bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi layer Attestation for Internet of Things using Blockchain
Authors:   research scholar, GITAM (Deemed to be University)., Mathane Vytarani , Lakshmi P V ,   professor, GITAM (Deemed to be University)
Published: March 2020

Internet of Things (IOT) by its nature comprises of heterogeneous devices with varying degree of resources and capabilities with common attributes that those are connected and uniquely identifiable over the network. Given the always on always connected nature of IoT devices along with virtually limitless applications, the attack surface of constituent IoT device is very large. Hence ability to attest IoT devices for its trustworthiness is very important factor in determining trustworthiness of IoT network. In past significant amount of research has focused on possible attestation mechanisms for IoT but all those proposals invariably depend on specific hardware implementation like TrustZone, SGX, TPM, RTC, memory with OTP etc. Sine all such security primitives are either architecture or manufacturer specific it is not possible to build common unified attestation scheme for all constituent IoT devices in a typical IoT network using any of those primitives. This research work proposes different pragmatic approach to define such common and scalable attestation scheme that all IoT devices within IoT network could deploy. The proposed scheme makes use of memory management which is one of most basic features of any processor or controller to build common and scalable attestation mechanism for all types of IoT devices. The approach is to understand threat model and then develop mitigations in pragmatic manner.
Enhanced CORDIC Based Rotator Design for Sinusoidal Transforms
Authors:   Electronics and Communication engineering department, Institute of Technology, Nirma University, Ahmedabad, India, Pratik Trivedi , Tanish Zaveri ,   Electronics and Communication engineering department, Institute of Technology, Nirma University, Ahmedabad, India
Published: March 2020

Transforms play an important role in conversion of information from one domain to the other. To be more specific transforms like Discrete Fourier transform (DFT) and Discrete Cosine transform (DCT) helps us to migrate from one time domain to frequency domain based on the basis function selected. The basis function of the every sinusoidal transform carries out a circular rotation to convert information from one domain to the other. There are applications related to communication which requires this rotation into the hyperbolic trajectory as well. Multiplierless algorithm like CORDIC improves the latency of the transforms by eliminating the number of multipliers in the basis function. In this paper we have designed and implemented enhanced version of CORDIC based Rotator design. The Enhanced version is simulated for order 1 to order 36 to emphasize on the results of the proposed algorithm. Results shows that the enhanced CORDIC rotator design surpasses the Mean square error after the order 18 compared to standard CORDIC. Unified CORDIC also can be implemented using the said algorithm to implement different three trajectories.
Optimal Feature Subset Selection for Imbalanced Class Data using SMOTE and Binary ALO Algorithm
Authors:   Assistant Professor, Department of Computer Application, Govt. Arts College, Chidambaram, India., Jayanthi K. , Sudha L. R. ,   Associate Professor, Department of Computer Science & Engineering, Annamalai University, Annamalainagar, India.
Published: March 2020

Feature selection in multispectral high dimensional information is a hard labour machine learning problem because of the imbalanced classes present in the data. The existing Most of the feature selection schemes in the literature ignore the problem of class imbalance by choosing the features from the classes having more instances and avoiding significant features of the classes having less instances. In this paper, SMOTE concept is exploited to produce the required samples form minority classes. Feature selection model is formulated with the objective of reducing number of features with improved classification performance. This model is based on dimensionality reduction by opt for a subset of relevant spectral, textural and spatial features while eliminating the redundant features for the purpose of improved classification performance. Binary ALO is engaged to solve the feature selection model for optimal selection of features. The proposed ALO-SVM with wrapper concept is applied to each potential solution obtained during optimization step. The working of this methodology is tested on LANDSAT multispectral image
Bit Error Rate Performance of Spread Spectrum Communication Systems for AWGN Channels
Authors:   Department of Electronics, Cochin University of Science and Technology, Kochi, India,, R Revathy , Pillai P. R. Saseendran ,   , Department of Electronics, Cochin University of Science and Technology, Kochi, India
Published: March 2020

The digital communication technologies have gained immense significance as it provides secure and error free services. One of the major advantages of digital communication is that they are much resistant to transmitted as well as interpreted errors. For ensuring the security of data, the most suitable method is to use spread spectrum technique. The spread spectrum technique has gained immense popularity for use in various systems as the spreading of the spectral bandwidth offer many advantages, including the establishment of secure communications, increasing resistance to interference, noise rejection, and so on. The signals which are modulated by using these techniques cannot be jammed and are very hard to interfere. This paper presents the results of investigation of BPSK based direct sequence spread spectrum systems for Additive White Gaussian Noise (AWGN) and undersea channels. The bit error rate performance of BPSK based direct sequence spread spectrum systems has been simulated for the AWGN channel and the results have been plotted.
Design and Analysis of Microstrip Patch Antenna Arrays for Millimeter Wave Wireless Communication
Authors:   Department of Electronics and Communication NERIST, Nirjuli, Arunachal Pradesh, India., Shah Md. Farid , Singh Aheibam Dinamani ,   Department of Electronics and Communication, NERIST, Nirjuli, Arunachal Pradesh, India.
Published: March 2020

