bluuebunny/crossref_metadata_2025 huggingface dataset:
Bio-Compatible Processing of LENSTM DepositedCo-Cr-W alloy for Medical Applications
Authors: Suresh Ganzi , L Narayana K , Kedar Mallik M
Published: April 2019

Developing a Medicinal implants or devices is a challenging task for the researchers, right from the selection of materials, design, bio-compatibility and implantation to the host tissue. At every stage it requires proper care in processing of medical implants. In recent years the demand for medical implants had grown rapidly due to the awareness in the society. Major share of implants is used by younger people as they are active in sports, motor vehicle accidents leads to facture. Even older people also preferring to implants for ease of living. The commonly used implants are, prosthetic joints, knee replacement, dental, maxillofacial reconstructions etc.There is huge demand for the medical implants in coming years, presently a few bio-materials available for implant devices such as Ti-alloys, Stainless steel and Co-Cr-Mo alloys. There a scope to the researchers to develop a new alloy that are bio-compatible in nature and bring down the cost of the implant procedure to the needed patients. In this context additive manufacturing (AM) is an advanced manufacturing technology emerging as prominent technique in medical fields. Laser Engineered Net ShapingTM (LENS) is one such metal additive technique which provides fabrication of parts with the help of laser power, melts the powder alloy completely and builds parts layer by layer directly from the CAD model.In the present study, samples are fabricated from LENS process and carried the In-Vitro and In -Vivo bio-compatible tests as cytotoxicity and sub chronic toxicity to verify the toxicants release and their sustainability as the medical implants by the LENS deposited Co-Cr-W alloy samples. From the studies it is observed that the alloy samples show acceptable result. MTT assay demonstrate that cell viability is better in Osteoblast cells compared to the Fibroblast cells. Osteoblast cells show slightly more viable to the cell treatment on the samples during the experimental period. Sub chronic toxicity conclude that LENS deposited Co-Cr-W alloy is not toxic in all the rats studied herein and did not produce any toxic signs or evident symptoms. LENS deposited Co-Cr-W alloy did not cause any lethality or produce any relative body organs weight and haematological studies didn’t show adverse effects.
On the Issue of Neural Modeling of Some Dynamic Parameters of Earthquake
Authors: P. Haritonova L
Published: April 2019

The author has attempted to refine the methods for modeling seismic effects. It is shown that applying the neural modeling and Artificial Neural Networks (ANN) are very prospective for analyzing such dynamic parameter earthquake foci as the moment magnitude. The further two input signals have been utilized: the power mode as well as the quantity of quakes. The author performed  the  analysis  of   regression for the predicted results and the target outputs. The article presents the equations of the regression (empirical dependences) for the outputs and target as well as the correlation factors for learning, assessment, checking, and the overall for the newly developed structure ANN for the moment magnitude. The use of the outcome obtained in this paper for the seismic designing and constructing structures and buildings will provide the conservation from   possible consequences of earthquakes, reduce negative consequences for industry, the economy as a whole and human life.
Comparison of Normal and Abnormal Conditions in ECG Using RR Variablity and Spectral Density
Authors: R. Thamizhvani T , Elsa Joseph Josline , Babu Bincy , Rithikka U , Rohini D , Josephin Arockia Dhivya A
Published: April 2019

Abnormality of the heart is monitored by Electrocardiograph (ECG). The ECG waveform is formed of PQRS pattern. Differentiation of the abnormalities based on the ECG signal is simple algorithm for diagnosis. ECG data of normal, atrial fibrillation and congestive heart failure is obtained from a authorized database. R peak from the QRS complex is detected using Pan-Tompkins algorithm for analysis. Mean RR and heart rate variability parameters are extracted from the QRS complex detected. With these results, the difference in the three ECG signals can be determined. For further detailed comparison, frequency component variation is analysed using power spectral density. Based on density spectrum, the differentiation of normal and abnormal ECG signals can be determined.
IOT based e – health care system
Authors: Chandrasekaran R , Uzma Farheen Syed , J.Hemalatha R , Babu Bincy , Arockiya Dhivya Josephin , R Thamizhvani T
Published: April 2019

One of the most important technological evolutions of our time is CLOUD COMPUTING, which describes the web computing power to store and process the information. The evolution and advancements are swiftly increasing in remote monitoring and Telemedicine. This paper aims at transmitting the physiological parameters of the subject to the private cloud called Thing Speak, an IOT based Sensor monitoring system. The physiological parameters are sent to the cloud via ESP8266 (IOT device). The cloud computing helps the physician to be connected with the patient’s data and it is helpful in monitoring the patients at any time through internet.
Statistical analysis of optical coherent tomography image by segmentation methods using euclidean distant model
Authors: J. Hemalatha R , G Mohandass , Krishnan G Hari
Published: April 2019

