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An Algorithm for Data Management of Higher Education Based on Fuzzy Set Theory - Association Rule Mining Algorithm 基于模糊集理论的高等教育数据管理算法--关联规则挖掘算法

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-12-09 DOI: 10.31449/inf.v47i9.5222

Youmeng Guan

引用次数: 0

Hyperparameter Optimization for Convolutional Neural Networks using the Salp Swarm Algorithm 使用 Salp Swarm 算法优化卷积神经网络的超参数

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-12-09 DOI: 10.31449/inf.v47i9.5148

Entesar Abdulsaed, Maytham Alabbas, Raidah S. Khudeyer

引用次数: 0

A Study of Identification of Corporate Financial Fraud Using Neural Network Algorithms in an Information-based Environment 在信息化环境中利用神经网络算法识别企业财务欺诈的研究

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-12-06 DOI: 10.31449/inf.v47i9.5220

Zilu Liang, Yunji Liang

引用次数: 0

Interval-Valued Pythagorean Fuzzy Extension of DEMATEL for Prioritizing and Casualty Analysis of Environmental Criteria of Organizational Behaviour in Higher Education Sector 高等教育部门组织行为环境准则的优先排序和损失分析的DEMATEL的区间值毕达哥拉斯模糊推广

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-12-06 DOI: 10.15388/23-infor541

Jafar Torkzadeh, Dragan Pamucar, Sadegh Niroomand

引用次数: 0

Enhancing Phishing Website Detection via Feature Selection in URL-Based Analysis 在基于 URL 的分析中通过特征选择加强钓鱼网站检测

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-12-05 DOI: 10.31449/inf.v47i9.5177

Marwa-Aqa Abd Al Hussein Qasim, Nahla A. Flayh

引用次数: 0

Selection of Suitable Cloud Vendors for Health Centre: A Personalized Decision Framework with Fermatean Fuzzy Set, LOPCOW, and CoCoSo 健康中心合适云供应商的选择:一个具有Fermatean模糊集、LOPCOW和CoCoSo的个性化决策框架

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-11-23 DOI: 10.15388/23-infor537

Sundararajan Dhruva, Raghunathan Krishankumar, Edmundas Kazimieras Zavadskas, Kattur Soundarapandian Ravichandran, Amir H. Gandomi

{"title":"Selection of Suitable Cloud Vendors for Health Centre: A Personalized Decision Framework with Fermatean Fuzzy Set, LOPCOW, and CoCoSo","authors":"Sundararajan Dhruva, Raghunathan Krishankumar, Edmundas Kazimieras Zavadskas, Kattur Soundarapandian Ravichandran, Amir H. Gandomi","doi":"10.15388/23-infor537","DOIUrl":"https://doi.org/10.15388/23-infor537","url":null,"abstract":"Cloud computing has emerged as a transformative technology in the healthcare industry, but selecting the most suitable CV (“cloud vendor”) remains a complex task. This research presents a decision framework for CV selection in the healthcare industry, addressing the challenges of uncertainty, expert hesitation, and conflicting criteria. The proposed framework incorporates FFS (“Fermatean fuzzy set”) to handle uncertainty and data representation effectively. The importance of experts is attained via the variance approach, which considers hesitation and variability. Furthermore, the framework addresses the issue of extreme value hesitancy in criteria through the LOPCOW (“logarithmic percentage change-driven objective weighting”) method, which ensures a balanced and accurate assessment of criterion importance. Personalized grading of CVs is done via the ranking algorithm that considers the formulation of CoCoSo (“combined compromise solution”) with rank fusion, providing a compromise solution that balances conflicting criteria. By integrating these techniques, the proposed framework aims to enhance the rationale and reduce human intervention in CV selection for the healthcare industry. Also, valuable insights are gained from the framework for making informed decisions when selecting CVs for efficient data management and process implementation. A case example from Tamil Nadu is presented to testify to the applicability, while sensitivity and comparison analyses reveal the pros and cons of the framework.\u0000PDF  XML","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"22 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138530665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Entropy Measure with its Application to the COPRAS Method in Complex Spherical Fuzzy Environment 一种新的熵测度及其在复杂球面模糊环境下COPRAS方法中的应用

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-11-20 DOI: 10.15388/23-infor539

Ebru Aydoğdu, Başak Aldemir, Elif Güner, Halis Aygün

{"title":"A Novel Entropy Measure with its Application to the COPRAS Method in Complex Spherical Fuzzy Environment","authors":"Ebru Aydoğdu, Başak Aldemir, Elif Güner, Halis Aygün","doi":"10.15388/23-infor539","DOIUrl":"https://doi.org/10.15388/23-infor539","url":null,"abstract":"A complex spherical fuzzy set (CSFS) is a generalization of the spherical fuzzy set (SFS) to express the two-dimensional ambiguous information in which the range of positive, neutral and negative degrees occurs in the complex plane with the unit disk. Considering the vital importance of the concept of CSFSs which is gaining massive attention in the research area of two-dimensional uncertain information, we aim to establish a novel methodology for multi-criteria group decision-making (MCGDM). This methodology allows us to calculate both the weights of the decision-makers (DMs) and the weights of the criteria objectively. For this goal, we first introduce a new entropy measure function that measures the fuzziness degree associated with a CSFS to compute the unknown criteria weights in this methodology. Then, we present an innovative Complex Proportional Assessment (COPRAS) method based on the proposed entropy measure in the complex spherical fuzzy environment. Besides, we solve a strategic supplier selection problem which is very important to maximize the efficiency of the trading companies. Finally, we present some comparative analyses with some existing methods in different set theories, including the entropy measures, to show the feasibility and usefulness of the proposed method in the decision-making process.\u0000PDF  XML","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"38 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138530666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Circular Intuitionistic Fuzzy ELECTRE III Model for Group Decision Analysis 群体决策分析的循环直觉模糊ELECTRE III模型