In present 4G the enormously growing of cellular user and the shortage of bandwidth which results in difficulty to provide a high data rate to each end user. To achieve wider bandwidth millimeter wave technology is considered to solve the problem of bandwidth shortage. This paper presents a 4x1 element circular phase array of inset fed rectangular patch antenna operating in the millimeter wave band (24.81GHz 33GHz). To achieve large impedance bandwidth the array is designed with edge coupled parasitic patch arrangement which provides dual resonance. The designed array used the ring-shaped sequential rotation feeding line to reduce the unwanted side lobe radiation. The design antenna array achieved good return loss – 10dB ≤ S11 ≤ – 18.64dB and maintaining 26% (24.81GHz 33GHz) bandwidth. The antenna array has achieved good return loss S11, -18.64dB at 29.09GHz and VSWR ≤ 1.85 (24.81GHz-33GHz). In millimeter wave wireless communication require high gain antenna to overcome the problem of path loss. The designed array has achieved 10.14dB gain. So the designed will be suitable for the future millimeter-wave wireless communication system.
RRR Concept and unknown Facts of Ransomware
Authors:   Department of Computer Science and Engineering, GITAM School of Technology, Bengaluru, India., V. Ranjitha
Published: March 2020

Ransomware is the word which is very popular nowadays. Ransomware is a malicious program that infects the device once it gets into and cannot decrypt the data until the key is provided by the hacker. Ransomware not only forbids the access but also infect the network, where it is communicating with, by encrypting the content that is located on mapped and unmapped network drives where the whole organization networks falls down. In Ransomware various families exist like Cryptoworm, Raas and many. This Ransomware Target is mainly on corporates for beneficial profits. Cryptocurrency is one of the enabling factors of Ransomware. In 2019 according to research work Ransomware raised because of phishing emails and smshing to 109 percent over 2017. Ransomware detections in the first half of the year were up 77% compared to the latter half of 2018. Around 851 million Ransomware contagious activities happened in 2018. 34% of corporates came across with this malware and took months or more to recover back and to access their own data. The algorithms that are used by the Ransomware is very complex which cannot be understood by the normal users. This article is to share research findings about Ransomware, some unknown facts where exactly how Ransomware is growing, and also Restrict Recognize React concept (RRR concept) of Ransomware which is mainly for avoiding Ransomware. Restricting is the measures that as to be carried out for avoiding the Ransomware, Recognize is for identifying the Ransomware if device is infected with it, React is mainly responding to the attack to get rid of Ransomware.
Energy Efficient Mobile Adhoc Network using Raspberry PI
Authors:   Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, India., M Anitha Mary , R Bharathy ,   Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, India, U Jhanani Shree ,   Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, India., R Surendar ,   Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, India.
Published: March 2020

This paper based on generation of power using wearable technologies from sustainable resources to establish Mobile Adhoc Network communication between multiple nodes using Raspberry pi-3 microprocessor. It mainly focuses on aiding in the search and rescue operations of explorers or mountaineers in case of avalanches or in case of some unfortunate disasters. An advanced routing mechanism called Better Approach to Mobile Adhoc Networking is used to establish communication between the explorers to transfer user location information to the base station.
A Framework for Web Application Vulnerability Detection
Authors:   CSE Department, Banasthali Vidyapeeth, Rajasthan India, Kalim Asra , Jha C K ,   CSE Department, Banasthali Vidyapeeth, Rajasthan India., Tomar Deepak Singh ,   CSE, MANIT, Bhopal, India, Sahu Divya Rishi ,   cse, SATI, Vidisha, India
Published: March 2020

Hardly a facet of human life is not influenced by the Internet due to the continuous proliferation in the Internet facilities, usage, speed, user friendly browsing, global access, etc. At flip side, hackers are also attacking this digital world with new tactics and techniques through exploiting the web application vulnerabilities. The analysis of these vulnerabilities is of paramount importance in direction to secure social digital world. It can be carried out in two ways. First, manual analysis which is error prone due to the human nature of forgiveness, dynamic change in technology and fraudulence attack techniques. Second, through the existing web application vulnerability scanners that sometime may suffer from generating false alarm rate. Hence, there is a need to develop a framework that can detect different levels of vulnerabilities, ranging from client side vulnerabilities, communication side vulnerabilities to server side vulnerabilities. This paper has carried out the literature survey in direction of identifying the new attack vectors, vulnerabilities, detection mechanism, research gaps and new working areas in same field. Continuous improvement in framework is easy. Hence, a framework is proposed to overcome the identified research gap.
Regional Flood Forecasting using SWMM for Urban Catchment
Authors:   M-Tech Student, Civil Engineering Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India, Harsha S. Sri , Agarwal Sunny ,   Assistant Professor, Civil Engineering Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India, Kiran C Hari ,   Project Manager, (DM), APSDMA, India.
Published: March 2020

