International Journal of Advanced Research in Computer Science最新文献

{"title":"PSO-BASED LOAD BALANCING WITH GEOGRAPHIC ROUTING USING GREEDY PERIMETER STATELESS ROUTING (PSO-GPSR) FOR WIRELESS SENSOR NETWORKS (WSNS)","authors":"B. Narasimhan","doi":"10.26483/ijarcs.v14i6.7030","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i6.7030","url":null,"abstract":"","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"435 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139170220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COMPARATIVE SURVEY OF 5G NETWORK ON DIFFERENT TECHNOLOGIES IN NETWORK SECURITY","authors":"A. Adegbenjo","doi":"10.26483/ijarcs.v14i6.7033","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i6.7033","url":null,"abstract":"","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"25 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139169384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E-COMMERCE PRODUCT RATING BASED ON CUSTOMER MINING FOR COMMENTS USING MACHINE LEARNING TECHNIQUE","authors":"Salah Zaher","doi":"10.26483/ijarcs.v14i6.7029","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i6.7029","url":null,"abstract":"","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"72 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139170836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ENHANCING PUNJABI-HINDI BRAILLE NEURAL MACHINE TRANSLATION VIA SYNTACTIC ANALYSIS","authors":"Harshita Samota","doi":"10.26483/ijarcs.v14i6.7034","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i6.7034","url":null,"abstract":"","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"754 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139169985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EVALUATING THE EFFICACY OF ALEXNET FOR DETECTION OF THYROID CANCER","authors":"Shiwangi Kulhari","doi":"10.26483/ijarcs.v14i6.7032","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i6.7032","url":null,"abstract":"","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"16 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139168918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AN ENHANCED SOFTWARE AS A SERVICE (SAAS) ARCHITECTURAL MODEL FOR CLOUD BASED SECURITY USING HYBRID SYMMETRIC ALGORITHM","authors":"Afiesimama Dimabo Joshua","doi":"10.26483/ijarcs.v14i3.7007","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i3.7007","url":null,"abstract":"Protecting cloud data from security breaches, preventing and ensuring safe cloud data is concealed from unauthorized access or infiltration by unwanted users are all part of cloud infrastructure security. This proposed technique is based on ensuring data confidentiality by adding extra-layer of security from the client side, developing a framework that implements the AES 256-bit key and Fernet 128-bits algorithms, which encrypt and decrypt files via random algorithm selection during uploads and downloads. When a file is uploaded to the cloud, the decryption key is recorded in the local server's file log. The software use randomized algorithm selection to provide security to ensure that an attacker having a prior link cannot reset the user account since the attacker cannot guess the token. Furthermore, invalidating this token ensures that the link cannot be used more than once if it was previously logged anywhere. To propose and verify the efficiency of the model the results generated(in quantitative values) are frequency (monobit) testing, with a minimum bit size of 64, given the P-values derived from the above study (i.e., 0.8838, 0.6187, 0.3768, 0.2817, 0.5843, 0.4167). The findings reveal throughput for encryption of 0.91531 and for decryption of 0.4854, space complexity of 0.4854, and entropy of 7.942616667.This research work studies the design of a robust, adaptable, and non-deterministic SaaS application that can be secure for enterprises and subsequent research studies will be conducted in the development.","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126009861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ADAS USING TOUCH SENSOR","authors":"Mohit B M,","doi":"10.26483/ijarcs.v14i3.7009","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i3.7009","url":null,"abstract":"EPS systems integrate Advanced Driver Assistance Systems (ADAS) while the driver controls the steering wheel. Touch sensors, torque, and position sensors improve driver involvement, safety, and control in EPS. ADAS features like lane-keeping assistance and adaptive cruise control are activated by the driver’s steering wheel touch. EPS with driver-enabled ADAS integration, using touch sensors, empowers drivers while leveraging enhanced automation. The vehicle model design incorporates touch sensors, Arduino, and motor drivers to enable Advanced Driver Assistance Systems (ADAS) exclusively when the driver holds the steering wheel. The touch sensors detect the driver’s touch on the steering wheel, triggering the ADAS functionalities and allowing the vehicle to move. The Arduino microcontroller, equipped with embedded C code, processes the touch sensor inputs and communicates with the motor drivers to initiate vehicle propulsion. The embedded C code facilitates real-time monitoring and control of the touch sensor inputs, enabling a seamless integration between driver interaction and vehicle movement, thereby enhancing both safety and user experience","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PPS-FPCM: PRIVACY-PRESERVING SEMI-FUZZY POSSIBILISTIC C-MEANS","authors":"M. Mahfouz","doi":"10.26483/ijarcs.v14i3.6991","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i3.6991","url":null,"abstract":"Applying traditional clustering techniques to big data on the cloud while preserving the privacy of the data is a challenge due to the required division and exponential operations in each iteration, which complicate its implementation on encrypted data. Several existing approaches are based on approximating the formulas of centers, weights, and memberships as three polynomial functions according to the multivariate Taylor formula. However, they usually suffer