Computer Science and Information Systems最新文献_第6页

The application of machine learning techniques in prediction of quality of life features for cancer patients 机器学习技术在预测癌症患者生活质量特征中的应用

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220227061s

Milos Savic, V. Kurbalija, Mihailo Ilic, M. Ivanović, D. Jakovetić, A. Valachis, Serge Autexier, Johannes Rust, T. Kosmidis

{"title":"The application of machine learning techniques in prediction of quality of life features for cancer patients","authors":"Milos Savic, V. Kurbalija, Mihailo Ilic, M. Ivanović, D. Jakovetić, A. Valachis, Serge Autexier, Johannes Rust, T. Kosmidis","doi":"10.2298/csis220227061s","DOIUrl":"https://doi.org/10.2298/csis220227061s","url":null,"abstract":"Quality of life (QoL) is one of the major issues for cancer patients. With the advent of medical databases containing large amounts of relevant QoL information it becomes possible to train predictive QoL models by machine learning (ML) techniques. However, the training of predictive QoL models poses several challenges mostly due to data privacy concerns and missing values in patient data. In this paper, we analyze several classification and regression ML models predicting QoL indicators for breast and prostate cancer patients. Three different approaches are employed for imputing missing values, and several settings for data privacy preserving are tested. The examined ML models are trained on datasets formed from two databases containing a large number of anonymized medical records of cancer patients from Sweden. Two learning scenarios are considered: centralized and federated learning. In the centralized learning scenario all patient data coming from different data sources is collected at a central location prior to model training. On the other hand, federated learning enables collective training of machine learning models without data sharing. The results of our experimental evaluation show that the predictive power of federated models is comparable to that of centrally trained models for short-term QoL predictions, whereas for long-term periods centralized models provide more accurate QoL predictions. Furthermore, we provide insights into the quality of data preprocessing tasks (missing value imputation and differential privacy).","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"67 1","pages":"381-404"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80673622","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: 2

Using neural network to automatic manufacture product label in enterprise under IoT environments 利用神经网络实现物联网环境下企业产品标签的自动制造

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220703019z

Kaiwen Zhang, C. Dong

引用次数: 0

Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying 结合离线和实时消歧来执行语义感知的XML查询

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220228063t

Joe Tekli, Gilbert Tekli, R. Chbeir

{"title":"Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying","authors":"Joe Tekli, Gilbert Tekli, R. Chbeir","doi":"10.2298/csis220228063t","DOIUrl":"https://doi.org/10.2298/csis220228063t","url":null,"abstract":"Many efforts have been deployed by the IR community to extend free-text query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. In this paper, we describe a new approach for XML keyword search aiming to solve the limitations mentioned above. Our solution first transforms the XML document collection (offline) and the keyword query (on-the-fly) into meaningful semantic representations using context-based and global disambiguation methods, specially designed to allow almost linear computation efficiency. We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. Experimental results highlight the quality and potential of our approach.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"2 1","pages":"423-457"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83670662","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

Solving the p-second center problem with variable neighborhood search 用变邻域搜索解决p秒中心问题

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis210804049r

D. Ristić, D. Urošević, N. Mladenović, R. Todosijević

引用次数: 0

RESNETCNN: An abnormal network traffic flows detection model RESNETCNN:一个异常网络流量检测模型