IF 2.9 4区计算机科学

Informatica Pub Date : 2023-11-17 DOI: 10.15388/23-infor536

Binyamin Yusoff, Dian Pratama, Adem Kilicman, Lazim Abdullah

{"title":"Circular Intuitionistic Fuzzy ELECTRE III Model for Group Decision Analysis","authors":"Binyamin Yusoff, Dian Pratama, Adem Kilicman, Lazim Abdullah","doi":"10.15388/23-infor536","DOIUrl":"https://doi.org/10.15388/23-infor536","url":null,"abstract":"ELECTRE III is a well-established outranking relation model used to address the ranking of alternatives in multi-criteria and multi-actor decision-making problems. It has been extensively studied across various scientific fields. Due to the complexity of decision-making under uncertainty, some higher-order fuzzy sets have been proposed to effectively model this issue. Circular Intuitionistic Fuzzy Set (CIFS) is one such set recently introduced to handle uncertain IF values. In CIFS, each element of the set is characterized by a circular area with a radius, r and membership/non-membership degrees as the centre. This paper introduces CIF-ELECTRE III, an extension of ELECTRE III within the CIFS framework, for group decision analysis. To achieve this, we define extensions for the group decision matrix and group weighting vector based on CIFS conditions, particularly focusing on optimistic and pessimistic attitudes. These attitudinal characters of the group of actors are constructed using conditional rules to ensure that each element of the set falls within the circular area. Parameterized by $alpha in [0,1]$ for the net score degree, we conduct an extensive analysis of group decision-making between optimistic and pessimistic attitudes. To illustrate the applicability of the proposed model, we provide a numerical example of the stock-picking process. Additionally, we conduct a comparative analysis with existing sets and perform sensitivity analyses to validate the results of the proposed model.\u0000PDF  XML","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"246 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138543107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PrSChain: A Blockchain Based Privacy Preserving Approach for Data Service Composition PrSChain:基于区块链的数据服务组合隐私保护方法

4区计算机科学

Informatica Pub Date : 2023-11-14 DOI: 10.31449/inf.v47i9.5081

Khemaissia Rofaida, Makhlouf Derdour, Mohamed Amine Ferrag, Mohammed Mounir Bouhamed

{"title":"PrSChain: A Blockchain Based Privacy Preserving Approach for Data Service Composition","authors":"Khemaissia Rofaida, Makhlouf Derdour, Mohamed Amine Ferrag, Mohammed Mounir Bouhamed","doi":"10.31449/inf.v47i9.5081","DOIUrl":"https://doi.org/10.31449/inf.v47i9.5081","url":null,"abstract":"The main goal of a Data Service Composition is combining multiple data services to provide for a user’s query a new service which uses data from multiple service providers that are incorporated in the composition. In this situation, the data privacy and especially of the service providers can be breached when their critical data can be seen by another party. Therefore, keeping the data privacy during the composition process is crucial by every work in the context of the service composition. Recent approaches rely on a central mediator that can be trusted or not to ensuring the privacy of the service providers during the query execution. The most recent approaches found problems in case of untrusted mediator where they enforce restrictions like k-protection that can affect the efficiency of their works. Therefore, we propose PrSChain which preserves the privacy of all service providers during service composition and execution using BlockChain technology. We used a permissioned BlockChain that acts as trusted mediator where it enables users to access to the BC if a valid certificate is given. We use Hyperledger Fabric to implement our solution where it stores sensitive data about the composition plan. In addition, the intermediate query results are saved in IPFS that acts as offchain storage. As a proof of concept, we have tested PrSChain on a real-world medical dataset to show its feasibility and efficiency for maintaining privacy in a secure and trusted manner.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"28 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134993150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detecting Breast Cancer in X-RAY images using image segmentation algorithm and neural networks 利用图像分割算法和神经网络在x射线图像中检测乳腺癌

4区计算机科学

Informatica Pub Date : 2023-11-08 DOI: 10.31449/inf.v47i9.4995

Rasha Talib Gdeeb

{"title":"Detecting Breast Cancer in X-RAY images using image segmentation algorithm and neural networks","authors":"Rasha Talib Gdeeb","doi":"10.31449/inf.v47i9.4995","DOIUrl":"https://doi.org/10.31449/inf.v47i9.4995","url":null,"abstract":"Breast cancer becomes is a nightmare threating woman all over the world, so, all the studies are trying for early detection of it to increase healing of it, it can save 30 percent from infected women which is a big percentage. Dangerous of breast cancer comes from the fact that all the women do not know about it until they have a mammogram image for the breast. It can be detected personally in late stages. That means it is important to make a medical examination periodically to investigate the presence of any cancerous lumps in breast tissue or underarm which can be an indicator for the existence of the tumour. Mammogram rays are an X-RAY applied on the breast which can used to find any problems in the breast like tumor blocks in breast, pain, secretions from nipples. Mammogram rays can detect breast cancer early and decrease the death cases. mammogram imaging starts in 40 age and must done every 3 years to assure the not infection of it. In cases of Genetic disease history, it is important to take the mammogram imaging before 40 age in the state of early tumor detection so it increases the recovery in early stages. This work is a study to create a method to estimate the breast cancer situation in X-RAY images to select an automatic medical solution which passes in three stages, primary aiding, chemical aiding, and eradication.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"24 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135390782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0