Applied Computing Review最新文献_第2页

RESTChain: a Blockchain-based Mediator for REST Interactions in Service Choreographies RESTChain:基于区块链的中介，用于服务编排中的REST交互

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577826

F. Donini, A. Marcelletti, A. Morichetta, A. Polini

{"title":"RESTChain: a Blockchain-based Mediator for REST Interactions in Service Choreographies","authors":"F. Donini, A. Marcelletti, A. Morichetta, A. Polini","doi":"10.1145/3555776.3577826","DOIUrl":"https://doi.org/10.1145/3555776.3577826","url":null,"abstract":"In inter-organizational contexts, different organizations cooperate exchanging information, to reach specific and shared objectives. The achievement of such interactions raises the need for a trusted communication environment to be used by the participants. This is a particularly relevant challenge when such interactions are specified in a peer-to-peer style, as in the case of Service Choreographies. Indeed, in such situations, the involved participants expect that all the interactions are performed abiding by the agreed specification. To support such a scenario, blockchain technology is gaining interest thanks to its security, trust, and decentralization characteristics. However, technological barriers still limit its adoption in real context due to the costly and time-consuming learning process. For this reason, we propose RESTChain, a general framework relying on blockchain technology enabling in an automatic way the interactions that take place among the participants in a service choreography. Starting from a choreography specification, the framework automatically derives a set of Mediators and a Smart Contract that coordinates the service interactions. In this way, each organization can communicate with the other services through the blockchain in a secure, auditable, and transparent manner.","PeriodicalId":42971,"journal":{"name":"Applied Computing Review","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74309412","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

Survey on Trust in Software Engineering for Autonomous Dynamic Ecosystems 自主动态生态系统软件工程信任研究

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577702

Barbora Buhnova, David Halasz, Danish Iqbal, Hind Bangui

{"title":"Survey on Trust in Software Engineering for Autonomous Dynamic Ecosystems","authors":"Barbora Buhnova, David Halasz, Danish Iqbal, Hind Bangui","doi":"10.1145/3555776.3577702","DOIUrl":"https://doi.org/10.1145/3555776.3577702","url":null,"abstract":"Software systems across various application domains are undergoing a major shift, from static systems of systems to dynamic ecosystems characterized by largely autonomous software agents, engaging in mutual coalitions and partnerships to complete complex collaborative tasks. One of the key challenges facing software engineering along with this shift, is our preparedness to leverage the concept of mutual trust building among the dynamic system components, to support safe collaborations with (possibly malicious or misbehaving) components outside the boundaries of our control. To support safe evolution towards dynamic software ecosystems, this paper examines the current progress in the research on trust in software engineering across various application domains. To this end, it presents a survey of existing work in this area, and suggests the directions in which further research is needed. These directions include the research of social metrics supporting trust assessment, fine-grained quantification of trust-assessment results, and opening the discussion on governance mechanisms responsible for trust-score management and propagation across the integrated software ecosystems.","PeriodicalId":42971,"journal":{"name":"Applied Computing Review","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75159526","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

Machine Learning Applied on Hydraulic Actuator Control 机器学习在液压执行器控制中的应用

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577695

Thomaz Pereira Da Silva Junior, Everson da Silva Flores, Vagner Santos Da Rosa, F. Borges

引用次数: 0

Discrete Wavelet Coefficient-based Embeddable Branch for Ultrasound Breast Masses Classification 基于离散小波系数的可嵌入分支超声乳腺肿块分类

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577727

Mingue Song, Yanggon Kim

{"title":"Discrete Wavelet Coefficient-based Embeddable Branch for Ultrasound Breast Masses Classification","authors":"Mingue Song, Yanggon Kim","doi":"10.1145/3555776.3577727","DOIUrl":"https://doi.org/10.1145/3555776.3577727","url":null,"abstract":"The progress of computer-aid-diagnosis system for ultrasound breast lesions reaches tremendous success in the past few years. However, conventional deep learning-based strategies in recent developments still have challenges particularly in characterizing tumor domain in ultrasound images due to the heterogeneous and complex variations of lesions along with similar intensity exhibited in target object. To address this, this work proposes a discrete wavelet coefficient-based embeddable branch that allows to additionally propagate geometrical features of tumors in an end-to-end trainable fashion. To be elaborate, such branch priorly enforce the wavelet pooling operation to select a certain coefficient to further collect gradient information of target domain. Further, the current work also investigates two different preprocessing strategies in which the internal and external gradients of lesion areas can be emphasized within the transformation. Thus, we examine the effects of the proposed method based on different preprocessing scenarios. To verify the usefulness, GradCam projection, and the cross-validation demonstrate the connection of the proposed branch encourages the importance of target features, thus boosting the overall discrimination between lesion groups. Lastly, the proposed branch can be easily incorporated with existing deep learning-based architectures.","PeriodicalId":42971,"journal":{"name":"Applied Computing Review","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74104069","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: 1

Type-based Termination Analysis for Parsing Expression Grammars 基于类型的表达式语法终止分析

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577620

Elton M. Cardoso, Regina De Paula, D. Pereira, L. Reis, R. Ribeiro

引用次数: 0

A Lightweight Authentication and Privacy Preservation Scheme for MQTT MQTT轻量级身份验证和隐私保护方案

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577817

Sijia Tian, V. Vassilakis

引用次数: 0

Hibernation Execution Interval based Hybrid Boot for Baseboard Management Controllers 基于休眠执行间隔的基板管理控制器混合启动

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577729

Ajung Kim, Gwangyong Kim, Bong-hoi Kim, Jiman Hong

引用次数: 1

Translating FOL-theories into SROIQ-Tboxes 将foll理论转化为sroiq - tbox

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577870

Fatima Danash, D. Ziébelin

引用次数: 0

A general methodology for building multiple aspect trajectories 建立多方面轨迹的一般方法

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577832

Francesco Lettich, Chiara Pugliese, C. Renso, Fabio Pinelli

引用次数: 2

Classification by Frequent Association Rules 频繁关联规则分类

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Applied Computing Review Pub Date : 2023-03-27 DOI: 10.1145/3555776.3577848

Md Rayhan Kabir, Osmar Zaiane

{"title":"Classification by Frequent Association Rules","authors":"Md Rayhan Kabir, Osmar Zaiane","doi":"10.1145/3555776.3577848","DOIUrl":"https://doi.org/10.1145/3555776.3577848","url":null,"abstract":"Over the last two decades, Associative Classifiers have shown competitive performance in the task of predicting class labels. Along with the performance in accuracy, associative classifiers produce human-readable predictive rules which is very helpful to understand the decision process of the classifiers. Associative classifiers from early days suffer from the limitation requiring proper threshold value setting which is dataset-specific. Recently some studies eliminated that limitation by producing statistically significant rules. Though recent models showed very competitive performance with state-of-the-art classifiers, their performance is still impacted if the feature vector of the training data is very large. An ensemble model can solve this issue by training each base learner with a subset of the feature vector. In this study, we propose an ensemble model Classification by Frequent Association Rules (CFAR) using associative classifiers as base learners. In our approach, instead of using a classical ensemble and a voting method, we rank the generated rules based on predominance among base learners and select a subset of the rules for predicting class labels. We use 10 datasets from the UCI repository to evaluate the performance of the proposed model. Our ensemble approach CFAR eliminates the limitation of high memory requirement and runtime of recent associative classifiers if training datasets have large feature vectors. Among the datasets we used, along with increasing accuracy in most cases, CFAR removes the noisy rules which enhances the interpretability of the model.","PeriodicalId":42971,"journal":{"name":"Applied Computing Review","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82466511","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: 1