Embedded Systems and Applications最新文献_第9页

Application of Cross-Wavelet and Singular Value Decomposition on Covid-19 and Bio-Physical Data 交叉小波和奇异值分解在Covid-19和生物物理数据中的应用

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120612

Iftikhar U. Sikder, James J. Ribero

引用次数: 0

Blockchain Enabled Diabetic Patients’ Data Sharing and Real Time Monitoring 区块链实现糖尿病患者数据共享和实时监测

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120620

Dodo Khan, L. T. Jung, M. Hashmani, Moke Kwai Cheong

{"title":"Blockchain Enabled Diabetic Patients’ Data Sharing and Real Time Monitoring","authors":"Dodo Khan, L. T. Jung, M. Hashmani, Moke Kwai Cheong","doi":"10.5121/csit.2022.120620","DOIUrl":"https://doi.org/10.5121/csit.2022.120620","url":null,"abstract":"According to the World Health Organization worldwide diabetes report, the number of diabetic patients has surged from 108 million in the 1980s to 422 million in 2014. According to researchers, the numbers will continue to climb in the next decades. Diabetes is a sickness that requires long-term self-care and close monitoring to be appropriately put under control. As a result, continuous monitoring of blood sugar levels has the potential to save millions of lives. This paper proposes a Blockchain-based platform that connects the patients, healthcare practitioners (HP), and caregivers for a continuous monitoring and care ofdiabetic patients. It lets the patients to securely connected to HP for the purpose of remote patient monitoring (telemedicine), whilst preserving patient data privacy using the blockchain technology. IoT sensors are used to read sugar levels and store these data in a tamper-proof immutable ledger (Hyperledger). This platform provides an End-to-End movement of the patient's data. That is, from the point where it is formed (sensors) to the point it ends up in the HP side. It gives patient a control-and-track function to maintain/track data movement. It provides a unique feature in allowing the patient to keep track of the private data and to pick who they want to share the data with and for how long (and for what reason). The platform is developed in two stages. Initially, the concept is implemented using the Hyperledger Fabric. Then, a Blockchain based on a novel Proof-of-Review (PoR) consensus model is included on to provide efficient performance and scalability in the Hyperledger fabric. Essentially, this proposed platform is to alleviate the pain points in traditional healthcare systems in the scopes of information exchange, data security, and privacy maintenance for real-time diabetic patient monitoring.","PeriodicalId":201778,"journal":{"name":"Embedded Systems and Applications","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134139861","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

Adaptive Forgetting, Drafting and Comprehensive Guiding: Text-to-Image Synthesis with Hierarchical Generative Adversarial Networks 自适应遗忘，起草和综合指导:文本到图像的合成与层次生成对抗网络

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120623

Yuting Xue, Heng Zhou, Yuxuan Ding, Xiao Shan

{"title":"Adaptive Forgetting, Drafting and Comprehensive Guiding: Text-to-Image Synthesis with Hierarchical Generative Adversarial Networks","authors":"Yuting Xue, Heng Zhou, Yuxuan Ding, Xiao Shan","doi":"10.5121/csit.2022.120623","DOIUrl":"https://doi.org/10.5121/csit.2022.120623","url":null,"abstract":"The generation task from text to image generates cross modal data with consistent content by mining the semantic consistency contained in two different modal information of text and image. Due to the differences between the two modes, the task of text to image generation faces many difficulties and challenges. In this paper, we propose to boost the text-to-image synthesis through an adaptive learning and generating generative adversarial networks (ALG-GANs). First, we propose an adaptive forgetting mechanism in the generator to reduce the error accumulation and learn knowledge flexibly in the cascade structure. Besides, to evade the mode collapse caused by a strong biased surveillance, we propose a multi-task discriminator using weaksupervision information to guide the generator more comprehensively and maintain the semantic consistency in the cascade generation process. To avoid the refine difficulty aroused by the bad initialization, we judge the quality of initialization before further processing. The generator will re-sample the noise and re-initialize the bad initializations to obtain good ones. All the above contributions have been integrated in a unified framework, which is an adaptive forgetting, drafting and comprehensive guiding based text-to-image synthesis method with hierarchical generative adversarial networks. The model is evaluated on the Caltech-UCSD Birds 200 (CUB) dataset and the Oxford 102 Category Flowers (Oxford) dataset with standard metrics. The results on Inception Score (IS) and Fréchet Inception Distance (FID) show that our model outperforms the previous methods.","PeriodicalId":201778,"journal":{"name":"Embedded Systems and Applications","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124874903","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

