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Cluster evaluation divides the records into groups which can be meaningful and beneficial. It`s also used as a start line for different functions of information summarization. This paper speak some very fundamental algorithms like k-means, Fuzzy C-method, Hierarchical clustering to give you clusters, and use R information mining device. The outcomes are examined at the datasets specifically on-line news popularity, Cyber Crime information Set information evaluation. All datasets became analyzed with specific clustering algorithms and the figures we`re displaying the running of them in R information mining tool. Each set of rules has its specialty and antithetical conduct.

K-means algorithm, Fuzzy C-method algorithm, Hierarchical clustering algorithm, R tool

[1]. J. Han and M. Kamber, Data Mining: Concepts and Techniques, second ed. Morgan Kaufmann, 2006.
[2]. C.C. Aggarwal and P.S. Yu, “Finding Generalized Projected Clusters in High Dimensional Spaces,” Proc. 26th ACM SIGMOD Int‟l Conf. Management of Data, pp. 70-81, 2000.
[3]. K. Kailing, H.-P. Kriegel, P. Kro ¨ger, and S. Wanka, “Ranking Interesting Subspaces for Clustering High Dimensional Data,” Proc.Seventh European Conf. Principles and Practice of Knowledge Discovery in Databases (PKDD), pp. 241-252, 2003.
[4]. K. Kailing, H.-P. Kriegel, and P. Kro ¨ger, “Density-Connected Subspace Clustering for High- Dimensional Data,” Proc. Fourth SIAM Int‟l Conf. Data Mining (SDM), pp. 246-257, 2004.
[5]. E. Mu ¨ ller, S. Gu ¨nnemann, I. Assent, and T. Seidl, “Evaluating Clustering in Subspace Projections of High Dimensional Data,” Proc. VLDB Endowment, vol. 2, pp. 1270-1281, 2009.
[6]. E. Agirre, D. Martı´nez, O.L. de Lacalle, and A. Soroa, “Two Graph-Based Algorithms for State-of-the-Art WSD,”Proc. Conf.Empirical Methods in Natural Language Processing (EMNLP), pp. 585- 593, 2006.
[7]. K. Ning, H. Ng, S. Srihari, H. Leong, and A. Nesvizhskii, “Examination of the Relationship between Essential Genes in PPI Network and Hub Proteins in Reverse Nearest Neighbor Topology,” BMC Bioinformatics,vol. 11, pp. 1-14, 2010.
[8]. D. Arthur and S. Vassilvitskii, “K-Means++: The Advantages of Careful Seeding,”Proc. 18th Ann. ACM-SIAM Symp. Discrete Algorithms (SODA),pp. 1027-1035, 2007.
[9]. I.S. Dhillon, Y. Guan, and B. Kulis, “Kernel k Means: Spectral Clustering and Normalized Cuts,”Proc. 10th ACM SIGKDD Int‟lConf. Knowledge Discovery and Data Mining,pp. 551- 556, 2004.
[10]. T.N. Tran, R. Wehrens, and L.M.C. Buydens, “Knn Density-Based Clustering for High Dimensional Multispectral Images,”Proc.Second GRSS/ISPRS Joint Workshop Remote Sensing and Data Fusion over Urban Areas,pp. 147-151, 2003.

Mir Abdul Samim Ansari, Gopal K. Shyam, "An Efficient Cluster Analysis of Cyber Crime Records using R", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.141-145, 2019.

CPU scheduling algorithms are integral part of learning operating system. Over the years, it has been experience that initially CS students face a lot of problems in understanding and further implementing the various Scheduling algorithm. Also generating and regenerating Gantt Charts is faced with difficulties by many CS students. However, teaching and learning CPU scheduling algorithms using conventional lectures and textbooks is faced with difficulties by many students. First, textbooks illustrate the CPU scheduling algorithms in an incomplete and unclear manner. Second, students solve problems manually. They don’t receive any immediate feedback on their solutions. Third, due to time restriction, the teacher has to select a few small problems. To overcome these problems, this can be used as an efficient tool for teaching and learning CPU scheduling algorithms. The tool is also capable of doing calculations different effectiveness criteria of an algorithm like waiting time of each process, average waiting time and turnaround time.

