bluuebunny/crossref_metadata_2025 huggingface dataset:
Frequencies and Lights Affecting IoT Devices
Authors:   Head, Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Haryana, India., Bhatia Shaveta , Singh Rishi ,   Student, Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Haryana, India., Khanna Raas ,   Student, Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Haryana, India, Gupta Madhur ,   Student, Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Haryana, India., Kaushik Vaishnavi ,   Student, Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Haryana, India.
Published: July 2020

IoT devices are everywhere, they are readily available to everyone around the world. These devices are predominately controlled via voice command. During my research I asked how we can prevent these devices from listening to us and are there any security risks associated with them. This led me to find articles on light commands where an intruder can point a laser at your hub and gain access to your IoT devices such as door locks and lights. We dive into the workings of a MEMs devices, which is included in all voice-controlled devices including your phone. We explore ways to attack these voicecontrolled devices in order to gain access to them. Now ways of preventing these devices to listen to us we can project a frequency that our ears cannot hear but these devices can pick up thus interfering with their microphones and improving our privacy without being a hassle to us. The frequency, (40 kHz) we use to jam these microphones theoretically should not be able to interfere with these microphones, but they do because of this frequency shadow that occurs. This shadow frequency is very interesting because you can do various things other than just jamming microphones for example data communication up to 4kbps and even use this in order to prevent unauthorized recordings of live performances and movies at the theaters. This findings can be applied to various fields where privacy is a key factor.
Automated Feature Performance Modelling of Inode Cache
Authors:   Assistant Professor, Electronics and Communication Engineering, JSS Science and Technological University, Mysuru, Karnataka, India., Madappa Eshwari A , S Swathi ,   M.Tech, Networking and Internet Engineering, JSS Science and Technological University, Mysuru, Karnataka, India., Agrawal Mayank ,   Member of Technical Staff at NetApp, Bangalore, Karnataka, India., Anjaneyalu Suresh ,   Member of Technical Staff at NetApp, Sunnyvale, US
Published: July 2020

Inode is one of the subsystems of WAFL(Write Anywhere File Layout) file system. Inode cache is a dynamic subsystem that is percentage factor of available memory. Based on different workflows and the datasets inode cache grows and shrinks. Based on the study of customer related issues it is found that deploying such a workload and datasets at the scale, that customers typically deploy and exercise inode cache for the whole duration of test is very challenging, considering quality assurance test typically focuses on multiple subsystems. Inode cache behavior differs with steady state versus performance disruptive workflows such as volume offline, volume online, volume migration and backup/vault use cases. Based on the behavior observed on the internal test systems it is found inode cache disruptive workflows are exercised only during certain stages but not repeatedly for the duration of test and also it is hard to find out which volume is experiencing performance issues due to inode cache invalidation/shrink/rewarning. In this paper, trying to exercise the performance behavior of inode subsystem like the way customer does and try to monitor and model the subsystem using automation. Here considering the different key attributes and typical operations that effect the inode cache behavior and some of the interested counters statistics that need to be monitored for analyzing the performance behavior of inode cache. Exercising inode cache operations requires constant focus on how the inode cache is performing. Repeat and Rerun some of the targeted workflows for inode cache population invalidation/ shrink operations at constant intervals to model the behavior of the inode subsytem.
MUACLP Modeling Unified Architecture of Cross Layer Parameters Strategy of Handoff for Next Generation Wireless Network
Authors:   Electronics and Communication Engineering B.M.S College of Engineering, VTU, Bangalore, India., Hemavathi  , Akhila S. ,   Electronics and Communication Engineering B.M.S College of Engineering, VTU, Bangalore, India.
Published: July 2020

The Quality of Service and Quality of experience is always a goal of future generation wireless systems. A suitably designed handoff plays an important role in achieving these goals. The traditional methods of handoff for wireless systems pose challenges in handling the smooth transition in the heterogeneous architecture of future generation architecture. This paper induces a model for synchronization of seamless handoff for a mobile user from a unified access point of a large cell to the small cell. The study is carried out considering a novel analytical model for facilitating a better form of vertical handoff mechanism in order to facilitate communication over 5G networks. The modeling is carried out considering the efficiency of channel capacity as well as considering near real-time constraint of latency and throughput. The typical design assumption for the unified architecture of the model for the handoff is for future generation wireless network that includes various physical layer parameters. For an effective analysis, the study considers that the receiving node will be identified on the basis of the non-erroneous node as the idea is to increase the proper utilization of the network resources. The core agenda of the study will be to ensure that irrespective of any form of traffic intensity as well as variable resource availability, the proposed scheme should be able to offer an extensive communication with the seamless performance during handoff operation. The study outcome exhibits that the proposed system offers better vertical handoff performance in contrast to the existing system on various test cases.
Portable Intrusion Detection System
Authors:   Student, Department of Electronics and Communication Engineering, B.N.M Institute of Technology, Bangalore, India, Rao Harshitha Prasad , R Anirudh M. ,   Student, Department of Electronics and Communication Engineering, B.N.M Institute of Technology, Bangalore, India., S Diksha U. ,   Student, Department of Electronics and Communication Engineering, B.N.M Institute of Technology, Bangalore, India., D Bhuvana Suganthi ,   Associate Professor, Department of Electronics and Communication Engineering, B.N.M Institute of Technology, Bangalore, India.
Published: July 2020