Optical Coherence Tomography (OCT) is a diagnostic measure of the images in retinal layers. The measure of retinal layers is done by image segmentation algorithm. In this work, algorithm of different threshold based segmentation techniques is computed in OCT image. Using the resultant image, comparison is done between the segmentation methods by statistical parameters such as noise factor of the signal peak, Normalized Absolute Error (NAE) and Average Difference (AD). Statistical analysis values are evaluated by multidimensional scaling (MDS) methods. By applying clustering methods in the multidimensional data, the Euclidean Distance model gives the relation distant between the algorithms. By this result, similarity or dissimilarity of segmentation methods was categorized.
Design & Simulation of Flexible Control For 3-phase Grid Connected Solar PV System
Authors: Srinivasan R. , R.Balamurugan C. , Shanmugasundaram N.
Published: April 2019

A non-linear control progression for 3-stage (phase) lattice (grid) associated of PV generator is proposed here. This system is designed with PV arrays; grid filter; a voltage source inverter and a stimulating lattice or network. The regulator purposes are classified into three sections: i) making sure that the Most power point tracking (MPPT) are having photovoltaic boards, ii) assuring  for power or control factor entity or unit in the grid plane iii) ensuring large-scale asymptotic constancy of the closed loop system. Lyapunov modelling approach is used by the controller and carried out by considering nonlinear model of the integral method. It is formally shown that the projected system controller congregates the scope of the objectives using a hypothetical constancy with stability analysis as well as simulation results.
Predicting customer churn using targeted proactive retention
Authors: Mishachandar B , Anil Kumar Kakelli
Published: April 2019

With the advent of innovative technologies and fierce competition, the choices for customers to choose from have increased tremendously in number. Especially in the case of a telecommunication industry, where deregulation is at its peak. Every year a new company springs up offering fitter options for its customers. This has turned the concentration of the business doers on churn prediction and business management models to sustain their places. Businesses approach churn in two ways, one is through targeted customer retention and through cause identification strategy. The literature of this paper provides a comprehensible understanding of the so far employed techniques in predicting customer churn. From that, it is quite evident that less attention has been given to the accuracy and the intuitiveness of churn models developed. Therefore, a novel approach of combining the models of Machine Learning and Big Data Analytics tools was proposed to deal churn prediction effectively. The purpose of this proposed work is to apply a novel retention technique called the targeted proactive retention to predict customer churning behavior in advance and help in their retention. This proposed work will help telecom companies to comprehend the risk associated with customer churn by predicting the possibility and the time of occurrence.
Enhancement of k-anonymity algorithm for privacy preservation in social media
Authors: Sharma Aanchal , Pathak Sudhir
Published: April 2019

In recent times, more and more social data is transmitted in different ways. Protecting the privacy of social network data has turn out to be an essential issue. Hypothetically, it is assumed that the attacker utilizes the similar information used by the genuine user. With the knowledge obtained from the users of social networks, attackers can easily attack the privacy of several victims. Thus, assuming the attacks or noise node with the similar environment information does not resemble the personalized privacy necessities, meanwhile, it loses the possibility to attain better utility by taking benefit of differences of users’ privacy necessities. The traditional research on privacy-protected data publishing can only deal with relational data and even cannot applied to the data of social networking. In this research work, K-anonymity is used for providing the security of the sensitive information from the attacker in the social network. K-anonymity provides security from attacker by making the graph and developing nodes degree. The clusters are made by grouping the similar degree into one group and the process is repeated until the noisy node is identified. For measuring the efficiency the parameters named as Average Path Length (APL) and information loss are measured. A reduction of 0.43% of the information loss is obtained.
Sentimental analysis using recurrent neural network
Authors: Thomas Merin , C.A Latha
Published: April 2019

Sentiment analysis has been an important topic of discussion from two decades since Lee published his first paper on the sentimental analysis in 2002. Apart from the sentimental analysis in English, it has spread its wing to other natural languages whose significance is very important in a multi linguistic country like India. The traditional approaches in machine learning have paved better accuracy for the Analysis. Deep Learning approaches have gained its momentum in recent years in sentimental analysis. Deep learning mimics the human learning so expectations are to meet higher levels of accuracy. In this paper we have implemented sentimental analysis of tweets in South Indian language Malayalam. The model used is Recurrent Neural Networks Long Short-Term Memory, a deep learning technique to predict the sentiments analysis. Achieved accuracy was found increasing with quality and depth of the datasets.
Improved LEACH protocol using cache nodes for wireless sensor network
Authors: Joshi Kamini , Kang Sandeep Singh
Published: April 2019

