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  Subjects -> ELECTRONICS (Total: 207 journals)
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International Journal of Advanced Research in Computer Science and Electronics Engineering
Number of Followers: 14  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2277-971X - ISSN (Online) 2277-9043
Published by Shri Pannalal Research Institute of Technology Homepage  [1 journal]

    • Authors: Qiu Yuwei, Song dekun; Liu Lihong, Zhang Jian, Liu jing, Li Yongfeng
      Pages: 1 - 5
      Abstract: In order to improve the corrosion resistance of 45 steel surface, fe-based alloy coating was prepared on the surface of 45 steel by laser cladding technology and the microstructure of Fe-based alloy coating was observed.Corrosion resistance test of Fe-based alloy coating and 45 steel in 3.5wt.% NaCl solution and 1mol/L HCl solution.The results show that the coating structure of the laser cladding Fe-based alloy is uniformly dense, and there are no obvious cracks, porosity and other defects on the surface of the coating.The self-corrosion potential (Ecorr) of the coating and 45 steel in 3.5wt.% NaCl solution was -570.96mV and -831.15mV, and the self-corrosion current density (icorr) was 12.13uA·cm-2 and 13.70uA·cm-2, respectively.The Ecorr of the coating and 45 steel in the 1mol/L HCl solution were -453.45mV and -497.00mV, respectively, and the icorr of the coating and 45 steel was 297.78uA·cm-2 and 379.31uA·cm-2, respectively.The coating has a greater arc capacitive than 45 steel, has a larger impedance modulus, and has better corrosion resistance.
      PubDate: 2022-08-21
      DOI: 10.26483/ijarcs.v13i4.6886
      Issue No: Vol. 13, No. 4 (2022)
  • Elevating Information Security Practices within Sudanese Healthcare
           Establishments' Staff

    • Authors: Khalid Mohammed Osman Saeed
      Pages: 6 - 8
      Abstract: In today’s digital era healthcare establishments find information technologies invaluable in daily tasks.The paper strongly based upon a research that is currently being conducted by the author and according to the results from the research survey only 20% of healthcare establishments in Sudan has security initiatives for their employees and make use of electronic security systems or even physical instruments to protect their assets and patients’ information, whilst on the contrary, 80% have no security measures or any security policies. This is due to there is a lack of academic and professional literature about information security management and information security culture. Moreover, as grew to the best knowledge of the author and extracted from the results, healthcare community thought their role is to heal patients and they do not have any responsibility to protect patients’ information, whereas they deem such role belong to the computer department, even if, these security breaches computer related (e.g. viruses), or socially motivated (e.g. theft of equipment).Therefore, the overall aim of this paper is to identify factors that assist the implementation of information security culture and practices within healthcare establishments, and assist when conducting awareness programmers, so it discusses the need to promote information security issues within contemporary Sudanese healthcare establishments and the consequent need for appropriate training and awareness schemes.In addition, the paper highlights sequence basic elements that healthcare establishments should consider when construct a training and awareness program.
      PubDate: 2022-08-21
      DOI: 10.26483/ijarcs.v13i4.6835
      Issue No: Vol. 13, No. 4 (2022)
  • Review on Scene Semantics Extraction for Decision Making System in
           Autonomous Vehicles

    • Authors: Yuvraj Bapu Hembade
      Pages: 9 - 13
      Abstract: Abstract: It is a worldwide witnessed fact that traditional manual driving mechanism will be superseded by Autonomous Vehicles [AVs] in coming years. Autonomous vehicles are going to be most foreseen development in the automotive industry. That would require Decision Making System which will enable AVs to intuitively interpret the real-time situations around. Most importantly scene recognition on streets & extracting relevant semantics from the scene is challenging task. So, image classification & object detection techniques using Deep Convolutional Neural Networks [DCNN] are going to play vital role in every other methodology designed for scene semantics extraction. As per the extracted scene semantics DMS actuates the necessary devices which control the speed of vehicle & steering angel. So for that matter information extraction from road scene images covering all aspects to take intuitive decisions has huge concern with overall performance of the AV’s. 
      PubDate: 2022-08-21
      DOI: 10.26483/ijarcs.v13i4.6882
      Issue No: Vol. 13, No. 4 (2022)