Every network connection made is exposed to a security threat. Due to this, crucial, confidential, important information can be lost or even exploited by an intruder. Hence an intrusion detection system (IDS) is needed to detect and notify the network administrators if such an event occurs. Though such systems are present in organizations, it is confined to a device or a rack. In this proposed system, an open source network intrusion detection system called SNORT is installed on to a Raspberry Pi. This is then implemented at a switch level, where it is connected to a configured SPAN port of a switch and is used to monitor the traffic through the switch. This system provides logs and information of the traffic, as well as notifies the network administrator through a message in real time. The intrusion detection system’s portability, ability to notify the administrator, and the display of packet information is what makes this system, more advanced and convenient for any organization’s security.
Density-Based Traffic Control System for Emergency Vehicles using ArtificialIntelligence
Authors:   Student, Department of Electronics and Telecommunications, S.P.I.T, Mumbai, India., Abhang Priyanka , Agrharkar Vinit ,   Student, Department of Electronics and Telecommunications, S.P.I.T, Mumbai, India., Akella Shriya ,   Student, Department of Electronics and Telecommunications, S.P.I.T, Mumbai, India., Bhagat Siddhant ,   Student, Department of Electronics and Telecommunications, S.P.I.T, Mumbai, India., Kaushik Shrishti ,   Student, Department of Electronics and Telecommunications, S.P.I.T, Mumbai, India., Mishra Piyush ,   currently a final year student in pursuing Electronics and Telecommunications Engineering at S.P.I.T, Mumbai. His research interests include Data Science, Machine Learning and IOT, Rao YS ,   Vice-Principal, Department of Electronics and Telecommunications Engineering Sardar Patel Institute of Technology
Published: July 2020

Fire brigade officers, health care personnel, police are often delayed due to traffic congestion, across major cities in India. Considering the predicament, Artificial Intelligence has the potential to enable us to solve such problems by adopting a number of unique perspectives and approaches, especially in this domain. The solution developed by us enables an emergency vehicle driver to select the route to reach the destination as quickly as possible. As cameras are deployed at most of the traffic signals today, especially in cities where traffic congestion is a major pain point, Video Analytics can be used for calculating vehicle count, which will be streamed and updated continually. We create effective algorithms to alter the time of the traffic signals based on this real-time vehicle count, the distance of the vehicle from the signal, the bearing angle made by the vehicle with the signal and also by making sure that the traffic congestion doesn’t increase exponentially and multiple emergency vehicles do not put the system in a deadlock. The loss of life due to accidents and the delay in getting the required treatment must be avoided. The designed system will automatically control traffic light intervals based on vehicle density. This solution will allow an emergency vehicle to reach its destination during emergencies, plying on the best possible route, in the most decongested traffic conditions, which will be facilitated by specifically developed algorithms. To save human life from accidents and unnecessary delays due to traffic congestion, is the main aim of our system.
Log Analyzer for Update Manager
Authors:   Computer Science Department, RVCE, Bengaluru, India, Shetty Shiva Sagar , G Poonam ,   Computer Science Department, RVCE, Bengaluru, India, Ashar Sadhana ,   ISSDC, HPE, Bengaluru, India.
Published: July 2020

Performing System updates is a very tricky and complicated task. You have to update new software on the same old hardware. This may introduce many errors in the system. For example a windows update on a single PC is generally prone to failures. Further updating a server is more challenging job. As a server can support many Operating systems their components, firmware’s and software’s etc, there are many possibilities that a server update may initiate many errors in the system. Thus, this paper proposes a tool that can go through all those thousands of log files generated during an update of a server and finds out where exactly the update went wrong. The paper describes about building a tool to perform log analysis from the scratch. It describes about developing parsers at the backend, building a user interface at the frontend and deploying the tool on to network. The proposed work supports building a Docker for the backend. Docker is a platform as a service product that uses OS-level virtualization to deliver software in packages called containers. The tool takes compressed log file as input. The tool analyses the structure of log file and then parses the contents of the log file according to its structure. Finally the proposed tool generates a report in JSON (JavaScript Object Notation) as well as CSV (Comma-Separated Values) format and that report consists of all the required fields to identify and classify the error that was responsible for failure during system update. This report is sent to concerned software development team to fix the defect that occurred in the update.
MapReduced Based A New Stream Cipher Technique for Data Encryption
Authors:   School of Computational Sciences, S.R.T.M. University, Nanded, India., AL Rummana Galal A. , Shinde G. N. ,   Yeshwant College, Nanded, Maharashtra, India., Al Ahdal Abdulrazzaq H A. ,   School of Computational Sciences, S.R.T.M. University, Nanded, India
Published: July 2020

