2023 IEEE 8th International Conference for Convergence in Technology (I2CT)最新文献_第2页

Multi-criteria Decision Theoritic Approach for Tour Package Selection using Fuzzy AHP and TOPSIS Methods: A Case Study on Cox’s Bazar 基于模糊层次分析法和TOPSIS法的旅游套餐选择多准则决策方法——以考克斯巴扎尔为例

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126334

Marufa Kamal, Rakib Hossain Rifat, Abanti Chakraborty Shruti, Md. Golam Rabiul Alam

{"title":"Multi-criteria Decision Theoritic Approach for Tour Package Selection using Fuzzy AHP and TOPSIS Methods: A Case Study on Cox’s Bazar","authors":"Marufa Kamal, Rakib Hossain Rifat, Abanti Chakraborty Shruti, Md. Golam Rabiul Alam","doi":"10.1109/I2CT57861.2023.10126334","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126334","url":null,"abstract":"The global tourism business is expanding as more people travel and visit new locations both abroad and locally. Cox’s Bazar is the longest natural unbroken sea beach in the world situated in Bangladesh accommodating millions of foreign and local tourists every year. This has been a very popular destination with various activities and beautiful natural attraction spots. There are numerous Cox’s Bazar trip packages available for travelers to choose from. Compared to the large number of tour packages found online for this destination at present, this paper proposes a methodology to help the tourists to select a tour package based on their likings and different criteria. A decision-making selection process has been proposed using the Fuzzy Analytic Hierarchy Process(FAHP) and TOPSIS method to rank the packages based on 12 criteria that are closely knitted to the preference of users during the time of tour selection. A dataset of 100 alternative tour packages has been built with existing tour packages found from online travel agency websites and multiple decision makers are used to make pairwise criterion comparison. The tourists/users input fuzzy numbers, and then using the proposed methodology a ranking of all the alternatives is provided to aid them in choosing the optimal tour package.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129643787","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

Predicting Returns of Exchange Rate from Oil Prices: Machine Learning Approach 从油价预测汇率收益:机器学习方法

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126372

B. T. Khoa, T. Huynh, Nguyen Thi Diem Huong

引用次数: 0

A Comprehensive Review on Precision Agriculture and Machine Learning Approach in Bangladesh 孟加拉国精准农业和机器学习方法综述

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126189

Syed Ishtiak Rahman, Shifa Chowdhury Iwase, Arefin Ittesafun Abian, Tapotosh Ghosh, D. Farid

{"title":"A Comprehensive Review on Precision Agriculture and Machine Learning Approach in Bangladesh","authors":"Syed Ishtiak Rahman, Shifa Chowdhury Iwase, Arefin Ittesafun Abian, Tapotosh Ghosh, D. Farid","doi":"10.1109/I2CT57861.2023.10126189","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126189","url":null,"abstract":"Agriculture is seen as a key pillar of the economy of Bangladesh. The country produces an enormous variety of crops. To ensure stability by preventing losses and maintaining supply and market demand, the integration of advanced technology like Machine Learning (ML) in agriculture is beneficial. With the growth of Big Data techniques and powerful computers, ML has opened up new possibilities for data-intensive research in a variety of disciplines of crop cultivation. Since crops are one of the main components of agriculture, our main concerns are issues relating to crops such as disease detection, crop price and yield prediction. Disease infected crops cause significant loss. Producers need to have the right information on which crops should be harvested where and when. Again, ensuring fair price of crops is mandatory for economical balance and stability. This paper provides an in-depth review of the research on ML applications in agricultural systems. A combination of ML and agriculture can provide great suggestions and in-depth insights for farmers in decision support and action.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121417963","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

Precision Agriculture: Classifying Banana Leaf Diseases with Hybrid Deep Learning Models 精准农业:用混合深度学习模型对蕉叶病害进行分类

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126431

D. Banerjee, V. Kukreja, S. Hariharan, Vandana Sharma

引用次数: 0

Message Queuing Telemetry Transport Based Data Logger 基于消息队列遥测传输的数据记录器

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126489

Archana Tiwari, Bharti Masram, Kritika Bharatdwaj

引用次数: 0

Defending Against Identity Threats using Adaptive Authentication 使用自适应身份认证防御身份威胁

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126295

Lalitha Sravanti Dasu, Mannav Dhamija, Gurram Dishitha, Ajith Vivekanandan, Sarasvathi V

{"title":"Defending Against Identity Threats using Adaptive Authentication","authors":"Lalitha Sravanti Dasu, Mannav Dhamija, Gurram Dishitha, Ajith Vivekanandan, Sarasvathi V","doi":"10.1109/I2CT57861.2023.10126295","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126295","url":null,"abstract":"Defending against identity-based threats and attacks which have tremendously grown in number in the age of remote working and access, requires intelligent, strategic, nonconventional, and dynamic ways of authentication and authorization. This paper aims to make identity security risk-based and hence adaptive by devising risk-scoring algorithms for five real-time use cases in detail. Zero-trust security principles are incorporated by continually collecting sign-in logs and analyzing them to check for any suspicious activities or anomalies to make it a dynamic approach. Based on the risk scores calculated users are segregated as risky and non-risky. While many adaptive authentication approaches have been proposed, the identities are confined just to users. Moreover, they lack emphasis on practical risk evaluation techniques. This work considers devices as an identity too and categorizes them as registered and unregistered devices. Further, results are made available to security administrators by displaying them on a dashboard for them to analyze and make necessary decisions like mitigation, multi-level authentication, or any other access control policies as such.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121678296","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