The wireless sensor network is the decentralized type of network which can sense information and pass it to base station. The energy consumption is the major issue of WSN due to small of sensor nodes and far deployment of the network. The clustering is the efficient approach to increase lifetime of the sensor network. In the approach of clustering cluster head are selected for the data aggregation. The fuzzy logic rules are derived based on node energy, distance to base station for the cluster head selection, which increase lifetime of sensor nodes in the existing system. In this research work, cache nodes are deployed in the network which reduce energy consumption of WSN. In the proposed approach cluster head send data to cache nodes and it will forward data to base station. The simulation is performed in MATLAB and proposed technique performs well in terms of number of packets transmitted, number of dead nodes, network lifetime, throughput and remaining energy.
Design of testing framework for code smell detection (OOPS) using BFO algorithm
Authors: Sharma Pratiksha , Arshpreet Kaur Er.
Published: April 2019

Detection of bad smells refers to any indication in the program code of a execution that perhaps designate a issue, maintain the software and software evolution. Code Smell detection is a main challenging for software developers and their informal classification direct to the designing of various smell detection methods and software tools. It appraises 4 code smell detection tool in software like as a in Fusion, JDeodorant, PMD and Jspirit. In this research proposes a method for detection the bad code smells in software is called as code smell. Bad smell detection in software, OOSMs are used to identify the Source Code whereby Plug-in were implemented for code detection in which position of program initial code the bad smell appeared so that software refactoring can then acquire position. Classified the code smell, as a type of codes: long method, PIH, LPL, LC, SS and GOD class etc. Detection of the code smell and as a result applying the correct detection phases when require is significant to enhance the Quality of the code or program. The various tool has been proposed for detection of the code smell each one featured by particular properties. The main objective of this research work described our proposed method on using various tools for code smell detection. We find the major differences between them and dissimilar consequences we attained. The major drawback of current research work is that it focuses on one particular language which makes them restricted to one kind of programs only. These tools fail to detect the smelly code if any kind of change in environment is encountered. The base paper compares the most popular code smell detection tools on basis of various factors like accuracy, False Positive Rate etc. which gives a clear picture of functionality these tools possess. In this paper, a unique technique is designed to identify CSs. For this purpose, various object-oriented programming (OOPs)-based-metrics with their maintainability index are used. Further, code refactoring and optimization technique are applied to obtain low maintainability Index. Finally, the proposed scheme is evaluated to achieve satisfactory results. The results of the BFOA test defined that the lazy class caused framework defects in DLS, DR, and SE. However, the LPL caused no framework defects what so ever. The consequences of the connection rules test searched that the LCCS (Lazy Class Code Smell) caused structured defects in DE and DLS, which corresponded to the consequences of the BFOA test. In this research work, a proposed method is designed to verify the code smell. For this purpose, different OOPs based Software Metrics with their MI (Maintainability Index) are utilized. Further Code refactoring and optimization method id applied to attained the less maintainability index and evaluated to achieved satisfactory results.
The Development of Resistivity Equipment for Subsoil Investigation
Authors: Jaisumroum Nattapon
Published: April 2019

This research aimed to develop the resistivity equipment for a groundwater investigation using 2D electrical resistivity technique. 2D electrical resistivity measurement was carried out at one profile with 90 meters long at Soi Dao district in Chantaburi Province, Thailand, where most of the areas are quite mountainous and longan plantation. Wenner electrode array was selected for 2D electrical resistivity measurement. The results showed that the instrument could be used to measure subsoil resistivity by using less capital cost with more convenient by weight and size and higher efficiency in depth measurement due to the higher voltage.
Implementation of Artificial Neural Networks for Prediction of Chloride Penetration in Concrete
Authors: Ahmed Mohamed Osama , Ati Modafar , Al Hawat Waddah
Published: April 2019

Artificial Neural Networks (ANN) has received a great attention from researchers in previous decade to predict different aspect of engineering problems. The aim of this research is to present an implementation of ANN to predict the Chloride penetration of self-consolidating concrete (SCC), containing various amounts of cement replacement minerals including fly ash, silica fume, and slag.  The ability of concrete to resist chloride penetration is measured using Rapid Chloride Penetration (RCP) test through an experimental program. One- and two-layer ANN models were developed by controlling the critical parameters affecting chloride penetration to predict the results of RCP test.  The ANN models were developed using various parameters including ratio of water-to-binder (w/b), course aggregate, fine aggregate, fly ash, and silica fume. It was shown that the prediction accuracy of ANN models was sensitive to combinations of learning rate and momentum. Data used to train and test the ANN were obtained through an experimental program conducted by the authors.
Cognitive Development in Active eLearning
Authors: Ratniece Dace
Published: April 2019

