bluuebunny/crossref_metadata_2025 huggingface dataset:
SIMULATION OF ONE-SIDED SATURATION OF MAGNETIC SYSTEMS OF ELECTRIC POWER SYSTEMS POWER TRANSFORMERS
Authors: VAKHNINA Vera V. , KUVSHINOV Aleksey A. , KUZNETSOV Vladimir N. , SHAPOVALOV Vladimir A.
Published: October 2018

A technique for modeling the magnetic fi elds of power transformers in the environment of the software product FEMM 4.2 is developed taking into account the design scheme and real geometric dimensions of the magnetic system and tank, quasi-permanent current components in high-voltage windings, and the experimental magnetization characteristics of electrical and structural steel. Modeling of magnetic fi elds of magnetic systems of rod and armored rod structures is carried out on the example of serial power transformers TRDN- 63000/115 / 6.3 / 6.3 and TDTs-400000/242/20. The dependences of the mean values of induction in the central cross sections of the rods and side yokes on the quasi-constant currents are determined. It is shown that the saturation of the magnetic system of the rod structure begins with the outer rods at a multiplicity of quasi-constant current equal to 2.2 relative to the nominal phase current of the high-voltage winding. The saturation of the magnetic system of the armored rod structure begins with the lateral yokes at a multiplicity of the quasi-constant current equal to 2.63 with respect to the idle current rating.
OPTIMIZATION OF ELECTROTECHNICAL POWER CONSUMPTION OF GAS COOLING SYSTEM COMPLEX
Authors: DANILUSHKIN Alexander I. , DANILUSHKIN Ivan A.
Published: October 2018

The problem of the optimal load distribution between electric drives of fans in a multi-section gas cooling unit is considered based on the minimum energy expenditure for cooling. The optimization problem is solved on the basis of the obtained analytical model for the gas temperature at the outlet of the cooling unit. The model takes into account the mutual infl uence of the operating modes of all fans of the installation. A technique for solving the problem of optimal load sharing between electric drives of fans for a linearized process model is developed using the procedure of integer programming. The optimization technique takes into account the individual characteristics of the devices.
CALCULATION OF THE DRAINAGE SYSTEM OF LEAVING FLUE GASES FROM THE TURBINE THROUGH THE COOLING TOWER
Authors: KUDINOV Anatoly A. , DEMINA Yulia E.
Published: October 2018

The article presents result of a research a system of the venting of exhaust gases of the recovery boiler the gas turbine plant through the natural draft cooling tower in the environment. The use of this scheme allows the fl ue gases to lower the temperature of the circulating water at the outlet of the cooling tower to provide a deeper vacuum in the condenser steam turbine combined cycle power plant with simultaneous reduction of capital to build chimneys. As a result of the application of this scheme, an increase in the absolute electric effi ciency of turbines is achieved. As stated in Article method of calculating the removal of exhaust fl ue gas systems with a perforated distributor ring allows to determine the level of engineering design and volume requirements of these systems.
TECHNOLOGIES OF PROTECTION OF HIGHWAYS FROM ROCKFALLS
Authors: SHEINA Tatyana V. , AVDEEVA Elena A.
Published: October 2018

The technology of the device of certain anti-dump structures for the sections of mountain roads subject to collapses is considered. A comprehensive analysis of rockfall risk factors has been identifi ed and justifi ed in order to select the most eff ective protection system. The measures on passive protection (catching structures and devices, anti-galleries galleries, simple drapery systems) and active protection (restraining structures and drapery systems with additional reinforcement) have been analyzed. The materials used in advanced anti- dump systems are distinguished, they are characterized by increased strength, enhanced corrosion protection, relatively low weight, which makes it possible to use light technology.
AIR-RADIANT HEATING ON THE BASIS OF A TWO-FLOW HEAT GENERATOR WITH INFRARED EMITTERS
Authors: PANCHENKO Valery V.
Published: October 2018

A scheme of a radiant heating regenerative system on the basis of a two-fl ow heat generator, and system and form of heat-radiating air ducts is proposed. It is shown that the system of radiant heating is more effi cient as compared to the conventional convection system. Traditionally, the convective scheme of heating is used wherein radiators installed near the fl oor are used. Water serves as the working fl uid in the radiators. The proposed radiant heating regenerative system is based on the transfer of heat in the form of infrared electromagnetic radiation. An effi cient two-fl ow heat generator with infrared emitt ers has been developed, which gives off heat only from the radiating surface of heat exchangers. This system allows you to reduce investment, operating costs and improve the effi ciency of the heating system.
STUDY OF THE POSSIBILITY OF USING MICROWAVE RADIATION FOR THE TREATMENT OF LIQUID MUNICIPAL WASTE
Authors: KICHIGIN Viktor I. , ZEMLYANOVA Marina V. , VYALKOVA Elena A.
Published: October 2018