Urban flooding is the inundation of land or property in a designed atmosphere, significantly in additional densely inhabited areas, caused by precipitation overwhelming the capability of drain systems, like storm sewers. Due to expeditious increment and improper urban designing the probabilities of creek, localized or flash urban floods have drastically multiplied. This study explores the application of Storm Water Management Model (SWMM) to densely populated area of Vijayawada city, which is fragmented into 58 sub-catchments. The study area is delineated in SWMM by the assistance of blueprint AutoCAD maps showing drainage network and Reference Level details. From this elaborated elevation data of drain networks, the flow direction has been evaluated to create the descriptive view of the area in SWMM. In this study area 2016, 2017 and 2018 extreme rainfall events of 24 hrs interval is considered for runoff analysis. The focus of the current wok is to model runoff conditions by applying Dynamic wave equation for routing floods and Green-Ampt equation for infiltration in SWMM. The model outputs guided in visualizing the runoff from extreme precipitation events and to analyze the accuracy of the storm water network system.
Free Vibration Response of Four-Parameter Functionally Graded Thick Spherical Shell Formulation on Higher Order Shear Deformation Theory
Authors:   Department of Mechanical Engineering, Andhra University, Visakhapatnam, India., Srilakshmi Raparthi , Ratnam Ch. ,   Department of Mechanical Engineering, Andhra University, Visakhapatnam, India., Badiganti Chandra Mouli ,   Department of Mechanical Engineering, RISE Group of Institutions, Ongole, India
Published: March 2020

This paper emphasizes on the free vibration (FV) responses of functionally graded thick spherical shell in rectangular form using traditional mathematical formulation on finite element method and governed by Higher order shear deformation theory (HOSDT). A functionally graded spherical shell made up of metal-rich on the top surface and in contrast, base surface of the model is ceramic-rich. The FG volume fraction of four-parameter power-law material constituents assumed in the thickness direction. To highlight the potential for the current method, convergence studies, and validation tests performed to establish the stability and accuracy attained by the current approach. The parametric studies presented to scrutinize the influence of choice of four parameters employed through power-law distribution. The eminence effect of spherical shell geometrical properties, and different types of support conditions, skew angle on the FV behavior of non-dimensional frequency responses examined in detail.
ENN Ensemble based Neural Network method for Diabetes Classification
Authors:   Dept of CSEGitam institute of Technology, Gitam University Visakhapatnam, India, Kumari G L Aruna , P Padmaja ,   Professor and Head,Dept.of Information Technology Anil Neerukonda Institute of Technology &Sciences, Visakhapatnam,India, G Jaya Suma ,   Professor and Head, Department of Information Technology JNTUK-University College of Engineering ,Vizianagaram, India
Published: March 2020

Diabetes is considered as one of the most chronic disease which has serious impact on human health and leading cause of mortality worldwide. The early prediction of diabetes can help clinicians to provide a better diagnosis to the patients. Recently, computed aided diagnosis systems have gained attention due to significant growth in data mining, and machine learning. Several approaches are present based on the machine learning techniques but due to poor classification performance and computational complexity, it becomes difficult to utilize for real-time applications. Ensemble classification approaches have reported a noteworthy improvement in diabetes classification but desired accuracy is still a challenging task. Hence, in this work we introduce a combined hybrid approach called as ENNEnsemble based neural network approach for diabetes classification. In this approach, a feature selection process is presented using neighboring search technique; the selected features are processed through the feature ranking model to generate the efficient feature subset for better classification accuracy. Finally, these features are learned and classified using neural network classifier. The experimental study shows that the proposed approach achieves better accuracy when compared with the existing techniques
Vertical In Vessel Composter for Stabilization of Market Vegetable Waste
Authors:   Civil Engineering, Vidyavardhaka College of Engineering, MYSURU, INDIA, S Dayananda H , S Shilpa B ,   Civil Engineering, Vidyavardhaka College of Engineering, MYSURU , INDIA.
Published: March 2020

Composting can be one of the solutions to tackle the issue of handling solid waste. In the present research work, a bench-scale vertical in-vessel aerobic composter was designed to stabilize the Devaraja market vegetable waste, Mysore using horse dung and plantain leaves as seeding material and bulking agent respectively. On average, Devaraja market generate 4.8-5.6 ton per day. Mix proportion of organic waste, bulking and seeding materials fed into composter was in the ratio of 5: 1: 0.5. Initial and variation in physico-chemical characteristics of waste were monitored during the composting period. The initial concentration of total nitrogen, phosphorous, total organic carbon and C/N ratio which was found to be 1.67%, 0.78%, 1.93%, 43.5% and 26 showed a variation of 2.4%, 1.1%, 2% 29% and 15 respectively at the end of 21 days of composting.
Developing of Entrepreneur Digitals Learning Model in the Industrial Revolution 4.0 to Improve 21st Century skills
Authors:   a is student at Fakultas Teknik, Universitas Negeri Padang,, Erdisna  , Ganefri  ,   lecturer at Fakultas Teknik, Universitas Negeri Padang,, Ridwan  ,   lecturer at Fakultas Teknik, Universitas Negeri Padang,, Efendi Raimon ,   lecturer at Faculty of Computer Science, Universitas Dharmas Indonesia,
Published: March 2020

