International Journal of Innovations in Science & Technology <p>International Journal of Innovations in Science and Technology (ISSN 2618-1630) is an international peer reviewed and "Open Access" multidisciplinary journal designed to explore advances in various disciplines of Science and Technology. Researcher can submit their field observations and the results of laboratory experiments to IJIST within "<a href="" target="_blank" rel="noopener">Aims and Scopes</a>" of the journal. Journal publish issues quarterly. </p> <ul> <li><strong>Rapid Publication:</strong> manuscripts are trasnparently reviewed by internaltional and local reviewers and the first decision is provided to authors within 10-15 Days. </li> <li><span style="font-weight: bolder;">High Visibility:</span> indexed in HEC, MDPI, REPEC and other <a href="" target="_blank" rel="noopener">database</a>......</li> <li><strong>Recognition of Reviewers: </strong>Reviewers providing timely decisions, thorough peer-review reports are acknowledged with a discount in <a href="" target="_blank" rel="noopener">Article Processing Charges.</a></li> </ul> en-US (Prof Dr. Ali Iqtedar Mirza) (Iqra Nazeer (Senior Managing Editor)) Sat, 02 Jul 2022 00:00:00 -0400 OJS 60 BCAS: A Blockchain Model for Collision Avoidance to Prevent Overtaking Accidents on Roads <p>Overtaking at high speeds, especially on non-divided roadways, is a leading cause of traffic accidents. During overtaking maneuvers, humans are more likely to make mistakes due to factors that cannot be predicted. For overtaking operations in autonomous vehicles, prior research focused on image processing and distant sensing of the driving environment, which didn't consider the speed of the surrounding traffic, the size of the approaching vehicles, or the fact that they could not see beyond impediments in the road. The past researches didn't focus on the speed of the surrounding traffic or the size of the approaching vehicles. Moreover, most of the techniques were based on single agent systems where one agent manages the source vehicle's (autonomous) mobility within its surroundings. This research conducts a feasibility study on a remote Vehicle-to-Vehicle (V2V) communication framework based on Dedicated Short-Range Communication (DSRC) to improve overtaking safety. This work also tries to improve safety by introducing a blockchain-based safety model called BCAS (Blockchain-based Collision Avoidance System). The proposed multi-agent technique strengthens the ability of real-time, high-speed vehicles to make decisions by allocating the total computation of processing responsibilities to each agent. From the experimental results, it is concluded that the proposed approach performs better than existing techniques and efficiently covers the limitations of existing studies.</p> Nadeem Malik, Saud Altaf, Muhammad Azeem Abbas Copyright (c) 2022 50sea Sat, 03 Sep 2022 00:00:00 -0400 Analyzing ML-Based IDS over Real-Traffic <p>The rapid growth of computer networks has caused a significant increase in malicious traffic, promoting the use of Intrusion Detection Systems (IDSs) to protect against this ever-growing attack traffic. A great number of IDS have been developed with some sort of weaknesses and strengths. Most of the development and research of IDS is purely based on simulated and non-updated datasets due to the unavailability of real datasets, for instance, KDD '99, and CIC-IDS-18 which are widely used datasets by researchers are not sufficient to represent real-traffic scenarios. Moreover, these one-time generated static datasets cannot survive the rapid changes in network patterns. To overcome these problems, we have proposed a framework to generate a full feature, unbiased, real-traffic-based, updated custom dataset to deal with the limitations of existing datasets. In this paper, the complete methodology of network testbed, data acquisition and attack scenarios are discussed. The generated dataset contains more than 70 features and covers different types of attacks, namely DoS, DDoS, Portscan, Brute-Force and Web attacks. Later, the custom-generated dataset is compared to various available datasets based on seven different factors, such as updates, practical-to-generate, realness, attack diversity, flexibility, availability, and interoperability. Additionally, we have trained different ML-based classifiers on our custom-generated dataset and then tested/analyzed it based on performance metrics. The generated dataset is publicly available and accessible by all users. Moreover, the following research is anticipated to allow researchers to develop effective IDSs and real traffic-based updated datasets.