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With the proliferation of crimes in today’s world, safety of the women is one of the most serious and compulsive requirements. Number of crimes against women is increasing drastically and over 4 million rape cases were reported across India between 2001 and 2017. Not only just this number, innumerable number of women is becoming victims of harassments and violence. Considering this alarming situation in the country, a wearable women safety device is proposed in this paper. The proposed model of the device “FeSecure” consists of hardware and software modules. The hardware module is designed considering the scenario wherein the attackers seize the mobile phone from victim and victim is incapable of accessing her phone. The model of wearable device consists of GPS, GSM and sensors. Sensors read vital parameters from the victim such as body temperature and heart rate, and alerts will be sent to emergency contacts and nearby police station with the help of location tracker module if any irregularities are detected in the read parameters. To alleviate the false positive alerts, reverse alarm, and alarm fatigue is incorporated in the system. Along with this, android application is also built that has various features like panic button, fingerprint recognition and voice recognition which can be used by victim to send alerts.

location tracker, safety, false positive, alarm fatigue, vital parameter reading, fingerprint and voice recognition

[1] S. Juhitha , M. Pavithra , E. Archana,"Design and Implementation of Women Safety System Using Mobile Application in Real-Time Environment",International Journal of Research in Engineering, Science and Management Volume-3, April-2020.
[2] Sanjana Babdi, Janhavi Jathar, Tejaswini Tambe, Prof. Simran Singhan"Women`s safety using Iot",International Research Journal of Engineering and Technology,Vol-07,Feb 2020.
[3] B. Sathyasri, U. Jaishree Vidhya, G. V. K. Jothi Sree, T. Pratheeba, K. Ragapriya,"Design and Implementation of Women Safety System Based On Iot Technology",International Journal of Recent Technology and Engineering,Vol-07,April 2019.
[4] Helly Patel, Parth Lathiya, Bhoomit Patel , Hirpara Nidhi , Divya Ebeneze,"Machine Learning Model integrated with Android for Women’s Safety",International Journal for Research in Applied Science & Engineering Technology,Vol-45.98,Feb-2020.
[5] Dudyala Sunitha, 2Ms. Udayini Chandana,"DESIGN AND IMPLEMENTATION OF WOMEN SAFETY SYSTEM BASED ON IOT TECHNOLOGIES",Vol 10, Sept 2019
[6] Wasim Akram, Mohit Jain, C. Sweetlin Hemalatha,"Design of a Smart Safety Device for Women using IoT",INTERNATIONAL CONFERENCE ON RECENT TRENDS IN ADVANCED COMPUTING,2019.
[7] Shirly Edward.A,Vijayakumari.S.G. Bhuvaneswari.M., "GSM Based Women’s Safety Device",International Journal of Pure and Applied Mathematics,Vol- 119 ,2018.
[8] M.Lakshmi Pradheepa,M.Nivetha, Lakshmi,"Women’s safety app in mobile application",International Journal of Science, Engineering and Management,Vol-2,Dec 2017.
[9] Shubham Sharma, Fasil Ayan, Rajan Sharma, Divya Jain,"IoT Based Women Safety Device using ARM7",IJESC ,Vol-7,2017.

Lakshmi R., Yashaswini K.M., Vinutha S., Likitha G., Nithin J., "Female Security System Using IoT and Mobile Computing - FeSecure," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.1-6, 2021.

In the past, before the advancement of computer technology, the control of home appliances was done manually at their various locations by a user. This kind of control has shortfalls such as lack of control of home appliances remotely and displeasing stress and discomfort to home appliance users, to mention but a few. However, these problems lead to this project research which is on the design and implementation of a Smart Home Control System, with the following objectives; to solve problems involving the lack of ease and comfort in the use and control of home appliances, provide help and support for home appliance users and generally bring technology and automation into various home appliances and devices. This research work followed the structured project design methodology with tools such as the Arduino Uno microcontroller, NodeMCU WIFI Module, Ethernet + WIFI Router, Smartphone with Android 2.3+, Arduino IDE platform with C++ programming language. The result of this research is to prove that the control of home appliances can be done wirelessly. The system when implemented, would be able to control electrical appliances and devices in the home with a relatively low cost design, user-friendly interface and ease of installation.

