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The task of identifying humans by their voice seems to be an easy task for human beings as people interact with a particular person, their mind is upskilled with that voice and the brain becomes proficient enough to easily recognize that particular voice next time. Using this human mind concept, the structure is designed and implemented. In the proposed system Convolutional Neural Network (CNN) has been used. 110 voice samples from 11 different participants/speakers have been collected. These voice signals were converted into the form of an image of the signal spectrogram. 90% of data were used for training and the remaining 10% was used for testing. Implementation was done in RStudio with R programming language. The system achieved 82% accuracy. The proposed system is facile and lucrative.

Convolutional neural network, speaker recognition, Keras, voice signal spectrogram, tuneR

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Sandeep Kumar, Samridhi Dev, "Speaker Recognition System Using Deep Learning with Convolutional Neural Network," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.60-64, 2020.

Wireless communications at its core is all about convenience – making it easy to apply a wide variety of network typologies quickly, easily, and cost-effectively. We often think of wireless in terms of a mobile device talking to a base station or access point – the point-to-multipoint topology, plus handoff between cells. And, normally, the interconnections between those cells use wire or perhaps a different form of point-to-point wireless. Suppose instead that the required interconnect was implemented as a form of relay, with one cell simply redirecting traffic wirelessly to the next, making it possible to implement almost any configuration; that’s the domain of the wireless mesh. In this research a mechanism on mobile data offloading using wireless mesh networks is performed. In which one source node is connected with a sink node or we can say base station for communication. When there is a traffic in between the communication then the source node can change their base station or sink node. This mechanism is shown in further results.

Mobile data offloading, HetNets, Queuing Theory, Incentive Schemes, Request Routing

[1] Apostolaras, A., Iosifidis, G., Chounos, K., Korakis, T. and Tassiulas, L., 2014, December. C2M: Mobile data offloading to mesh networks. In 2014 IEEE Global Communications Conference (pp. 4877-4883). IEEE.
[2] Ajith, A. and Venkatesh, T.G. Mobile Data Offloading for Streaming-Class Traffic with QoS Guarantee. International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 7(4), pp.26-42, 2015.
[3] Andrews, J.G., Singh, S., Ye, Q., Lin, X. and Dhillon, H.S. An overview of load balancing in HetNets: Old myths and open problems. IEEE Wireless Communications, 21(2), pp.18-25, 2014.
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[15] Kazdaridis, G., Keranidis, S., Fiamegkos, A., Korakis, T., Koutsopoulos, I. and Tassiulas, L., Dynamic Frequency Selection through Collaborative Reporting in WLANs.

Shubham Pathania, Jatinder Singh Saini, "A Mechanism for Mobile Data Offloading to Wireless Mesh Networks," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.65-70, 2020.

Novel coronavirus (COVID-19 or 2019-nCoV) pandemic which doesn’t have neither a clinically proven vaccine nor drugs. As the No. of Cases Increasing Day by Day, the public was panicking. In the process of increasing Number of Tests, Some Rapid tests are also Taking place. If you take these rapid tests into consideration, where we are getting false results like False Positives, True Positives which results in a panic among the people who have tested. Due to these false results, the public was in a panic situation. To avoid that panic among the public, we define machine learning approach to predict the COVID where it represents False Positive rate, and True Positive rate through ROC(Receiver Operating Characteristic) curve and, we also get a Confusion Matrix which visually represents True Negatives, False Positives, False Negatives and True positives and it also generates a new dataset from a given dataset, by eliminating them without sampling using clinical spectrum data of ‘SARS-Cov-2 exam result’.

