Volume-11 , Issue-4 , Apr - 2023 Go Back

Today, the world has become like a small village, and the success of any institution has become closely related to communication with the outside world through the Internet. As each institution needs to exchange information from one place to another that exposes sensitive information to danger and spread. Such institutions require the existence of mechanisms to protect this information. The firewall plays an important role in protecting information from unauthorized access. However, the available firewalls are not suitable for all institutions due to their high cost. This paper proposes a micro-firewall for reducing the cost of firewall by avoiding the additional services while maintaining the security, and thus the proposed micro-firewall will suitable the small and medium institutions. The proposed micro-firewall uses two computers, one of them is connected with the internet and the other is connected with the local network, the communication between the two computers is done by using the server and client protocols. The role of the computer connected with the internet is to receive the request from the external user who want access the internal network and verify the identity of the user if he/she is an authorized user or not. If yes it sends the request to the computer connected with the internal network, unless the request is rejected. The role of internal computer is similar to external computer but for internal user. The proposed micro-firewall was compared with other firewalls in terms of the cost reduction. The results showed that the cost of proposed micro-firewall has reduced compared with the cost of the other firewalls.

firewall, client, server, agent, proxy, packet filtering, user filtering, network security.

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Mohammed Alwajeeh, Saleh Noman Alassali, Yasser Ali Alahmadi, "A Framework for Reducing the Cost of the Firewall," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.1-6, 2023.

Sign and voice translation is a critical tool for individuals who cannot hear or speak , or for those who speak different languages. Machine learning techniques have been increasingly used to find or improve the accuracy and efficiency of sign and voice translation systems. These systems make use of machine learning models to analyze and interpret sign language or speech and translate them into written or spoken language. Machine learning models can recognize patterns in sign language gestures or speech, and convert them into text or speech output. The model`s accuracy is dependent on the quality of its training data and the complexity of the model architecture. Recent improvisation in machine learning has increased the performance of sign and voice translation systems, enabling them to recognize more complex gestures and accents. Overall, the use of machine learning in sign and voice translation has the potential to improve the accessibility of information and communication for individuals who are deaf or hard of hearing, or for those who speak different languages. However, there is still much room for improvement, and ongoing research and development are needed to optimize the performance of these systems

Computer Vision, Recognition of Sign Language, Hand Gesture Recognition, Features Extraction

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Nandini, Avni Verma, Sandeep Kumar, "Sign and Voice Translation using Machine Learning and Computer Vision," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.7-13, 2023.

In our day to day life humans interact with computers or machines very frequently and these interactions result in completion of meaningful tasks or scheduled jobs. These interactions can involve a lot of applications like gaming, typing, scrolling, pointing, remote arm movement, etc. Out of all the ways of interacting such as mechanical movement like mouse, keyboard, joystick, etc., speech recognition, etc. The most effective one is thought to be through hand because the mechanical ones even include the movement of hand ultimately, so in order to make this interaction more convenient and efficient there was an idea of developing hand gesture recognition and it was later implemented but often it involved special instruments such as gloves with sensors or particular background. This proposed paper emphasizes the more effective way of human computer interaction which is hand gesture recognition. There are three main modules which are hand detection and hand tracking and hand gesture recognition. There are several applications of this way of interaction the user can customize to their own use. This model is fast and accurate and it can go up to 30fps and the main applications include the video game stimulation, virtual board and many other useful human computer interactions. The proposed model can detect hand even in strained backgrounds and without gloves in almost all of the cases and the model is robust and smooth. The hand gestures are one of the most natural ways of communication in humans rather than input through keyboards and mouse. This model can be used in VR and AR stimulations which would need a better way of human computer interaction than a keyboard and mouse. The main objective of this paper is to employ a new model to improve the human computer interaction. In the proposed model a menu will be displayed with the numbers representing the action desired by the user let us say 1. Represents the virtual mouse 2. Represents the virtual keyboard 3. Represents the other menu where a series of actions can be defined by the user. The proposed model uses the hand sign detection for the recognition of the numbers by the finger counting module and again using other hand sign detection module. The objective is to form a neural network to distinguish the hand signs in order recognize the hand sign to implement the desired action of the user. We have utilized Google`s Mediapipe Frame Work Arrangements has further developed hand recognition model and may understand 21 3D landmarks of Palm. Subsequently we`ll endeavor to know it and the method for utilizing this Library Python to understand our objective.