There has been an ongoing debate amongst educators about the role of memory versus intelligence in fostering effective learning. It has long been held that learners are more successful in retaining new content if they consciously think about what’s being taught, as opposed to simply memorizing what they see on the slides or on a computer screen. The learning theory of cognitive development plays a huge role in the case of the former approach—understanding by thinking. Because of its very nature, where time and distance often separate instructors and learners, the cognitive process plays an even more important role in eLearning.Nowadays learning style has been changed. A suitable technique for teaching courses needs to be adopted to improve the learning effectiveness of students. Modern technology and an up-to-date tool affect student learning abilities, especially in 21st century learning, which requires students to learn by doing. Active learning and eLearning tools and environment are aspects that can encourage students to have high learning efficiency.
Analysis of Faculty Teaching using Multi-criteria Decision Making Approach
Authors: Ghosh Dhrubajyoti , Pal Anita
Published: April 2019

In order to maintain a good standardof any college, the institution should follow paper  based  approach  or  web-based approach  to  gather  student  feedback  on  faculty  teaching to maintain the qualities of the faculty. Students have very much concerned about their teachers who have played a vital role in their life in both outside or inside of the institutions which helps them to justify a teacher and it comes in form of their feedback. In this paper, we introduce a ranking method of the given feedback's factors of teacher's performances with the help of multi-criteria decision making approach using neutrosophic logic.  We  use  the  score   and  accuracy functions  and  the  hybrid  score-accuracy  functions  of single  valued  neutrosophic  numbers  (SVNNs)  and ranking  method  for  SVNNs.
Estimation of Daily Life Time Series Data Affected by Rainfall
Authors: Hochin Teruhisa , Nomiya Hiroki
Published: April 2019

The amount of sewage flow, which is one of daily life data, was estimated for their efficient management. The amounts of flow of a typical day were tried to be adjusted to those of a day. The values for the adjustment were tried to be estimated by using the multiple regression analysis. This method is applied to the estimation of the ammonia nitrogen concentration, which is the major factor of the quality of sewage flow. The estimation results show that this method is applicable to the estimation of the ammonia nitrogen concentration, and that the amount of rainfall is dominant in estimating the ammonia nitrogen concentration.
The Data of the Initial Motivation – a Valuable Source for the Development of the Course Content. A Case Study in the Group of Business Students
Authors: Daugule Iveta , Kapenieks Atis
Published: April 2019

This study continues the authors’ previous search for key factors to determine the stickiness of different kinds of knowledge. In the authors’ opinion, identifying the stickiness of every type of knowledge in the e-course it is possible to create the optimal distribution of the intensity of time and study materials, paying more attention to the more complex knowledge, while promoting the acquisition of the free flow of knowledge with some tasks aimed at collaboration between students. Also, our previous study showed that individual motivation plays an important role in students’ success. That is why the scope of this study embraces the link of students' personal characteristics with their behavior and achievements in a learning environment. In this study, we are looking for key features for the future development of a more advanced learning system. Our scope of this study embraces the aspects of student’s initial motivation – how to ascertain, define and then use it for the development of the further learning content. Students were divided into three groups, according to their plans for engagement in business projects. The study was conducted in the course, that’s organized according to the blended learning delivery approach. Part of this course takes place in a classroom, while the other part is embedded in an electronic environment on an Open edX platform-based E-Learning environment.
Cloud-based solutions to the levelling education in physics in the context of Latvian education
Authors: Juskaite Loreta
Published: April 2019

With the rapid development of new technologies, the priority directions and goals of education are also changing. As the intensity of life is constantly growing, it requires new solutions. There is a high demand for not only different teaching materials, but also for a different organization of the learning process, a different educational policy, as well as the opportunity to quickly and continuously introduce new solutions. In 2017, “i-Zvaigzne.lv” publishing company presented a new cloud-based solution [1] "Online Tests in Physics for Grade 12" and [2] "Physics: High School course!" These are extensive electronic collections of online learning tasks, tests, tasks solution examples and tasks for self-testing in the Latvian language. The aim of the research - to theoretically analyse and empirically justify the use of cloud services in the context of levelling education.
Technology-enhanced language learning: Recent developments and what to expect next
Authors: Mikašytė Vilma
Published: April 2019

One of the key characteristics that are expected from a contemporary instructor is being able to creatively implement innovation in his/her day-to-day teaching activities. An example of such innovative approaches to teaching is the integrated teaching of, for instance, STEM subjects with foreign languages (FL). The latter can be successfully achieved via technology-enhanced learning (TEL) approach. Currently, there are numerous apps and platforms available or still being developed for teaching STEM subjects, which could be combined with learning FLs in order to ensure successful learning outcomes even more. However, the full educational potential of TEL tools for teaching FLs should be investigated and disclosed beforehand. To this end, the present paper provides an overview of the most recent developments in technology-enhanced language learning (TELL). It firstly surveys state-of-the art and then gives an insight into what to expect from the near future studies on TELL.
On approach to the agreement of diverse stakeholders’ interests and goals in the governance
Authors: K. Avdeeva Zinaida , V. Kovriga Svetlana
Published: April 2019