Logistic Regression, ROC (Receiver Operating Characteristic) Curves, Confusion Matrix

[1] Jay Furst-“False-negative COVID-19 test results may lead to a false sense of security”. Source: mayo clinic
[2] Steven Woloshin, M.D., Neeraj Patel, B.A., and Aaron S. Kesselheim, M.D., J.D., M.P.H.-“False Negative Tests for SARS-CoV-2 Infection — Challenges and Implications, Journal published on June 5, 2020, in The New England Journal of medicine”.
[3] John Wiley& sons “Machine Learning: Hands-on for Developers and Technical Professionals”
[4] Lin Jia Kewen Li?Yu Jiang Xin Guo Ting zhao, "Prediction and analysis of Coronavirus Disease", Populations and Evolution, 2020.
[5] Sanjib Halder “A Mathematical Model to Forecast & Compare Covid-19 Outbreak in Male & Female using Polynomial Regression Analysis”-IJCSE ,vol.8,issued on 5,May 2020.
[6] Saroj S. Date “Forecasting novel Covid-19 confirmed cases in India using Machine Learning Methods” –IJCSE, vol.8, issued on 6,June 2020.

M. Vennela, G. Lavanya Devi, P.R.S. Naidu, "Analysing COVID- 19 Cases by Eliminating False Negatives and False Positives through Machine Learning Approach," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.71-74, 2020.

This paper describes an approach to overcome a situation of monitoring and managing a parking area using arduino based effective parking management system. With the rapid increasing of cars the need to find available parking space in the most efficient manner, to avoid traffic congestion in a parking area become difficult. This paper aimed at develop a effective car parking management system that is more cost effective and user friendly existing system, confusion free and easy parking. The main purpose of effective parking system is to reduce time to locate the parking areas, hence it reduce fuel consumption. The system counts the number of cars in any parking places and checks if there’s any vacancy. The first phase aimed at making cars datable in the parking lot through the use of sensor used for searching the unoccupied parking facility. The discussed system will be able to reduce the problems which are arising due to unavailability of a reliable, efficient and modern parking system, while the economic analysis technique will help in analyzing the project feasibility.

Arduino UNO, infrared sensor, LCD display, Servo motor, proteus professional

[1] Mr. Vedant Chikhale, Mr. Raviraj Gharat, Ms. Shamika Gogate, Mr. Roshan Amireddy, “Smart Car Parking Using Arduino Microcontroller ,” International Journal of New Technology and Research (IJNTR), Volume.3, Issue.6, June 2017 .
[2] Suvarna Nandyal, Sabiya Sultana , Sadaf Anjum, “Smart Car Parking System using Arduino UNO,” International Journal of Computer Applications, Volume.169,issue No.1, July 2017.
[3] Simple Batra, “IoT-Future Smart Systems,” International Journal of Computer Sciences and Engineering” Vol.6, Issue no.5, May 2018.
[4] V. Manideep Goud1, B. Srinivas Rao2, “Smart Car Parking System based on RFID,” International Journal of Computer Sciences and Engineering, Vol..7, Issue no.8, Aug 2019.
[5] Kusay F.Tabatabaie, Sadeer D. Abdulameer, “Applying Arduino For Controlling Car Parking System,” Journal of Applied Computer Science Methods, vol. 15, no. 2, July 2019.
[6] Himani Malik1, Gourav Nagpal, “Smart Parking Using Internet of Things”, International Educational Applied Research Journal, volume. 03, issue. 09, sep 2019.
[7] Mohammed Omar BA. Sabbea, Muhammed Irfan, Saeed Karama Altamimi, Saeed Mabkhot Saeed, A. H. M. Almawgani, Hisham Alghamdi,“Design and Development of a Smart Parking System,” journal of automation and control engineering vol. 6, issue no. 2, december 2018.
[8] Shruthi Mudaliar, Shreya Agali , Sujay Mudhol , Chaitanya K Jambotkar, “Iot Based Smart Car Parking System”,( IJSART),volume.05, issue .01,january 2019.
[9] J. Cynthia, C. Bharathi Priya, P. A. Gopinath , “iot Based Smart Parking Management System,” International Journal of Recent Technology And Engineering, (IJRTE), volume.7, issue.4, november 2018.
[10] Fei-Yue Wang, Liu-Qing Yang, Fellow, Jian Yang, “ Urban Intelligent Parking system based on Parallel Theory”, IEEE-ICNC, 2016.
[11] .Shubham Kumar, Deepak Rasaily , Mohit Mukhia, Aarfin Ashraf “Biometric Attendance System using Microcontroller” International Journal of Engineering Trends and Technology (IJETT) Volume. 32 ,issueNumber.06, pp. 306-308, February 2016.
[12] Shweta Chanda, Deepak Rasaily, Prerna Khulal “Design and Implementation of a Digital Code Lock using Arduino” International Journal of Engineering Trends and Technology (IJETT) Volume. 32 ,issue Number.05, pp. 213-215, February 2016.
[13] suman Poudyal, Rajena Pradhan, Deepak Rasaily, Sabina Sharma, Tenzing Sherpa, Mukesh Kumar Sharma, Abishek Pradhan “Wi-Fi Based Scrolling Digital Display With RTC using Arduino” 2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)2019.
[14] Donald Rai, Nitesh Kumar, Deepak Rasaily, Pravin Gurung, Tenzing Wangmu Tamang, Chandan Chettri, Palman Kami, Ganden Bhutia “Arduino-GSM Interfaced Secure and Smart Cabin for Smart Office” 2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT) 2019.
[15] Ashis Rai, Manjil Rai, Nisha Jogi, Bikash Rai, Shahil Rai, Deepak Rasaily “Low Cost Laser Light Security System in Smart Home” 2019 International Conference on Innovative Sustainable Computational Technologies (CISCT) Year: 2019.
[16] Yashal Dorzee Lepcha, Deepak Rasaily, Jigmee Sherpa “Design of Electronic Voting Machine using Microcontroller” International Journal of Engineering Trends and Technology (IJETT), Volume.32, Number.5,February 2016.