    • Authors: Shivani Yadav, Bal Kishan
      Pages: 14 - 22
      Abstract: Software reliability plays a vital role in the emerging field of digitalization. Everyone wants cost and time-efficient software along with reliability which is achieved using CBS. In CBS, if the individual components are computed for a large or complicated system, then integration becomes complex which results in difficulty in predicting CBSR. To solve this problem several computational intelligence techniques such as SVM, ACO, PSO, ABC, GA, Neural network, are used but in our paper, we have focused on optimization techniques Fuzzy, ACO, ABC, PSO. These techniques help in estimating and predicting reliability models for CBS. Also, we have done, an assessment and comparative analysis based on a literature review of ABC, ACO, and PSO that have also been presented, for choosing suitable parameters for software reliability modeling.
      PubDate: 2022-08-21
      DOI: 10.26483/ijarcs.v13i4.6887
      Issue No: Vol. 13, No. 4 (2022)
  • A Review on Optimization Technique for Fault Tolerance in Cloud Computing

    • Authors: Nilophar .
      Pages: 23 - 27
      Abstract: It is the outcome of the emergence of on demand service in big scale distributed computing models. Adaptable technology because it delivers software and resources that can be flexibly scaled up and down. These systems have varying degrees of reliability. Tolerance to unexpected hardware or software failures is measured by a system's fault tolerance. As a result of cloud computing’s inability to handle a wide range of errors, its reputation has been tarnished. Tolerating Byzantine errors is difficult since they typically go unnoticed at the beginning and can quickly spread to other virtual machines before being discovered. Thus, vital applications such as air traffic control, online baking, and so on are still avoiding the cloud because of these concerns. As well as some existing models, the goal of this research is to better understand and compare fault tolerance strategies utilised for fault tolerance in cloud systems. The purpose of this work is to evaluate a cloud -based fault-optimization strategy that will address the shortcomings of existing algorithms.
      PubDate: 2022-08-21
      DOI: 10.26483/ijarcs.v13i4.6883
      Issue No: Vol. 13, No. 4 (2022)
  • Implementation of Cyber Security Attacks and Strategic Mitigation

    • Authors: Rushabh Bhagwandas Kela, Abhinav Chawla, Pratishtha Gaur, Manikandan K
      Pages: 28 - 34
      Abstract: Cyber threats have increased drastically in the recent years and the most common targets are organisation applications or systems for data theft, disrupting the operations or any other malicious use. Incorporating website security prevents these sorts of attacks on the system. It is the act/practice of protecting websites from unauthorized access, use, modification, destruction, or disruption. A web application will be created and tested on various attacks such as Brute Force Dictionary attack, Denial-of-Service attacks, Cross Site Scripting (XSS) attack, NoSQL injections and WebSocket attacks. The vulnerabilities will be analyzed, and resolved to ensure that the confidentiality, integrity, and authenticity of the user data is not compromised. To improve the website security and privacy, measures will be taken to add security features and the code of the website will be modified.
      PubDate: 2022-08-22
      DOI: 10.26483/ijarcs.v13i4.6890
      Issue No: Vol. 13, No. 4 (2022)
  • A Fingerprint Based Gender Detector System using Fingerprint Pattern

    • Authors: Faluyi Ibitayo Bamidele, Olowojebutu Olanrewaju Akinyemi, Makinde Oyeladun Bukola
      Pages: 35 - 47
      Abstract: Humans have distinctive and unique traits which can be used to distinguish them thus, acting as a form of identification. Biometrics identifies people by measuring some aspect of individual’s anatomy or physiology such as hand geometry or fingerprint which consists of a pattern of interleaved ridges and valleys. The aim of this research is to analyse humans fingerprint texture in order to determine their gender, and correlation of RTVTR and Ridge Count on gender detection. The study is to analyze the effectiveness of physical biometrics (thumbprint) in order to determine gender in humans. Humans have distinctive and unique traits which can be used to distinguish them thus, acting as a form of identification. Biometrics identify people by measuring some aspect of individual’s anatomy or physiology such as hand geometry or fingerprint which consists of a pattern of interleaved ridges and valleys. This work developed a system that determines human gender using fingerprint analysis trained with SVM+CNN (for gender classification). To build an accurate fingerprint based model for gender detection system using fingerprint pattern analysis, there are certain steps that must be taken, which include; Data collection (in conducting research, the first step is collecting data in the form of a set of fingerprint image), Pre-processing Data (before entering the training data, pre-processing data is performed, which is resize the fingerprint image 96x96 pixels). Training Data (in this processing the dataset will be trained using the Convolutional neural network and Support vector machine methodology. This training data processing is a stage where CNN + SVM are trained to obtained high accuracy from the classification conducted). Result Verification (after doing all the above process, at this stage, we will display the results of gender prediction based on fingerprint images in the application that has been making). SOCOFing database is made up of 6,000 fingerprint images from 600 African subjects. It contains unique attributes such as labels for gender, hand and finger name as well as synthetically altered versions with three different levels of alteration for obliteration, central rotation, and z-cut. The values for accuracy, sensitivity and precision using the CNN classifier at threshold 0.25 were 96%, 97.8% and 96.92% respectively. At threshold 0.45 the values were 96.3%, 97.6% and 97.6% respectively. At threshold 0.75 the values were 96.5%, 97.3% and 97.9% respectively. In case of the SVM classifier, at threshold 0.25 were 94.3%, 96.6% and 95.8% respectively. At threshold 0.45 the values were 94.5%, 96.4% and 96.2% respectively. At threshold 0.75 the values were 94.8%, 97.3% and 96.8% respectively. From the 600 fingerprints classified, it was observed that a total of 450 fingerprints were detected for male and 150 for female. Results were obtained for gender accuracy, sensitivity and precision through several thresholds to compare the two classifiers. However, it should be verified that the results obtained showed that the CNN classification yielded better accuracy, sensitivity and precision than SVM.
      PubDate: 2022-08-26
      DOI: 10.26483/ijarcs.v13i4.6885
      Issue No: Vol. 13, No. 4 (2022)
  • Grid-based Design for Dual Monitoring Applications in WSN with Mobile Sink