The paper proposes the use of a collective cognitive map when solving governance problems as an effective means of diverse stakeholders’ interests and goals agreement. For compose such a map, an original approach is proposed that combines (1) the clarification and agreement of stakeholder representations on the governance problem using a number of criteria for improving the map quality and (2) the clusterization of similar stakeholder representations.
Increasing the collaboration’s effectiveness in networked online groups by the using of competency-based workflow
Authors: Slavin Alexander , Slavin Boris
Published: April 2019

The article is devoted to the investigation of the possibility of increasing the effectiveness of the collaboration of experts using network tools for communication during general expert work. It is shown that the use of standard network tools simulating a "common room" on the Internet makes the communication of experts chaotic and uneven. Other situation arises, if in network communication to include workflow elements, when each expert will have his own task, there will be his partners. At the same time, tasks should be based on the competence of experts, related both to their knowledge and their ability to perform analytical or creative functions. In this case, communication becomes more homogeneous, and the effectiveness of general tasks to be solved is higher.
Criminal intelligence analysis based on ontological knowledge representation model
Authors: A. Jalil M , Mohd F , P. Ling C , M. M. Noor N
Published: April 2019

Nowadays, community security is an issue which is given higher priority by all agencies, aiming to reduce crime incidence. As knowledge representation is the appropriate way to apply on complex crime analysis information, hence ontology-based case matching model is proposed to represent the relationships among the knowledge. Therefore, in this study, the ontology model is developed using semantic web modelling tool, TopBraid Composer Standard Edition in order to represent the crime information with the well-defined classes and relationships. The advantage of TopBraid is the ability in offering comprehensive supports for building, managing and testing the configuration of ontology and Resource Description Framework (RDF) graphs.
Non-Classical Resource Approach as A Strategy for The Internationalization of Enterprises: Objectives Against General Obstacles
Authors: Popławski Łukasz , Szymczyk Katarzyna
Published: April 2019

The authors of the paper discuss the basic foundations of internationalization of private enterprise,  related concepts of international business management, as well as key determinants and tendencies prevailing in contemporary realities of business management in global conditions. The main objective of the paper is to analyze the issues concerning the operation of enterprises in the international environment based on the concept of non-classical resource approach. The authors focus on interpreting the elementary categories of strategic management in relation to the phenomenon of internationalization, external and internal factors affecting the internationalization of enterprises, and, in terms of the non-classical resource approach, they evaluate to what extent the owned or required resources may determine the functioning of the company in the foreign markets.
Calculation methods for multicircuit transport network fluid dynamic processes
Authors: S. Poveshchenko Tamara , O. Podryga Viktoriia , A. Poveshchenko Yury
Published: April 2019

The aim of the work is to create an algorithm for a fast and sufficiently accurate calculation of the parameters of a hydraulic network through which fluid transport is carried out. This type of network is characterized by the presence of a large number of contours, elements for various purposes, and branching. The presence of many contours in the network increases the probability of losing the density of connections, the occurrence of leaks, and accordingly the emergency situation. In paper the construction of a finite-difference scheme and the corresponding calculation algorithm is considered, taking as a basis the model of heat and mass transfer by the flow of a single-phase compressible fluid. The proposed solution method is a generalization of the sweep method to the problems of calculating the heat and mass transfer circuit with an arbitrary number of branching and pipe joints.
Speech synthesis systems: disadvantages and limitations
Authors: Kuligowska Karolina , Kisielewicz Paweł , Włodarz Aleksandra
Published: April 2019

The present speech synthesis systems can be successfully used for a wide range of diverse purposes. However, there are serious and important limitations in using various synthesizers. Many of these problems can be identified and resolved. The aim of this paper is to present the current state of development of speech synthesis systems and to examine their drawbacks and limitations. The paper dis-cusses the current classification, construction and functioning of speech synthesis systems, which gives an insight into synthesizers implemented so far. The analysis of disadvantages and limitations of speech synthesis systems focuses on identification of weak points of these systems, namely: the impact of emotions and prosody, spontaneous speech in terms of naturalness and intelligibility, preprocessing and text analysis, problem of ambiguity, natural sounding, adaptation to the situation, variety of systems, sparsely spoken languages, speech synthesis for older people, and some other minor limitations. Solving these problems stimulates further development of speech synthesis domain.
Single-Camera Computer Vision Algorithm for Robot Shortest Path Estimator using morphological structuring element with variable sizes
Authors: Hasan Sami , Th.Yousir Naeem , S. Jumaa Shereen
Published: April 2019