Robin Chettri, Deepak Rasaily, Shyam Chhinal, Bikash Rai, Gulsan Sharma, Greacy Lepcha, "Effective Parking Management System Based On Search and Occupy Algorithem Using Arduino UNO," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.75-79, 2020.

We do have a general idea about the history of microprocessors. The microprocessor has evolved over the years; from the; ‘first single-chip’ microprocessor introduced by Intel-the INTEL 4004, that was a 4-bit microprocessor to the recent 64-bit microprocessors. History has it; Intel has been a leader in technology innovation. Intel has given some of the biggest contributions to the evolution of microprocessors. One such salient microprocessor introduced by Intel was the Intel 80386, which is also known as i386 or 386. 386 was the first 32-bit microprocessor launched in October 1985 that brought along the feature of virtual mode.

32-bit microprocessors, virtual, 3rd gen, intel, x86 family, 386

[1] Sameera A’amer Abdul-Kader, “Emulation of the microprocessor intel 80386”, Diyala Journal of Engineering Sciences, Vol.2, No.1, pp. 13-34, 2009.
[2] Barry B. Brey, “Intel Microprocessors”, Pearson Prentice Hall, Ohio, pp. 677-718, 1987.
[3] Sen-Cuo Ro, Sheau-Chuen Her, “i386/i486 Advanced Programming”, Springer Publishing Co Inc., U.S., pp. 54-196, 1993.
[4] Tiwari, R. Sam, and S. Shaikh, "Analysis and prediction of churn customers for telecommunication industry," 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, 2017, pp. 218-222. doi: 10.1109/I-SMAC.2017.8058343
[5] S. Navadia, P. Yadav, J. Thomas and S. Shaikh, "Weather prediction: A novel approach for measuring and analyzing weather data," 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, 2017, pp. 414-417, doi: 10.1109/I-SMAC.2017.8058382
[6] Vidhi Tiwari, Pratibha Adkar “Implementation of IoT in Home Automation using android application” IsroSet-Journal (IJSRCSE), Vol.7, Issue.2, pp.11-16, Apr-2019
[7] A. Fasiku, Ayodeji Ireti, B. Olawale, Jimoh Babatunde, C. Abiola Oluwatoyin B., "Comparison of Intel Single-Core and Intel Dual-Core Processor Performance", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.1, pp.1-9, 2013
[8] M. Sora, J. Talukdhar, S. Majumder, P.H Talukdhar, U. Sharmah, "Word level detection of Galo and Adi language using acoustical cues", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.1, pp.10-13, 2013
[9] Manish Mishra, Piyush Shukla, Rajeev Pandey, "Assessment on different tools used for Simulation of routing for Low power and lossy Networks (RPL)", International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.4, pp.26-32, 2019
[10] Neha N. Badwaik, Achal J. Wakade, SudhaShrikanth “Underground Cable Fault Detection System by Using IoT” Journal (IJSRNSC), Vol.8, Issue.1, pp.25-28, Feb-2020