CPU utilization and system throughput

[1] S. Abraham, Peter B. Galvin and Greg Gagne, “Operating System
Concepts, ” 9th ed., John Wiley & Sons, 2012.
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Sudhir K. Pandey, Gopal Krishna, "Effectiveness of Teaching and Learning CPU Scheduling Algorithms: A Survey", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.146-151, 2019.

Traditional typing methods have become quite outdated nowadays and there is a need to constantly upgrade this technology. AWK: Arduino Wearable Keyboard is an ergonomic input device which is wearable. Arduino Wearable Keyboard is a device whichallows users to effectively communicate by providing various input letters present inthe English Alphabet. This is made possible without using the traditional QWERTY keyboard setup; and rendering an immediate display ofthe output. AWK is highly effective for communication on the go, especially for people with speech disorders. The components used to meet this are Arduino Uno Board, LCD Screen, Bread Board, Push Buttons and Resistors. It makes use of these push buttons to reciprocate interactions during "key" taps or pressesto provide a response of an immediate display of a letter on given the LCD Screen; and reduce the accuracy needed in various positions of hand while typing on a traditional QWERTY keyboard. Thereby, eliminating any need for a traditional QWERTY keyboard.

Arduino Wearable Keyboard, QWERTY Keyboard, Multitap, Input Language, Arduino UNO

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[11] https://www.arduino.cc/en/Guide/Introduction
[12] https://www.merriam-webster.com/dictionary/LCD
[13] https://www.arduino.cc/en/main/software

Alyina Mohsin, Anannya Roshan, Anisha Gupta, RishabhAgarwal, MeenakshiSundaram A, "AWK: Arduino Wearable Keyboard", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.152-157, 2019.

This paper is a proposition for Cloud-Based Home Automation Using Artificial Intelligence-Google Assistant, Home Computerization or Home-Automation. We have gone over a few home Computerization advances presented throughout the years, from Bluetooth controlled robotization to Expert-System. Though the Google-Home cost is around ₹7,999 (INR) with an extra cost of ₹3,999 (INR) for the Gadgets associated concerning Google-Home, the complete expense for the Structure will be ₹11,998 (INR). Apple-Home Kit alone is more costly than Google-Home, around ₹10,473 (INR) for an essential gadget. A savvy Gadget which is constrained by the Google-Assistant, Amazon-Echo, and Siri, which utilizes voice assistant, for giving directions will cost around ₹7,999 (INR). So also, A solitary Smart light is valued around ₹799 (INR) and this can be controlled both by Siri and Google-Assistant. To Transform home Computerization, we need to contribute, around ₹11,999 (INR) for a straightforward setup. Imagine a scenario in which we can Computerize (Automate) our home inside (the Smartphone cost is does excluded as it is possessed by everybody) ₹2,999 (INR) and can control up to 4 contraptions utilizing Google-Assistant, in this paper, we depict the Planning and actualizing of such a sort of framework. The procedure includes Natural language handling, NLP (voice direction) which is given through the Google-Assistant with the assistance of IFTTT (If-This-Then-That) versatile application, Adafruit Cloud and the Arduino IDE application the guidance is sent to the Microcontroller, thusly, controls the transfers associated with regarded contraptions as required, turning the gadget (relay) On or OFF directions given to the Google-Assistant. The Micro-controller utilizes Node-MCU (ESP8266) and the correspondence is built up by means of Wi-Fi (Internet).

