Computer Science and Information Systems最新文献

{"title":"Studying the Effects of Being Einstein: An Experiment in Social Virtual Reality","authors":"I. Cummins, D. Schofield","doi":"10.5539/cis.v16n2p1","DOIUrl":"https://doi.org/10.5539/cis.v16n2p1","url":null,"abstract":"Previous research has found that when using virtual reality, a person can have a sense of ownership over the body that is being substituted for their own in the virtual world, and that the body’s appearance may lead to different behavioral, attitudinal, and perceptual changes. As Virtual Reality (VR) becomes more widespread, it is increasingly important to understand the effects on its users. This study utilized a novel methodology to conduct remote testing in virtual reality, leveraging a popular social virtual reality platform to test whether participants using Einstein as their virtual body performed better at a cognitive task than participants using other virtual bodies, and did not find any effect or correlation of the virtual body with any of the factors measured. The results suggest that the effects of virtual embodiment on the user stemming from the virtual body's appearance is more complex than previously assumed, warranting further study.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77672577","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 Role of Machine Learning in the Detection and Classification of Brain Tumors: A Literature Review of the Past Two Years","authors":"Jianyi Wang","doi":"10.5539/cis.v16n2p20","DOIUrl":"https://doi.org/10.5539/cis.v16n2p20","url":null,"abstract":"A brain tumor is an abnormal growth of cells in the brain. There are four common types of brain tumors.  Doctors can segment and identify the tumors manually, but it is very time-consuming. There exist automatic segmentation algorithms that can facilitate the process. Deep learning is a new method of creating powerful AI models. As a result, there is a need for automatic segmentation algorithms that can facilitate the process and improve the accuracy of brain tumor detection. Artificial intelligence (AI) and machine learning (ML) have emerged as promising tools for developing such algorithms. In particular, deep learning (DL) methods, such as convolutional neural networks (CNNs), have shown great potential for accurately identifying brain tumors in medical images. This paper presents a literature review of recently published papers (2020-2022) on brain tumor classification and detection using artificial intelligence. The review covers various AI and DL methods, including supervised learning, reinforcement learning, and unsupervised learning. It evaluates their effectiveness in detecting and classifying brain tumors in medical images. The review also discusses the challenges and limitations of these methods, as well as future directions for research in this field.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91341475","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":"From Zero to Infinity: Research on the Development Process of Intelligent Manufacturing","authors":"Chen Peng","doi":"10.5539/cis.v16n2p29","DOIUrl":"https://doi.org/10.5539/cis.v16n2p29","url":null,"abstract":"Intelligent manufacturing is flourishing in the 21st century. This paper takes the brief history of exploring the development of intelligent manufacturing as a staring point, explains the current intelligent and informative technologies and achievements of intelligent manufacturing by describing the impact of intelligent manufacturing on traditional manufacturing, proposes reflections on the shortcomings and limitations of intelligent manufacturing in China. And our country advocates human-centered intelligent manufacturing, continuously improves the system and innovates technology, while reasonably plans the three directions. Finally, we extend to digital twin technology and explore it in the intelligent manufacturing to promote the further upgrade. Besides, the study shows that the country will continue to use intelligent manufacturing as a traction and the industrial internet as a means to seize new opportunities and create a new ecology of production.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80787614","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":"Self-service kits to scale knowledge to autonomous teams - concept, application and limitations","authors":"Alexander Poth, Mario Kottke, A. Riel","doi":"10.2298/csis211112048p","DOIUrl":"https://doi.org/10.2298/csis211112048p","url":null,"abstract":"In large organizations, it is not trivial to spread knowledge to all teams. Often, individual teams need to handle similar topics and re-invent the wheel. Another scenario is that a group of people with a common role (for example ?guild? in Spotify model) has to distill their practices to make them shareable. Trainings should have empower participants so to apply the learnings easily in their daily businesses. To realize this, the proposed Self-Service Kit (SSK) approach can be used in the context of a holistic methodology that fosters team autonomy while leveraging knowledge spread and sharing throughout a large organization. Such a methodology is presented and instantiated in an enterprise context in facing the mentioned challenges.