This study aims to develop a learning model of Information System Design Analysis in Vocational Education that is valid, effective and practical. Based on preliminary studies and needs analysis conducted on the Information Systems Design Analysis course, it was found that learning is not optimal. The needs analysis also found that there were privices / needs of lecturers and students who had high expectations of the learning process that were able to improve 21st century competence, i.e. This type of research is Research and Development which refers to the 4D model. The analysis technique uses the Aiken'V test, and validity uses expert testing and Focus Group Discussion (FGD). The research findings are an Entrepreneur Digitals Learning Model (ERDIS) that is equipped with model books, teaching material books, lecturer manuals and student manuals. Models and support systems meet the validity criteria, are based on research and development models and are suitable for use by experts. The results of testing the validity of the results show that all products already have the results of product validity are at a score> 0.677. The results of testing the practicality of the product according to students 82%, based on the perception of lecturers 85% means the product has a high practicality. The results of the analysis of the effectiveness of the cognitive domain showed a t-test score of 3,252> t table of 2.010 which means that Hypothesis (Ha) was accepted, the affective domain hypothesis testing showed a t-count score of 3,688> t table of 2,010 which meant that Hypothesis (Ha) at the 95% significance level . The results of research in the psychomotor domain through the evaluation of ERDIS 1 and 2 projects are in the Good category, this means that the products are valued for effectiveness
Local Versus Full Width Pavement Rehabilitation in the Frame of Old Water Supply Network Repair
Authors:   Assistant Professor, University of Thessaly, Larissa, Greece., Papageorgiou Grigorios , Zografos Christos ,   M.Sc. Degree in Infrastructure Engineering, Dept. of Civil Engineering T.E., Technological Educational Institute of Thessaly., Alamanis Nikolaos ,   M.Sc. Degree in Infrastructure Engineering, Dept. of Civil Engineering T.E., Technological Educational Institute of Thessaly., Xafoulis Nikolaos ,   M.Sc. Degree in Infrastructure Engineering, Dept. of Civil Engineering T.E., Technological Educational Institute of Thessaly., Farsirotou Evangelia ,   , Professor , Department of Ichthyology & Aquatic Environment, School of Agricultural Sciences, laboratory of “Ecohydraulics & Inland Water Management” at the University of Thessaly
Published: March 2020

Since the global financial crisis of 2008, all construction related activities are now subject to cost control of each project. An important component of the optimal choice is the implementation cost. The evaluation of construction activities can be conducted by estimating their environmental as well as their cost footprint, which is also the demand and consumption measure for the societies' needs. Water and sewerage projects have a key role in the standard of living, Public Health and environment. Therefore, water supply network replacements are important to upgrade the quality and quantity of water, through cost-effective choices. The purpose of this study is to present and comment on the uniform cost footprint through the complete replacement of the old water supply network along with complete reconstruction of pavement compared to local repair activities. Usual practices in repair works of old networks and flexible pavement rehabilitations are presented, assessing the benefits of total reconstruction by carrying out life cycle cost analysis in terms of uniform cost per year. The project of replacing the water supply network in the municipality of Larissa, Greece for the period 2015-2019 is analyzed, linking water savings with simultaneous total pavement rehabilitation, calculating average cost per inhabitant and hydrometer, comparing cost and pavement surface area between total and localized rehabilitation activities for a twenty-year rollback period. The fruitful findings of this research study, indicate that full-width pavement rehabilitation along with new water supply network establishment is economically advantageous compared to local rehabilitation treatments, according to the time period considered. Thus, competent authorities can use the proposed methodology as a useful tool to conclude to the optimal choice for maintaining water supply networks in a cost-effective way.
A New Perceptive of E Voting with Blockchain
Authors:   Research Scholar, Department of Mathematics, J,C.Bose University of Science and Technology, YMCA, Faridabad, India, Jindal Shalini , Garg Tarun Kumar ,   Associate Professor, Department of mathematics, Satyawati college, University of Delhi, India., Singh Ajeet ,   Assistant Professor, Department of mathematics, satyawati college, university of Delhi, India.
Published: March 2020