ArduinoUno, Ethernet, SmartSystems, NodeMCU

[1] S. Kumar, "Ubiquitous Smart Home System Using Android app," International Journal of Computer Networks & Communications, vol. 6, pp. 33-43, January 2014.
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[3] A. McEwen, Designing the Internet of Things, London: John Wiley & Sons, 2013
[4] S. K. S. L. U. B. Sabin Adhikari, Android Controlled Home Automation, Sabin Adhikari, 2014.
[5] ] R. Piyare, "Ubiquitous Home Control and Monitoring System using Android-based Smart Phone," International Journal of Internet of Things, vol. 2, pp. 5-11, 2013.
[6] M. S. H. Khiyal, A. Khan, and E. Shehzadi, "SMS Based Wireless Home Appliance Control System (HACS) for Automating Appliances and Security," Issues in Informing Science and Information Technology, vol. 6, pp. 887-894, 2009.
[7] R. Piyare and M. Tazil, "Bluetooth based home automation system using cell phone," in IEEE 15th International Symposium on Consumer Electronics, Singapore, 2011, pp. 192 – 195.
[8] A. Alonzi, "Project Results," 2019. Available: https://proposalsforngos.com/project-results-outputs-outcomes-impact/.
[9] Zhang, Y., Zhao, G., & Zhang, Y. A smart home security system based on 3G. In Computer Science-Technology and Applications, 2009. IFCSTA`09. International Forum on (Vol. 2, pp. 291-294).
[10] B. C. Limited, First Steps with Embedded Systems, Canada, 2002.
[11] S Kumar Ubiquitous Smart Home System using Android Application, International Journal of Computer Networks & Communications vol. 6, no. 1 pp. 33-43, 2014
[12] V Pimente and B G Nickerson “Communicating and Displaying Real-Time Data with WebSocket in IEEE Internet Computing” 2012

H.A. Okemiri, S.C. Chukwu, E. Uche-Nwachi, K.C. Oketa, S.C. Eze, V.I. Aniji, A.Y. Idris, "Development of a Smart Home Control System," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.7-20, 2021.

It is very often heard about the Smuggling of the trees such as Sandal, Teak etc. are taking place throughout the world. These trees are highly expensive as well as less available in the world. Because of huge amount of money involved in selling of such trees, lot of incidents are happening in cutting of trees. In order to avoid the illegal activities on these trees some measures are to be taken. The main objective of the anti-poaching sensor system is to monitor the smuggling of trees and forest fires using flex and flame modules and alerting the user about the same.

Smuggling, Anti-Poaching, Sensor system, Flex and Flame modules, Wireless technology

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[3] Bhatti, U. and Hanif. M, “Validity of Capital Assets Pricing Model.Evidence from KSE”, Pakistan.European Journal of Economics, Finance and Administrative Science, 3 (20), 2010
[4] Naveenraj M, Arunprasath, Jeevabarathi C.T, Srinivasan R, “IoT Based Anti-Poaching Alarm System for Trees in Forest”, International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-6S, April 2019
[5] R. Q. V. P. Chandrasekharan, “Forest Fire Detection Using Temperature Sensors Powered by Tree and Auto alarming Using Gsm”, Ijrsi 2(3) 23-28, vol. II, no. 100817, pp. 23–28, 2015.
[6] Pushpalatha R, Darshini M.S, “Real Time Forest Anti-Smuggling Monitoring System based on IOT using GSM”
[7] Ketaki Vinod Patil, Chakka Sai Abhishek, “Prevention of Theft of Sandalwood trees using IOT and Arduino”, International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-8, Issue-5S, May, 2019
[8] Ghousia Sultana B “IOT Based Anti-Poaching Alarm System for Trees in Forest using Wireless Sensor Network” Volume 9, Special Issue No. 3, May 2018.
[9] B S Sudha “Forest Monitoring System Using Wireless Sensor Network”. E-ISSN: 2454-8006 Volume 4, Issue 4 April-2018.
[10] Ankita Dalvi,” Undetected Detective to protect the Forest Trees against Poaching Using WSN Technology” Vol. 3, No.6, 2018.
[11] Mr Rohan Solarpurkar, “Real Time Forest Anti-Smuggling Monitoring System based on IOT using GSM” International Journal for Research in Engineering Application & Management (IJREAM) ISSN: 2454-9150 Special Issue- ICSGUPSTM 2018.
[12] Dr.Rangarajan, Dr.Sakunthala, “Innovative Protection of Valuable Trees from Smuggling Using RFID and Sensors”, International Journal of Innovative Research in Science, Engineering and Technology Vol.6, Issue3, March 2017
[13] Sridevi Veerasingam, Saurabh Karodi, Sapna Shukla, “Design of Wireless Sensor Network node on Zigbee for Temperature Monitoring",2009 International Conference on Advances in Computing, Control and Telecommunication Technologies, IEEE Journals 978-0-7695-3915-7/09,2009.