Mediapipe, Sign language recognition [SLR], Human computer interaction, Gesture recognition

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[17] Yellapu Madhuri and Anburajan Mariamichael)”Vision based sign language translation device” conference paper: February 2013

Shaik Sai Rohit, Raunak Kandoi, Sandeep Kumar, "Hand Gesture Recognition for Human Computer Interaction through KNN Algorithm and Mediapipe," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.14-18, 2023.

Nonverbal communication is important in everyday interactions, and its contribution to communication can be as high as 93%. Video surveillance, expression analysis, paralinguistic communication, and detection all benefit from the application of facial emotion analysis. We provide a thorough description of FER (Facial Emotion Recognition), which is based on traditional machine learning (ML), in our suggested system. In-depth research is required to make learning problems detection simpler because it is still laborious and time-consuming. Dyscalculia is characterised by difficulties counting, comparing numbers, and adding mathematical operations. This learning disability is thought to affect between 3 and 6% of school-aged youngsters. One of the special learning disabilities (SLD) with a mathematical impairment is dyscalculia. As the results of these individual tests alone are insufficient for identification, a variety of tests must be administered and analysed manually in order to discover dyscalculia. When analysing complex medical data, artificial intelligence (AI) for healthcare uses Random Forest algorithms to simulate human cognition. The screening procedure for these particular learning problems makes use of machine learning techniques. Counting accuracy, time spent per question during the counting phase, number comparison accuracy, time spent per question during the number comparison phase, arithmetic addition accuracy, and time spent per question during the addition phase were the six inputs used to develop the model. The model, which categorises children as dyscalculic or not, was constructed using the Random Forest method.

Facial emotion recognition (FER), Artificial intelligence, Random Forest, and dyscalculia.

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Sujith Kumar R., Soundar Sriram J., Sridhar C., Fathima G., "Facial Emotion Recognition Based Prediction of Affective State Of Children with Autism Using Ml," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.19-25, 2023.

In today’s world the stock market has a huge impact on the economy making it difficult for stock market investors to predict stock prices. Financial market investors cannot use simple models to more accurately predict stock prices to invest in stocks. Deep learning helps computer to solve complex problems which humans takes more time to solve. This paper is based on developing a model to predict inventory value using recurrent neural network (RNN) and long- short term memory model (LSTM).

Stock Market, Predicting, LSTM Model, RNN Model, Prices, Complex Data, Density

[1]. A S Pradeep, Soren Goyal and M. Miller, “Detection of statistical arbitrage using machine learning techniques in Indian Stock market”, PhD Thesis, Computer Science Department, IIT Kanpur, 2019.
[2]. Dhiraj Mundada, Gaurav Chhaparwal, Sachin Chaudhari, Trupti Bhamare, “Stock Value Prediction System”, International Journal on Recent and Innovation Trends in Computing and Communication, Vol. 3, Issue 4, pp. 2217 - 2219, 2015. https://doi.org/10.17762/ijritcc.v3i4.4214
[3]. Rakhi Mahant, Trilok Nath Pandey, Alok Kumar Jagadev and, Satchidananda Dehuri, “Optimized Radial Basis Functional Neural Network for Stock Index Prediction”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Vol. 7, Issue 11, pp. 1252 - 1257, 2016. Doi: 10.1109/ICEEOT.2016.7754884
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Rohit Tetarwal, Rohit Tushir, "Simulation Based Exploration of Stock Market Using LSTM Model," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.26-29, 2023.