The article is devoted to the study of the infl uence of microwave electromagnetic radiation (UHF EMP) on the properties of sewage sludge. The possibility of using microwave radiation for their processing is shown. The results of experiments confi rming the positive eff ect of the process under study on the degree and speed of compaction of a mixture of precipitation and activated sludge, improvement of their moisture yield, an increase in the yield of heavy metal impurities in decanted water, a decrease in the specifi c resistance of fi ltration and capillary suction of the sediment, precipitation. A hypothesis is proposed for the eff ect of UHF EMP on wastewater sludge.
PROMOTING ART, MANUFACTURES AND COMMERCE IN ONE—THE SOCIETY'S ROLE IN THE DEVELOPMENT OF A BRITISH MARBLE INDUSTRY
Authors: WALKDEN GORDON
Published: October 2018

Amongst its promotions at the start of the nineteenth century, the Society for the Encouragement of Arts, Manufactures and Commerce included calls for British marbles. The calls were repeated annually for two decades but what initiated them was more than just an altruistic desire to promote indigenous sources of statuary and decorative stone. Supplies of both, especially statuary marble, greatly relied upon imports from France and Italy. At the time of the first calls these were jeopardised by the revolutionary and Napoleonic upheavals and other sources of stone became necessary, but the Society never cited political pressures as a driver behind their calls for British marbles. The term ‘marble’ was to be interpreted widely, and the response brought limestones, serpentines, granites and true marbles from across the British nations including much from southern Ireland. Two Gold Medals were awarded, one for a spectacular revelation of Devonshire marbles, and one for sheer guts and determination shown in bringing to market a fine marble from a remote part of Scotland. Within a decade of the Society's initiative there was a substantial renaissance in the use of decorative stone in Britain and much came from new indigenous sources. Although a good British white statuary marble never emerged, some spectacular coloured and textured British decorative stones became widely available and well used. Art, manufactures and commerce were the direct beneficiaries, but it is unlikely that the Society's initiative alone was responsible for this ‘marble renaissance’ of the mid-nineteenth Century.
Pediatric Nasolacrimal Duct Obstruction
Authors: Golan Shani ,   Department of Ophthalmology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY, US, Lelli Jr Gary J ,   Department of Ophthalmology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY, US
Published: October 2018

Nasolacrimal duct obstruction (NLDO) is common in the pediatric population and presents as persistent epiphora, recurrent conjunctivitis, crusting of the eyelids, and occasionally dacryocystits. It is typically congenital and occurs at the level of the valve of Hasner. Treatment options for pediatric NLDO include non-surgical and surgical procedures. Treatment may be carried out either in-office or in the operating room. In this review, we discuss the pathogenesis of pediatric NLDO and provide an update on current treatment options, including medical management with massage, which remains highly successful, and surgery, which may be warranted in children over the age of 3 years, those with anatomic variations and craniofacial anomalies, patients unresponsive to medical therapy and probing, and patients with acquired NLDO. In addition, we explore the benefits of new technologies and endoscopic approaches, including shorter operative time and no scarring, as well as the ability to perform bilateral procedures and simultaneously address any additional intranasal pathology.
Human Resource is being Trafficked by Luring in the World instead of Using as a Resource: An Empirical Study of Human Trafficking in Bangladesh
Authors: Rahman Md. Motiar
Published: October 2018

At present human resource is being trafficked by luring in the world instead of using as a resource. This heinous crime and social scar have become a global concern recently. The uneducated and innocent feeble people are illegally immigrated seeking a better future abroad but they are abused. Data have been collected from primary and secondary sources by questionnaire and interview method. The development of any country depends on the development of human resource. But today the traffickers consider human trafficking as a profitable industry. They target some illiterate workers and take them abroad by promising lucrative job as well as an attractive salary that dreams the workers standard life leading opportunity. But the workers are not given the promised job abroad. They are used as a slave, forced or bonded labor or commercial sexual exploitation. Even the workers often face isolation, sexual abuse, fear, rape that can be caused by death. But if this human resource is used properly instead of abuse, they will be a great resource for any country.
Структура потребительских расходов как фактор формирования индивидуального человеческого капитала
Authors: Сазонова Екатерина Олеговна , Моргунов Василий Петрович
Published: October 2018

Теория человеческого капитала получила значительное развитие в контексте развития постиндустриальной экономики. Большинство теорий человеческого капитала связаны с формирование особых профессиональных качеств и компетенций, применяемых в первую очередь в сфере производства. Но, нам кажется, что теория человеческого капитала может быть расширена. В условиях усиления связи между производством и потреблением, их взаимным проникновением, концепция человеческого капитала может быть применена для объяснения поведения потребителя. Связь между потреблением и формированием человеческого капитала включает несколько аспектов. В результате реализации человеческого потенциала растет благосостояние и улучшается структура потребления. С другой стороны, определенная структура потребления может способствовать накоплению человеческого капитала, укреплению здоровья и повышению образования. Потребительские расходы на специфические товары и услуги, способствующие становлению и накоплению человеческого капитала, могут рассматриваться как личные инвестиции в человеческий капитал. Развитие теории человеческого капитала обогащает наши знания о его формах, в частности исследование социального человеческого капитала, позволяет пролить свет на характер поведения сетевого потребителя.
Research on the Scientific Evolution of the Flavonoid Agathisflavone
Authors: De Amorim Vanessa Cristina Meira , Júnior Markley Silva Oliveira , Bastos Eduardo Muniz Santana , Da Silva Victor Diogenes Amaral , Costa Silvia Lima
Published: October 2018