Shruthi K.R., Jatin V., Rakshitha J., Sukruthi S., Tejaswini G., "IOT Based Anti-Poaching Sensor System for Commercial Trees," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.21-26, 2021.

Healthcare is a sought after task in the human life. One in four deaths are due to heart disease in India alone. In order to reduce the number of deaths, there is a need to automate the prediction process and alert the patient well in advance. Healthcare industry contains a lot of medical data which aids machine learning algorithms in making decisions accurately in predicting the heart diseases. This project makes use of the heart disease dataset available in Cleveland database of UCI machine learning repository. This project has delved into different algorithms namely Decision tree, k-nearest neighbour algorithm (KNN), Random Forests. The database consists of 303 instances and 14 attributes. Using the decision tree algorithm, we will be able to identify those attributes which are the best one that will lead us to a better prediction of the datasets. Here each internal node of the tree represents an attribute, and each leaf node corresponds to a class label. Random Forests consists of multiple decision trees that operate as an Ensemble. Random Forests out perform as they are collection of large relatively uncorrelated models. KNN can easily identify and classify people with heart disease from healthy people. The proposed project compares the results using different performance measures, i.e. accuracy, precision, etc. This project delivers the prediction valued from no presence to likely presence. The proposed project’s aim is to try and reduce the occurrences of heart diseases in patients and thus assist doctors in diagnose it effectively.

Health care, Prediction, Random Forest, Classification, Machine Learning

[1] Vembandasamy, K., R. Sasipriya, and E. Deepa. "Heart diseases detection using Naive Bayes algorithm." International Journal of Innovative Science, Engineering & Technology 2.9: 441-444, 2015.
[2] Kumar, Priyan Malarvizhi, and Usha Devi Gandhi. "A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases." Computers & Electrical Engineering 65: 222-235, 2018.
[3] Alarsan, Fajr Ibrahem, and Mamoon Younes. "Analysis and classification of heart diseases using heartbeat features and machine learning algorithms." Journal of Big Data 6.1: 1-15, 2019.
[4] Kannan, R., and V. Vasanthi. "Machine learning algorithms with ROC curve for predicting and diagnosing the heart disease." Soft Computing and Medical Bioinformatics. Springer, Singapore. 63-72, 2019.
[5] Dhar, Sanchayita, et al. "A hybrid machine learning approach for prediction of heart diseases." 2018 4th International Conference on Computing Communication and Automation (ICCCA). IEEE, 2018.
[6] Singh, Jagdeep, Amit Kamra, and Harbhag Singh. "Prediction of heart diseases using associative classification." 2016 5th International conference on wireless networks and embedded systems (WECON). IEEE, 2016.
[7] Devulapalli, Sudheer, et al. "Experimental evaluation of unsupervised image retrieval application using hybrid feature extraction by integrating deep learning and handcrafted techniques." Materials Today: Proceedings, 2021.
[8] Sudheer, D., R. SethuMadhavi, and P. Balakrishnan. "Edge and Texture Feature Extraction Using Canny and Haralick Textures on SPARK Cluster." Proceedings of the 2nd International Conference on Data Engineering and Communication Technology. Springer, Singapore, 2019.