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis221124004l

Yimin Li, Dezhi Han, Mingming Cui, Yuan Fan, Yachao Zhou

{"title":"RESNETCNN: An abnormal network traffic flows detection model","authors":"Yimin Li, Dezhi Han, Mingming Cui, Yuan Fan, Yachao Zhou","doi":"10.2298/csis221124004l","DOIUrl":"https://doi.org/10.2298/csis221124004l","url":null,"abstract":"Intrusion detection is an important means to protect system security by detecting intrusions or intrusion attempts on the system through operational behaviors, security logs, and data audit. However, existing intrusion detection systems suffer from incomplete data feature extraction and low classification accuracy, which affects the intrusion detection effect. To this end, this paper proposes an intrusion detection model that fuses residual network(RESNET) and parallel cross-convolutional neural network, called RESNETCCN. RESNETCNN can efficiently learn various data stream features through the fusion of deep learning and convolutional neural network (CNN), which improves the detection accuracy of abnormal data streams in unbalanced data streams, moreover, the oversampling method into the data preprocessing, to extract multiple types of unbalanced data stream features at the same time, effectively solving the problems of incomplete data feature extraction and low classification accuracy of unbalanced data streams. Finally, three improved versions of RESNETCNN networks are designed to meet the requirements of different traffic data processing, and the highest detection accuracy reaches 99.98% on the CICIDS 2017 dataset and 99.90% on the ISCXIDS 2012 dataset.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"217 1","pages":"997-1014"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73630116","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

Using artificial intelligence assistant technology to develop animation games on IoT 利用人工智能辅助技术开发物联网动画游戏

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220719021z

Rong Zhang

引用次数: 0

Read between the interactions: Understanding non-interacted items for accurate multimedia recommendation 在交互之间阅读:了解非交互项目，以便进行准确的多媒体推荐

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis221031041k

Jiyeon Kim, Taeri Kim, Sang-Wook Kim

{"title":"Read between the interactions: Understanding non-interacted items for accurate multimedia recommendation","authors":"Jiyeon Kim, Taeri Kim, Sang-Wook Kim","doi":"10.2298/csis221031041k","DOIUrl":"https://doi.org/10.2298/csis221031041k","url":null,"abstract":"This paper addresses the problem of multimedia recommendation that additionally utilizes multimedia data, such as visual and textual modalities of items along with the user-item interaction information. Existing multimedia recommender systems assume that all the non-interacted items of a user have the same degree of negativity, thus regarding them as candidates for negative samples when training the model. However, this paper claims that a user?s non-interacted items do not have the same degree of negativity. We classify these non-interacted items of a user into two kinds of items with different characteristics: unknown and uninteresting items. Then, we propose a novel negative sampling technique that only considers the uninteresting items (i.e., rather than the unknown items) as candidates for negative samples. In addition, we show that using the multiple Bayesian personalized ranking (BPR) losses with both unknown and uninteresting items (i.e., all the non20 interacted items) in existing multimedia recommendation methods is very effective in improving recommendation accuracy. By conducting extensive experiments with three real-world datasets, we show the superiority of our ideas. Our ideas can be easily and orthogonally applied to any multimedia recommender systems.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"39 1","pages":"933-948"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77857088","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

Adaptive multiscale sparse unmixing for hyperspectral remote sensing image 高光谱遥感图像的自适应多尺度稀疏解混

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220828009l

Yalan Li, Qian Du, Yixuan Li, Wenwu Xie, Jing Yuan, Lin Li, Chen Qi

{"title":"Adaptive multiscale sparse unmixing for hyperspectral remote sensing image","authors":"Yalan Li, Qian Du, Yixuan Li, Wenwu Xie, Jing Yuan, Lin Li, Chen Qi","doi":"10.2298/csis220828009l","DOIUrl":"https://doi.org/10.2298/csis220828009l","url":null,"abstract":"Sparse unmixing of hyperspectral images aims to separate the endmembers and estimate the abundances of mixed pixels. This approach is the essential step for many applications involving hyperspectral images. The multi scale spatial sparse hyperspectral unmixing algorithm (MUA) could achieve higher accuracy than many state-of-the-art algorithms. The regularization parameters, whose combinations markedly influence the unmixing accuracy, are determined by manually searching in the broad parameter space, leading to time consuming. To settle this issue, the adaptive multi-scale spatial sparse hyperspectral unmixing algorithm (AMUA) is proposed. Firstly, the MUA model is converted into a new version by using of a maximum a posteriori (MAP) system. Secondly, the theories indicating that andnorms are equivalent to Laplacian and multivariate Gaussian functions, respectively, are applied to explore the strong connections among the regularization parameters, estimated abundances and estimated noise variances. Finally, the connections are applied to update the regularization parameters adaptively in the optimization process of unmixing. Experimental results on both simulated data and real hyperspectral images show that the AMUA can substantially improve the unmixing efficiency at the cost of negligible accuracy. And a series of sensitive experiments were undertook to verify the robustness of the AMUA algorithm.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"15 1","pages":"551-572"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80463118","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