Purpose: Flavonoids are a group of secondary metabolites of the polyphenols class present in several plant species. Among them, the biflavonoid agathisflavone is of interest since it bears several biological effects that include: antiviral, antitumoral, antiprotozoal and neurogenic actions. In this sense, this study aims to use the important tool of scientific prospecting to assess the level of research development concerning the flavonoid agathisflavone. Methods: The experimental design was carried out through strategic reach with keywords on the PubMed (National Center for Biotechnology Information - NCBI) and Science Direct platforms. The articles were compiled and exported to Microsoft Office Excel 2007, where they were analyzed, stored and distributed in charts organized as to different countries, year of publication of scientific articles and journals RESULTS: The prospective research resulted in the identification of 81 scientific productions, published in several journals, submitted by different countries, in several areas of medical domain and in different years of publication over the last 50 years (1965 - 2018). It was also possible to investigate the advances in the study of agathisflavone for the development of new therapeutics. Conclusion: Although agathisflavone has been known in the literature since at least 1969, only 23 of the eligible articles found evaluated its possible therapeutic effects. The demonstrated biological activities of agathisflavone range from antiprotozoal to neurogenesis and neuroprotection, however, the molecule needs to be better studied at the in vivo and human level.
Techniques for Component-Based Software Architecture Optimization
Authors: Ali Abdelaziz Adil , Nasir Wan
Published: October 2018

Although Component-Based System (CBS) increases the efficiency of development and reduces the need for maintenance, but even good quality components could fail to compose good product if the composition is not managed appropriately. In real world, such as industrial automation domain, this probability is unacceptable because additional measures, time, efforts, and costs are required to minimize its impacts. Many general optimization approaches have been proposed in literature to manage the composition of system at early stage of development. This paper investigates recent approach es used to optimize software architecture. The results of this study are important since it will be used to develop an efficient optimization framework to optimize software architecture in next step of our ongoing research.
Lightweight Solar Vehicle Impact Analysis Using ABAQUS/EXPLICIT
Authors: Passarella Rossi , Taha Zahari
Published: October 2018

This paper described the Abaqus/Explicit 6.7 simulation work performed to study the frontal crash impact condition for an in-house designed and produced lightweight solar vehicle main structural body. The structural body was fabricated from aluminum hollow pipes welded together. The analysis is needed to safeguard the safety of the vehicle driver. The dynamic response of the vehicle structure when subjected to frontal impact condition was simulated, according to NASA best practice for crash test methodology. The simulated speed used was based on the NHTSA standard. Comparison of the analysis with the standard Head Injury Criteria (HIC) and Chest Injury Criteria (CIC) revealed that the driver of the designed vehicle would not be risk because the acceleration resultant was found to be lower than 20 G.Â  The analysis also proved that structural component was able to protect the driver during any frontal collision incident. However, to ensure the safety of the driver, safety precautions such as the use of seatbelt and helmet as well as driving below the speed limit are recommended.DOI:Â 10.18495/comengapp.12.085096
A Survey of Hand Gesture Dialogue Modeling For Map Navigation
Authors: Pang Yee Yong , Ismail Nor Azman
Published: October 2018

Human trends to use hand gesture in communication. The development of ubiquitous computer causes the possibility of human to interact with computer natural and intuitive. In human-computer interaction, emerge of hand gesture interaction fusion with other input modality greatly increase the effectiveness in multimodal interaction performance. It is necessary to design a hand gesture dialogue based on the different situation because human have different behavior depend on the environment. In this paper, a brief description of hand gesture and related study is presented. The aim of this paper is to design an intuitive hand gesture dialogue for map navigation. Some discussion also included at the end of this paper.
Using Power-Law Degree Distribution to Accelerate PageRank
Authors: Jin Zhaoyan , Wu Quanyuan
Published: October 2018

The PageRank vector of a network is very important, for it can reflect the importance of a Web page in the World Wide Web, or of a people in a social network. However, with the growth of the World Wide Web and social networks, it needs more and more time to compute the PageRank vector of a network. In many real-world applications, the degree and PageRank distributions of these complex networks conform to the Power-Law distribution. This paper utilizes the degree distribution of a network to initialize its PageRank vector, and presents a Power-Law degree distribution accelerating algorithm of PageRank computation. Experiments on four real-world datasets show that the proposed algorithm converges more quickly than the original PageRank algorithm.
Robotics Current Issues and Trends
Authors: Nurmaini Siti
Published: October 2018

