Informatica最新文献

{"title":"A Digital Evidences Preservation Framework for a Logic Based Smart Contract","authors":"Walaa Alomari, Khair Eddin Sabri, Nadim Obeid","doi":"10.31449/inf.v47i8.4132","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4132","url":null,"abstract":"Recently, smart contracts were introduced as a necessity to automatically execute specific operations within blockchain systems. The popularity and diversity of blockchain systems attracted intensive attentions from academia, industry and other sectors. Blockchain systems were implemented using different programming languages that used in defining the triggering events and their consequent actions within the smart contract. In this article, we propose a digital evidences preservation framework that supports logic-based smart contracts to manage entries associated with digital evidences. Combining logic-based approach and blockchain systems may result in ensuing contracts that have technical advantages over procedural coding. The paper shows the motivation for choosing logic-based approach to define a smart contract. We introduce the rules and structure of the proposed logic-based contract.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135351258","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":"Research on financial risk prediction and prevention for small and medium-sized enterprises - based on a neural network","authors":"Xiaohui Wang","doi":"10.31449/inf.v47i8.4884","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4884","url":null,"abstract":"For companies, timely and accurate risk prediction plays an an essential role in sustaining business growth. In this paper, firstly, the financial risk of small and medium-sized enterprises (SMEs) was simply analyzed. Some financial indicators were selected, and then some of the indicators were eliminated by Mann-Whitney U test and Pearson test. For risk prediction, an improved sparrow search algorithm-back-propagation neural network (ISSA-BPNN) method was designed by optimizing the BPNN with the piecewise linear chaotic map (PWLCM)-improved SSA. Experiments were performed on 82 special treatment (ST) enterprises and 164 non-ST enterprises. The results showed that the BPNN had higher accuracy in risk prediction than methods such as Fisher discriminant analysis; the optimization of the ISSA for the BPNN was reliable as the accuracy and F1 value of the ISSA-BPNN method were 0.9834 and 0.9425, respectively; the prediction was wrong for only one sample out of 20 randomly selected samples. The results demonstrate the reliability and practical applicability of the ISSA-BPNN method.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135739379","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":"Research on Chord Generation in Automated Music Composition Using Deep Learning Algorithms","authors":"Ming Zhu","doi":"10.31449/inf.v47i8.4885","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4885","url":null,"abstract":"With the development of technology, automated music composition has received widespread attention in music creation. This article mainly focuses on the generation of chords in automated music composition. First, relevant music knowledge was briefly introduced, and then the composition of the Transformer model was explained. A two-layer bidirectional Transformer method was designed to generate chords for the main melody and chorus separately, followed by the establishment of chord coloring and sound production models. Ten music professionals and 40 ordinary college students compared the coherence, pleasantness, and innovation of the chords generated by Hidden Markov Model (HMM), Long Short-Term Memory (LSTM), and the method proposed in this paper. The results showed that the chord generated by the method proposed in this paper achieved higher scores in the evaluation. Overall, the scores given by the music professionals and ordinary college students were 3.64 and 3.91, respectively, which were higher than those of the HMM and LSTM methods. The experimental results prove the superiority of the chord generation method proposed in this paper. The method can be applied to automated music composition.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388624","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":"Mobile Spyware Identification and Categorization: A Systematic Review","authors":"Muawya Naser, Hussein Albazar, Hussein Abdel-Jaber","doi":"10.31449/inf.v47i8.4881","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4881","url":null,"abstract":"Smartphones have revolutionized the way we live, work, and interact with the world. They have become indispensable companions, seamlessly integrating into our daily routines. However, with this pervasive usage comes a growing security concern. Mobile phones are increasingly becoming targets of cyber-attacks, with more than 26,000 attacks happening daily. Among these threats, spyware is one of the most prevalent and insidious threat. Researchers have explored various techniques for identifying and categorizing mobile spyware to address this issue. These efforts are crucial for enhancing the security of our mobile devices and protecting our sensitive data from prying eyes. In this paper, we have conducted a comprehensive survey of the existing techniques and summarized their strengths and limitations. Our analysis encompasses a range of approaches, from signature-based detection to machine learning-based classification. We also explore the latest advancements in behavioral analysis and intrusion detection systems. By consolidating this knowledge, we provide a valuable reference point for future research on mobile spyware detection and prevention. In conclusion, this paper highlights mobile security’s critical role in our digital lives. It underscores the importance of ongoing research and innovation in mobile security to safeguard our personal information and prevent cyber-attacks.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388427","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":"Research on Multimedia Data Information Security Algorithm Based on Chaos Theory","authors":"Jie Zhao","doi":"10.31449/inf.v47i8.4606","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4606","url":null,"abstract":"Chaos theory is a fast, parallel, and globally retrievable modern intelligent optimization algorithm. At present, it has been widely used in the field of computer technology and intelligent control. Based on the full analysis of chaos theory, this paper constructs a multimedia data information security algorithm, which can analyze the data analysis model and model convergence in detail. Finally, the experimental results show that the proposed algorithm has good performance and can effectively enhance the security and protection of multimedia data information.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388790","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":"Hybrid Variable-Length Spider Monkey Optimization with Good-Point Set Initialization for Data Clustering","authors":"Athraa Qays Obaid, Maytham Alabbas","doi":"10.31449/inf.v47i8.4872","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4872","url":null,"abstract":"Data clustering refers to grouping data points that are similar in some way. This can be done in accordance with their patterns or characteristics. It can be used for various purposes, including image analysis, pattern recognition, and data mining. The K-means algorithm, commonly used for clustering, is subject to limitations, such as requiring the number of clusters to be specified and being sensitive to initial center points. To address these limitations, this study proposes a novel method to determine the optimal number of clusters and initial centroids using a variable-length spider monkey optimization algorithm (VLSMO) with a hybrid proposed measure. Results of experiments on real-life datasets demonstrate that VLSMO performs better than the standard k-means in terms of accuracy and clustering capacity.