Informatica最新文献

{"title":"Improved Model for Identifying the Cyberbullying based on Tweets of Twitter","authors":"Darwin Samalo, Rizky Martin, D. N. Utama","doi":"10.31449/inf.v47i6.4534","DOIUrl":"https://doi.org/10.31449/inf.v47i6.4534","url":null,"abstract":"The surge of cyberbullying on social media platforms is a major concern in today's digital age, with its prevalence escalating alongside advancements in technology. Thus, devising methods to detect and eliminate cyberbullying has become a crucial task. This research meticulously presents a refined model for identifying instances of cyberbullying, building on previous methodologies. The process of devising the model involved a thorough literature review, object-oriented design","PeriodicalId":56292,"journal":{"name":"Informatica","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45112721","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}

{"title":"The Effect of Topic Modelling on Prediction of Criticality Levels of Software Vulnerabilities","authors":"Prarna Mehta, Shubhangi Aggarwal, Abhishek Tandon","doi":"10.31449/inf.v47i6.3712","DOIUrl":"https://doi.org/10.31449/inf.v47i6.3712","url":null,"abstract":"identify a critical","PeriodicalId":56292,"journal":{"name":"Informatica","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45171018","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}

{"title":"Data Processing of Municipal Wastewater Recycling Based on Genetic Algorithm","authors":"Zijun Zhao, Jianchao Zhu, Kaiming Yang, Song Wang, Mingxiao Zeng","doi":"10.31449/inf.v47i3.4038","DOIUrl":"https://doi.org/10.31449/inf.v47i3.4038","url":null,"abstract":"In order to accurately process the data of urban sewage recycling, this paper designs an adaptive genetic algorithm, which integrates genetic algorithm, adaptive genetic algorithm and traditional PID respectively, and designs simulation experiments to compare their performance. The simulation results show that the self-adaptive PID control algorithm is superior to the genetic PID control algorithm in both control accuracy and dynamic characteristics. The PID controller with good optimization performance is applied to the control object of sewage treatment system. Through simulation analysis, the adaptive genetic algorithm only needs 52s when adjusting the step response simulation. The overshoot of the system is 8%. The interference in the simulation is restored to a stable state within the interference 18S, and the adjustment time in the robustness simulation is reduced by about 15s compared with the genetic algorithm. In conclusion, the adjustment time of the system is shortened, the overshoot of the system is reduced, and the anti-interference and robustness are enhanced. For the dissolved oxygen concentration of the key object in the control system, the above controller with good performance is applied to the sewage treatment control system, which not only reduces the overshoot and regulation time, but also improves the control accuracy, and can well meet the control requirements of sewage treatment.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135752698","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}

{"title":"Deep Learning-based Cnn Multi-modal Camera Model Identification for Video Source Identification","authors":"Surjeet Singh, Vivek Kumar Sehgal","doi":"10.31449/inf.v47i3.4392","DOIUrl":"https://doi.org/10.31449/inf.v47i3.4392","url":null,"abstract":"There is a high demand for multimedia forensics analysts to locate the original camera of photographs and videos that are being taken nowadays. There has been considerable progress in the technology of identifying the source of data, which has enabled conflict resolutions involving copyright infringements and identifying those responsible for serious offences to be resolved. This study focuses on the issue of identifying the camera model used to acquire video sequences used in this research that is, identifying the type of camera used to capture the video sequence under investigation. For this purpose, we created two distinct CNN-based camera model recognition techniques to be used in an innovative multi-modal setting. The proposed multi-modal methods combine audio and visual information in order to address the identification issue, which is superior to mono-modal methods which use only the visual or audio information from the investigated video to provide the identification information.According to legal standards of admissible evidence and criminal procedure, Forensic Science involves the application of science to the legal aspects of criminal and civil law, primarily during criminal investigations, in line with the standards of admissible evidence and criminal procedure in the law. It is responsible for collecting, preserving, and analyzing scientific evidence in the course of an investigation. It has become a critical part of criminology as a result of the rapid rise in crime rates over the last few decades. Our proposed methods were tested on a well-known dataset known as the Vision dataset, which contains about 2000 video sequences gathered from various devices of varying types. It is conducted experiments on social media platforms such as YouTube and WhatsApp as well as native videos directly obtained from their acquisition devices by the means of their acquisition devices. According to the results of the study, the multimodal approaches suggest that they greatly outperform their mono-modal equivalents in addressing the challenge at hand, constituting an effective approach to address the challenge and offering the possibility of even more difficult circumstances in the future","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135752475","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}

{"title":"Designing A Permissioned Blockchain Network For The Insurance Claim Process Using Hyperledger Fabric And Composer","authors":"Archana Hombalimath, Neha Mangla, Arun Balodi","doi":"10.31449/inf.v47i3.4158","DOIUrl":"https://doi.org/10.31449/inf.v47i3.4158","url":null,"abstract":"This research aims to examine the benefits of blockchain technology (BCT) in the vehicle insurance process. The article addresses a number of benefits offered by BCT, including automating the identity verification and doing away with the need for numerous parties to manually certify the legitimacy of transactions. India's financial and business networks can be anticipated to change the accounting process to a different extreme with the introduction of BCT. Unfortunately, they are having some difficulties implementing and acclimating to this modern technology. Here is the solution, blockchain technology may help us solve the existing problem. Insurance firms and car owners can benefit from blockchain technology since it can effectively open up communication channels, encourage industry integration, and improve insurance provider’s ability to access record. Using BCT, banking operations will be more efficient, quicker, and less expensive because to the removal of middlemen. Decentralization, transparency, and secure transactions will be the main advantages.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135752696","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}