The ongoing research and development work in the field of robotics have resulted in so many new technological trends. There are revolution which are being achieved with the use of latest technology in robotics, giving birth to new possibilities for automating tasks and enriching human lives for better. One can easily witness the presence of robotics in every sphere of life from industrial robots, service robots to personal robots. It other words, robots have become a part of our world to meet new demands of a new society.DOI:Â 10.18495/comengapp.21.117120
An Immune Based Patient Anomaly Detection using RFID Technology
Authors: Rosa Sri Listia , Shamsuddin Siti Mariyam , Evizal Evizal
Published: October 2018

Detecting of anomalies patients data are important to gives early alert to hospital, in this paper will explore on anomalies patient data detecting and processing using artificial computer intelligent system. Artificial Immune System (AIS) is an intelligent computational technique refers to human immunology system and has been used in many areas such as computer system, pattern recognition, stock market trading, etc. In this case, real value negative selection algorithm (RNSA) of artificial immune system used for detecting anomalies patient body parameters such as temperature. Patient data from monitoring system or database classified into real valued, real negative selection algorithm results is real values deduction by RNSA distance, the algorithm used is minimum distance and the value of detector generated for the algorithm. The real valued compared with the distance of data, if the distance is less than a RNSA detector distance then data classified into abnormal. To develop real time detecting and monitoring system, Radio Frequency Identification (RFID) technology has been used in this system. Keywords: AIS, RNSA, RFID, AbnormalDOI:Â 10.18495/comengapp.21.121142
Proposed Developments of Blind Signature Scheme based on The Elliptic Curve Discrete Logarithm Problem
Authors: El Kinani E.H. , Amounas Fatima
Published: October 2018

In recent years, Elliptic Curve Cryptography (ECC) has attracted the attention of researchers due to its robust mathematical structure and highest security compared to other existing algorithm like RSA. Our main objective in this work was to provide a novel blind signature scheme based on ECC. The security of the proposed method results from the infeasibility to solve the discrete logarithm over an elliptic curve. In this paper we introduce a proposed to development the blind signature scheme with more complexity as compared to the existing schemes.Â Keyword: Cryptography, Blind Signature, Elliptic Curve, Blindness, Untraceability.DOI:Â 10.18495/comengapp.21.151160
Automatic Iranian Vehicle License Plate Recognition System Based on Support Vector Machine (SVM) Algorithms
Authors: Aghaie Mahdi , Shokri Fatemeh , Zade Tabari Meisam Yadolah
Published: October 2018

There are far more cars on the road now than there used to be. Therefore, Controlling and managing the huge volume of traffic is virtually impossible without the use of computer technology. This paper represents design and implement of an intelligent system for license plate recognition based on three main steps. This process includes the detection of license plate location, character segmentation and character recognition. In this study, we used Classifier svm to detect the characters. According to the results, the performance of the proposed system is better compared to similar algorithms such as neural network. It is worth mentioning that Recognition Approach is tested in various conditions and results are described. Â  Keyword- Vehicle license plate recognition, Morphology Operations, Histogram, The edge detection, Classifier SVMDOI:Â 10.18495/comengapp.21.161174
An Analysis of Adaptive Approach for Document Binarization
Authors: Malik Reza Firsandaya , - Saparudin , Septyliana Intan
Published: October 2018

Abstract Binarization is an initial step in document image analysis for differentiate text area from background. Determination of binarization technique is really important to retrieve all the text information especially from degraded document image. This paper explains about adaptive binarization using Gatosâ€™s method. Gatosâ€™s method is doing preprocessing, foreground estimation using Sauvolaâ€™s method, background estimation, upsampling, final thresholding and postprocessing. In this paper, Sauvolaâ€™s method is final thresholding from Wiener filter image result and source image, and count F-Measure from both of these binary image results. By using optimum constant value on k value, n local window, Ksw and Ksw1, Gatosâ€™s method can produced binary image better than Sauvolaâ€™s method based on F-Measure value. Sauvolaâ€™s method produces average value F=84,62%, Sauvolaâ€™s method with Wiener filter produces average value F=99.06% and Gatosâ€™s method produces average value F=99,43%. Keyword : Degraded Document Image, Adaptive Approcah for Binarization, Gatosâ€™sÂ  Method, Sauvolaâ€™s MethodDOI:Â 10.18495/comengapp.22.185194
An Immune Based Patient Anomaly Detection using RFID Technology
Authors: Rosa Sri Listia , Shamsuddin Siti Mariyam , Evizal Evizal
Published: October 2018

Online product reviews is considered as a major informative resource which is useful for both customers and manufacturers. The online reviews are unstructured-free-texts in natural language form. The task of manually scanning through huge volume of review is very tedious and time consuming. Therefore it is needed to automatically process the online reviews and provide the necessary information in a suitable form. In this paper, we dedicate our work to the task of classifying the reviews based on the opinion, i.e. positive or negative opinion. This paper mainly addresses using ensemble approach of Support Vector Machine (SVM) for opinion mining. Ensemble classifier was examined for feature based product review dataset for three different products. We showed that proposed ensemble of Support Vector Machine is superior to individual baseline approach for opinion mining in terms of error rate and Receiver operating characteristics Curve.