The robotic challeng of developing and implementing a  shortest-path finding algorithm to reach a destination without bumping into  obstacles has been tackled in this  paper. The proposed algorithm is utilized a single ceiling fixed camera and based on the mask and robot size with different sizes for dilation mask. The implementation has been successfully produced thirty-three computer vision figures and two comparison tables of simulation results by using morphological structuring element with different sizes. This paper’s proposal of optimal path finding algorithm is effeciently save robot energy in reaching targets.
Using Machine Learning Algorithms on data residing in SAP ERP Application to predict equipment failures
Authors: Kohli Manu
Published: April 2019

Asset intensive Organizations have searched long for a framework model that would timely predict equipment failure. Timely prediction of equipment failure substantially reduces direct and indirect costs, unexpected equipment shut-downs, accidents, and unwarranted emission risk. In this paper, the author proposes a model that can predict equipment failure by using data from SAP Plant Maintenance module. To achieve that author has applied data extraction algorithm and numerous data manipulations to prepare a classification data model consisting of maintenance records parameters such as spare parts usage, time elapsed since last completed maintenance and the period to the next scheduled maintained and so on. By using unsupervised learning technique of clustering, the author observed a class to cluster evaluation of 80% accuracy. After that classifier model was trained using various machine language (ML) algorithms and subsequently tested on mutually exclusive data sets with an objective to predict equipment breakdown. The classifier model using ML algorithms such as Support Vector Machine (SVM) and Decision Tree (DT) returned an accuracy and true positive rate (TPR) of greater than 95% to predict equipment failure. The proposed model acts as an Advanced Intelligent Control system contributing to the Cyber-Physical Systems for asset intensive organizations.
Safety critical software ground rules
Authors: Chaya Addagarrala Krishna , Kinnicutt Patrick
Published: April 2019

Safety critical software development field is one of the active research areas in many industries like automotive, medical, railways, nuclear and aerospace are placing increased value on safety and reliability. Safety critical software systems are those systems whose failure could result in the death or a serious injury to the people’s life, security is one of the important topics in the field of safety-critical systems and it must be addressed completely in order to operate safety critical software successfully. In this paper we present a study about the set of standards and different ground rules to be followed in critical software development practices in different industries and the challenges in applying these standards. We also discuss the role of static analysis and software integrity levels in these standards, similarities in these standards and the set of activities followed in the development process of these standards.
On cellular automata, traffic and dynamical systems in graphs
Authors: Alexander P Buslaev , Alexander G Tatashev , Marina V. Yashina
Published: April 2019

Qualitative studies of discrete dynamical systems behavior on networks are relevant in many fields such as system biology, transportation, information traffic, material sciences and so on. We consider cellular automata on one-dimensional and two-dimensional toroidal supporters. At every discrete time moment, each cell of a cellular automaton is in one of two states 0 and 1. We introduce concept of the cellular automaton mass at fixed time. The cellular automaton mass is the quantity of cells such that these cells are in the state 1. The mass conservation law takes place if the mass of cellular automaton is the same at every time. Concepts of explosion and annihilation have been introduced. Explosion takes place if the mass of cellular automaton increases at each iteration until all cells are in the state 1. Annihilation takes place if the mass of cellular automaton decreases at each iteration until all cells are in the state 0. We consider classes of cellular automata such that the state of cell at the next time depends on the state at current time and states of neighboring cells belonging to fixed set. We have found sets of cellular automata such that the mass conservation law, explosion or annihilation takes place for these automata.
Modeling principles of the digital infrastructure of it services in sustainable low carbon transport systems
Authors: Yu. V Trofimenko , A G Nekrasov , A S Sinitsyna , K I Atyev
Published: April 2019

The principles of adaptive management of sustainable low carbon transport systems (SCTS) are developed based on the interaction of intellectual and Internet technologies, which ensure the effectiveness of core elements of the system throughout the life cycle of digital infrastructure and IT services. The technologies of proactive (anticipatory) management are accompanied by targeted procedures for reconfiguring the structures of transport system, and provide a comprehensive forecast of the system's behavior and increase its efficiency on the basis of a large array of digital data. The 4D model of SCTS transformation into the digital environment is developed, which allows integrate the most important modules of the transport system, ensuring highly efficient interaction of various objects in the interest of customers.
Integrated Framework for Prognosis of Coronary Artery Disease
Authors: Rajeswara Rao D , V.R Murthy J
Published: April 2019

Coronary Artery Disease, commonly known as Heart Disease, has resulted in casualties all over the world. Currently, diagnosis of these  conditions mainly relies on experience of doctors and partly on few decision support systems. Most decision support systems built for  this domain have limitations. The major limitation is requirement of huge quantity of historical conditions data and appropriate related diagnosis labels. Proposed framework addresses this limitation by providing diagnosis  comparable with existing systems while only taking available data in absence of labels.  This is achieved by forming a novel framework using Self Organizing Networks and  Learning Vector Quantization. Here, competitive learning paradigm of soft  computing is primary focus. Proposed framework is compared with four well established  existing systems namely Support Vector Machine, Decision Tree, Random Forest and Multi Layer Perceptron. After comparison and analysis it has been proved that proposed framework gives comparable results even without supplying labeled data.In future this framework can be extended to variegated applications in various domains.
A Study on SDLC For Water Fall and Agile
Authors: Naga malleswari D , Pavan Kumar M , Sathvika D , Ajay Kumar B
Published: April 2019

