2022 5th International Symposium on Informatics and its Applications (ISIA)最新文献

Traffic signals control system based on intelligent recommendation

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993579

Sahar Smaali, Chafia Bouanaka, Samah Smaali, Khaoula Kitouni

引用次数: 0

A Deep Learning-based 3D CNN for Automated COVID-19 Lung Lesions Segmentation from 3D Chest CT Scans 基于深度学习的3D CNN从3D胸部CT扫描中自动分割COVID-19肺部病变

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993505

A. Kermi, Hadj Cheikh Djennelbaroud, M. T. Khadir

引用次数: 0

A Hybrid Semantic Statistical Query Expansion for Arabic Information Retrieval Systems 面向阿拉伯语信息检索系统的混合语义统计查询扩展

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993572

A. Nehar, Slimane Bellaouar, Djamila Mahfoud, Fatima Zohra Daoudi

{"title":"A Hybrid Semantic Statistical Query Expansion for Arabic Information Retrieval Systems","authors":"A. Nehar, Slimane Bellaouar, Djamila Mahfoud, Fatima Zohra Daoudi","doi":"10.1109/ISIA55826.2022.9993572","DOIUrl":"https://doi.org/10.1109/ISIA55826.2022.9993572","url":null,"abstract":"Query-document vocabulary mismatch, the lack of query expressiveness for user needs and the phenomenon of short queries are the main issues associated with information retrieval systems. Query Expansion (QE) is one of the well-known alternative for overcoming these problems. It mainly involves finding synonyms or related words for the query terms. There are several approaches in the query expansion field such as statistical and semantic approaches; they focus on expanding the individual query terms rather than the entire query during the expansion process. An other category of approaches deals with the whole query by using a neural approach based on Pseudo Relevance feedback (PRF) documents. In this work, we carried out an ablation study to measure the impact of the classical and semantic (word embedding, order, context) based query expansion on the retrieval performance. The experiments conducted on the Arabic EveTAR dataset reveal that our hybrid proposed approach combining classical (PRF) and transformer (AraBERT) is competitive with the state-of-the-art methods. In fact, the obtained result in terms of the Mean Average Precision (MAP) is up to 0.72.","PeriodicalId":169898,"journal":{"name":"2022 5th International Symposium on Informatics and its Applications (ISIA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117001862","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

PSCP-CNN: Protein Structural Class Prediction using a Convolutional Neural Network PSCP-CNN:使用卷积神经网络进行蛋白质结构分类预测

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993605

Rached Yagoubi, A. Moussaoui, Ali Dabba, M. Yagoubi

{"title":"PSCP-CNN: Protein Structural Class Prediction using a Convolutional Neural Network","authors":"Rached Yagoubi, A. Moussaoui, Ali Dabba, M. Yagoubi","doi":"10.1109/ISIA55826.2022.9993605","DOIUrl":"https://doi.org/10.1109/ISIA55826.2022.9993605","url":null,"abstract":"The knowledge of the protein structural class is one of the most important sources of information in many biological fields, such as function analysis, protein structure, drug design, and protein folding. However, the protein structural class prediction is still a challenge when dealing with low similarity sequences. Therefore, the accuracy of the top-performing prediction methods remains unsatisfying, especially for proteins from the + ß class. This paper proposes a novel approach for Protein Structural Class Prediction using a Convolutional Neural Network (PSCP-CNN). Our approach consists of two stages. The first is the preprocessing stage which allows the preparation of the data. The second stage is a CNN classifier that automatically extracts the needed features for the classification. To evaluate the performance of our approach, we performed the jackknife test on four low similarity benchmark datasets: 25PDB, 640, 1189, and FC699. The experimental results show that PSCP-CNN achieved high prediction accuracy, where the overall accuracy on datasets 25PDB, 640, 1189, and FC699 is 93.8%, 94.5%, 94.0%, and 98.0%, respectively. Furthermore, comparing the results obtained with existing methods shows that PSCP-CNN outperforms state-of-the-art techniques and confirms that using a convolutional neural network allows a better prediction of protein structural classes.","PeriodicalId":169898,"journal":{"name":"2022 5th International Symposium on Informatics and its Applications (ISIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123168745","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

Residual Attention Network: A new baseline model for visual question answering 剩余注意网络:一种新的视觉问答基线模型

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993583

Salma Louanas, Hichem Debbi

引用次数: 0

Enhanced analysis of Open Government Data: Proposed metrics for improving data quality assessment 加强对政府公开数据的分析:改进数据质量评估的建议指标

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993482

Khadidja Bouchelouche, A. R. Ghomari, Leila Zemmouchi-Ghomari

{"title":"Enhanced analysis of Open Government Data: Proposed metrics for improving data quality assessment","authors":"Khadidja Bouchelouche, A. R. Ghomari, Leila Zemmouchi-Ghomari","doi":"10.1109/ISIA55826.2022.9993482","DOIUrl":"https://doi.org/10.1109/ISIA55826.2022.9993482","url":null,"abstract":"The release of Open Government Data (OGD) in recent years has maintained a very rapid pace to enable the OGD initiative to reach its full potential, such as enhancing transparency, citizen collaboration, and participation and boosting economic innovation value. Moreover, by publishing OGD, citizens can participate in governance processes, like policy-making and decision-making. Using Linked Open Data (LOD) technology allows us to understand and correctly use the released data by humans and machines. However, expert evidence shows that releasing data without quality control can threaten the reuse of datasets and negatively affect the benefits of the OGD initiative. Data accessibility is classified among the essential categories in Linked Open Data (LOD) quality models to enable efficient access to the released datasets. Most existing evaluations of data accessibility for the OGD portals focus on defining dimensions and measures, but there is no closed formulation to apply them. Some works propose marks to assess the data that meet the defined measures, and there is no broad scale of marks to standardize the application of these measures. This leads to difficulties in comparing and benchmarking evaluations. This paper aims to propose a percentage scale of marks for metrics to assess the accessibility of data in the OGD portals. Finally, we experiment with the proposed scale of marks on the American OGD portal since America launched the OGD initiative, and its portal is considered an example of OGD initiatives.","PeriodicalId":169898,"journal":{"name":"2022 5th International Symposium on Informatics and its Applications (ISIA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132696140","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

Towards a Simplified Evaluation of Graphical DSL Workbenches 面向图形化DSL工作台的简化评估

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993580

Amel Dembri, M. Redjimi

引用次数: 0

Analysis of road accident factors using Decision Tree Algorithm: a case of study Algeria 基于决策树算法的道路交通事故因素分析——以阿尔及利亚为例

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993530

Ouennoughi Nedjmedine, Mehenni Tahar

引用次数: 0

Computational Identification of Author Style on Electronic Libraries - Case of Lexical Features 电子图书馆作者风格的计算识别——以词汇特征为例

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993513

S. Ouamour, H. Sayoud

引用次数: 0

Methodology for fast prototyping of distributed real-time systems 分布式实时系统的快速原型设计方法

2022 5th International Symposium on Informatics and its Applications (ISIA) Pub Date : 2022-11-29 DOI: 10.1109/ISIA55826.2022.9993590

Zakaria Sahraoui, A. Labed

引用次数: 0