an increase in complexity and a slight drop in accuracy. In this paper, a novel Privacy-Preserving semi-fuzzy clustering algorithm based on the possibilistic paradigm, termed PPS-FPCM, is presented. Its main feature is that it avoids exponentiation and division operations, at each iteration, without losing accuracy. By restricting the typicality to an ordered set of discrete values between zero and one decided by the data owner (DO), the computation is simplified. The second key idea is the use of this soft typicality to detect outliers and compute the corresponding semi-fuzzy memberships, which is used to increase the in-between cluster distance. However, the initial typicality requires a magnitude relation comparison, which is still difficult to do over encrypted data. In this research study, we show how the existing incomplete re-encryption method can be used to tackle this problem. In each iteration, centers and distances to the new centers are computed on a calculator cloud server (CaCS) which is responsible for storing the cipher texts of the (DO)’s data and processing them. Then, CaCS sends the incompletely re-encrypted difference between these distances and iteratively updated bin values that correspond to the discrete possibilistic memberships that are initially decided by the (DO) to the comparator cloud server (CoCS). CoCS decrypts the difference and returns the results of comparisons. When CaCS receives the results of comparison from CoCS, it decides on an appropriate soft typicality or resends the difference of the same distance to another bin value. The required number of comparisons is O(log the number of bins). CaCS iteratively computes the corresponding semi-fuzzy memberships, computes the refined memberships, and updates the centers. In the end, CaCS sends the final soft memberships and centers to the (DO). The proposed algorithm is applicable to normal data and homomorphically encrypted data, is more effective than several related algorithms, and can produce accurate results using large enough (16 or more) discrete values with a high reduction on runtime as the number of comparisons is much less complex than exponential and division operations with added communication cost between CaCS and CoCS.","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116728335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-WEAR: SMART TEXT READER FOR BLIND/VISUALLY IMPAIRED STUDENTS USING RASPBERRY PI WITH AUDIO-VISUAL CALL AND GOOGLE ASSISTANCE","authors":"Allen Llorca","doi":"10.26483/ijarcs.v14i3.6997","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i3.6997","url":null,"abstract":"The goal of this research is to create a prototype referred to as AI-WEAR: Smart Text Reader for Blind or Visually Impaired Students, which utilizes Raspberry Pi equipped with Audio-Visual Call and Google Assistance. The prototype incorporates various functionalities including text-to-speech capability for reading, Google assistance for online support, and video streaming through Jitsi Meet, enabling students to interact with their teachers. The device offers two modes of control: voice commands and user-friendly buttons with Braille letters engraved on them. OCR (Optical Character Recognition) and Text-to-Speech are integrated into the system. Synthesis techniques on the Raspberry Pi platform. By utilizing OCR, the device scans and extracts text, which is then converted into audio output through a headset. Additionally, the device employs GSM/GPRS technology to access the internet via cellular data when Wi-Fi connectivity is unavailable. The researcher employed the Long-Short Term Memory and Image processing algorithms in this project, and extensive testing and maintenance have been conducted, resulting in favourable evaluation outcomes. The prototype has successfully met the desires of the ISO/IEC 25010 standard. Although some adjustments may be necessary, this proposed device has significant potential to provide visually impaired individuals with innovative learning opportunities, especially in distance education settings. Furthermore, a cost-comparative analysis for future mass production of this assistive prototype tool for blind and visually impaired has been conducted.","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121704482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MECHANISMS AND TOOLS USED FOR RESOURCE ALLOCATION IN THE CLOUD","authors":"J. Kaur","doi":"10.26483/ijarcs.v14i3.7006","DOIUrl":"https://doi.org/10.26483/ijarcs.v14i3.7006","url":null,"abstract":"Pay-as-you-go access to computer resources is a major selling point of the cloud computing model. Cloud tenants demand complete networking of their dedicated resources to simply implement network functions and services, in addition to the conventional computer resources. The flexibility and convenience of on-demand resource provisioning make cloud computing a compelling computing platform. The key to meeting fluctuating needs and maximizing return on investment from Cloud-supporting infrastructure is dynamic resource allocation and reallocation. For traditional IaaS, we offer an energy-efficient resource allocation strategy based on bin packing. In this paper, we present an accurate energy-conscious method for initial resource allocation by casting the issue of energy-efficient resource allocation as a bin-packing model. The available VMs (virtual machines) employ a modified version of the max-min scheduling technique, which saves money and resources. The results of this study give a framework for comparing and contrasting the many different resource distribution approaches that have been proposed by other researchers. The importance of efficient data centers for the cloud is growing. Power consumption has been a major problem due to its expanding size and widespread usage. The overarching purpose of this effort is to create models and algorithms for resource allocation that are both energy-efficient and take into account a variety of relevant factors","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121573447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}