This examination manages an essential and basic issue in PC world. It is worried about the improvement procedure of programming. This objective can be accomplished with the assistance of different programming improvement models accessible. The improvement models are instruments that enable us to effectively take after the means to make programming that meets a business require. There are diverse SDLC models with their separate upsides and downsides. In IT world every one of these procedures are joined Any model is executed by taking in setting each perspective and legitimate secrecy and uprightness. Accessibility controls are arranged and incorporated with programming application directly through the product lifecycle. Right now, the utilization of, mindfulness in, and discussion about dexterous approach have acknowledged sensational development. We have portrayed the characteristics of some conventional and dexterous systems that are far and wide utilized as a part of programming advancement. We have likewise examined the qualities and shortcoming between the two contradicting techniques and gave the difficulties related actualizing nimble procedures in the product business.
Detection of noxious gases by implementing internet of things technology
Authors: Arun Sai G , Bharat Kumar B , Sai Likhitha K , Anitha Raju
Published: April 2019

Harmful gas leakage accidents are the main reason for workers death in industries which work mainly using chemicals. Gas leakage can be easily detected and controlled by using latest trends in information technology by applying internet of things. This project intended to avoid industrial accidents and to monitor harmful gases and to intimate alert message to safety control board of industry using arduino Uno r3 and internet of things. Arduino Uno r3 board is used as central microcontroller which is connected with sensor. Such as temperature, gas sensor, alcohol sensor which can continuously monitor respective environmental parameters. Hence this device may be used as multi gases detection apparatus more over the rate of response is high. An alarm is produced instantly if the level of the gases goes above the normal level means indication through the internet specific receiver section. Data received by sensor  is stored in internet which can be used for further processing and it can be analyzed for improving safety regulations. This model can be future extended for providing better living environment for people in and around industries with a pollution controlled environment.
Dialectics of English Linguistics
Authors: Raja Ambethkar M Dr , K B Glory Dr
Published: April 2019

The research article “DIALECTICS OF ENGLISH LINGUISTICS” is an outcome of the direct study and observation of the use of English, of the teaching faculty at about 21 colleges, particularly Engineering colleges in Coastal Andhra area. It intends to expose various dialectics of English as a second language, identify redundant usage and use effective English. Change of trends in meaning and usage occurs mainly in the two components of communication, namely vocabulary and grammar, due to lack of clear understanding of Syntax and Semantics. Form of words like heterophones, besides other forms, confuses the learners. Confusion over the use of the American, the Australian, the British and the Indian English, in pronunciation, spelling as well as meaning: Word such as ‘Offing’ to mean ‘likely to happen soon’ is quite misleading. Exposure to Mass Usage has great influence on pronunciation of words by the masses and media Ex. Koombing, ‘baeverse’ etc. Bilingual errors, the result of undue influence of mother tongue, is a proven case, in all Indian States. Similarly the use of double positives, wrong association of words, double negatives, and mistaken negatives as positives has become the worst cases of mass influence. Use of colloquial or slang words due to interaction with people from different regions on account of L.P.G, result in assimilation, integration of this class of vocabulary, percolating subconsciously by the process of osmosis. Lack of suitable vocabulary, among English professionals ranging from lecturers to professionals, lead to monotonous use of words. For example, the word “beautiful” is used to describe many nouns.
A prediction scheme of mobility of cognitive femtocells LTE-A / LTE-UE under different speed scenarios
Authors: Vara Prasad Padyala Venkata , K.V.D.Kiran Dr
Published: April 2019