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388802","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":"A New Divergence Measure for Intuitionistic Fuzzy Matrices","authors":"Alka Rani, Pratiksha Tiwari, Priti Gupta","doi":"10.31449/inf.v47i8.3638","DOIUrl":"https://doi.org/10.31449/inf.v47i8.3638","url":null,"abstract":"Data available in the real world may not be in a crisp format. Intuitionistic fuzzy matrices are applicable in uncertainty and useful in decision making, relational equation, clustering, etc. Divergence or similarity measures help to characterize dissimilarity or similarity between any two sets. This paper presents a new divergence measure for intuitionistic fuzzy matrices with the verification of its validity. The fundamental properties are demonstrated for the new intuitionistic fuzzy divergence measure. A technique to solve multi-criteria decision-making problems is developed by utilizing the proposed intuitionistic fuzzy divergence measure. Finally, application in the medical diagnosis of this intuitionistic fuzzy divergence measure to decision making is shown using real data.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388789","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":"Covid-19 Detecting in Computed Tomography Lungs Images using Machine and transfer Learning","authors":"Dalila Cherifi, Abderraouf Djaber, Mohammed-Elfateh Guedouar, Amine Feghoul, Zahia Zineb Chelbi, Amazigh Ait Ouakli","doi":"10.31449/inf.v47i8.4258","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4258","url":null,"abstract":"Coronavirus disease 2019 (COVID-19) is a fast-spreading disease infectious that causes lung pneumonia which killed millions of lives around the world and has a significant impact on public healthcare. The diagnostic approach of the infection is principally divided into two broad categories, a laboratory-based and chest radiography approach where the CT imaging tests showed some advantages in the prediction over the other methods. Due to the restricted medical capability and the impressive raise of the suspected cases, the need for finding an immediate, accurate and automated method to alleviate the overcapacity of radiologists’ efforts for diagnosis has emerged . In order to accomplish this objective, our work is based on developing machine and deep learning algorithms to classify chest CT scans into Covid or non-Covid classes. To obtain a good performance, the accuracy of the classifier should be high so the patients may have a clear idea about their state. For this purpose, there are many hyper parameters that can be changed in order to advance the performance of the artificial models that are used for the identification of such illnesses. We have worked on two non-similar datasets from different sources, a small one of 746 images and a larger one with 14486 images. In the other hand, we have proposed various machine learning models starting by an SVM which contains different kernel types, KNN model with changing the distance measurements and an RF model with two different number of trees. Moreover, two CNN based approaches have been developed considering one convolution layer followed by a pooling layer then two consecutive convolution layers followed by a single pooling layer each time. The machine learning models showed better performance comparing to the CNN on the small dataset. While on the large dataset, CNN outperforms these algorithms. In order to improve performance of the models, transfer learning also have been used in this project where we trained the pre-trained InceptionV3 and ResNet50V2 on the same datasets. Among all the examined classifiers, the ResNet50V2 achieved the best scores with 86.67% accuracy, 93.94% sensitivity, 81% specificity and 86% F1-score on the small dataset while the respective scores on the large dataset were 97.52%, 97.28%, 97.77% and 98%. Experimental interpretation advise the potential applicability of ResNet50V2 transfer learning approach in real diagnostic scenarios, which might be of very high usefulness in terms of achieving fast testing for COVID19.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387910","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":"Feature Extraction of English Semantic Translation Relying on Graph Regular Knowledge Recognition Algorithm","authors":"Lidong Yang","doi":"10.31449/inf.v47i8.4901","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4901","url":null,"abstract":"Under the background of big data, people are not only pursuing the quantity but also the accuracy of knowledge in acquiring knowledge, especially for English. Because of the ambiguity, variety, and irregularity of English translation, people's reading has brought a lot of trouble. This paper aims to study the feature extraction of English semantic translation and suggests a recognition algorithm that relies on graph common knowledge. Through the analysis of graph regularization and the construction of the model, the recognition algorithm is improved, and the feature extraction methods are compared and analyzed. At the same time, experiments are intended to investigate the improvement of the English semantic translation of the improved recognition algorithm after feature extraction. The experimental results in this paper show that the improved English semantic translation has increased by 10%-15% in terms of translation accuracy. This degree of improvement has great application significance in actual English semantic translation.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388803","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":"Provably Efficient Multi-Cancer Image Segmentation Based on Multi-Class Fuzzy Entropy","authors":"Zaid Ameen Abduljabbar","doi":"10.31449/inf.v47i8.4840","DOIUrl":"https://doi.org/10.31449/inf.v47i8.4840","url":null,"abstract":"One of the segmentation techniques with the greatest degree of success used in numerous recent applications is multi-level thresholding. The selection of appropriate threshold values presents difficulties for traditional methods, however, and, as a result, techniques have been developed to address these difficulties multidimensionally. Such approaches have been shown to be an efficient way of identifying the areas affected in multi-cancer cases in order to define the treatment area. Multi-cancer methods that facilitate a certain degree of competence are thus required. This study tested storing MRI brain scans in a multidimensional image database, which is a significant departure from past studies, as a way to improve the efficacy, efficiency, and sensitivity of cancer detection. The evaluation findings offered success rates for cancer diagnoses of 99.08%, 99.87%, 94%; 97.08%, 98.3%, and 93.38% sensitivity; the success rates of the LED Internet connection in particular were 99.99%; 98.23%, 99.53%, and 99.98%.","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388623","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}