</p> Shafqat Ali Siyyal, Faheem Yar Khuawar, Erum Saba, Abdul Latif Memon, Muhammad Raza Shaikh Copyright (c) 2022 50sea Thu, 30 Jun 2022 00:00:00 -0400 Design and Implementation of Autonomous Trolley with E Billing <p>Shopping became one of the most important tasks that people conduct on a daily basis. A mart is a place where various things can be purchased within a roof. Customers must patiently wait in lengthy lines, especially on weekends, until it is their turn. Due to people's busy schedules, this is a time-consuming process that leaves them exhausted and dissatisfied with the services provided at the checkout counters. We proposed and implemented an autonomous trolley with an electronic billing system. The proposed and developed system is separated into two sections, the first section consists of RFID tags and camera-based product scanning and detection, while the second section consists of bill generation and e-payment. The second output is of a shopping receipt, which was printed using a thermal printer effectively, and smart trolley-based bill detection will be accomplished. This self-billing is a new technology that can present us with numerous advantages. Currently, everyone is familiar with e-payments, and because our system is also based on direct bank transactions. This smart trolley-based bill detection will ultimately be accomplished through the user's bank and Jazz Cash. Automated trolley systems are designed to provide customers with knowledge about their collected items and decision-making abilities based on prior purchase patterns in order to ensure a hassle-free shopping experience. </p> Hira Beenish, Saman Khan, Wasif Mairaj, Muhammad Fahad Copyright (c) 2022 50sea Thu, 30 Jun 2022 00:00:00 -0400 The Impact of Language Syntax on the Complexity of Programs: A Case Study of Java and Python <p>Programming is the cornerstone of computer science, yet it is difficult to learn and program. The syntax of a programming language is particularly challenging to comprehend, which makes learning arduous and affects the program's testability. There is currently no literature that definitively gives quantitative evidence about the effect of programming language complex syntax. The main purpose of this article was to examine the effects of programming syntax on the complexity of their source programs. During the study, 298 algorithms were selected and their implementations in Java and Python were analyzed with the cyclomatic complexity matrix. The results of the study show that Python's syntax is less complex than Java's, and thus coding in Python is more comprehensive and less difficult than Java coding. The Mann-Whitney U test was performed on the results of a statistical analysis that showed a significant difference between Java and Python, indicating that the syntax of a programming language has a major impact on program complexity. The novelty of this article lies in the formulation of new knowledge and study patterns that can be used primarily to compare and analyze other programming languages.</p> Kashif Munawar, Muhammad Shumail Naveed Copyright (c) 2022 50sea Thu, 30 Jun 2022 00:00:00 -0400 Diastolic Dysfunction Prediction with Symptoms Using Machine Learning Approach <p>Cardiac disease is the major cause of deaths all over the world, with 17.9 million deaths annually, as per World Health Organization reports. The purpose of this study is to enable a cardiologist to early predict the patient’s condition before performing the echocardiography test. This study aims to find out whether diastolic function or diastolic dysfunction using symptoms through machine learning. We used the unexplored dataset of diastolic dysfunction disease in this study and checked the symptoms with cardiologist to be enough to predict the disease. For this study, the records of 1285 patients were used, out of which 524 patients had diastolic function and the other 761 patients had diastolic dysfunction. The input parameters considered in this detection include patient age, gender, BP systolic, BP diastolic, BSA, BMI, hypertension, obesity, and Shortness of Breath (SOB). Various machine learning algorithms were used for this detection including Random Forest, J.48, Logistic Regression, and Support Vector Machine algorithms. As a result, with an accuracy of 85.45%, Logistic Regression provided promising results and proved efficient for early prediction of cardiac disease. Other algorithms had an accuracy as follow, J.48 (85.21%), Random Forest (84.94%), and SVM (84.94%). Using a machine learning tool and a patient’s dataset of diastolic dysfunction, we can declare either a patient has cardiac disease or not.</p> Muhammad Shoaib Anjum, Omer Riaz, Muhammad Salman Latif Copyright (c) 2022 International Journal of Innovations in Science & Technology Thu, 30 Jun 2022 00:00:00 -0400 Adaptive clustering in energy efficient routing protocol for mobile nodes in WSNs <p><strong>Introduction:</strong> Wireless Sensor Networks (WSN) is a collection of large number of small sensor nodes which communicate sensed data over a radio channel covering wide geographical region.