Seeded region growing (SRG) segmentation is utilized frequently in image processing, computer vision, and machine intelligence applications. The accuracy of the segmentation produced by the fundamental SRG algorithm relies on the proper seed selection. In this paper, seeds are allocated for each color component of the input image using a keypoint detector. Two methods for obtaining seeds are examined; the first method uses the keypoints as the seeds, while the second method uses the centers of the triangles constructed using the keypoints as the seeds for the SRG algorithm. After that, each color plane is subjected to the SRG algorithm, and the result is then concatenated. Subsequently, this segmentation is enhanced by employing a statistical region-merging algorithm. Several traditional keypoint detectors, such as SIFT, SURF, KAZE, and Harris, are compared and examined using the well-known Berkeley segmentation dataset (BSD) images. Finally, the provided technique is compared with two other approaches for image segmentation: K-means and mean shift.

Region growing, seeds, image segmentation, keypoints detector, triangulations centers

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[2]. Shaik Salma Begum, D. Rajya Lakshmi, “A Review of Current Methods in Medical Image Segmentation,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.12, pp.67-73, 2019. https://doi.org/10.26438/ijcse/v7i12.6773
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Ibrahim El rube, "Seed Selection for Region-Growing Image Segmentation Based on Detected Keypoints," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.30-38, 2023.

Current technology often uses the computer mouse or finger to move the cursor along the screen. A mouse or finger movement is detected by the system and mapped to the cursor movement. HCI (Human-Computer Interface) involves the use of computer technology to provide a human-computer interface. Communication between humans and computers needs to be made more effective through appropriate technology. Interaction between humans and computers is crucial. It is therefore important to find a method for enabling individuals with disabilities to communicate with computers and be part of the Information Society in an equal way. In this project, a virtual mouse is built that works based upon the movement of the pupil of an eye, where the detection takes place with the help of a webcam. Here, the system detects the face of the user using facial landmark detectors. Then using the Canny Edge detection algorithm, the pupil of the eye is detected. Then the mouse is calibrated to the pupil. Left click and right click are implemented by detecting left blink and right blink of eye using Eye Aspect Ratio algorithm. The system is expected to be easy to use, take fast input, and work as an alternative to a physical mouse.

Pupil control system, Pupil tracking systems, Mouse cursor, Webcam, Eye movement, Virtual mouse

[1] Hafiz Hamza Ashraf, Syed Muhammad Tahir Saleem, Sammat Fareed, Farzana Bibi, Arsalan Khan, Shahzad Gohar, “IMouse: Eyes Gesture Control System,” International Journal of Advanced Computer Science and Applications, Vol. 9, Issue 9, pp.1-5, 2018.
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[3] Kalyani Ijardar,Palak Jaiswal, Mansi Dhakiter, Mayuri Kadke, Tushar Barai “Human eye based computer mouse.”, “International Research Journal of Modernization in Engineering Technology and Science”, Vol. 04, Issue 12, pp.1-5,2022
[4] Aleksei Bukhalov, Viktoriia Chafonova, "An Eye Tracking Algorithm based on Hough transform" IEEE COMPEL 2018, Padova, Italy, pp. 1-2, 2018
[5] Sunil Kumar Beemanapally, Chetan Kumar, Diksha Kumari “Eye Ball Based Cursor Movement”,” International Research Journal of Modernization in Engineering Technology and Science”, Vol. 02, Issue:09 ,2020
[6] Nitasha, Shammi Sharma, Reecha Sharma, " Comparison Between Circular Hough Transform and Modified Canny Edge Detection Algorithm for Circle Detection", International Journal of Engineering Research & Technology (IJERT) Vol. 1 Issue 3, pp. 1-5, May – 2012
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[12] Vamsh i Krishna M Mane, Gopu Abhishek Reddy, B. Prashanthi, M. Sreevani “Green Virtual Mouse Using OpenCv”, , International Journal of Computer Sciences and Engineering(IJCSE),Vol.-7, Issue-4, April 2019.
[13] Aruna Kumar B, T.Hashmitha, Swathi S.G, Vineeth P, “Recognizing Mouse Events through Head/Hand Movement”, International Journal of Computer Sciences and Engineering(IJCSE), Vol.-7, Special Issue-14, May 2019.
[14] Robert Gabriel Lupu, Florina Ungureanu, Valentin Siriteanu, "Eye tracking mouse for human computer interaction", 2013 E-Health and Bioengineering Conference (EHB), Iasi, Romania, pp. 1-2, 2014