Electronic voting is most growing field in the area of voting system. Digital users are growing with the expo-national growth in every country. In the country like India where mobile or internet user are 391 million, e-voting system reduce a huge amount of current voting methods. But in this current scenario e-voting system are vulnerable and not threat proof. Blockchain is new emerging field in security and for distributed systems. Only few methods are applied in the past where E-Voting system used the blockchain technology. So, the objective of this research is to review the different algorithms applied in e-voting using blockchain through various parameters to help researchers working to provide more security using blockchain.
Data Analytics in Master Cam Setup Sheet for Improved Manufacturing
Authors:   Associate Professor, Department of Mechanical Engineering Shri Ramdeobaba College of Engineering and Management, Nagpur, M.S., India, Shukla V. V. , Sawalakhe P. V. ,   Assistant Professor, Department of Mechanical Engineering Shri Ramdeobaba College of Engineering and Management, Nagpur, M.S., India, Shaaikh J. A. ,   Lecturer, Department of Mechanical Engineering, Debre Tabor University, Ethiopia, Trivedi M. G. ,   Assistant Professor, Department of Mechanical Engineering, Shri Ramdeobaba College of Engineering and Management (RCOEM), Nagpur, India., Gudadhe N. P. ,   Assistant Professor, Department of Mechanical Engineering, Shri Ramdeobaba College of Engineering and Management (RCOEM), Nagpur, India.
Published: March 2020

The paper focusses on providing the awareness of smart manufacturing utilizing simulation through modelling in order to facilitate data analytics. Data analytics related to manufacturing will prove its noteworthy benefits to processes involved in industry. Models simulated for manufacturing techniques can be utilized to facilitate data analytics in numerous ways. The provision offered in Mastercam offer programmers to support models simulated to various sectors like logistics, management, transportation, health systems and manufacturing making simulation tool a popular one. It provides three types of stages of process knowledge namely a machine level, a shop level and a universal level. The universal level is related to the knowledge of a process independent of machine or individual shop which facilitates the process. Furthermore, analogous process knowledge like shape capabilities of machining and manufacturing processes offers to progress processes involved in manufacturing through Mastercam.
Examination of Savonius VAWT Blade Made of Stainless Steel and Aluminum using Ansys
Authors:   Assistant Professor, Department of Mechanical Engineering,, Vinayaka Mission’s Kirupananda Variyar Engineering College, VinayakaMission’s Research Foundation(Deemed to be University), Salem – 636 308, Tamilnadu, India., Saravanan M.
Published: March 2020

This paper studies roof mounted savonius type Vertical Axis Wind Turbine systems with the goal of maximizing the efficiency and reducing the cost. The efficiency of the wind turbine depends on the material, shape and angle of the blade. So material plays an important role in the design of wind turbine. In this paper, Stainless Steel and Aluminum material are used to design savonius wind blades of 1 m height and 0.5 m chord length with 4 different arc radii. Modeling software Solid Works is used to model savonius wind blade and static structural and modal analysis of the Stainless Steel and Aluminum blades are done by using ANSYS Workbench software.
Mechanical Designing of Acoustic Chamber Based Muffler for Sound Reduction
Authors:   Assistant Professor, Department of Fire Technology & Safety Engineering Medi-Caps University, Indore, India, Yadav Sandeep , Raghuvanshi Rituraj ,   Assistant Professor, Department of Fire Technology & Safety Engineering Medi-Caps University, Indore, India
Published: March 2020

Sound of exhaust system makes a substantial contribution to the interior as well as exterior noise of automobiles. Accurate prediction and control of noise from automobiles is of significant importance in automotive exhaust system design. When it comes into the term of acoustic performance there are several parameters that describe the performance of a muffler, the Transmission Loss (TL) being the most popular one for validating an analytical model. Acoustic characteristics of silencers filled with fibrous material are also studied.
Matrix Converter for Induction Motor Drive
Authors:   Assistant Professor, Sanjay Ghodawat University, Kolhapur, INDIA, Dhawale Pravin G. , Gaurkhede Sushil D. ,   Assistant Professor, ITM-College of Engineering, Nagpur
Published: March 2020

This paper presents the comparison of performance between matrix converter and conventional DC-link converter fed induction motor drive system. It is noted that conventional converter required two stages for power conversion whereas matrix converter required single stage. The output current from conventional converter contains odd harmonic component which produces additional losses in drive causes de-rating and torque pulsation of motor. This unhealthy operation of drive is reduced by matrix converter which has the unique feature of producing pure sinusoidal output current waveform with minimum harmonic distortion. The main objective of this paper is to reduce total harmonic distortion by employing proper switching of matrix converter. The simulated result is compared with conventional converter to show that proposed system is better than conventional system. This paper also presents modeling and simulation of matrix and conventional converter fed induction motor drive system using MATLAB/SIMULINK software.
Computer Algorithm for Creation Classic Mosaic Fillings Based on the Vector Guide Lines
Authors:   State university of infrastructure and technologies, Department of Information Technology, Kyiv, Ukraine., Petrushevski Andri , Us Victoriia ,   National Aviation University, Interior Design department, associate professor, Kyiv, Ukraine.
Published: March 2020