</p> <p><strong>Problem statement:</strong> A number of algorithms have been developed to enhance the network lifetime of WSN by efficiently utilizing the sources of energy. The most commonly used approach is clustering that is prone to uneven load balancing and instability issues. Furthermore, topological changes in WSN structure especially with mobile nodes significantly effect network lifetime.</p> <p><strong>Methodology:</strong> In this study, we have proposed an Adaptive-Cluster-based Energy Efficient Routing Protocol (A-EECBRP), which employs a novel geometrical Voronoi-based configuration to solve load balancing and mobility issues while maintaining network stability and coverage. Furthermore, energy cost function and Energy Harvesters (EH) devices were implemented to reduce energy consumption and increase network life. Moreover, the concept of handshaking and random waypoint model for nodes movement between cluster groups was examined to define mobile nodes.</p> <p><strong>Results:</strong> Simulation results obtained from network analysis performed on MATLAB® showed that A-EECBRP reduced energy consumption by almost 1500 rounds as compared to LEACH-M. This significantly improved the network lifetime of WSN as compared to the LEACH-M routing protocol. Therefore, our proposed scheme provides a huge potential for implementing energy-efficient routing protocols in mobile wireless sensor networks.</p> Zawar Khan Khattak, Majid Ashraf Copyright (c) 2022 International Journal of Innovations in Science & Technology Thu, 30 Jun 2022 00:00:00 -0400 A Review on Impacts, Resistance Pattern and Spoilage of Vegetables Associated Microbes <p>Vegetable spoilage produces various microbes of different origins like parasites, fungi, viruses, and bacteria. This causes infections and diseases in vegetables, and later on, when humans eat these vegetables; diseases induce in humans. So, to prevent human diseases, the symptoms of various infections in vegetables must be known. Moreover, the conditions supporting the infections in vegetables must be understood. So that spoiled vegetable consumption can be prevented. Sometimes spoiled vegetables are regarded as disease free and suitable for consumption. These misconceptions sometimes lead to lethal human diseases, which in history led to major outbreaks. The antimicrobial resistance is faced by microbes which deteriorate the situation and make the cure of diseases.</p> Wajiha Yousuf, Javaid Yousuf, Saif Ud Din, Maisoor Ahmed Nafees, Abdul Razaq, Babar Hussain Copyright (c) 2022 50sea Thu, 30 Jun 2022 00:00:00 -0400 Service oriented Architecture for Agriculture System Integration with Ontology <p>Ontology is becoming a famous technique for converting unstructured data into meaningful data which acts as a key factor for decision-making, planning, and implementation in many areas, and agriculture is one of them. There are a lot of issues in agriculture practices e.g., farming, application of pesticides, and provision/ distribution of water to crops. However, some of the issues are critical and need to be resolved urgently to save cultivation from big hazards. In this paper, we have analyzed a few issues based on available literature. A variety of issues are faced in agriculture constantly and need to be resolved on an urgent basis. We have discussed the various ontology systems to acquire more precise results. Since ontology is based on a relation of data through which a user can get the maximum efficiency. Among all the challenges in agriculture, the lack of context-aware agriculture employs ontology with high concerns. This paper proposes a model to fill the gap in a service-oriented architecture.</p> Muhammd Fahad, Dr Tariq Javid, Hira Beenish Copyright (c) 2022 50sea Thu, 21 Jul 2022 00:00:00 -0400 Computer Malware Classification, Factors, and Detection Techniques: A Systematic Literature Review (SLR) <p>A Systematic Literature Review (SLR) was conducted using tailored searches based on our study topic. We completed all SLR processes, including periodic reviews as SLR. Researchers may find out about the justification, the review procedure, and the research question by using search keywords. This paper describes the trial approach to elaborate the search keywords, resources, restrictions, and validations that were, and explores search strategies made. The reviews are carried out by assessing the publication's quality, devising a data extraction approach, and synthesizing the results. All four research questions were used to analyze the papers concerning the findings. Finally, reports on the categorization of computer malware were analyzed for their detection methods, factors, and how they infiltrate computer systems have been published. SLR identifies the element, characteristics, and detection techniques that are explained in this research paper. Computer malware infects the computer system. This comprehensive literature review's is mainly based on recommendations by earlier studies.</p> Asad Hussain, Sunila Fatima Ahmad , Mishal Tanveer, Ansa Sameen Iqbal Copyright (c) 2022 50sea Mon, 29 Aug 2022 00:00:00 -0400