Devulapalli Sudheer, Anupama Potti, N. Anjali devi, C. Chandana Reddy, "Study of Predicting Heart Diseases Using KNN, Decision Tree and Random Forest Methods," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.27-29, 2021.

Automatic license plate detection is one of the most common video analytics. Existing system fails if the license plate is deformed (broken or blurred). The main cause for the deformation of the number plate is when the vehicle met with an accident or whenever car robbery takes place. Recognizing various disfigured numbers on deformed number plates has been one of the challenging issue in the field of research. This paper concentrates on deformed number plate detection and recognition. Here MATLAB software is used to extract the alphanumeric values which is deformed. Template matching being the oldest method has been used to recognize the alphanumeric values. Our algorithm has been applied on various types of number plates and achieved an accuracy of 78% for the deformed number plates. This study has importance in various real world applications like traffic control, toll control or parking lot access.

MATLAB, preprocessing, character reconstruction and segmentation, character recognition, Template matching

[1] Suhaila Abd Halim and Mohd Syazreen Zulkifli “Detection and Recognition of Broken Character in Car Plate Image” International Jasin Multimedia & Computer Science Invention and Innovation Exhibition, 2020.
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[3] M. S. Farag, M. M. E. Din, & H. E. Shenbary, “Parking entrance control using license plate detection and recognition,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 15, no. 1, pp. 476- 483, 2019.
[4] K. Kaur, & A. K. Bathla, “A Review on Segmentation of Touching and Broken Characters for Handwritten urmukhi Script,” International Journal of Computer Applications, vol. 120, no. 18, pp. 13–16, 2015.
[5] Monika Arora, Anubha Jain, Shubham Rustagi, Tushar Yadav, “Automatic Number Plate Recognition System Using Optical Character Recognition” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019 IJSRCSEIT | Volume 5 | Issue 2 | ISSN : 2456-3307. DOI : https://doi.org/10.32628/CSEIT1952280
[6] Divya Rastogi, Mohammad Shahbaz Khan, Kanav Jindal, Karan Singh, “A Real-Time Vehicle Number Plate Detection and Recognition System”, Journal of Xi`an University of Architecture & Technology, Volume XII, Issue IV, 2020.
[7] Montazzolli, Sérgi, Jung Claudio, “License Plate Detection and Recognition in Unconstrained Scenarios”, European Conference on Computer Vision (ECCV 2018) At: Munich, Germany
[8] Cheng-Hung Lin and Ying Li, “A License Plate Recognition System for Severe Tilt Angles Using Mask R-CNN”, International Conference on Advanced Mechatronic Systems, 2019.
[9] H. Li, P. Wang, and C. Shen, “Towards end-to-end car license plates detection and recognition with deep neural networks,” CoRR, vol. abs/1709.08828, 2017. [Online]. Available: http://arxiv.org/abs/1709. 08828
[10] M. V. Srinu and B. S. Shankar, "Real Time Car Parking System and Parking Fee Display Using Raspberry Pi," International Journal of Research, vol. 3, pp. 421-426, 2016.

Chiyyedu Manasa, Pooja N., Sushmitha, Deepika C., Monisha R., "Detection of Deformed Number Plates in Natural Scene Images," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.30-33, 2021.

Linguistics have been instrumental in developing a deeper understanding of human nature. Words are indispensable to bequeath the thoughts, emotions, and purpose of any human interaction, and critically analyzing these words can elucidate the social and psychological behavior and characteristics of these social animals. Social media has become a platform for human interaction on a large scale and thus gives us scope for collecting and using that data for our study. However, this entire process of collecting, labeling, and analyzing this data iteratively makes the entire procedure cumbersome. To make this entire process easier and structured, we would like to introduce TLA (Twitter Linguistic Analysis). In this paper, we describe TLA and provide a basic understanding of the framework and discuss the process of collecting, labeling, and analyzing data from Twitter for a corpus of languages while providing detailed labeled datasets for all the languages and the models are trained on these datasets. The analysis provided by TLA will also go a long way in understanding the sentiments of different linguistic communities and come up with new and innovative solutions for their problems based on the analysis.