The article suggests algorithms for filling mosaic surfaces. Today, there are a number of algorithms that use the software design environment to automate the creation of images that correspond to mosaic compositions based on raster images. However, they do not allow realizing the principles of the classical construction of mosaic works, which guide professional mosaics. In this case, the main task is the problem of optimizing the filling of space from a mathematical point of view. From the point of view of the artist, this is not the main problem, moreover, the distance between the parts of the mosaic can vary, act as an artistic element. Much more important is the organization of the structure of the mosaic surface. This article is dedicated to this problem. The sequence of actions is given - algorithms that allow the artist to achieve the desired effect and gain full control when filling mosaic surfaces. These algorithms allow you to create mosaic fillings based on linear patterns without color and tonal design, which is impossible for existing algorithms. The authors proposed the construction of the topology of classical mosaics using vector guides. When forming the algorithm, vector guide lines or “power lines” are taken as a basis, on which mosaic elements (tesserae) are subsequently placed. Variants of using existing algorithms at each stage of the solution of the problem are proposed. Algorithms and results of filling a mosaic panel with a line-by-line and equidistant method are presented. This technology will allow not only creating mosaic surfaces, but also using it as a tool for creating real art projects for implementation in design and art. The possibility of using existing technologies in this technique is commented.
A Comprehensive Understanding of Airflow in Non Air conditioned Bus Coaching System
Authors:   Assistant Professor, Department of Mechanical and Automobile Engineering at CHRIST (Deemed to be University), Bengaluru, Karnataka, India., J Niranjana S , Kubsad Shivalingapa S ,   Professor and Head, Department, and R&D Head in various engineering colleges in Karnataka, India., G Ravichandran ,   Assistant Professor, Department of Mechanical and Automobile Engineering at CHRIST (Deemed to be University), Bengaluru, Karnataka, India., N Santhosh ,   Assistant Professor, department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University) Bengaluru, Karnataka, India.
Published: March 2020

Bus is a Major mode of transport in India and the passenger safety is significant during the travel. This Comprehensive comprehension on the literatures available discusses various parameters used to improve the Vehicle Design, Safety, Fuel Efficiency and decrease in drag of the vehicle. The outcomes obtained from CFD investigation is tabulated, and the exploratory outcomes obtained from aerodynamic tests are contrasted and numerical examination and the outcomes are additionally incorporated. The impact of temperature and the wind stream is likewise considered in this investigation. Various kinds of ventilations given in the transport vehicles are recorded, and the outcomes acquired from the various configurations in the structure is considered for opening and closing of Windows (Combination of windows). The cooling air inside the transport straightforwardly relies upon the outside climate condition. By overhauling the current vehicle transport model, the eco-friendliness will be improved and the drag power will be diminished.
Video Frame Illumination Inconsistency Reduction using CLAHE with Kekre’s LUV Color Space
Authors:   Computer Department, PC Co E-SPPU, Pune, India., Abin Deepa , Thepade Sudeep D. ,   Computer Department, PC Co E-SPPU, Pune, India.
Published: March 2020

Visual frame quality is of utmost significance and is relevant in numerous computer vision applications such as object detection, video surveillance, optical motion capture, multimedia and human computer interface. Under controlled or uncontrolled environment, the video visual frame quality gets affected due to illumination variations. This may further hamper the interpretability and may lead to significant loss of information for background modeling. An excellent background model can enhance good visual perception. In this work, local enhancement technique with improved background modeling, Clipped Adaptive Histogram Equalization (CLAHE) is explored with Kekre’s LUV color space to reduce the illumination inconsistency especially with darker set of video frames and a significant improved average entropy of 7.7225 has been obtained, which is higher than the existing explored variations of CLAHE. .
Facial Expression Detection using Deep Neural Networks
Authors:   Assoc. Prof., Department of Computer Science, K L Educational Foundation, Guntur, India., Reddy M. Sandeep , Chinmai Ch. ,   Department of Computer Science, K L Educational Foundation, Guntur, India., Teja B. Sai ,   Department of Computer Science, K L Educational Foundation, Guntur, India., Kumar P. M. Ashok ,   Department of Computer Science, K L Educational Foundation, Guntur, India.
Published: March 2020

Facial Expression conveys nonverbal communication, which plays an important role in acquaintance among people. The facial expression detection system is an activity to identify the emotional state of the person. In this system, a captured frame is compared with trained data set that is available in the database and then state of the captured frame is defined. This system is based on Image Processing and Machine Learning. For designing a robust facial feature descriptor, we apply the Xception Modelling algorithm. The detection performance of the proposed method will be evaluated by loading the dataset and pre-processing the images for feeding it to CNN model. Experimental results with prototypic expressions show the superiority of the Xception-Model descriptor against some well-known appearance-based feature representation methods. Experimental results demonstrate the competitive classification accuracy for our proposed method.
Robolution: Real Time Predictive Analytics for Industrial Robots
Authors:   Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, India., Suhane Sajal , Patil Pramod D. ,   Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, India., Mishra Ravi ,   Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, India., Koul Simran ,   Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, India., Shukla Ridima ,   Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, India., Rao Jyoti ,   Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, India.
Published: March 2020