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Key words: Opinion, Classification, Machine Learning.
Proposed Developements of Blind Signature Scheme Based on ECC
Authors: Amounas F. , El Kinani E. H.
Published: October 2018

Detecting and gaining clues from the crime scene plays a major role in the process of investigation. Now a days with increase of cybercrime and fraud on the internet, digital forensics gaining importance. It needs to collect information the events happened at crime place. This paper deals with event reconstruction process which is useful for digital crime scene. The process of reconstruction is based on crime event and event characteristics. It also furnishes crime rate guess using some semi-formal techniques.

Keyword: Digital Investigation, Digital Forensics, Events, Attack Trees, Reconstruction
On Constructing Static Evaluation Function using Temporal Difference Learning
Authors: Ping Man Samuel Choi
Published: October 2018

An Outlier is a data point which is significantly different from the remaining data points. Outlier is also referred as discordant, deviants and abnormalities. Outliers may have a particular interest, such as credit card fraud detection, where outliers indicate fraudulent activity. Thus, outlier detection analysis is an interesting data mining task, referred to as outlier analysis. Detecting outliers efficiently from dataset is an important task in many fields like Credit card Fraud, Medicine, Law enforcement, Earth Sciences etc. Many methods are available to identify outliers in numerical dataset. But there exist limited number of methods are available for categorical and mixed attribute datasets. In the proposed work, a novel outlier detection method is proposed. This proposed method finds anomalies based on each recordâ€™s â€œmulti attribute outlier factor through correlationâ€ score and it has great intuitive appeal. This algorithm utilizes the frequency of each value in categorical part of the dataset and correlation factor of each record with mean record of the entire dataset. This proposed method used Attribute Value Frequency score (AVF score) concept for categorical part. Results of the proposed method are compared with existing methods. The Bank data (Mixed) is used for experiments in this paper which is taken from UCI machine learning repository.

Keyword: Outlier, Mixed Attribute Datasets, Attribute Value Frequency Score
Design Concept of Convexity Defect Method on Hand Gestures as Password Door Lock
Authors: Passarella Rossi , Fadli Muhammad , Sutarno Sutarno
Published: October 2018

In this paper we purpose a several steps to implement security for locking door by using hand gestures as password. The methods considered as preprocessing image, skin detection and Convexity Defection. The main components of the system are Camera, Personal Computer (PC), Microcontroller and Motor (Lock). Bluetooth communication are applied to communicate between PC and microcontroller to open and lock door used commands character such as â€œOâ€ and â€œCâ€. The results of this system show that the hand gestures can be measured, identified and quantified consistently.
Human Perception Based Color Image Segmentation
Authors: Gargote Neeta Pradeep , Devaraj Savitha , Shahapure Shravani
Published: October 2018

Color image segmentation is probably the most important task in image analysis and understanding. A novel Human Perception Based Color Image Segmentation System is presented in this paper. This system uses a neural network architecture. The neurons here uses a multisigmoid activation function. The multisigmoid activation function is the key for segmentation. The number of steps ie. thresholds in the multisigmoid function are dependent on the number of clusters in the image. The threshold values for detecting the clusters and their labels are found automatically from the first order derivative of histograms of saturation and intensity in the HSI color space. Here the main use of neural network is to detect the number of objects automatically from an image. It labels the objects with their mean colors. The algorithm is found to be reliable and works satisfactorily on different kinds of color images.
Improvement and Comparison of Mean Shift Tracker using Convex Kernel Function and Motion Information
Authors: Chaudhari S. B. , Warhade K. K. , Wadhai V. M. , Choudhari N. N.
Published: October 2018

Any tracking algorithm must be able to detect interested moving objects in its field of view and then track it from frame to frame. The tracking algorithms based on mean shift are robust and efficient. But they have limitations like inaccuracy of target localization, object being tracked must not pass by another object with similar features i.e. occlusion and fast object motion. This paper proposes and compares an improved adaptive mean shift algorithm and adaptive mean shift using a convex kernel function through motion information. Experimental results show that both methods track the object without tracking errors. Adaptive method gives less computation cost and proper target localization and Mean shift using convex kernel function shows good results for the tracking challenges like partial occlusion and fast object motion faced by basic Mean shift algorithm.
Power Line Communication Performance Channel Characteristics
Authors: Duche Dipashree Navanath , Gogate Vidya
Published: October 2018

