover, the sufficient descent condition will be holden without any line search. The global convergence is established for nonconvex function under suitable conditions. Numerical results show that the proposed methods are competitive to the normal conjugate gradient method.