Indian Journal of Computer Science and Engineering最新文献

EVALUATION OF FUZZING ON WEB API FROM OFFENSIVE AND DEFENSIVE PERSPECTIVES 从攻防角度评估网络应用程序接口的模糊测试

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i2/241502029

Danar Gumilang Putera, Ruki Harwahyu

引用次数: 0

A DEEP LEARNING MODEL IMPLEMENTATION OF TABNET FOR PREDICTING PEPTIDE-PROTEIN INTERACTION IN CANCER 用于预测癌症中肽与蛋白质相互作用的 tabnet 深度学习模型实现

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i1/241501032

Hanif Aditya Pradana, Ahmad Ardra Damarjati, Isman Kurniawan, W. Kusuma

{"title":"A DEEP LEARNING MODEL IMPLEMENTATION OF TABNET FOR PREDICTING PEPTIDE-PROTEIN INTERACTION IN CANCER","authors":"Hanif Aditya Pradana, Ahmad Ardra Damarjati, Isman Kurniawan, W. Kusuma","doi":"10.21817/indjcse/2024/v15i1/241501032","DOIUrl":"https://doi.org/10.21817/indjcse/2024/v15i1/241501032","url":null,"abstract":"Cancer has become one of the deadliest diseases in the world, mainly caused by the accumulation of somatic and inherited mutations. However, this phenomenon can be traced back to the molecular level, specifically, to proteins. Proteins are molecules responsible for various bioprocesses in the human body through their interactions with other molecules. Abnormalities in these interactions can lead to various undesirable outcomes, including disease and cancer. Peptides have the potential to serve as molecules that can be used in protein interactions to treat cancer. However, identification of peptides corresponding to target proteins in the laboratory is time-consuming and expensive. Therefore, there is a need for computational methods to aid identification. TabNet, a deep learning-based computational method was used in this study. For comparison purposes, we selected techniques from ensemble learning, including Random Forest and Extreme Gradient Boosting, along with methods from deep learning such as Convolutional Neural Network and Stacked Autoencoder-Deep Neural Network. Predictions are performed on a multi-feature peptide-protein interaction dataset, and the features include position-specific scoring matrices, intrinsic disorder, amino acid sequence, and physicochemical properties. Among our selected metrics, we found that TabNet achieved a better score in AUC of 0.7 and lower false negatives compared to other models.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680122","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}

引用次数: 0

ENHANCING PERFORMANCE OF TRAFFIC CLASSIFICATION WITH FEATURE SELECTION METHODS 利用特征选择方法提高交通分类性能

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i2/241502031

Htay Htay Yi, Khaing Khaing Wai

引用次数: 0

MACHINE LEARNING MODEL FOR ANOMALY-BASED INTRUSION DETECTION USING RANDOM FOREST CLASSIFIER 使用随机森林分类器的异常入侵检测机器学习模型

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i2/241502004

Ebiesuwa Seun, Nwachukwu Victor, Falana Taye, Adegbenjo Aderonke, Dipo Tepede, Adio Adesina

引用次数: 0

New Hybrid Model with Fine Blend of Agile and Waterfall 敏捷与瀑布式完美融合的新型混合模式

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i1/241501028

P. Vijaya, V. Reddy

{"title":"New Hybrid Model with Fine Blend of Agile and Waterfall","authors":"P. Vijaya, V. Reddy","doi":"10.21817/indjcse/2024/v15i1/241501028","DOIUrl":"https://doi.org/10.21817/indjcse/2024/v15i1/241501028","url":null,"abstract":"The paper recommends a new hybrid model for software projects delivery with fine blend of the both agile and waterfall models by addressing the drawbacks of both models. The traditional waterfall model development goes one phase after the other and any changes to previous phase is addressed late in the delivery cycle thus most of the times implemented software and customer expectation will not by in sync or sometimes poles apart. The trending agile focuses on small chunks development with iterative cycles, going back to the customer for feedback at every phase and reaching the expectation and delivering the functionality which client was looking for. The agile model may not be suitable for projects where the requirements are very intricate and cannot be easily fragmented into smaller iterations and requirements are definite and constant, and where deviations to the requirements are improbable. The waterfall model may not be suitable for projects where the requirements are uncertain or likely to change, as changes to the requirements need changes to previous phases. The paper recommends a new fine blended model with the best of agile and waterfall approaches with the collaboration of Delivery with Sprints and POD teams, and gets the delivery with optimal cost and speed. The projected novel model is a fine blend of best of both models by eliminating shortfalls of the Agile and Waterfall.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681898","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}

引用次数: 0

POSITION CONTROL FOR AN ELECTROHYDRAULIC VERTICAL LAUNCHING SYSTEM BASED ON PSOPID STRATEGY 基于 PSOPID 策略的电液垂直发射系统的位置控制

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i2/241502035

Ayman A. Aly, Mousa G.