Nowadays, data keeps increasing; this in turn makes big data one of the hot topics in the modern era of technology. The biggest challenge, however, is big data security and cryptography is one of the most secure techniques. In this proposed model, we use this technique to secure data via a proposed new stream cipher technique to process more than one block by dividing the total size of the block into two parts, and swapping them then, combine and apply XOR operation with key and make some of mathematical operation. This operation is of fifteen rounds which make it very difficult for attacks to guess the plaintext.
Effect of Secondary Raw Material on the Change of Single Extensive Elongation of Non Woven Fabrics
Authors:   Faculty of textile Technology, Tashkent Institute of Textile and Light Industry, Tashkent, Uzbekistan, Patxullaev S.U. , Isaeva D.H. ,   Faculty of Technology of Light Industry and Design, Tashkent Institute of Textile and Light Industry, Tashkent, Uzbekistan, Shumqorova Sh.P. ,   Faculty Technology of light industry, Jizzakh polytechnic institute, Jizzakh Uzbekistan, Yodgorova X.I. ,   Faculty Technology of light industry, Jizzakh polytechnic institute, Jizzakh, Uzbekistan, Orazbayeva R.I. ,   Faculty Technology of Textile, Tashkent Institute of Textile and Light Industry, Tashkent, Uzbekistan
Published: July 2020

The article describes research studies in the laboratories of the departments of "Spinning Technology" and "Silk Technology". For this purpose were taken samples of cotton fiber and silk waste from the carding machine in the spinning process, 100% cotton fiber waste, 50% cotton fiber, 30% silk, 20% mulberry bark fiber, 70% cotton fiber, 15% silk, 15% mulberry bark fiber, non-woven fabrics were produced from 75% cotton fiber 10% silk 15% mulberry bark fiber blends. The single-period elongation deformation of the obtained non-woven fabrics was determined using the device "Stoyka".
Multi User Chat Application
Authors:   Electronics and Communication Engineering, National Engineering College, Kovilpatti, Tamil nadu., Gayathri R. , Kalieswari C. ,   Electronics and Communication Engineering, National Engineering College Kovilpatti, Tamil nadu
Published: July 2020

The latest development of the Internet has brought the world into our hands. Everything happens through internet from passing information to purchasing something. Internet made the world as small circle. This project is also based on internet. This paper shows the importance of chat application in day today life and its impact in technological world. This project is to develop a chat system based on Java multithreading and network concept. The application allows people to transfer messages both in private and public way .It also enables the feature of sharing resources like files, images, videos, etc.This online system is developed to interact or chat with one another on the Internet. It is much more reliable and secure than other traditional systems available. Java, multi threading and client-server concept were used to develop the web based chat application. This application is developed with proper architecture for future enhancement. It can be deployed in all private organizations like Colleges, IT parks, etc.
A Juxtaposition Between Integer Wavelet Transform and Discrete Wavelet Transform for Secure Image Steganography
Authors:   School of Electronics Engineering,, Vellore Institute of Technology, Vellore, India., Ranjan Ravi , Thirani Subham ,   School of Electronics Engineering,, Vellore Institute of Technology, Vellore, India,, Priyadarsini M.Jasmine Pemeena ,   School of Electronics Engineering,, Vellore Institute of Technology, Vellore, India,, Rajini G.K. ,   School of Electronics Engineering,, Vellore Institute of Technology, Vellore, India,, Jabeena A. ,   School of Electronics Engineering,, Vellore Institute of Technology, Vellore, India,
Published: July 2020

Image steganography is a technique that is used to hide information. The information can be of various types like image, video, or audio. Steganography is done so that no one apart from the correct receiver can retrieve the information. This paper consists of all advantages and highlights of the wavelet transform but with the additional features like randomness and some default values that are already built-in it. Various algorithms can be used in steganography and they provide good hiding capacity and low detectability. Here we have hidden the image into the cover image using Integer Wavelet Transform (IWT) and also using Discrete Wavelet Transform (DWT) and compared which technique gives better results. It is very difficult to predict the presence of a hidden image inside the stego image since it looks exactly like the cover image. There is no loss in quality from the secret image to the extracted image since the PSNR (Peak Signal to noise ratio) is high for both of them. This process was done using both DWT and IWT and the results prove that that the IWT technique is not only simpler but also more efficient than the DWT technique since it gives higher PSNR values. Through the proposed algorithm, an increase in the strength and imperceptibility is noticed and it can also maintain various transformations such as scaling, translation, and rotation with algorithms that already exist. The final results, after comparing both the transforms prove that the algorithm which is being proposed in IWT is indeed effective
Human Activity Recognition Methods
Authors:   ECE, S.E.A College of Engineering and Technology, Visvesvaraya Technological University, Bangalore, Karnataka, India., S Dhivya Karunya , Kumar Krishna ,   ECE, Gopalan College of Engineering and Management, Visvesvaraya Technological University, Bangalore, Karnataka, India.
Published: July 2020