TLA, Machine Learning, Analysis, NLP

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[13] S. Amrita, Jobin Joseph, Rona Shaji, Athul Prasad, Rahul Gopal, "E-Stress Detector", International Journal of Computer Sciences and Engineering, Vol.8, Issue.6, pp.25-29, 2020.
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[15] P. J. Tighe, R. C. Goldsmith, M. Gravenstein, H. R. Bernard, R. B. Fillingim, “The painful tweet: text, sentiment, and community structure analyses of tweets pertaining to pain”, Journal of medical Internet research, vol. 17, No.4, pp. e84, 2015
[16] J. Blair, C.-Y. Hsu, L. Qiu, S.-H. Huang, T.-H. K. Huang, S. Abdullah,”Using tweets to assess mental well-being of essential workers during thecovid-19 pandemic”,In the Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1-6, 2021
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[18] J. Devlin, M.-W. Chang, K. Lee, K. Toutanova, ”Bert: Pre-training of deep bidirectional transformers for language understanding”, arXiv preprint arXiv:1810.04805.
[19] Saurav Singla, Vikash Kumar, "Multi-Class Sentiment Classification using Machine Learning and Deep Learning Techniques", International Journal of Computer Sciences and Engineering, Vol.8, Issue.11, pp.14-20, 2020.

Tushar Sarkar, Nishant Rajadhyaksha, "TLA: Twitter Linguistic Analysis," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.34-37, 2021.

Class Imbalance is inarguably one of the most significant and common problem faced while training supervised machine learning models to identify anomalies. In paradigms like spam filtering, medical diagnosis, intrusion detection etc. the amount of data available on negative class is much greater than that on the positive class and hence training traditional machine learning model on such data biases it in favor of the negative class at the cost of the positive class leading the model to give a false sense of accuracy and hence undermine its own purpose. Owing to the importance of this problem several techniques have been developed to tackle it and this paper is aimed to provide an empirical comparative evaluation of a gamut of these techniques to mitigate the adverse effect of class imbalance pertaining to spam classification. In this paper I have compared the effect of 8 resampling techniques including ROS, SMOTE, ADASYN, Near-Miss and TOMEK-LINKS on the performance of eight different learning classifiers which were selected cautiously to incorporate diverse strategies used for classification. In addition to this the performance of four Ensemble learning methods, including EasyEnsemble and SMOTEBoost, are contrasted when trained on an imbalanced dataset. The AUC-ROC performance metric calculated using a stratified 5-fold cross validation was used to evaluate the effect of different imbalance handling techniques. Furthermore, Statistical tests were performed on the results obtained to posit the best model for spam classification for the dataset used.

Imbalance, spam classification, resampling, ensemble learners, statistical test

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[6] M. RAZA, N. D. Jayasinghe and M. M. A. Muslam, "A Comprehensive Review on Email Spam Classification using Machine Learning Algorithms," in the Proceedings of the 2021 International Conference on Information Networking (ICOIN), pp. 327-332, 2021.
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[15] Haibo He, Yang Bai, E. A. Garcia and Shutao Li, "ADASYN: Adaptive synthetic sampling approach for imbalanced learning," in the Proceedings of the 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), pp. 1322-1328, 2008.
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[26] A. Abdullah ALFRHAN, R. Hamad ALHUSAIN and R. Ulah Khan, "SMOTE: Class Imbalance Problem In Intrusion Detection System," in the Proceedings of the 2020 International Conference on Computing and Information Technology (ICCIT-1441), pp. 1-5, 2020.
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Gopalkrishna Waja, "Comparative Study of Techniques for Alleviating Class Imbalance in Spam Classification," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.38-45, 2021.