Cognitive Femtocells have been standardized suitably to the technical framing of the Fourth cohort compact project to place them inside and outside the cell. Cognitive femtocells expand the coverage area and meet the future demands of higher data rates. However, as a result of the massive deployment of cognitive femtocells, users experience additional delay and unnecessary deliveries. The different hand off mechanisms are 1. Hard handover (break before make) 2. Smooth or soft handover (make-before-break). This can seriously affect the quality of service (QoS) of jam sensitive applications, such as Voice over long-term evolution (VoLTE). The 4GPP LTE-A / LTE-UE wireless networks aim to provide uninterrupted movement and rapid transfer pillar for (Real Time) RT and non-RT application services under the giant vigour. The prediction of mobility is an effective technique to identify a domestic NodeB (eNB / HeNB) evolved in the future and improve the overall service quality of the network and satisfy the end user experience. The different hand over mechanisms are, the first sense of a difficult delivery or transfer is one in which an breathe link should be penetrate ahead a unused one is created. The second new 3G technologies use CDMA where it is possible to have adjoining cells at the same frequency and this opens the odds of boast a transfer or transfer from where it is not required to repair the connection. This is called soft transfer, and is defined as a handover in which a not used tie-in is established before the used one is released. The third type of delivery is called smoother delivery or transfer. In this case, a pristine signal is added or deleted from the spry signal group. It can also happen when a signal is replaced by a burly signal from another sector under the base station. This type of transfer is available within UMTS and CDMA2000. “The cognitive femtocell will do in the delivery mechanism is that it will detect the new channel to transmit the data. With this we can avoid the delivery handover mechanism”. This study investigates the role of mobility prediction in reducing the end-to-end delay of VoLTE and the delay of handover under different user equipment (UE) speeds in mixed femtocell and macrocell environments. We propose a mobility based forecasting scheme based on the user path and measurements of the received signal reference signal and the quality reference signal (RSRP / RSRQ) with mixed RT traffic and not RT and then estimated using a network model new. The survey analysis shows that the proposed scheme will reduce the delivery delay by 35% to keep VoLTE at the end of the delay.
JAIKISAN: An Interface For Telugu Farmer
Authors: Srilekha S , Navya Sri P , SriSagar G , S. V. S. Sridhar P
Published: April 2019

An Indian farmer is one of the important members of society. The farmer has many kinds of work to do in the fields. Agriculturists furrow their fields. They sow the seeds, waters the fields frequently. They should be careful with the products. They have conjointly to sprinkle pesticides in the fields. Farmers basically depend on the rain. Sometimes rainfall will occur according to the season but sometimes no rainfall or very less rainfall and sometimes floods may occur damaging all crops and consequently great losses for farmers. Now we have decided to develop an interface in Telugu language, where farmers can easily find solutions to their problems. Interface helps the Agriculturists to get the information regarding rainfall, types of crops suitable for that particular land. Besides, we will also provide some related videos and expert advisors. The consumer can find their required information, queries through the interface. They receive supposed statistics, associated videos. The interface helps the Agriculturists to get the information regarding rainfall, types of crops suitable for that particular land.
Analysis Of Single And Hybrid Data Mining Techniques For Prediction Of Heart Disease Using Real Time Dataset
Authors: Ahmed Yasin Syed , P.V.R.D.Prasad Rao Dr
Published: April 2019

Data mining and healthcare has strong relations as data mining is a process where we can analyze enormous set of data and after extraction meaning of data can be understood. As medical data is in bulk which leads to the need of data analytics tool for extraction of useful information or knowledge .Disease Prediction is one of the applications where many researchers are working so that they can answer whether to apply single or compound data mining technique. Heart related disease is the major cause of deaths in past decades. Use of single technique in treatment of heart disease is showing variable accuracy. Current leading research study is all about to check the effect of compound data mining technique will show enhanced results in the prognosis of heart related disease or not, but the major issue arises of identification a suitable treatment for heart disease patient. This survey paper notify gap in research findings on heart disease prognosis and prescription data and proposes a model which will fill the gap and shows enhanced accuracy.
Comparison of Transmission Loss Allocation by Proportional Sharing Principle Method and Aumann Shapley Method
Authors: K. Sarada Mrs. , Anush Kumar P , Sadiq Rahiman Sd , Mohan Sai Krishna Ch
Published: April 2019

In the current scenario of the electricity market in the world the cost allocation became the thematic part and the essential usage to individual distributor and to the consumer. Allocation is nothing but a share of anything that been shared in the equal amount to the assigned terms of the quantity. Here in the power sector, losses and the respective costs have been shared among the generators and the loads. To achieve the linear nature and invariant characteristics, allocation of losses is done. To such allocation of losses there are many methods, popular methods of them named, Proportional Sharing Principle Method and Aumann-Shapley Method are compared in this paper based on loss and cost allocation, and results are verified through Mat lab platform.
A Survey on User Awareness of Cloud Security
Authors: Gudapati Syam Prasad Dr , S. Gaikwad Vidya
Published: April 2019

The cloud computing technology provides cost effective, powerful computation resources on the fly. It minimizes the need to procure and maintain expensive hardware, software and reserve space for IT infrastructure. These features for cloud computing encourages organizations and individuals to migrate their resources needs and services to the cloud. However, cloud computing services provided by third-party vendors possesses various security threats. The cloud services store sensitive data (such as credentials, personal information, etc.) of various users on the shared environment that escalates security concerns. The  aim of this research survey paper are three-fold: i) provides guideline for researchers who are new to the cloud computing security area, ii) provides the state-of-the-art survey of cloud computing security issues and challenges, and iii) provides the further research directions required into security assurance of the cloud computing.