Human action in a video based application plays a significant role that alerts the researchers towards recognizing the motion of human. Other video applications also have video content extraction, summarization, and human computer interactions. The existing methods needs manual footnote of pertinent portion of actions of our interest. Recognition of human action can be done authentic without physical commentary of applicable parts of action of any one’s interest. In this paper we try to update the previous reviews on many ways of recognizing Human activities in videos that had different techniques like Hidden Markov model, feature extraction, segmentation etc. the recognition of human activity in applications like visual observation in mobile, human fall detection, video conference, robotics.
Design of Cost effective QoL Infotainment System
Authors:   Department of Computer Science and Engineering, University of Dhaka, Dhaka, Bangladesh., Bhattacharya Arunava , A. Jabeena ,   Department of Computer Science and Engineering, University of Dhaka, Dhaka, Bangladesh.
Published: July 2020

In vehicle infotainment (IVI) systems are becoming increasingly popular in vehicles. It is less a modern luxury and more a utility as the quality of life (QoL) of the average individual improves. The aim of this project is to attempt a more efficient design with low cost hardware that improves the Quality of Life (QoL) of the driver and passengers of a vehicle. The method of design is to use commonly available resources and appropriately interfacing them to create an infotainment system that collects, displays and stores information. The collection of information is local, the display is both local and over a cloud, and the storage is over a cloud. The data collected by the sensors could also be processed according to a manufacturer at either the microcontroller, or the phone application, and relevant information can be displayed on an attached screen and on the cloud for analysis by a manufacturer
Effect of Alccofine and Zeolite on the Properties of Concrete Containing Polypropylrne Granules
Authors:   Assistant Professor, Department of Civil Engineering, Princeton Instuite of Engineering and Technology for Women, Hyderabad, India., Geetha Kurendha , Rajani Akula ,   Assistant Professor, Department of Civil Engineering, Princeton Instuite of Engineering and Technology for Women, Hyderabad, India
Published: July 2020

Reinforced concrete structures are affected by various durability problems during their service life. Innovative materials are required in the field of concrete technology for the better construction of the structure. Keeping in view, the present work has been carried out by replacing the cement partially with mineral admixtures namely, Alccofine and Zeolite in different concentrations and by incorporating Polypropylene granules to the concrete. In the present investigation the specimens were divided into three sets. One made with only OPC as binder i.e. conventional mix, second made with OPC and Alccofine/ Zeolite together i.e. binary mix and, third made with OPC, Alccofine and Zeolite together i.e. ternary mix. The varying percentages of Alccofine and Zeolite has been taken as 10% and 15% as a replacement of cement and the polypropylene granules has been fixed at constant 1% for all mix proportions of concrete. The w/c ratio was adopted as 0.45. DOE method of mix design has been adopted. The compressive strength, flexural strength and tensile strength tests have been conducted after the curing period of 28 and 56 days. Results showed that Concrete with 15% replacement of cement by Alccofine and 10% replacement of cement by Zeolite along with 1% Polypropylene granules had shown significant improvement in various mechanical properties at the age of 56 days. It was also observed that concrete with 15% replacement of cement by Alccofine along with 1% Polypropylene granules had shown significant improvement in various mechanical properties at the age of 28 days. Thus, the conjoint presence of Alccofine/Zeolite along with polypropylene granules yields better than concrete without any admix.
Automated Essay Grading System using NLP Techniques
Authors:   Student, Department of Computer Science, K. J. Somaiya College of Engineering, Vidyavihar, Ghatkopar East, Mumbai, Maharashtra, India., Shetty Pramit , Yadav Kaushal ,   Student, Department of Computer Science, K. J. Somaiya College of Engineering, Vidyavihar, Ghatkopar East, Mumbai, Maharashtra, India., Kunder Prithvi ,   Student, Department of Computer Science, K. J. Somaiya College of Engineering, Vidyavihar, Ghatkopar East, Mumbai, Maharashtra, India.
Published: July 2020

The purpose of the study is to develop an automated essay grading system (AES) which can grade students essays based on various factors. Our proposed system performs grading of essays based on two features. Simple features consist of finding syntactic errors such as spelling mistakes, grammatical errors, punctuations and sentence proportions. Complex features consist of finding semantic errors through discourse analysis, thematic analysis and detection of undesirable style of writing. Many existing AES systems fail to consider the semantic parts of the essay which is addressed in this study. Calculation of score would be done based on what is specified in rubrics. The proposed system is evaluated using datasets from kaggle. The accuracy of model and obtained results show an agreement with teachers’ grading. This gives us an indication that the model can be deployed for assessment of students’ essay, thereby leading to reduction in time, efforts and cost for evaluating an essay.
Fast Discrete Curvelet Decomposition with Gradient Fusion Based Technique for Pansharpening of Multispectral Image.
Authors:   Associate Professor, Department of ECE, Vivekananda Institute of Technology, Bangalore,, P Leelavathi H , Prakash J ,   Prof and Head, Department of ISE, Bangalore Institute of Technology, Bangalore, Karnataka State, India
Published: July 2020