Anas Sayed, Shaikh Mohd Ashfaque, "80386: A Beginning of 32-bit Microprocessor by Intel," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.80-82, 2020.

Requirements engineering plays an important role in coordinating with various stakeholders / customer expectations and ensures developers build applications that meets virtually all stakeholder / customer requirements. Appropriate requirements management tool results in a better solution for the organizations` defined problem. Handling several thousands of requirements needs a Requirements management tool, so handling is a daunting task. This paper discusses the web-based requirements management tool that can easily trace requirements, online tender management, bug and defect, use cases and related information throughout the project`s planning and development process. It has the centralized database; the solution can be updated from solitary consign. It can be easily used with any software development processes including, Waterfall, Spiral and Agile. This paper considers six leading Web based Requirements Management tools; IRIS Business Architect, ACCOMPA, JAMA Contour, Gatherspace, AgileSpecs, Blueprint, ReQtest, Orcanos and CASE Spec. It discusses their features including collaboration, History, Tracking, and Comments for Requirements, Status Reporting, Traceability, and Centralized database, Import /Export Data, Summary Reports and User Defined Attributes. Besides this, the paper also focuses on Project management attributes; regaining project control, reduce project risks, and decrease failure costs.

requirements;requirements mangement tools, waterfall, spiral, agile

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[36] F.Masood, A.R.Faridi, "An Overview of Distributed Ledger Technology and its Applications", International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.422-427, 2018.
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[39] M.Haris, R.Z. Khan, "A Systematic Review on Cloud Computing", International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.632-639, 2018.

Shams Tabrez Siddiqui, Md Oqail Ahmad, Mohammad Shuaib, S. Gulzar Ahmed Rizvi, "Cloud Based Requirements Management Tools Should Be Selected on the Basis of Project Requirements," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.83-88, 2020.

The condition of security on the web is extremely poor. Hacking is an action in which, an individual adventures the shortcoming in a framework for self-benefit or delight. Privately owned sectors often make newer and bigger amounts of their simple targets and applications, for example, electronic business, showcasing and database access to the Internet, at that point crackers consider the opportunity to be a better chance to access sensitive information. These actions of crackers in order to get sensitive information is caught by an white cap cracker who is also called an ethical hacker and Moral hacking is an indistinguishable action which plans to discover and redress the shortcoming and vulnerabilities in a framework. Moral hacking portrays the way toward hacking a system in a moral way, in this way with well-meaning plans. In This paper, hacking types with its different phase and ethical hackings techniques are discussed. Major problem in ethical hacking is to understand the insider issues. The usage of white-top software engineers limit dangers and additionally screen the conduct of moral programmers.

Component, Formatting, Style, Styling, Insert

[1] Brijesh Pandey Alok Singh & Lovely Balani “Ethical Hacking Tools, Techniques and Approaches” 2015.
[2] Nicholson, Scott. "How ethical hacking can protect organisations from a greater threat." Computer Fraud & Security 2019, no. 5 15-19, 2019.
[3] B. Smith ; W. Yurcik ; D. Doss, “Ethical hacking: the security justification redux” In the Proceeding of : IEEE 2002 International Symposium on Technology and Society (ISTAS`02). Social Implications of Information and Communication Technology, USA, 2002.
[4] Prakash Chandra Behera and Chinmaya Dash, “Ethical Hacking: A Security Assessment Tool to Uncover Loopholes and Vulnerabilities in Network and to Ensure Protection to the System”, Volume 4, Special Issue9, pp.54-61. 2015.
[5] Georg, Thomas, Burmeister Oliver, and Low Gregory. "Issues of Implied Trust in Ethical Hacking." The ORBIT Journal 2, no. 1 :pp. 1-19, 2018.
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Aniket Kamat, Shuchita Beri, Mayank Kothari, "A Review on Issues and Benefits of Ethical Hacking," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.89-93, 2020.