The primary objective of this paper is to find out an efficient approach for converting 2D medical images into a desktop level VR model. The target is achieved in three stages: segmentation, 2D to 3D reconstruction, and 3D to VR modeling. Segmentation is the process of partitioning the digital image into sub parts or meaningful segments which help in segregating the cognitive information in the region of interest. Several segmentation algorithms are used to segment the input image. Best segmentation techniques are preferred for 3D reconstruction. Two types of 3d reconstruction techniques are used in formulating a 3D model. The AMILab 3.2.0 is used to provide non immersive visualization. Quantitative metrics such as Accuracy, Sensitivity, Specificity, Precision, F Score, Border Error, Jaccard Distance, Volumetric Overlap Error, Relative Volume Difference, Average Symmetric surface Distance and Maximum Symmetric surface Distance are used to evaluate the performance. Constructed VR model helps students in learning human anatomy efficiently.

Medical Image, Segmentation, 3D Reconstruction, Non Immersive VR

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M. Mohamed Sathik, A. Farzana, S. Shajun Nisha, "An Efficient Approach for Converting 2D Medical Images Into Non Immersive VR Model," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.46-51, 2021.

In order to benefit from different social schemes, the beneficiaries need to submit his/her Life Certificate in offline or online modes which are not affordable by the common man. This certificate is used as a proof to ensure that the person mentioned in the ‘Life Certificate’ is alive. The current prevailing methods for this are time-consuming as well as tedious for senior citizens as the have to stand in long queues. This paper presents a computationally simple and efficient enhancement technique that uses voice-verification algorithms to distinguish the beneficiaries and perform verification. The proposed method uses online mode along with feature extraction and pattern matching techniques.

MFCC(Mel Frequency Cepstral Coefficient), DTW(Dynamic Time Warping), Speaker Identification, Spekaer recognition, IVRS(Interactive Voice Response System), Identification, Verification, DCT(Discrete Fourier Transform)

[1] Researchgate.net. [Online]. Available: https://www.researchgate.net/publication/329595695_Some_Commonly_Used_Speech_Feature_Extraction_Algorithms/citation/download. [Accessed: 27-Aug-2021].
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Vibhuti Velgekar, Shreya Sawant, Samiksha Gawade, Vishvesh shirgaonkar, Basil Jose, Snehal Bhogan, Gaurav Naik, "AI Based Online Verification of Scheme Beneficiary," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.52-56, 2021.

We have developed E-jacket with cooling, heating, charging & health monitoring using renewable energy source. Our device/product is capable to deal with certain weather conditions like cold & warm and will keep the soldier body temperature normal in every kind of weather. We are using Proteus & Arduino IDE software platform with simulating & programming the product Algorithm and we are using Arduino Uno, Heart Beat sensor, Peltier plate, Solar panel as hardware. The objectives of this work are to develop an Environmentally friendly product which will be used by military to keep themselves safe in difficult weather conditions also, it will also provide continuous health monitoring of soldier & send data of it to the head quarter. The system consists of three main parts: 1) Solar panel: We used solar panel as source so energy to complete system which is reusable & easily accessible. 2)Peltier plate: This is the heart of E-jacket, it will provide cooling & heating effect to the body according to the conditions and selected mode. 3)Heartbeat sensor: This will provide continuous sensing of one’s pulse by which we can get his health information at every instant of time

Peltier plate, Sensor, Heat & Cool, LM 35, E-jacket, ESP8266

[1] Adarsh K S, Jyothi Elizabeth D: “E-Uniform for Soldier’s Who Work at Extreme Temperature Regions”, International Journal of Engineering Research and General Science Volume 3, Issue 3, pp. 993 – 998, May-June, 2015.
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[6] Prof. S.M.D. Tuljapurkar, Ashitosh Gadhve, Sumit Gulve, Nilesh Mandane, “Solar Based E-Uniform for Soldier Working at Extreme Whether Condition.” IERJ Volume 3 Issue 3 Page 5639-5641, 2019 ISSM 2395-1621

Rushikesh S. Katake, Sachin S. Hiwale, Yogita L. Kamble, Vinayak K. Bairagi, "E-Jacket with Health Monitoring System Using Renewable Source of Energy," International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.57-59, 2021.