The Process of improving the local details of multispectral image using the information captured from different image sensors is called pansharpening. In this paper, the information captured from three different satellite sensors such as synthetic aperture radar (SAR), multispectral (MS) and panchromatic (PAN) of the same scene is combined effectively using the proposed a novel approach. This approach consists of three stages of fusion scheme, where block based wrap fast discrete curvelet decomposition technique is used in the first stage, which results an intermediate PAN image that contain the almost complete spatial details of SAR image and nonadaptive sparse details of the SAR and PAN images. Next the gradient fusion based technique is used to combine the SAR and an intermediate PAN image which retains more information in the PAN-SAR (PS) fused image. Further pansharpening of the MS image is accomplished by using the hybrid technique which is based on injecting the primary and secondary high frequency components into the original MS image. In this algorithm, the high frequency details are extracted by taking difference between the PS and synthesized intensity image, then the extracted high frequency details are modulated by local adaptive and post processing fusion parameter. The experimental outputs reveal that the proposed algorithm results better performance than other techniques by providing more spatial information in multispectral image while preserving the spectral details and has the potential characterize urban areas in a fused image in a better way.
Color Based Object Sorting System using Deep Learning
Authors:   Junior, Department of Electronics and Communication Engineering, VIT University, Vellore, India., Roy Pratik , Roy Satakshi ,   Student, Department of Electronics and Communication, Vellore Institute of Technology, Vellore, India., Agrawal Rahul ,   Student, Department of Electronics and Communication, Vellore Institute of Technology, Vellore, India., Sharma Sonal ,   Student, Department of Electronics and Communication, Vellore Institute of Technology, Vellore, India.
Published: July 2020

Object sorting is a very common industrial application but at the same time it is a tiresome process as handling so many objects is a menial task which is not so promising in maintaining consistency and thereby arising quality issues. Object sorting, if done manually, is not only time consuming but also it seems to be an uphill task pragmatically. Nowadays amid various technological advancements, industries have become fully automated so an automated sorting system is essentially required to replace this conventional system of manual sorting knowing that this process can be made completely autonomous by properly channeling the use of technology. The main objective of this paper is to propose a smarter, intelligent and cost-effective object sorting system which categorizes the objects based on their respective color and will place them at their designated locations to minimize the cost and optimize the productivity. We have implemented the sorting system using Raspberry pi (an open-sourced Linux based board) interfaced with a camera module along with some side electronic circuitry such as servo motors and sensors. The color recognition is done using the IBM Watson visual recognition model where we have uploaded the dataset of captured images. For picking and sorting the objects, we have made use of a robotic arm that will rotate with the help of servo motor up to certain angles.
Sarcastic Sentiment Detection with Fuzzy Logic
Authors:   Information Technology Department Marathwada MitraMandal's, College of Engineering, Pune, Bidve Vijaykumar S. , Pathak Kalyani ,   Information Technology Department Marathwada MitraMandal's, College of Engineering, Pune, Bhagwat Kruttika ,   Information Technology Department Marathwada MitraMandal's, College of Engineering, Pune, Suryawanshi Karishma ,   Information Technology Department Marathwada MitraMandal's, College of Engineering, Pune
Published: July 2020

In the context of text classification of sentiment detection to great, instances are naturally fuzzy and therefore to get clear-cut outcome by extracting the opinion in a new innovative way i.e. In a fuzzy combination way and assign a relevant sentiment, usually either positive or negative. Due to this new approach it will be possible to have advancement for extracting the opinions of people more deeply even if instance in a sentences are manipulated more complexly.
Object Detection using Convolutional Neural Network and Extended SURF with FIS
Authors:   Computer Science & Engineering, Jahangirnagar University, Savar, Dhaka, Nuzhat Adila , Tabassum Fahima ,   Institute of Information Technology, Jahangirnagar University, Savar, Dhaka., Islam Md. Imdadul ,   Computer Science & Engineering, Jahangirnagar University, Savar, Dhaka.
Published: July 2020

The aim of the paper is to detect object using the combination of three algorithms: convolutional neural network (CNN) and extended speeded up robust features (SUFR) and Fuzzy inference system (FIS). Here three types of objects are considered: first, we consider RGB images of hundred different types of objects (for example anchor, laptop airplane, car etc.) taken from benchmark database; second, we take grayscale images of human fingerprint from recognized database; third, Bangla handwritten alphabet from standard database. In this paper we extend the SURF algorithm then the result of the extended SURF is applied in FIS to enhance accuracy of detection. Finally, three algorithms are combined and the accuracy of detection of combined technique is found better than individual one. The combined algorithm provides the average recognition rate for objects of first case as 94.21%, for human finger print as 92.17%%, for Bangla letter as 92.38% and for the Bangla digit as 93.69%.
Monitoring & Controlling of Information against Unethical Hacking using Effective Machine Learning Techniques
Authors:   Research Scholar, Computer Science And Engineering , Acharya Nagarjuna University, Nagarjuna Nagar, Guntur, Andhra Pradesh, India., Pullagura Sudheer , Srinivasu S.V. Naga ,   Professor, Dept. Of CSE , Narasaraopeta Engineering College, Narasaraopet , Andhra Pradesh, India
Published: July 2020