    • Authors: Shivani S Bhasgi, Dr. Sujatha Terdal
      Pages: 48 - 51
      Abstract: Wireless sensors are used in ample number of applications for sensing different data. They are used in environmental monitoring or event based, but applications requiring both are not very familiar. These kinds of applications require data to be delivered based on the deadline. Such hybrid systems are considered and a method feasible for both is proposed in this paper.  Sensors are grouped into clusters and group heads are selected based on some parameters which will help to save energy, balance the network as well as extend the lifetime. The sensors collect data and send to group heads using TDMA and data is collected by mobile sink time slots are allotted for time sensitive event data. The proposed technique is implemented in NS2 and compared with existing algorithms in terms of lifetime, delay etc. The proposed procedure has 15% more lifetime than previous methods. 
      PubDate: 2022-08-31
      DOI: 10.26483/ijarcs.v13i4.6894
      Issue No: Vol. 13, No. 4 (2022)
  • Internet of Things (IoT) Technologies for Shimla City-A Case Study

    • Authors: Anshul Kalia, Rishi Rana, Sumesh Sood, Aayushi Kalia, Nikhlesh Kumar Badoga
      Pages: 52 - 55
      Abstract: The large deployment of Internet of Things (IoT) is actually enabling Smart City projects and initiatives all over the world. Objects used in daily life are being equipped with electronic devices and protocol suites in order to make them interconnected and connected to the Internet. According to a recent Gartner study, 50 billion connected objects have been deployed in smart cities by 2020. These connected objects will make our cities smart. However, they will also open up risks and privacy issues. As various smart city initiatives and projects have been launched in recent years, we have witnessed not only the expected benefits but the risks introduced. The current and future trends of smart city with respect to IoT have been described. It also discussed the interaction between smart cities and IoT. The drivers behind the evolution & development of IoT and smart cities have been explained. Finally, the IoT weaknesses and how they can be addressed when used for smart cities has been discussed.
      PubDate: 2022-08-31
      DOI: 10.26483/ijarcs.v13i4.6900
      Issue No: Vol. 13, No. 4 (2022)
  • A survey on Effective Machine Learning Techniques in the field of Cyber

    • Authors: Rishin Pandit, Lagan Gupta, Dr. MANIKANDAN K
      Pages: 56 - 61
      Abstract: Machine learning techniques have many cybersecurity applications, and they have entered the mainstream in a variety of fields. Examples include threat analysis, anomaly-based intrusion detection of frequent attacks on important infrastructures, malware analysis, particularly for zero-day malware detection, and many others. Machine learning-based detection is being employed by researchers in many cybersecurity solutions as a result of the inefficiency of signature-based methods in identifying zero day attacks or even modest modifications of existing assaults. In this paper, we cover a number of cybersecurity applications for machine learning. We also give a few examples of adversarial assaults on machine learning algorithms that aim to corrupt classifiers' training and test data in order to render them useless.

      PubDate: 2022-09-01
      DOI: 10.26483/ijarcs.v13i4.6893
      Issue No: Vol. 13, No. 4 (2022)
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