Efficient neural network accelerators with optical computing and communication 具有光计算和通信功能的高效神经网络加速器

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220131066x

Chengpeng Xia, Yawen Chen, Haibo Zhang, Hao Zhang, Fei Dai, Jigang Wu

{"title":"Efficient neural network accelerators with optical computing and communication","authors":"Chengpeng Xia, Yawen Chen, Haibo Zhang, Hao Zhang, Fei Dai, Jigang Wu","doi":"10.2298/csis220131066x","DOIUrl":"https://doi.org/10.2298/csis220131066x","url":null,"abstract":"Conventional electronic Artificial Neural Networks (ANNs) accelerators focus on architecture design and numerical computation optimization to improve the training efficiency. However, these approaches have recently encountered bottlenecks in terms of energy efficiency and computing performance, which leads to an increase interest in photonic accelerator. Photonic architectures with low energy consumption, high transmission speed and high bandwidth have been considered as an important role for generation of computing architectures. In this paper, to provide a better understanding of optical technology used in ANN acceleration, we present a comprehensive review for the efficient photonic computing and communication in ANN accelerators. The related photonic devices are investigated in terms of the application in ANNs acceleration, and a classification of existing solutions is proposed that are categorized into optical computing acceleration and optical communication acceleration according to photonic effects and photonic architectures. Moreover, we discuss the challenges for these photonic neural network acceleration approaches to highlight the most promising future research opportunities in this field.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"94 1","pages":"513-535"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81747468","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

Data-centric UML profile for agroecology applications: Agricultural autonomous robots monitoring case study 农业生态学应用的以数据为中心的UML概要文件:农业自主机器人监测案例研究

IF 1.4 4区计算机科学

Computer Science and Information Systems Pub Date : 2023-01-01 DOI: 10.2298/csis220301064b

S. Bimonte, Hassan Badir, Pietro Battistoni, Houssam Bazza, Amina Belhassena, C. Cariou, G. Chalhoub, Juan F. Corrales, Adrian Couvent, J. Laneurit, Rim Moussa, Julián Eduardo Plazas, M. Sebillo, N. Tricot

{"title":"Data-centric UML profile for agroecology applications: Agricultural autonomous robots monitoring case study","authors":"S. Bimonte, Hassan Badir, Pietro Battistoni, Houssam Bazza, Amina Belhassena, C. Cariou, G. Chalhoub, Juan F. Corrales, Adrian Couvent, J. Laneurit, Rim Moussa, Julián Eduardo Plazas, M. Sebillo, N. Tricot","doi":"10.2298/csis220301064b","DOIUrl":"https://doi.org/10.2298/csis220301064b","url":null,"abstract":"The conceptual design of information systems is mandatory in several application domains. The advent of the Internet of Things (IoT) technologies pushes conceptual design tools and methodologies to consider the complexity of IoT data, architectures, and communication networks. In agroecology applications, the usage of IoT is quite promising, but it raises several methodological and technical issues. These issues are related to the complexity and heterogeneity of data (social, economic, environmental, and agricultural) needed by agroecology practices. Motivated by the lack of a conceptual model for IoT data, in this work, we present a UML profile taking into account different kinds of data (e.g., sensors, stream, or transactional) and non-functional Requirements. We show how the UML profile integrates with classical UML diagrams to support the design of complex systems. Moreover, We prove the feasibility of our conceptual framework through a theoretical quality assessment and its implementation in the agroecology case study concerning the monitoring of autonomous agricultural robots.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":"19 1","pages":"459-489"},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89845205","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