{"title":"Comparative Study of Missing Value Imputation Techniques on E-Commerce Product Ratings","authors":"Dimple Chehal, Parul Gupta, Payal Gulati, Tanisha Gupta","doi":"10.31449/inf.v47i3.4156","DOIUrl":"https://doi.org/10.31449/inf.v47i3.4156","url":null,"abstract":"Missing data is a common occurrence in practically all studies, and it adds a layer of ambiguity to data interpretation. Missing values in a dataset mean loss of important information. It is one of the most common data quality issues. Missing values are values that are not present in the data set. These are usually written as NAN’s, blanks, or any other placeholders. Missing values create imbalanced observations, biased estimates and sometimes lead to misleading results. The majority of real-world datasets have missing values. As a result, to deliver an efficient and valid analysis and the solutions should be taken into account appropriately. By filling in the missing values a complete dataset can be created and the challenge of dealing with complex patterns of missingness can be avoided. Missing values can be of both continuous and categorical types. To get more precise results, a variety of techniques to fill out missing values can be used. In the present study, nine different imputation methods: Simple Imputer, Last Observation Carried forward (LOCF), KNN Imputation (KNN), Hot Deck, Linear Regression, MissForest, Random Forest Regression, DataWig, and Multivariate Imputation by Chained Equation (MICE) were compared. The comparison was performed on Amazon real-time dataset based on three evaluation criteria: R- Squared (R 2 ), Mean squared error (MSE), and Mean absolute error (MAE). As a result of the findings KNN had the best outcomes, while DataWig had the worst results for R- Squared (R 2 ). The R-squared value ranges from 0-1. In terms of mean squared error (MSE) and mean absolute error (MAE), the Hot deck imputation approach fared best, whereas MissForest performed worst (MAE). The hot deck imputation method appears to be of interest and merits further investigation in practice.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"240 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135752699","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}

{"title":"Computational Analysis of Uplink NOMA and OMA for 5G Applications: An Optimized Network","authors":"Shelesh Krishna Saraswat, Vinay Kumar Deolia, Aasheesh Shukla","doi":"10.31449/inf.v47i3.4145","DOIUrl":"https://doi.org/10.31449/inf.v47i3.4145","url":null,"abstract":"In This paper, the non-orthogonal multiple access (NOMA) schemes are compared with the multiple orthogonal access (OMA) schemes on the basis of the resource allocation validity of uplinks. By reflecting the involvement of a measure of each user’s data on the system’s total amount, we analyze the main reasons why NOMA provides justice service distribution over OMA on unequal channels. Moreover, the Jain index is observed and proposed to quantify the irregularity of numerous user channels, according to the metric for the Jain index based on the Jain index. More importantly, the proposed metric establishes the criteria for choosing between NOMA and OMA to share resources correctly. Based on this debate, we offer a program that combines NOMA and OMA to increase user integrity. Imitation effects substantiate the exactness of the proposed matrix and display improvement of the accuracy of the showcased NOMA-OMA mixture system as compared to standard OMA as well as NOMA systems.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135752697","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}

{"title":"Group Decision Support Model for Tech-Based Startup Funding using Multistage Fuzzy Logic","authors":"M. Devanda, D. N. Utama","doi":"10.31449/inf.v47i6.4569","DOIUrl":"https://doi.org/10.31449/inf.v47i6.4569","url":null,"abstract":"","PeriodicalId":56292,"journal":{"name":"Informatica","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46360174","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}

{"title":"Personalized Recommendation System of E-learning Resources Based on Bayesian Classification Algorithm","authors":"Xiuhui Wang","doi":"10.31449/inf.v47i3.3979","DOIUrl":"https://doi.org/10.31449/inf.v47i3.3979","url":null,"abstract":"In order to meet learners' personalized learning needs, realize learners' personalized development, and solve the problem of learners' information Trek and overload, a development scheme of e-learning resources personalized recommendation system based on Bayesian algorithm is proposed. This paper studies the personalized Association recommendation model integrating association rule mining and Bayesian network, and improves the association rule mining algorithm by combining historical record pruning and Bayesian network verification. In the process of association rule mining, combined with user history, the frequent itemsets in association rules are filtered, and the itemsets below the given threshold are pruned. The pruned item set is input into the Bayesian verification network for personalized verification, and the verification results are sorted and recommended according to the ranking, so as to give priority to the readers who really like the books. The recommendation model solves the problem of weak personalization in the existing recommendation system to a certain extent. Experiments show that Bayesian network can improve the personalization of association recommendation.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"316 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135691747","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}

{"title":"AHP Algorithm for Indoor Air Pollution Detection and Evaluation System Design","authors":"Wen Fan, Chengyang Chang, Ning Yao, Linxue Xu, Hongyan Ju","doi":"10.31449/inf.v47i3.3932","DOIUrl":"https://doi.org/10.31449/inf.v47i3.3932","url":null,"abstract":"In order to extract a description of indoor air quality, the concentration of indoor pollutants needs to be obtained and then evaluated. Aiming at the existing indoor air quality monitoring and evaluation system, an AHP algorithm for the design of indoor air pollution detection and evaluation system is proposed, which combines the principles and methods of fuzzy mathematics to evaluate air quality in a confined environment. An experiment was carried out, using the analytic hierarchy process to assign weights. According to the principle of maximum subordination, comprehensive evaluation of air quality in a confined environment was carried out through fuzzy mathematical model. The experimental results show that the humidity value reached 54% RH when the temperature was 25°C, and the humidity value reached 60% RH when the temperature was 19°C. The evaluation results more scientifically reflect the true state of air quality.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135691746","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}