Many services are currently utilizing AI estimates to pick high-stake options. Determining the proper selection unequivocally relies on the rightness of the relevant information. This fact offers encouraging motivators to hackers to attempt to mislead Artificial Intelligence estimations through managing the relevant information that is taken care of to the estimates. But at that point, standard AI computations are certainly not wanted to become protected while encountering surprising details resources. At the moment, deal with the concern of ill-disposed AI; i.e., our experts will most likely generate risk-free AI calculations robust within the attraction of a loud or an adversely managed information. Ill-disposed Artificial Intelligence will be even more screening when the perfect turnout has a mind-boggling framework. At this moment, noteworthy limelight gets on adversarial AI for preparing for organized returns. To begin with, our team build up yet another calculation that dependably carries out accumulated collection, which is an organized expectation concern. Our discovering approach works and also is described as a curved square system. This method is sure about the desire calculation in both the closeness as well as the absence of an opponent. Next off, our team looks into the problem of criterion learning for strenuous, coordinated projection models. This technique develops regularization capacities dependent on the restrictions of the adversary. Now, illustrate that durability to the command of details corresponds to some regularization for a tremendous edge arranged assumption and the other way around.A typical device commonly either requires more computational capability to structure a clear-cut best assault, or it doesn't have adequate records about the trainee's design to accomplish, therefore. Consequently, it routinely tries to use many unnatural changes to the payment to a desire to bring in an accomplishment. This reality advises that on the occasion that our experts confine the usual lousy luck job under ill-disposed commotion, we will get vitality against ordinary opponents. Failure preparing seems like such an outcry mixture circumstance. Our experts calculate a regularization technique for an enormous edge parameter, discovering depending on the failure system. We stretch out dropout regularization to non-straight parts in a handful of oneof-a-kind means. Empirical analyses show that our systems reliably pounded the standards on a variety of datasets. This proposition integrates a recently dispersed and individual coauthored component.
Credit Card Fraud Detection using Deep Learning based on Neural Network and Auto encoder
Authors:   Department of Electronic and Communication, Usha Mittal Institute of Technology, SNDT University, Mumbai, India., Sharma Priyanka , Pote Santoshi ,   Department of Electronic and Communication, Usha Mittal Institute of Technology, SNDT University, Mumbai, India.
Published: July 2020

Credit card fraud is an event problem and fraud detecting techniques getting more sophisticated each day. Mainly internet is becoming more common in almost every domain. Online transactions, shopping, and e-commerce are expanding step by step. Due to which in the online payment system, fraudulent activities have also increased. It has cost banks and their customers a loss of billions of rupees. The techniques used now a day detects the anomaly only after the fraud transaction takes place. The intruders have found ways to crack the system loopholes and defeat the security. These frauds are not consistent in their actions, they constantly alter. Thus, Artificial Intelligent (AI) algorithms are used to detect the behavior of such activity by learning the past behavior of the transaction of the users. An unsupervised algorithm is used to detect online transactions, as fraudsters commit fraud once by online media and then move on to other techniques. This paper discusses the performance analysis and the comparative study of the two Deep Learning algorithms which include auto-encoder and the neural network. In this paper accuracy, precision, recall, and AUC curve are considered as a model evaluation factor.
A Robust Blockchain Framework for Healthcare Information System
Authors:   Information Technology, PSG College of Technology, Coimbatore, India., Dharani D. , Kumari K. Anitha ,   Information Technology, PSG College of Technology, Coimbatore, India, Aishwarya S. ,   Information Technology, PSG College of Technology, Coimbatore, India, Sangavi G. M. ,   , Information Technology, PSG College of Technology, Coimbatore, India., Lavanya N. ,   Information Technology, PSG College of Technology, Coimbatore, India.
Published: July 2020

Nearly every organization needs solution to handle sensitive data. Though there are different systems to store and transmit electronic records, users often deal with missing or tampered information when they distribute it in a public network. When the data is distributed, the traceability and governance of it throughout the globe is impractical. The evolving world of Data Security demands healthcare industry to have an infrastructure in place to deal with patient records. Regardless of the nature of present and future security risks, Blockchain Technology will play a vital role to maintain the originality of the digital data. Blockchain stores data in a decentralized, distributed ledger for achieving immutability and transparency. The system analyses a case study which aims at maintaining Healthcare records in Blockchain ledger to facilitate secure storage of the patient’s details. For efficient prediction of diabetes the Blockchain and machine learning algorithms are integrated. The various other applications of combining Blockchain technology with machine learning algorithms are Smart city applications, Forensic information storage systems, Energy data management systems, banking and finance management systems.
Performance Analysis of Energy Efficient Distributed Cluster Routing Techniques in Wireless Sensor Networks
Authors:   Research Scholar, Dept of ECE, NIE Institute of Technology, Mysuru, Karnataka, V Harish S.
Published: July 2020