Home Computerization, IFTTT(If-This-Than-That) Mobile-App, NodeMCU (ESP8266), Arduino IDE Application, Internet of Things (IoT), Google-Assistant, NLP-Voice Control, Smartphone

[1] IFTTT: https://ifttt.com/discover https://www.pocketlint.com/SmartHome/SmarHomenews
[2]Adafruit:https://io.adafruit.com/
[3] NodeMCU: https://nodemcu.readthedocs.io/en/master https://iotbytes.wordpress.com/nodemcupinout/
[4] Google Assistant: https://assistant.google.com/intl/en_in/ https://www.pocketlint.com/Apps/Appsnews/Googleappnews
[5] IoT: https://internetofthingsagenda.techtarget.com/definition/IoT-device
[6] Vamsi Krishna, HariBabuKandala, p Ravi Babu : Paper 2007
[7] Lovely Goyal, AnanthVaibhav : Paper 2010
[8] Rajeev Piyare and Seong Ro Lee : paper 2013
[9] Ronnie D. Caytiles and Byungjoopark : Paper 2016
[10] Ana marieD.Celebre : Paper 2016
[11] Webhooks: https://webhooks.pbworks.com/w/page/13385124/FrontPage
[12] Arduino IDE: https://www.arduino.cc/en/Guide/Environment
[13] Wikipedia: https://www.wikiped

Sunil Kumar B.S, Vanitha G.C, Veena S, Vishnuvardhan Reddy, Chaithra.N, "Cloud Based Home Automation System Using Artificial Intelligence-Google Assistant", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.158-164, 2019.

Agriculture plays a vital role within the lifetime of associate degree economy. It`s the backbone of our financial system. Agriculture not solely provides food and stuff however additionally employment opportunities to a really giant proportion of population. The manual assortment of information and human intervention within the field is labor intensive. Automation of information assortment at regular and frequent interval reduces labor demand and price. The aim of this work is introduce a system to gather field knowledge at regular and frequent interval and to scale back labor with the assistance of ESP 32.It is a IoT based system for effective assortment and method. The method is tested in the field considering various parameters. It works efficiently in all environmental condition and variation of parameters such as soil moisture, tempreture, humidity. This process is very economical and price effective crop yielding.

IoT, Automation, ESP32, Process all knowledge, Information transfer, cost effective, reduce labor

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[2] Pranita A. Bhosale, Prof. V. V. Dixit, “Water Saving-Irrigation Automatic Agricultural Controller”,in International Journal of Scientific and Technology Research, Volume 1, Issue 11, December 2012 (ISSN 2277-8616)
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[13] S. R. Nandurkar, V. R. Thool, R. C. Thool, “Design and Development of Precision Agriculture System Using Wireless Sensor Network”, IEEE International Conference on Automation, Control, Energy and Systems (ACES), 2014
[14] JoaquínGutiérrez, Juan Francisco Villa-Medina, Alejandra Nieto-Garibay, and Miguel Ángel Porta-Gándara, “Automated Irrigation System Using a Wireless Sensor Network and GPRS Module”,IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 0018-9456,2013 [15] Dr. V .Vidya Devi,G. Meena Kumari, “Real- Time Automation and Monitoring System for Modernized Agriculture” ,International Journal of Review and Research in Applied Sciences and Engineering (IJRRASE) Vol3 No.1. PP 7-12, 2013
[16] Y. Kim, R. Evans and W. Iversen, “Remote Sensing and Control of an Irrigation System Using a Distributed Wireless Sensor Network”, IEEE Transactions on Instrumentation and Measurement, pp. 1379–1387, 2008.
[17] Q. Wang, A. Terzis and A. Szalay, “A Novel Soil Measuring Wireless Sensor Network”, IEEE Transactions on Instrumentation and Measurement, pp. 412–415, 2010
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Tanmoy Chowbey, Mallikarjun M Kodabagi, "IoT Based Advanced Smart Cultivation System", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.165-170, 2019.

Technologies are rapidly increasing and dependent on the Internet. In near future, Hardware will be embedded with software and interconnected to the Internet to send or receive data, which is termed as Internet of Things. Resulting to Database shared between different devices, technology of Distributed Database is Blockchain. Using these latest technologies, Internet of things (IOT), block chain, and Near Field Communication (NFC) for providing data protection, we are developing a system for authentication on Android applications. In this paper, we are using Zero knowledge authentication system to login into Android application using Hashing Technique along with NFC. The data generated in Android Application and transferred to block chain server which convert the transaction details into blocks, which ever growing and store it in blockchain storage. With the help of all these technologies we are providing more Secure environment which prevent data tampering and modification. As well restricted data or block visibility. With unbreakable authentication system.