Robots have been playing a very important role in our day-to-day lives and will be a necessity in the coming future. Whenever we hear automation, the first thing that strikes our mind is a robot performing the given task. But if a robot fails to do the task, it could cost an individual or corporate a huge financial loss. In this study, we have learned the working of various robots and drawbacks that hold them back. For this work, we did make a study of drives used in the robot and after that applied the machine learning algorithms to predict the classification of whether the robot will function properly or not, based on the data of drive(s).
Proposing PDM Model for Securing Data Storage on Cloud Servers
Authors:   CS Dept, Engineering College, Ajmer, Rajasthan, India, Chaturvedi Amit Kumar , Chahar Meetendra Singh ,   Ph.D. Scholar, CS Dept., Bhagwant Univ., Ajmer , Raj. India, Sharma Kalpana ,   CS Dept., Bhagwant Univ. Ajmer, Raj., India.
Published: March 2020

Clouds are the group of resources like data storage, processors, security tools, etc. that are shared by the big resource providers like Amazon, Google, Yahoo etc. and the users of these resources. There is the requirement of privacy policy when we work in such a shared, unknown, untrusted, and pay per use environment. Computing industry is now shifted their orientation from arranging first the resources to developing new applications or application of new ideas. Because in the cloud computing world , every resource required for developing and executing an idea or application is available or pay per use basis. But even though everything is available with scalability or these resources, the data of the business transaction with authenticity is prime for all either business organization or customer. As we know that user’s and transaction data is very important and unauthorized access is illegal and harmful for everyone. Because worldwide the use of online services is increasing exponentially and the use of cloud computing for these solutions is also increasing. We have considered this problem for our research work and in this paper, we are proposing a PDM privacy preserving model for more securing the cloud data.
Control of 3 Axis Satellite Reaction Wheel using PID Control Optimized Genetic Algorithms
Authors:   Physics of Engineering , Universitas Nasional, Jakarta, Indonesia, Wati Erna Kusuma , Ramadhan Yulio ,   Physics of Engineering , Universitas Nasional, Jakarta, Indonesia, S Hari Hadi ,   Physics of Engineering , Universitas Nasional, Jakarta, Indonesia
Published: March 2020

Satellite Attitude Determination and Control System (ADCS) uses an active actuator with a Reaction wheel. This study uses PID and genetic algorithms to control the Reaction wheel. The initial population was 200, and the crossover rate was 0.8, the mutation constant was 0.01 with a stop generation criteria of 50 generations. Reaction Wheel Control in a closed ring with optimized PID control The Genetic Algorithm has transient response characteristics that are 1 seconds rise time, 9 seconds set time, 33.2% overshoot with an ITAE performance index of 481,9479. Use the Matlab program to conduct a Smart Nanosatellite Attitude Propagator (SNAP) simulator to create a 3-axis reaction wheel model as its actuator. The satellite is the object of control, simulating the satellite conditions in a tumbling state having the initial angular velocity [0.5 0.5 0.5] ° / second then stumbling which makes the satellite angular velocity to [0 0 0] ° / second. Roll and yaw axes have a significant enough error that is1 rad / s and -1 rad / s while the pitch axis has a small error that is 1.5 10−3 / and −1.5 10−3 /s.
Alzheimer’s Disease Diagnosis using Deep Learning Techniques
Authors:   Faculty of Engineering and Technology, Shoolini University, Himachal Pradesh, India., Salehi Ahmad Waleed , Baglat Preety ,   Faculty of Engineering and Technology, Shoolini University, Himachal Pradesh, India., Gupta Gaurav ,   Faculty of Engineering and Technology, Shoolini University, Himachal Pradesh, India.
Published: March 2020

Deep learning is one of the machine learning approach which has shown promising results and performance as compare to traditional algorithms of machine learning in terms of high dimensional data of MRI brain image. In this article the application of deep learning in medical field is addressed. A thorough review of various algorithms of deep learning for diagnosis of Alzheimer’s disease is done, in which this disease is a progressive brain disorder that destroy the brain memory gradually, it is a common disease in older adults which is caused by dementia. It has been obtained in most research papers that the most widely used and represented algorithm is Convolutional Neural Networks (CNN) when it deals with brain image analysis. After study of various related papers for diagnosing of AD, we have come to this point and suggested that the AD prediction at earlier stages can be increased by using an advance deep learning techniques in different dataset (ADNI, OASIS) combining to one.
Exploration of Collaboration Filtering Techniques for Product Recommendation
Authors:   Master of Technology, Department of Computer Science and Engineering, SRM Institute of Science and Technology, KTR Campus, Chennai, Tamilnadu, India., Kumar Ajith , Madhavan P. ,   Associate Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, KTR Campus, Chennai, Tamilnadu, India.
Published: March 2020