K. Gnana Prasuna, M. Harshitha, G. Chaitanya Deepti, K. Shalini, B. Baby, "Implementation of Virtual Mouse Using Pupil Detection for Physically Disabled," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.39-45, 2023.

There are many new disciplines that have emerged as a result of technological advancement. Every day, enormous amounts of data are produced in many different areas, including science, engineering, health, and business. Data mining is a technique for gathering data from various sources and organizing it to produce insightful conclusions. Companies’ today look to stay ahead of the competition by making it a priority to keep up with all new developments in data science and analytics. This paper explains data mining`s applications in various areas as well as its methods and tools. This study concentrated on different data mining tools that are beneficial and identified as key fields of data mining technology. We are aware of the numerous domestic and international businesses, as well as small and big organizations.

Data mining, Data set, KDD, Tools & Techniques, Rapid Miner, Weka, KNIME

[1] Aarti Sharma, Rahul Sharma, Vivek Kr. Sharma, Vishal Shrivastava, ?Application of Data mining-A Survey Paper? in International Journal of Computer Science and Information Technologies, Vol. 5 (2), 2023-2025 2014, ISSN: 0975-9646.
[2] Bharati M. Ramageri, ?Data Mining Techniques and Applications? in Indian Journal of Computer Science and Engineering, Vol. 1 No. 4 301-305, Dec 2014.
[3] Saima Anwar Lashari, Rosziati Ibrahim, Norhalina Senan, N. S. A. M. Taujuddin,? Application of Data Mining Techniques for Medical Data Classification: A Review? in MATEC Web of Conferences 150, 06003, (2018),UCET2017.
[4] D.Usha Rani, ?A Survey on Data Mining Tools and Techniques in Medical Field? in International Journal of Advanced Networking & Applications (IJANA), Volume: 08, Issue: 05 Pages: 51-54 (2017) Special Issue.
[5] Manpreet Kaura, Shivani Kanga, ?Market Basket Analysis: Identify the changing trends of market data using association rule mining? in International Conference on Computational Modeling and Security (CMS 2016), Procedia Computer Science 85 ( 2016 ) 78 – 85.
[6] Dr. M. Dhanabhakyam, Dr. M. Punithavalli, ?A Survey on Data Mining Algorithm for Market Basket Analysis? in Global Journal of Computer Science and Technology Volume 11 Issue 11 Version 1.0 July 2011, Publisher: Global Journals Inc. (USA) Online ISSN: 0975-4172 & Print ISSN: 0975-4350.
[7] MohammadReza Keyvanpoura, Mostafa Javidehb, Mohammad Reza Ebrahimia,? Detecting and investigating crime by means of data mining: a general crime matching framework? in Procedia Computer Science 3 (2011) 872–880. Available:
[8] Chauhan, Dipti, Jay Kumar Jain, and Sanjay Sharma. "An end-to-end header compression for multihop IPv6 tunnels with varying bandwidth." 2016 Fifth international conference on eco-friendly computing and communication systems (ICECCS). IEEE, 2016.
[9] Jain, Jay Kumar, Devendra Kumar Jain, and Anuradha Gupta. "Performance analysis of node-disjoint multipath routing for mobile ad-hoc networks based on QOS." International Journal of Computer Science and Information Technologies 3.5 (2012): 5000-5004
[10] Pushpesh Pant, SriramPandey, ?Application of Data Mining Tools and Techniques in Material Selection? in International Journal of Scientific & Engineering Research, Volume 8, Issue 4, April-2017.
[11] V.K. Jha, R.K. Singh ?Application of Data Mining in Manufacturing Industry? in International Journal of Information Sciences and Application.. Seoul, Korea, Apr 8, 2014. In: PAPADOPOULOS, Symeon, ed. and others. Proceedings of the SNOW 2014 Data Challenge co-located with 23rd International World Wide Web Conference (WWW 2014), Seoul, Korea, pp. 57-63, April 8, 2014 ISSN 0974- 2255 Volume 3, Number 2 (2011), pp. 59-64.
[12] Ashish Dutti, Maizatul Akmar Ismaili, Tutut Herawan, ? A Systematic Review on Educational Data Mining? in Digital Object Identifier 10.1109/ACCESS.2017.2654247, Volume 5, 2017.
[13] Dr. S. Vijiyarani, Ms. E. Suganya, ?Research Issues in Web Mining? in International Journal of Computer- Aided Technologies (IJCAx) Vol.2, No.3, July 2015.Brijendra Singh, Hemant Kumar Singh, ?Web Data Mining Research: A Survey? in IEEE International conference.
[14] Abdullah H. Wahbeh, Qasem A. Al-Radaideh, Mohammed N. Al -Kabi, and Emad M. Al.
[15] Jain, Jay Kumar, and Sanjay Sharma. "Performance Evaluation of Hybrid Multipath Progressive Routing Protocol for MANETs." International Journal of Computer Applications 71.18 (2013).
[16] Smitha, T., & Kumar, V. S. (2013). Applications of big data in data mining. International journal of emerging technology and advanced engineering, 7(3).