Wireless sensor network consists of small sensing nodes having unique characteristics in networks field and energy awareness routing for communication capabilities, computational power consumption. A wireless sensor network (WSN) is a grouping of sensor nodes in a network that perform to support Sensing, Signal processing, Communications and Connectivity for data processing and transmit the information to the destiny (Base station) through neighboring nodes with the help of energy source (batteries). The batteries used in WSN neither to be recharged nor be replace. It is necessary to extend the network lifetime for better performance. Many protocols have their own specific design but major issue is energy awareness. Based on number of nodes present in the field and the speeds at which the multiple parameters like Packet delivery ratio, network lifetime, overhead control are compared. In this paper, the proposed protocol is an efficient energy routing protocol which tries to provide fairness in network. Simulation results through MATLAB are presented.
Edge Detection Enhancement Based on Filtering and Threshold Estimation
Authors:   Al-Imam Mohammad Bin Saud Islamic University, College of Computer Science. Riyadh, Saudi Arabia., Alshalfan Khalid , Zakariah Mohammed ,   King Saud University, College of Computer Science and Information, Riyadh, Saudi Arabia.
Published: July 2020

An edge detection is a critical tool under image processing and computer vision. It is used for security and reliability purposes to provide enhanced information about an object and recognize the contents of the image for the applications of object recognition in computer vision. The most prominent application may be pedestrian detection, face detection, and video surveillance. Traditional edge detection method has many issues that are discussed in this paper. In this study, we enhanced the edge detection technique by applying filtering and detecting the threshold values to differentiate between different contrasts in the image. Differential operations are used to detect two adaptive thresholds on the histograms of the images. We have examined this technique on three databases Pascal, Corel, and Berkeley. The results obtained were then examined with qualitative and quantitative assessments test. Entropy, Mean Squares Error, and Peak Signal to Noise Ratio values were examined and it gave better results.
Signal Processing and Analysis of a Person on the Basis of Time, Age and Gender
Authors:   Research Scholar, Department of MSIT, MATS University, Raipur (C.G), India., Khalid Taiba , Narain Bhavana ,   Associate Professor, Department of MSIT, MATS University, Raipur (C.G.), India.
Published: July 2020

Nowadays, signal processing is very common in machine learning. Tools like MATLAB and PRAAT made this really easy. Best example is google search using voice, this can be mostly beneficial for illiterate people and children. I have collected the sample of speech of 160 people of different age group, different genders, and at different and constant time as databases and then these databases are analysed.. Each database consists of samples of human speech uttering the same first 10 alphabets of hindi varnamala .I have used two parameters i.e. formants and intensity for analysing the results of database.I have also characterized it into the form of constant time and variant time. Our aim is to identify the voices of a person on the basis of age and gender through different paremeters like frequency and formants
Unstructured Data Processing using Spark for Topics Modelling
Authors:   Computer science and Engineering, Alakh Prakash Goyal Shimla University, Shimla, India., Sokegbe Adjovi Irène , Nainwal Ayushi ,   Computer science and Engineering, Alakh Prakash Goyal Shimla University, Shimla, India.
Published: July 2020

Information Technology domain is facing changes day by day. Furthermore, the size of data increases, as well as the demand to process them. There are two types of data: structured and unstructured data. The multiple sources and the variety of data today involve the use of “Big data” instead of data. It is related that 80% of enteUprise’s data is unstructured [1]. However, the procedures to handle unstructured data are more complex than those for structured data. Thus, it becomes necessary to have a clear idea about this type of data and to know how to extract useful information from this data set. In this paper we will study how to retrieve useful information from unstructured data in E-commerce area using data analysis tools: Spark. To solve this issue, first an overview on structured and unstructured data and data analysis is provided, then information retrieval algorithm will be implemented using Spark MLlib tool in order to determine for a set of reviews, negative or positive, which subjects are more discussed by the customers. This study is needed in order to improve business based on customer satisfaction reviews. In that case, Unsupervised Machine Learning Latent Dirichlet Allocation (LDA) algorithm constitutes our model. Finally, the evaluation of the model will be given based on some parameters.
Grebeg Sudiro dan Representasi Keberagaman di Sudiroprajan, Kota Surakarta
Authors: Hakim Latifa Dinar Rahmani
Published: July 2020