Power lines form the medium of transmission in PLC systems. The original purpose of these lines is the transportation of electric signals at 50 or 60 Hz .This paper proposes a new channel modeling method for power line communications networks based on the multipath profile in the time domain. The new channel model is developed to be applied in a range of Power line Communications (PLC) research topics such as impulse noise modeling, deployment and coverage studies, and communications theory analysis. The statistical multipath parameters such as path arrival time, magnitude and interval for each category are analyzed to build the model. Each generated channel based on the proposed Power line communication that a performance channel characteristic represents a different realization of a PLC network
A Hybrid Approach for Scheduling based on Multi-criteria Decision Method in Data Grid
Authors: Mansouri Najme
Published: October 2018

Grid computing environments have emerged following the demand of scientists to have a very high computing power and storage capacity. One among the challenges imposed in the use of these environments is the performance problem. To improve performance, scheduling technique is used. Most existing scheduling strategies in Grids only focus on one kind of Grid jobs which can be data-intensive or computation-intensive. However, only considering one kind of jobs in scheduling does not result in suitable scheduling in the viewpoint of all system, and sometimes causes wasting of resources on the other side. To address the challenge of simultaneously considering both kinds of jobs, a new Hybrid Job Scheduling (HJS) strategy is proposed in this paper. At one hand, HJS algorithm considers both data and computational resource availability of the network, and on the other hand, considering the corresponding requirements of each job, it determines a value called W to the job. Using the W value, the importance of two aspects (being data or computation intensive) for each job is determined, and then the job is assigned to the available resources. The simulation results with OptorSim show that HJS outperforms comparing to the existing algorithms mentioned in literature as number of jobs increases.
Classification of Smart Card Operating Systems
Authors: Asgari Reza , Atani Reza Ebrahimi
Published: October 2018

Today, smart cards are widely used in variety of applications of human life.The nature of these cards depends on theirs operating system, in other words the operating system determines that card can be used in what field. Hardware development on the one hand and increasing use of smart cards on the other, have led to that the operating systems have progressed dramatically.Moving from special-purpose operating systems with single application into multi-purpose operating systems with open architecture, is proof of claim.Increase the number of operating systems and variety of their applications, caused that the need to categorize and classify operating systems be felt more than ever.Smart card operating systems can be categorized based on different parameters such as file management, applications management, and historical generations. In this paper we will discussion about smart card operating systems and their classification based on these parameters.
NFC based inventory control system for secure and efficient communication
Authors: Iqbal Razi , Ahmad Awais , Gilani Asfandyar
Published: October 2018

This paper brings up this idea of using Near Field Communication (NFC) for inventory control system instead of using traditional barcodes. NFC because of its high security, ease of use and efficiency can be very suitable for systems like inventory control. In traditional inventory control systems, each product has a barcode pasted on it, which is vulnerable to attacks as barcodes are open and have no security. Furthermore, barcodes are prone to damages and can be unreliable when pasted on different types of products e.g. hot and frozen products, circular shaped products and irregular shaped products like clothes etc. NFC on the other hand is very efficient, secure and reliable when it comes to short-range wireless communication. In this paper we will present our prototype for the inventory control system of an electronic store in which each product has a passive NFC tag pasted to it. When a customer buys a product the receipt of the product is generated using NFC between the NFC passive tag on the product and NFC enabled device (e.g. smart phone or reader) at the cash counter.
Words Stemming Based on Structural and Semantic Similarity
Authors: Dianati Mohammad Hassan , Sadreddini Mohammad Hadi , Rasekh Amir Hossein , Fakhrahmad Seyed Mostafa , Taghi-Zadeh Hossein
Published: October 2018

Words Â stemming Â is Â one Â of Â the Â important Â issues Â in Â the field Â of Â natural Â languageÂ processing Â and Â information retrieval. Â There Â are Â different Â methods Â for stemmingÂ which are mostly language-dependent. Therefore, these Â stemmers are onlyÂ applicable Â to Â particular Â languages. Â Because Â of the importance Â of Â this issue, Â in Â thisÂ paper, the proposed method for stemming is aimed to be language-independent. InÂ the Â proposed Â stemmer, Â a Â bilingual Â dictionary Â is Â used and Â all Â of Â the Â words Â in Â theÂ dictionary are firstly clustered. The wordsâ€™ clustering is based on their structural andÂ semantic similarity. Finally, finding the stem of new coming words is performed byÂ making use of the previously formatted clusters. To evaluate the proposed scheme,Â words Â stemming is Â done on both Â Persian Â and Â English Â languages. Â The encouragingÂ results Â indicate Â the Â good Â performance Â of Â the proposed Â method Â compared Â with Â itsÂ counterparts.
Cost Modeling and Risk and Benefit Modeling Approach as a Tools For Decision Making in Adoption Cloud Computing as IT Strategic Business
Authors: Putra Rian Rahmanda , Kinasih Wanda , Sensuse Dana Indra
Published: October 2018

Cloud computing is an innovation that allows the use of IT as a utility based on-demand. Since cloud computing is a new technology, its led to a variety of risks that required an assessment model to assess the organization's readiness to adopt cloud computing. Moreover, by using cloud computing services means organizations or outsourcing involves a third party. Before adopting cloud computing technology, organizations need to consider some of the effects that arise as a result of cloud computing, namely in terms of costs, risks and benefits. To assist organizations to consider the migration of existing IT systems to the cloud, it can be used the cost approach valuation models and risk and benefit. This paper discusses two models of cost-based assessment of risk and benefit modeling and modeling that can be used as a tool to assist organizations in making decisions related to the migration of existing IT systems to the cloud.