Recommender systems utilize the opinions of a residential district of users. It assists individuals for the reason that the community more effectively identifies the content of great interest from a set that is potentially overwhelming. The instructor provides an online course which consists of the learning materials, self-quiz, and learning path in a virtual classroom. Typical learners study course material and do self-quiz so that you can evaluate their knowledge. The essential thing that is important to the success learners relates to the standard of the educational materials that are not only be determined by given materials by the instructor but additionally be determined by other learners’ recommendations. Recommender systems have now been a helpful tool to recommend items in a lot of online systems, including e-learning. However, not much research has been done to gauge the learning effects regarding the learners if they use e-learning with a recommender system. Instead, most of the researchers were concentrating on the recommender system precision in forecasting the learner’s recommendation as opposed to the knowledge gain. The detailed literature review is presented by the various researchers in the Recommender Systems for the Smart E-Learning environment in this survey article.

E-Learning, Education, Recommender System, Big Data Analytics, Machine Learning

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[3] Picciano, Anthony G. "The evolution of big data and learning analytics in American higher education." Journal of asynchronous learning networks Vol.16, Issue.3 ,pp. 9-20,2012
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M. Murugeswari, S. Vimala, "The Recommender System for Smart E-Learning System Using Big Data: A Survey," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.94-99, 2020.

Sentiment classification is the process of using NLP, statistics, or machine learning methods to extract, identify, or otherwise characterize the sentiment content of a text unit. Based on a sample of tweets, how are people responding to this ad campaign/product release/news item? There are several application of opinion mining such as on business intelligence, Politics/political science, Law/policy making, Sociology, Psychology etc. By use of digital platform administration can collect response from consumer and by means of applying opinion mining technique a useful information from user collected data. In this paper we have given a brief review over different work done in the field of sentiment classification and given tabular comparison among different opinion classification technique based on accuracy.

TPR,FNR,ML,NL,SVM ANN

[1] B. Vamshi Krishna, Ajeet Kumar Pandey and A. P. Siva Kumar Feature Based Opinion Mining and Sentiment Analysis Using Fuzzy Logic Springer 2018.
[2] Y. Wang, J. Zhang Keyword Extraction from Online Product Reviews Based on Bi-Directional LSTM Recurrent Neural Network IEEE 2017.
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Varsha Pal, Akshay Varkale, "Statistical Modeling for Sentiment Classification: A Review," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.100-105, 2020.

In biomedical researches a massive amount of data are produced day after day, using machine learning algorithms to discover the knowledge is very important in early diagnosis, prevention and treatment, as well as drug development. Biomedical data like DNA microarray suffers from curse of dimensionality phenomenon, since there are a huge number of features (genes) with high ambiguity. Feature selection is still a hot topic which cares about reducing the high of dimensionality by applying different techniques. Different contributions are conducted with new models, frameworks, methodologies and algorithms aiming to dissolve the curse of dimensionality problem and produce more meaningful and reliable data. The objective of this study is to explain the concept of feature selection, its methods, the algorithms and techniques that have been recently used in microarray data and the most popular microarray datasets were used. Moreover, the challenges that can appear when selecting more informative and non-redundant features from high dimensional datasets.

Feature Selection, Filter Method, Wrapper Method, Hybrid Method, DNA microarray, Metaheuristic

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Khadija Abdullah Uthman, Fadl Mutaher Ba-Alwi, Suad Mohammed Othman, "A Survey on Feature Selection in Microarray Data: Methods, Algorithms and Challenges," International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.106-116, 2020.