IOT, Blockchain, NFC, Android Application

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Farheen Shaik, Satish G.C, "Implementation of IoT System using Blockchain with Authentication and Data Protection", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.171-175, 2019.

Technological advancements are happening at the speed of thought, and technology plays a vital role in all fields, including education. College Information Management System (CIMS) provides an easy interface for maintenance of student data. It may be utilized by academic institutes and faculties to take care of the records of students easily. Technology is a huge contributor to the well being of human kind. Reports are an integral part of schools but generating it manually in a shorter span of time is very hectic and often prone to calculation errors. The creation and management of correct, up-to-date data concerning a student’s academic career and faculty details is critically vital within the universities. This system deals with all kinds of student, faculty details and academic reports. It tracks all exam details, internal and external marks which is available through a secure online interface embedded in the college’s website. It also facilitates the activities happening in the university.

Student Information System, Database, Excel Sheets, HTML, JSP

[1] Zhibing Liu, HuixiaWang,HuiZan “Design and implementation of student information management system.” 2010 International symposium on intelligence information processing and trusted computing. 978-0-7695- 4196-9/10IEEE.R.
[2] S.R.Bharamagoudar1,Geeta R.B.2 , S.G.Totad “Web BasedStudent Information Management System” International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 6, June 2013.
[3] Jin Mei-shan1 Qiu Chang-li 2 Li Jing 3. “The Designment of student information management system based on B/S architecture”. 978-1- 4577-1415-3/12 2012 IEEE.
[4] TANG Yu-fang,ZHANG Yong-sheng, ,“Design and implementation of college student information management system based on the web services”. Natural Science Foundation of Shandong Province(Y2008G22), 2009IEEE

Rasika Chandrasekaran, Divya S, Akshatha Patil, Anushree Patil, "Web Based College Information Management System", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.176-180, 2019.

The headway of convolutional neural systems (CNNs) and Deep learning (DL) in the previous decade brought about significant upgrades in computer vision. One of the recipients of these advances is the task of object detection, where the goal is to distinguish and locate real-world objects inside pictures or videos. Real-time object tracking on a drone under a dynamic situation has been a difficult issue for a long time, with existing methodologies utilizing off-line calculation or powerful computation units on board. This paper displays lightweight real-time on board object tracking methodology, which varies, from basic image classification in that the AI demonstrate needs to distinguish numerous objects in a single frame, and figure out where these objects are found. The advances in procedures, joined with the improved PC equipment, put real-time object detection well inside the capacities of present day processors. Real-time object recognition is essential for some utilization of Unmanned Aerial Vehicles (UAVs), for example, observation and reconnaissance, search-and-rescue, and foundation assessment. In the previous couple of years, Convolutional Neural Networks (CNNs) have ascended as an unbelievable class of models for recognizing picture content, and are seen as the standard strategy for generally issues.

Detection, Drone, Pattern Matching, Privacy Preserving, Security Vulnerabilities, Sensitive Items, Yolo

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[2]“Arvind and Rishiyur S. Nikhil. Executing a program on the MIT tagged-token dataflow architecture. IEEE Trans. Comput., 39(3):300–318, 1990.”
[3]“Jack Clark. Google turning its lucrative web search over to AI machines, 2015.”
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[6] “T. P. Breckon, S. E. Barnes, M. L. Eichner, and K. Wahren, “Autonomous real-time vehicle detection from a medium-level UAV,” in Proc. 24th International Conference on Unmanned Air Vehicle Systems, pp. 29.1-29.9, 2009”
[7] “M. Bhaskaranand, and J. D. Gibson, “Low-complexity video encoding for UAV reconnaissance and surveillance,” in Proc. IEEE Military Communications Conference (MILCOM), pp. 1633-1638, 2011.”