Anshu Shrivastava, Jay Kumar Jain, Dipti Chauhan, "Literature Review on Tools & Applications of Data Mining," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.46-54, 2023.

The Procedure for utilizing premade standardized tags to perceive a thing during charging process is drawn-out and work through .The most common way of checking the every single item takes additional time and charging the bill and giving it to the client requires greater investment . This requires part of handling the work on the items to prepare them for ID and grouping. This paper presents an elective framework that chips away at the standard of self-checking of items and computerization includes that consequently produces the bill to such an extent that there will be no wastage of time To execute this framework we want to create some distance from customary techniques for programming and utilize an alternate worldview for planning the scanner which should be able to connect it with data base which stores the information of the products .we use machine learning model implemented in-order to perform the data in libraries like cv, numpy, pyzbar and Front-end using Tkinter and a Database for Mysql and connection of the Mysql with python. This paper describes about the disengaged programming System from charging the process without worrying about the gear Environment. We pick python and Tkinter to design the qr or normalized ID scanner and the front end for the customized show and SQL for the capacity of the information of the items to execute the framework over a circulated network inside any Estabilishment that needs to integrate this cycle so every hub that needs to handle charging need that needs to deal with charging need not need to stick to the equipment prerequisite forced on them to run the different models dependent on the GPU-based tensor engineering of tensor Stream.

python3, MySQL, Tkinter, QR scanner

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Bongu Raviteja, Mohammad Adnan Zargar, Sandeep Kumar , "Billing System Using Machine Learning Techniques," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.55-60, 2023.

Plagiarism is considered a serious academic and ethical offense, as it undermines the values of originality, honesty, and integrity in academic and creative work. India has a diverse linguistic landscape, with over 22 official languages and many more regional languages spoken across the country. Several Indian states have taken steps to promote regional language education in recent years. In this case study we are exposing a very accurate plagiarism checker for all indian regional languages. We are facing many challenges to develop this sort of software. So, mainly the data indexing methods are very interesting in this case. Here we are exposing how data indexing methodology works using ‘Taylor series’ formula in cloud-based storage for Indian regional languages.

Indexing, Encryption, Data Sequence, Search Key.

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Prashanth Kumar H.M., Subramanya Bhat S., "Plagiarism Checker Data Indexing Technology for Indian Regional Language," International Journal of Computer Sciences and Engineering, Vol.11, Issue.4, pp.61-62, 2023.