Implementing Federated Learning based on RainForest Model 基于雨林模型的联邦学习实现

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126333

Mainul Karim, Niloy Kumar Kundu, Dipu Saha, Sarah Kabir, Sumaiya Mim, Dewan Md. Farid

{"title":"Implementing Federated Learning based on RainForest Model","authors":"Mainul Karim, Niloy Kumar Kundu, Dipu Saha, Sarah Kabir, Sumaiya Mim, Dewan Md. Farid","doi":"10.1109/I2CT57861.2023.10126333","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126333","url":null,"abstract":"Federated Learning (FL) is a new concept in machine learning that trains predictive models across multiple nodes and machines holding local training data without sharing that data with other nodes. It’s also known as collaborative learning. In FL, instead of sending the training data, only parameter values are uploaded to the master node or server. On the contrary, Rainforest is a concept for dealing with big data using a decision tree (DT) classifier. DT is one of the popular machine learning algorithms, which is a top-down recursive divide and conquer method. In this paper, we utilized the concept of federated learning by applying the Rainforest algorithm, where datasets are divided into several subsets of data using the clustering technique, from which scalable decision trees are constructed. From each subset of data, we have an AVC (attribute-value, class-label) table, which is sent to the central master node or server to create the full decision tree by using matrix addition. To train the model, we used ten different datasets and evaluated the proposed model. The experimental analysis shows very good accuracy and precision in overall performance.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127635218","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: 1

Intrusion Detection System using Ensemble Learning Analytics 基于集成学习分析的入侵检测系统

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126368

Anil Kumar Dasari, Saroj K. Biswas, Saptarsi Sanyal, B. Purkayastha

{"title":"Intrusion Detection System using Ensemble Learning Analytics","authors":"Anil Kumar Dasari, Saroj K. Biswas, Saptarsi Sanyal, B. Purkayastha","doi":"10.1109/I2CT57861.2023.10126368","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126368","url":null,"abstract":"An Intrusion Detection System (IDS) monitors and analyses data to find any intrusions into a system or network. The network generates data at a tremendous volume, variety, and speed, making it difficult to detect attacks using conventional techniques like a virus detection system, misuse detection software i.e. the database of attack signatures that it uses to compare packets. Despite the researchers' significant efforts, IDS still struggles to identify new intrusions, to improve detection accuracy, and to reduce false alarm rates. To overcome the problems mentioned above this paper proposes an unique model named Intrusion Detection System using Machine Learning Analytics (IDSMLA), which uses SMOTE oversampling technique to deal with class imbalance problem, it also uses Minimum Redundancy Maximum Relevance (mRMR) to perform feature selection as feature selection reduces time complexity by eliminating irrelevant features and hence increasing the accuracy of the model and finally to perform classification task, the proposed model IDSMLA uses Extra Trees(ET) bagging ensemble technique. The performance of the proposed model IDSMLA is measured using accuracy and F1-score using 10-folds cross validation. Experimental results have demonstrated that the proposed model IDSMLA greatly outperforms different single-classifier based models, different ensemble models as well as different models present in literature.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126363970","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

Multi-Objective Optimal Bidding Approach for both Small & Large Customers in Competitive power Market 电力市场竞争中大、小客户多目标最优竞价方法

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126351

Manisha Saini, Ajay Bhardwaj, Sarfaraz Nawaz

{"title":"Multi-Objective Optimal Bidding Approach for both Small & Large Customers in Competitive power Market","authors":"Manisha Saini, Ajay Bhardwaj, Sarfaraz Nawaz","doi":"10.1109/I2CT57861.2023.10126351","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126351","url":null,"abstract":"In the present scenario of the electricity energy market, power generation firms seek to maximize revenue by optimizing the bid in the electricity market. In a competitive market, Strategic bidding allows each participant to improve his individual profit; however, this has a detrimental effect on public benefit. This study presents a mechanism for developing a strategic bid for electricity producers and users in a pool co-style energy market. The system is dispatched to maximize social welfare, with each supplier/large consumer bidding a linear supply/demand function. Price takers require a proper bidding structure to identify the best bidding tactics. As a result, the model must be thought of as a two-level optimization issue. Price takers submit strategic bids to the Independent System Operator (ISO) at the lower level, while the ISO Market Clearing Price (MCP) is used to maximize social welfare at the upper level in a day-ahead power market to maximize social welfare at the upper level using a pay-as-bid mechanism in a sealed auction in the competitive power market. On the IEEE-30 bus system, the proposed method's efficiency was tested. Four different evolutionary algorithms such as NSGA-II, NSGA-III, MOGWO, and MOPSO were used to address the problem from two separate perspectives for solving proposed multi-objective problems. The result section presents a comparative analysis of the total profit and market clearing price, showing that the NSGA-III algorithm offers superior results than other methods.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126409013","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

Design and Development of Control Algorithm for a DC Microgrid System 直流微电网系统控制算法的设计与开发

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126209

A. Shirodkar, C. Vyjayanthi

引用次数: 0