引用次数: 0

ARABIC SIGN LANGUAGE RECOGNITION SYSTEMS: A SYSTEMATIC REVIEW 阿拉伯手语识别系统：系统回顾

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2023/v15i1/241501008

Ahmad M. J. AL Moustafa, Mohd Shafry Mohd Rahim, M. Khattab, Akram M. Zeki, Safaa S. Matter, Amr Mohmed Soliman, Abdelmoty M. Ahmed

引用次数: 0

MACHINE LEARNING MODELS FOR HEART DISEASE PREDICTION-A REVIEW 预测心脏病的机器学习模型--综述

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i2/241502003

Parvati Kanaki, Dr Gyanappa A. Walikar

引用次数: 0

SCALABILITY ASSESSMENT AND PERFORMANCE OPTIMIZATION OF HYPERLEDGER FABRIC 超级账本结构的可扩展性评估和性能优化

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i1/241501051

Cho Cho Htet, Aye Myat Thu

{"title":"SCALABILITY ASSESSMENT AND PERFORMANCE OPTIMIZATION OF HYPERLEDGER FABRIC","authors":"Cho Cho Htet, Aye Myat Thu","doi":"10.21817/indjcse/2024/v15i1/241501051","DOIUrl":"https://doi.org/10.21817/indjcse/2024/v15i1/241501051","url":null,"abstract":"The feature of Blockchain as distributed ledger that are shared among nodes within a computer network, renowned for its pivotal role in cryptocurrency systems by ensuring a secure and decentralized the role of transaction record which is ensured for maintenance of security and decentralization in cryptocurrency systems. The Linux Foundation host the open-source framework of private blockchain, the Hyperledger Fabric (HLF). Smart contracts are utilized for transaction management and a modular architecture of blockchain framework, providing a foundation for the development of blockchain-based applications through plug-and-play components. In the realm of distributed systems, scalability emerges as a crucial design goal for developers. The most appropriate blockchain platform for the operations of the business industry, which need for the seamless addition of more users and resources without perceptible performance loss. An assessment of scalability is required as a large number of nodes involvement in the implementation of blockchain frameworks. In this paper, the impact of system configurations such as, transaction volume, node types is focused in the transition of V2.2.4 with the various significant issues with the architecture. The throughput, latency, processor, and memory usages are mainly analyzed based on the different number of transactions. According to the performance results of the proposed system, the scalability of the possible number of transactions and the different peer nodes can be supported in the implementation of blockchain-based system for HLF blockchain.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681779","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}

引用次数: 0

AN AUTOMATAED DEEP LEARNING MODEL TO CLASSIFY DISEASES IN AREACANUT PLANT 一种自动深度学习模型，用于花生病害分类

Indian Journal of Computer Science and Engineering Pub Date : 2024-04-20 DOI: 10.21817/indjcse/2024/v15i1/241501036

S. A. Kumar, A. Dharani, Deepak Mb, Aishwarya K Kamble

{"title":"AN AUTOMATAED DEEP LEARNING MODEL TO CLASSIFY DISEASES IN AREACANUT PLANT","authors":"S. A. Kumar, A. Dharani, Deepak Mb, Aishwarya K Kamble","doi":"10.21817/indjcse/2024/v15i1/241501036","DOIUrl":"https://doi.org/10.21817/indjcse/2024/v15i1/241501036","url":null,"abstract":"Detecting diseases in plant at an early stage is important for ensuring healthy crops and reducing economic losses. Traditional methods are slow and require expertise. The recent technological developments bring in a lot of computational techniques that enables the detection of diseases at an early stage and more accurate. The proposed work has been implemented using deep learning algorithms The work focuses on identifying the diseases in Arecanut leaf and analyzing the efficiency of the deep learning techniques in detecting the type of diseases. Different CNN algorithms like ReNet, MobiNet and VGG Net have been implemented and tested for thier efficiency. The appropriate model is then optimized and deployed in an Android device so as to enable the farmer to use the application efficiently. The proposed work is implemented by collecting a dataset of arecanut diseased leaf images and dividing it for training, validation, and testing. The performance of the models are compared using the parameters (trainable and non-trainable) and the utilisation of the memory during runtime. The models are evaluated based on accuracy and precision. For the given dataset, ResNet performed with 79% accuracy, MobiNet with 86% and VGG with 92% accuracy. The performance efficiency of VGGNet is better than the other two architectures and deployed in Android device to help the stakeholders.","PeriodicalId":52250,"journal":{"name":"Indian Journal of Computer Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680921","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}

引用次数: 0