Several studies stated the role of government is one of the keys that influence success in overcoming diversity in a plural society. Through the case study in Sudiroprajan village, this study aims to explain the success of overcoming the problem of diversity not only because of the role of the government, but through community involvement. Using a qualitative approach, the results of this study show that the Sudiroprajan community collective awareness is an effective way to overcome the problem of diversity that has the potential to cause conflict. Collective awareness is built through socio-economic similarity, historical experience, needs and acceptance, interaction and negotiation. The building of collective awareness in the Sudiroprajan community is able to produce diversity products in the form of the Grebeg Sudiro tradition. The Grebeg Sudiro tradition has become a symbol of the Sudiroprajan village diversity as well as a medium of diversity for people outside the village.
Strategi Optimalisasi Pembiayaan Mudharabah Pada Bank Syariah
Authors: Gurhanawan Gurhanawan
Published: July 2020

Islamic banks provide mudharabah financing to foster the business. This service is offered to various scale of business, encompassing smaller or larger ones. However, the amount of mudaraba financing is less prevalent than the murabaha financing, in which the latter aimed for consumptive purpose. This paper aims to determine the constraints of Islamic banks in promoting mudarabah and optimizing it as one of the means to proliferate individual financial independence through owning a business. The study  uses a field research which is descriptive qualitative in nature. The findings are corroborated  using SWOT analysis to discover internal and external factors related to Mudharabah. Primary data  are obtained interviews with related parties in Islamic banks. Secondary data is also utilized  and obtained through literature studies. The results show that the strategy established by Islamic banks in optimizing mudharabah financing by implementing the linkage program. Islamic banks cooperate with BPRS and Cooperatives using mudharabah contracts, then BPRS and Cooperatives distribute the fund to the  public in, improving the economc activities.
Habitabilidad y relaciones socio-espaciales en conjuntos habitacionales de interés social. Casos de estudio en Ensenada, Baja California, México
Authors: Organista-Camacho Mariel , Tello-Peón Lucía
Published: July 2020

El estudio de la habitabilidad debe considerar requerimientos existenciales,proxémicos y contextuales en donde se propicie el bienestar humano a partir de lasrelaciones socio-espaciales. El objetivo del presente artículo es mostrar los hallazgosde la estimación de habitabilidad en conjuntos habitacionales de interés social en laciudad de Ensenada, Baja California. Se considera un enfoque metodológico mixto.Se desarrolla y aplica cuatro instrumentos de análisis: cuestionario de habitabilidad,test de técnicas proyectivas, bases de datos y fotografías terrestres y aéreas. El modeloteórico de habitabilidad se basa en siete dimensiones: subsistencia, protección, afecto,entendimiento, participación, identidad y libertad. Se seleccionaron cuatro conjuntoshabitacionales con un total de 5 443 viviendas de interés social. Se aplicaron al azar266 cuestionarios. Los resultados mostraron un patrón de baja o nula participación.La fragmentación espacial se presenta como vía de protección ante la inseguridad.La horizontalidad del conjunto favorece a cinco dimensiones de la habitabilidad (subsistencia, protección, afecto, entendimiento e identidad) y mejora la percepciónde las condiciones socio-espaciales hacia el interior del conjunto; mientras que en losconjuntos verticales fue mayor la relación con los espacios exteriores y la ciudad. Seconcluye que la habitabilidad depende de un complejo entramado de mediacionesentre lo privado, lo común y lo público. El entorno condiciona las relaciones sociales,las cuales se consideran impersonales, apresuradas y de conveniencia. En lo espacial,se presentan espacios dispersos, desorganizados y fragmentados que funcionan comomedio de transición, lo que afecta negativamente a la habitabilidad.
Concreción urbana-arquitectónica de los asentamientos derivados de la colonización del siglo XIX en México
Authors: Aguilar-Méndez Carlos , Arista-González Gerardo
Published: July 2020

El siglo XIX en México se caracterizó por el poblamiento del territorio, conénfasis en la parte norte, derivado de una política colonizadora ejecutada por extranjeros.El objetivo de este trabajo es explicar el surgimiento y los grados de consolidación quepresentaron los asentamientos poblacionales derivados y coadyuvar en el entendimientode su trascendencia.La metodología aborda el periodo de 1880 a 1910 con base en la aplicación de la políticacolonizadora. Se comienza con el análisis de la concreción espacial de la legislación y laidentificación de las colonias emanadas. Posteriormente se muestra la caracterización decuatro casos de estudio y un análisis comparativo de su medio físico, los habitantes, suscaracterísticas urbanas y arquitectónicas.Como resultado se vislumbró que la política colonizadora fue basada en especulaciones alfirmarse 201 contratos y concretarse sólo 44 colonias. Los proyectos resultantes tomaroncomo base el modelo urbano estadounidense con cánones tendientes a la funcionalidady racionalidad del espacio. La arquitectura introducida fue adecuada con base en losmateriales y las características climáticas de la región. El aspecto social se derivó de lasintenciones de los desarrolladores, los habitantes y el gobierno mexicano.Se concluye que las características físicas de los proyectos coadyuvaron en el desarrollo delas poblaciones y la previsión de su futuro crecimiento a costa de una homogenización;la dimensión social, caracterizada por la discordancia de las intenciones de los actores,influyó en la apropiación del espacio y su crecimiento urbano y demográfico derivandoen distintos grados de consolidación.