Today, recommendation system has been globally adopted as the most effective and reliable search engine for knowledge extraction in the field of education, economics and scientific research. Collaborative filtering is a proven techniques used in recommender system to make predictions or recommendations of the unknown preferences for users based on the known user preferences. In this paper, collaborative filtering task and their challenges are explored, study the different recommendation techniques and evaluate their performance using different metrics.
Brain MRI Classification using Deep Learning Algorithm
Authors:   Research Scholar, Sathayabama Institute of Science and Technolgy, Chennai, India. Assistant Professor, MITWorld Peace University, Pune, India., Kulkarni Sunita M. , Sundari G. ,   ECE Department, Sathayabama Institute of Science and Technolgy, Chennai, India.
Published: March 2020

The brain tumor is one of the most dangerous, common and aggressive diseases which leads to a very short life expectancy at the highest grade. Thus, to prevent life from such disease, early recognition, and fast treatment is an essential step. In this approach, MRI images are used to analyze brain abnormalities. The manual investigation of brain tumor classification is a time-consuming task and there might have possibilities of human errors. Hence accurate analysis in a tiny span of time is an essential requirement. In this approach, the automatic brain tumor classification algorithm using a highly accurate Convolutional Neural Network (CNN) algorithm is presented. Initially, the brain part is segmented by thresholding approach followed by a morphological operation. The AlexNet transfer learning network of CNN is used because of the limitation of the brain MRI dataset. The classification layer of Alexnet is replaced by the softmax layer with benign and malignant training images and trained using small weights. The experimental analysis demonstrates that the proposed system achieves the F-measure of 98.44% with low complexity than the state-of-arts method.
Hardware Implementation of a Communication Link for 5G Communication in the Tropical Regions
Authors:   Department of ECE, Techno International Newtown, Rajarhat, kol- 700156,India., Patra Trilochan , Mitra Swarup Kumar ,   Department of ECE, MCKV Institute of Engineering,Liluah,Howrah-711204,India
Published: March 2020

The 5G communication system comprises various ingredients essential for the recent radio access network. The 5G wireless technology can open a greater scope for device manufactures and application developers. In this paper a communication link model has been designed and implemented for 5G communication for the tropical regions. Spatial Diversity Technique has been used to design the communication link model. This model has also been designed using Xilinx system generator and implemented utilizing FPGA kit. As a result, the bit error rate (BER) of the signal gets attenuated from the transmitter as well as from the receiver portion of the aforesaid model. This model relies on the samples per frame, M-Aray number and number of transmitting antennas for rate 3/4 at the transmitter section. It also depends on the computation delay; receive delay, number of receiving antennas for rate 3/4 at the receiver portion. The channel frequency is based on the 5G communication frequency ranging from 600MHz to 100 GHz.
Detection of Brain Tumor using KNN and LLOYED Clustering
Authors:   Pursuing M.E.( E & TC Engineering) in Dr D Y Patil School Of Engineering, Lohegaon Pune, Aiwale Priyanka , Ansari Saniya ,   Associate Professor in Dr. D Y Patil School of Engineering, Lohegaon, Pune
Published: March 2020

Today world the brain tumor is life threatening and the main reason for the death. The growth of abnormal cells in brain leads to brain tumor. Brain tumor is categorized into malignant tumor and benign tumor. Malignant is cancerous whereas Benign tumor is non-cancerous. Diagnosing at earlier stage can save the person. It is actually a great challenge to find the brain tumor and classifying its type. Detection of Brain Tumor and the correct analysis of the Tumor structure is difficult task. To overcome the drawbacks of exiting brain tumor detection methods the proposed system is presented using KNN & LLOYED clustering. Undoubtedly, this saves the time as well as it gives more accurate results as in comparison to manual detection. The proposed method is a novel approach for detection Tumor along with the ability to calculate the area (%age) occupied by the Tumor in the overall brain cells. Firstly, Tumor regions from an MR image are segmented using an OSTU Algorithm. KNN& LLOYED are used for detecting as well as distinguishing Tumor affected tissues from the not affected tissues. Total twelve features are extracted like correlation, contrast, energy, homogeneity etc. by performing “wavelet transform on the converted gray scale image”. For feature extraction DB5 wavelet transform is used.
Smart Helmet using IoT
Authors:   UG Student, Institute of Electronics and Communication, Saveetha School of Engineering, SIMATS, Thandalam, Chennai, India., S P. Brahmendra , Prakash  ,   Institute of Electronics and Communication, Saveetha School of Engineering, SIMATS, Thandalam, Chennai, India.
Published: March 2020

The goal of the adroit guarded top is to give a systems and mechanical social affair to recognizing and revealing mishaps. Sensors, and passed on enrolling frameworks are used for building the structure. The occurrence conspicuous evidence framework gives the accelerometer respects to the processor which dependably screens for unusual combinations. Right when a disaster occurs, the related nuances are sent to the emergency contacts by utilizing cloud based assistance. The vehicle area is acquired by utilizing the general masterminding structure. The framework guarantees a reliable and brisk development of data identifying with the episode constantly and up dated to cloud which are gotten to by IOT. In this way, by utilizing the unavoidable framework which is a striking part for the watchful urban zones, a mind blowing protective top for calamity ID is created.