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A new DWT-SVD based robust watermarking scheme for real property rights
Authors: Babakalak Sedigeh Razavi , Balafar Mohammad Ali , Farzan Ali
Published: October 2018

In this paper, a new robust digital image watermarking algorithm which was based on singular value decomposition (SVD) and discrete wavelet transform (DWT) was proposed and simulated for protecting real property rights. A gray scale logo image, rather than a randomly generated Gaussian noise type watermark, was used as a watermark. Its embedding algorithm hid a watermark LL sub-band blocks in the lowâ€“low (LL) and high-high (HH) sub-bands of a target non-overlapping block of the host image by modifying singular values on SVD version of these blocks. A semi-blind watermark extraction was designed to estimate the original coefficients.

Experimental results showed that the proposed scheme made significant improvements in terms of both transparency and robustness and was superior to the existing methods which were considered in this paper.
Predicting Academic Performance with Applying Data Mining Techniques (Generalizing the results of two Different Case Studies)
Authors: Oskouei Rozita Jamili , Askari Mohsen
Published: October 2018

Several research works are attempted to predict students academic performance andÂ assess Â the Â evaluating students knowledge Â or Â detecting Â studentsâ€™ Â weakness andÂ probability of failure in final semester examinations. However, several factors affectÂ the performance of students in different countries or even in different states of oneÂ country. Therefore, understanding these factors and analyzing the effects of each oneÂ of those factors in each country, is necessary for improving instructorsâ€™ decisions inÂ selecting Â  the best teaching method for helping weak students or Â  increasingÂ performance Â of Â other Â students. This study is motivated Â to Â study Â the Â studentsâ€™Â academic performance in high Â school Â and Â bachelor Â degree Â studies Â in Â Iran andÂ comparing these analysis results with the similar studyâ€™s results in India.
A New Method for Intelligent Message Network Management in Ubiquitous Sensor Networks
Authors: Karimi Maryam , Javidan Reza , Keshtgari Manijeh
Published: October 2018

Ubiquitous Sensor Network (USN) computing is a useful technology forautonomic integrating in different environments which can be available anywhere.Managing USN plays an important role on the availability of nodes and paths. Inorder to manage nodes there is a cyclic route starts from manager, passing nodes,and come back to manager as feedback. In this paper, a new, self-optimizing methodpresented for finding this cyclic path by combining epsilon greedy and geneticalgorithm and then it is compared with other well-known methods in terms of cost ofthe route they find and the power consumption. The results show that the route thatis found by our new method costs at least 53% less than other methods. However insome cases, it uses 32% more energy for finding the route which can be compensatein traversing the shorter route. The overall simulation results in prototype data showthe effectiveness of the proposed method.
An Improved Multi-Cycle Deadlock Detection and Resolution Algorithm for Distributed Systems
Authors: Askari Mohsen , Oskouei Rozita Jamili
Published: October 2018

Distributed systems exhibit a high degree of resource and data sharing creating aÂ state in which deadlocks might make their appearance. Since deadlock detection andÂ resolution Â is one of the important concerns in distributed systems which lead toÂ minimizing available resources, therefore instigating Â  the Â system Â throughputÂ decrease. Â Our Â proposed algorithm detects and resolves Â the Â multi-cycle Â deadlocks,Â whether the initiator is involved in the deadlock cycle directly or indirectly. Also theÂ chance Â of Â phantom Â deadlock Â detection is minimized. This Â algorithm Â not Â only Â canÂ manage the simultaneous execution of it but also detects the multi-cycle deadlocksÂ in Â the Â distributed Â systems. Our Â algorithm introduces a modified probe and victimÂ message Â structure. Moreover, Â no Â extra Â storage Â required Â to Â store Â prob message Â inÂ each node which is known as memory overhead in the distributed systems.
Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks
Authors: Karimi Nazli Bagherzadeh , Razavi Seyed Naser
Published: October 2018

In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications.
An imperialist competitive algorithm for the winner determination problem in combinatorial auction
Authors: Mostafavi Reza , Razavi Seyed Naser , Balafar Mohammad Ali
Published: October 2018