Shiva Kumar R Naik, Kushal A, Lakshmi Narayan S, Sreeraam V Chatrapathi, Sagar T, "YOLO Based Object Detection Using Drone", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.181-184, 2019.

The Email Spam is known as direct mail. Email junk mail is the exercise of sending undesirable email messages, regularly through marketable enterprise content, into huge portions to a random set of recipients. Spam is mounted at the internet due to the fact that the operation rate of digital communiqué is considerably much fewer than any trade shape of conversation. There are a lot of spam filters with extraordinary strategies to recognize the received message as spam, starting from white listing/ black listing, Bayesian analysis, key word matching, mail header evaluation, postage, law and content material scanning, etc. Widely used supervised tool analyzing strategies specifically C 4.5 Decision tree classifier, Multilayer Perceptron, Naive Bayes Classifier be designed for mastering the competencies of unsolicited mail with the version be constructed via education by means of identified spam and ham emails.

Classifier, Machine learning, Mail header, and Spam filter

[1] K Shubba Ready, Dr E Srinivasa Ready, “A Survey on Spam Detection Methodologies in Social Networking sites” IJCSN, Volume 6, Issue 4, August 2017
[2] Sarju S, Riju Thomas, Emilin Shyni C, “Spam Email Detection Using Structural Features”, IJCA, Volume 89, No 3, March 2014
[3] Rohit Giyanani, Mukthi Desai, “Spam Detection Using Natural Language Processing”, IOSR-JCE, Volume 16, Issue 5, Sep-Oct 2014
[4] Rekha, Sandeep Negi, “A Review on Different Spam Detection Approaches” IJETT, Volume 11, Number 6, May 2014
[5] Priyanka Sao, Pro. Kare Prashanthi, “E-mail Spam Classification Using Naïve Baysian Classifier” IJARCET, Volume 4, Issue 6, June 2015
[6] S Roy, A Patra, S.Sau, K Mandal, S Kunar, “an Efficient Spam Filtering Techniques for Email Account” AJER, Volume 2, Issue 10, 2013
[7] Reena Sharma, Gurjot Kaur, “Spam detection techniques” IJSR, 2013

Navya N.C, Ashwinkumar U.M, "Email Spam Filtering Using Supervised Machine Learning Techniques", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.185-188, 2019.

The objective of this project is to monitor the patients remotely. In this new era of IOT there are many technique with which we can do so many things with the help of various devices like sensors, GSM modules and LCD displays .The internet of things is one of the best Smart technology in this new era with which we can connect internet into physical device and can do various activity. We can also collect all types of information. This leads to the effective framework. Recent approach in wireless sensor networks have facilitate the cognizance of pervasive health care monitoring system for patients. In this project, we propose a off the beaten track medical monitoring system for heartbeat, blood pressure, ECG, and temperature data. Monitoring centre is a station which consist of real time analysis and warning mechanism for emergency diagnosis .We are using sensors like heart beat sensor, blood pressure sensor, microcontroller Lpc2148, an temperature sensor to detect the abnormalities in the human body and send a message through GSM module and also give alarm during emergency .These all can done using mobile application with the help of sensors. We use embedded C which is a very easy coding language to write the code and install it in the Arduino. We also use the LCD display to show the message.

microcontroller Lpc2148, temperature sensor, blood pressure sensor, heart beat sensor, ECG Sensor, LCD display, GSM module, Embedded C, Arduino, Wi -Fi module, Mobile application

[1] Yuan Wang, Yiping Zheng, Ou Bai, Qisong Wang, Dan Liu, Xin Liu, Jinwei Sun,” A multifunctional wireless body area sensors network with real time embedded data analysis”, Biomedical Circuits and System Conference(BioCAS) 2016 IEEE, pp. 508-511 , 2016.
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Poorvi Tyagi, Puja Kumari, Puttul Kumari, Rakshitha KM, Ashwin Kumar UM, "Body Sensor Networking", International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.189-192, 2019.