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72769762","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 proposal of new Ethereum request for comments for supporting fractional ownership of non-fungible tokens","authors":"Miroslav Stefanović, D. Przulj, Darko Stefanović, S. Ristić, D. Capko","doi":"10.2298/csis230127038s","DOIUrl":"https://doi.org/10.2298/csis230127038s","url":null,"abstract":"During the last couple of years, non-fungible tokens became the most prominent implementation of blockchain technology apart from cryptocurrencies. This is mainly due to their recent association with digital art, but the application of non-fungible tokens has been in the focus of researchers since the appearance of Blockchain 2.0. It was usually tightly coupled with the research on possible applications of blockchain technology in some real-life applications, such as land administration, healthcare, or supply chain management. Since the initial release of the Ethereum blockchain in 2015, until 2022, more than 44 million smart contracts have been created, and out of those that are still active, more than 70% are based on some prominent templates. In the Ethereum blockchain, the creation of non fungible tokens is usually based on Ethereum Request for Comments 721. In this paper, the authors are proposing the creation of a new standard that would support 23 fractional ownership of non-fungible tokens. Fractional ownership is necessary so 24 non-fungible tokens and blockchain technology could be applied to an even wider 25 number of use cases. This paper also presents an example of a possible implementation of the newly proposed standard in the Solidity programming language.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75932415","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":"Heart sounds classification using adaptive wavelet threshold and 1D LDCNN","authors":"Jianqiang Hu, Qingli Hu, Mingfeng Liang","doi":"10.2298/csis230418059h","DOIUrl":"https://doi.org/10.2298/csis230418059h","url":null,"abstract":"Heart sounds classification plays an important role in cardiovascular disease detection. Currently, deep learning methods for heart sound classification with heavy parameters consumption cannot be deployed in environments with limited memory and computational budgets. Besides, de-noising of heart sound signals (HSSs) can affect accuracy of heart sound classification, because erroneous removal of meaningful components may lead to heart sound distortion. In this paper, an automated heart sound classification method using adaptive wavelet threshold and 1D LDCNN (One-dimensional Lightweight Deep Convolutional Neural Net work) is proposed. In this method, we exploit WT (Wavelet Transform) with an adaptive threshold to de-noise heart sound signals (HSSs). Furthermore, we utilize 1D LDCNN to realize automatic feature extraction and classification for de-noised heart sounds. Experiments on PhysioNet/CinC 2016 show that our proposed method achieves the superior classification results and excels in consumption of parameter comparing to state-of-the-art methods.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68464415","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":"Evaluation of smart city construction and optimization of city brand model under neural networks","authors":"Yingji Li, Yufeng Qian, Qiang Li, Linna Li","doi":"10.2298/csis220715010l","DOIUrl":"https://doi.org/10.2298/csis220715010l","url":null,"abstract":"The study aims to avoid the phenomenon that thousand cities seem the same in the construction of smart cities and the efforts of all walks of life are jointed to implement the construction of smart cities and the creation of city brands. First, the basic theory of smart city construction is introduced. Second, the restricting and promoting factors influencing smart city construction and development are analyzes, and the evaluation system of smart city development is established. Then, the model for smart city construction and development based on the neural network is implemented. Finally, some domestic cities are selected as the dataset to build a training model, and the city brand optimization strategy is proposed. On this basis, an evaluation system for smart city development based on the intelligent neural network and Grey relational analysis Back Propagation Neural Network (GRA-BPNN) is obtained. The entropy weight method (EWM), grey relational analysis (GRA) method and the evaluation method based on Technique for Order Preference by Similarity to an Ideal Solutionv (TOPSIS) are regarded as the members of the control group, and the results of different methods for evaluating the development of smart cities are compared. The results show that the modeling of smart city construction based on neural networks can help to implement an evaluation model for smart city construction and development, and it can help evaluate smart city construction and development accurately. And then the corresponding strategies are proposed to speed up the construction of smart cities with its local characteristics, and then city brands are built. Compared with other evaluation algorithms, the performance of the algorithm proposed is better and more stable and the evaluation results are more reasonable than those of the others, which can prove that the evaluation algorithm is feasible and scientific. This study provides a new idea for the application of deep learning to smart city construction and city brand building","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74958698","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":"Cloud-based ERP construction process framework in the customer's perspective","authors":"Hyeong-Soo Kim, Deuk-Soo Oh, Seung-Hee Kim","doi":"10.2298/csis211230045k","DOIUrl":"https://doi.org/10.2298/csis211230045k","url":null,"abstract":"Process frameworks for the implementation of cloud enterprise resource planning (ERP) were derived and each process was examined through detailed comparisons with on-premise ERP construction processes, using process engineering characteristics. The process frameworks for implementing cloud ERP are classified into infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), content-as-a-service (CaaS), and software-as-a-service (SaaS), depending on the construction type, and are defined based on 6 derived processes, 21 activities, and numerous specific tasks. The process engineering characteristics of the final proposed process framework were further analyzed and examined in comparison to on-premise ERP construction processes with respect to differences and similarities. This study provides a theoretical foundation of standardized research on cloud ERP construction methods. As a practical guideline for stakeholders, it can be used in practice as a process tailoring tool, providing information on specific activities and tasks for each construction phase, contributing to the construction and spread of reliable cloud-based ERP systems from the customer?s perspective.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76576108","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":"Landslide detection based on efficient residual channel attention mechanism network and faster R-CNN","authors":"Yabing Jin, Ou Ou, Shanwen Wang, Yijun Liu, Haoqing Niu, X. Leng","doi":"10.2298/csis220831003j","DOIUrl":"https://doi.org/10.2298/csis220831003j","url":null,"abstract":"Accurate landslide detection plays an important role in land planning, disaster prediction and disaster relief. At present, field investigation and exploration based on professional personnel is the most widely used landslide mapping and detection technology, but this method consumes a lot of manpower and material resources and is inefficient. With the development of artificial intelligence, landslide identification and target detection based on deep learning have attracted more and more attention due to their remarkable advantages over traditional technologies. It is a technical problem to identify landslides from satellite remote sensing images. Although there are some methods at present, there is still room for improvement in the target detection algorithm of landslides against the background of the diversity and complexity of landslides. In this paper, target detection algorithm models such as Faster R-CNN apply to landslide recognition and detection tasks, and various commonly used recognition and detection algorithm network structures are used as the basic models for landslide recognition. Efficient residual channel soft thresholding attention mechanism algorithm (ERCA) is proposed, which intends to reduce the background noise of images in complex environments by means of deep learning adaptive soft thresholding to improve the feature learning capability of deep learning target detection algorithms. ERCA is added to the backbone network of the target detection algorithm for basic feature extraction to enhance the feature extraction and expression capability of the network. During the experiment ERCA combined with ResNet50, ResNet101 and other backbone networks, the objective indicators of detection results such as AP50 (Average Precision at IOU=0.50), AP75 (Average Precision at IOU=0.75) and AP (Average Precision) were improved, and the AP values were all improved to about 4%, and the final detection results using ResNet101 combined with ERCA as the backbone network reached 76.4% AP value. ERCA and other advanced channel attention networks such as ECA (Efficient Channel Attention for Deep Convolutional Neural Networks) and SENet (Squeeze-and-Excitation Networks) are fused into the backbone network of the target detection algorithm and experimented on the landslide identification detection task, and the detection results are that the objective detection indexes AP50, AP75, AP, etc. are higher for ERCA compared with other channel attention, and the subjective detection image detection effect and feature map visualization display are also better. We released our code at: https://github.com/fluoritess/Efficient-residual-channel-attention-mechanism-network-and-Faster-R-CNN.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81281257","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":"Supporting 5G service orchestration with formal verification","authors":"Peter Backeman, Ashalatha Kunnappilly, C. Seceleanu","doi":"10.2298/csis211001059b","DOIUrl":"https://doi.org/10.2298/csis211001059b","url":null,"abstract":"The 5G communication technology has the ability to create logical net works, called network slices, which are specifically carved to serve particular application domains. Due to the mix of different application criticality, it becomes crucial to verify if the applications? service level agreements are met. In this pa per, we propose a novel framework for modeling and verifying 5G orchestration, considering simultaneous access and admission of new requests to slices as well as virtual network function scheduling and routing. By combining modeling in user friendly UML, with UPPAAL model checking and satisfiability-modulo-theories based model finding, our framework supports both modeling and formal verification of service orchestration. We demonstrate our approach on a e-health case study showing how a user, with no knowledge of formal methods, can model a system in UML and verify that the application meets its requirements.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82185798","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}