Winner Determination problem (WDP) in combinatorial auction is an NP-complete problem. The NP-complete problems are often solved by using heuristic methods and approximation algorithms. This paper presents an imperialist competitive algorithm (ICA) for solving winner determination problem. Combinatorial auction (CA) is an auction that auctioneer considers many goods for sale and the bidder bids on the bundle of items. In this type of auction, the goal is finding winning bids that maximize the auctioneerâ€™s income under the constraint that each item can be allocated to at most one bidder. To demonstrate, the postulated algorithm is applied over various benchmark problems. The ICA offers competitive results and finds good-quality solution in compare to genetic algorithm (GA), Memetic algorithm (MA), Nash equilibrium search approach (NESA) and Tabu search.
Learning from Imbalanced Multi-label Data Sets by Using Ensemble Strategies
Authors: Javidi Mohammad Masoud , Shamsezat Fatemeh
Published: October 2018

Multi-label classification is an extension of conventional classification in which a single instance can be associated with multiple labels. Problems of this type are ubiquitous in everyday life. Such as, a movie can be categorized as action, crime, and thriller. Most algorithms on multi-label classification learning are designed for balanced data and donâ€™t work well on imbalanced data. On the other hand, in real applications, most datasets are imbalanced. Therefore, we focused to improve multi-label classification performance on imbalanced datasets. In this paper, a state-of-the-art multi-label classification algorithm, which called IBLR_ML, is employed. This algorithm is produced from combination of k-nearest neighbor and logistic regression algorithms. Logistic regression part of this algorithm is combined with two ensemble learning algorithms, Bagging and Boosting. My approach is called IB-ELR. In this paper, for the first time, the ensemble bagging method whit stable learning as the base learner and imbalanced data sets as the training data is examined. Finally, to evaluate the proposed methods; they are implemented in JAVA language. Experimental results show the effectiveness of proposed methods.

Keywords: Multi-label classification, Imbalanced data set, Ensemble learning, Stable algorithm, Logistic regression, Bagging, Boosting
Network Attacks Detection by Hierarchical Neural Network
Authors: Javidi Mohammad Masoud , Nattaj Mohammad Hassan
Published: October 2018

Intrusion detection is an emerging area of research in the computer security and net-works with the growing usage of internet in everyday life. Most intrusion detection systems (IDSs) mostly use a single classifier algorithm to classify the network traffic data as normal behavior or anomalous. However, these single classifier systems fail to provide the best possible attack detection rate with low false alarm rate. In this paper,we propose to use a hybrid intelligent approach using a combination of classifiers in order to make the decision intelligently, so that the overall performance of the resul-tant model is enhanced. The general procedure in this is to follow the supervised or un-supervised data filtering with classifier or cluster first on the whole training dataset and then the output are applied to another classifier to classify the data. In this re- search, we applied Neural Network with Supervised and Unsupervised Learning in order to implement the intrusion detection system. Moreover, in this project, we used the method of Parallelization with real time application of the system processors to detect the systems intrusions.Using this method enhanced the speed of the intrusion detection. In order to train and test the neural network, NSLKDD database was used. Creating some different intrusion detection systems, each of which considered as a single agent, we precisely proceeded with the signature-based intrusion detection of the network.In the proposed design, the attacks have been classified into 4 groups and each group is detected by an Agent equipped with intrusion detection system (IDS).These agents act independently and report the intrusion or non-intrusion in the system; the results achieved by the agents will be studied in the Final Analyst and at last the analyst reports that whether there has been an intrusion in the system or not.

Keywords:

Intrusion Detection, Multi-layer Perceptron, False Positives, Signature- based intrusion detection, Decision tree, Nave Bayes Classifier
Proposing a novel method for clock synchronization by Reducing the Number of Synchronization Messages and Eliminating Non-Deterministic Errors in Wireless Sensor Network
Authors: Kazeminezhad Seyed Kazem , Babaie Shahram , Shiri Amir
Published: October 2018

Wireless sensor networks (WSNs) of spatially distributed autonomous sensors are used to monitor physical or environmental conditions such as temperature, sound, pressure, etc. They are also used to cooperatively pass the collected data through the network to a main location. Due to the application of wireless sensor networks as a monitoring device in the real world, the physical time of the occurrence of events is important. Since WSNs have particular constraints and limitations, synchronizing the physical times for these networks is considered to be a complex task. Although many algorithms have been proposed for synchronizing time in the network, there are two main error factors in all the proposed algorithms. The first factor is the clock drift which might be caused by the influence of different environmental factors such as temperature, ambient temperature, humidity, it might be generated on crystal oscillator which is inevitable The second error factor is indeterminacy which is attributed to the existence of non-deterministic delays in sending and receiving messages between sensor nodes. These two factors together reduce the precision of synchronization algorithms. In this paper, the researchers proposed a new approach for dealing with the above-mentioned two problems and achieving better synchronization. The proposed approach is a combination of flooding time synchronization protocol (FTSP) and reference broadcast synchronization (RBS).This approach is intended to increase synchronization accuracy and network lifetime by reducing the number of synchronization messages sent between nodes and eliminating the most of non-deterministic errors in sending messages. The results of simulations conducted in the study indicated that the proposed approach is significantly more efficient than the FTSP and RBS methods in terms of parameters such as accurate synchronization, amount of sent packets and power consumption.