Deep Learning Framework Mindspore and Pytorch Comparison 深度学习框架Mindspore和Pytorch的比较

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120617

Xiangyu Xia, Shaoxiang Zhou

引用次数: 0

An IR-based QA System for Impact of Social Determinants of Health on Covid-19 基于ir的健康社会决定因素对Covid-19影响的QA系统

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120615

Priyanka Addagudi, W. MacCaull

引用次数: 0

Mutual Inlining: An Inlining Algorithm to Reduce the Executable Size 相互内联:一种减少可执行文件大小的内联算法

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120601

Y. Ben-Asher, Nidal Faour, Ofer Shinaar

{"title":"Mutual Inlining: An Inlining Algorithm to Reduce the Executable Size","authors":"Y. Ben-Asher, Nidal Faour, Ofer Shinaar","doi":"10.5121/csit.2022.120601","DOIUrl":"https://doi.org/10.5121/csit.2022.120601","url":null,"abstract":"We consider the problem of selecting an optimized subset of inlinings (replacing a call to a function by its body) that minimize the resulting code size. Frequently, in embedded systems, the program’s executable file size must fit into a small size memory. In such cases, the compiler should generate as small as possible executables. In particular, we seek to improve the code size obtained by the LLVM inliner executed with the -Oz option. One important aspect is whether or not this problem requires a global solution that considers the full span of the call graph or a local solution (as is the case with the LLVM inliner) that decides whether to apply inlining to each call separately based on the expected code-size improvement. We have implemented a global type of inlining algorithm called Mutual Inlining that selects the next call-site (f()callsg() to be inline based on its global properties. The first property is the number of calls to g(). Next property is determining if inlining g() to f() may prevent inlining other more beneficial neighboring callsites. Finaly repeated inlining iterations over the call graph are performed until there are no more beneficial inlinings to perform. Hence, considering the effect of previously made inlinings on the next call-site to be inline. Our results show small but consistant improvement compare to LLVM’s Oz.","PeriodicalId":201778,"journal":{"name":"Embedded Systems and Applications","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122602443","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

Deep Learning Frameworks Evaluation for Image Classification on Resource Constrained Device 资源受限设备上图像分类的深度学习框架评价

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120603

Mathieu Febvay, Ahmed Bounekkar

引用次数: 0

Unsupervised Blind Image Quality Assessment based on Multi-Feature Fusion 基于多特征融合的无监督盲图像质量评估

Embedded Systems and Applications Pub Date : 2022-03-26 DOI: 10.5121/csit.2022.120627

Qinglin He, Chao Yang, P. An

引用次数: 0

(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling 区间调度、资源受限调度和低秩调度的(In-)近似结果

Embedded Systems and Applications Pub Date : 2022-03-11 DOI: 10.48550/arXiv.2203.06171

M. Maack, Simon Pukrop, A. R. Rasmussen

{"title":"(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling","authors":"M. Maack, Simon Pukrop, A. R. Rasmussen","doi":"10.48550/arXiv.2203.06171","DOIUrl":"https://doi.org/10.48550/arXiv.2203.06171","url":null,"abstract":"We consider variants of the restricted assignment problem where a set of jobs has to be assigned to a set of machines, for each job a size and a set of eligible machines is given, and the jobs may only be assigned to eligible machines with the goal of makespan minimization. For the variant with interval restrictions, where the machines can be arranged on a path such that each job is eligible on a subpath, we present the first better than $2$-approximation and an improved inapproximability result. In particular, we give a $(2-frac{1}{24})$-approximation and show that no better than $9/8$-approximation is possible, unless P=NP. Furthermore, we consider restricted assignment with $R$ resource restrictions and rank $D$ unrelated scheduling. In the former problem, a machine may process a job if it can meet its resource requirements regarding $R$ (renewable) resources. In the latter, the size of a job is dependent on the machine it is assigned to and the corresponding processing time matrix has rank at most $D$. The problem with interval restrictions includes the 1 resource variant, is encompassed by the 2 resource variant, and regarding approximation the $R$ resource variant is essentially a special case of the rank $R+1$ problem. We show that no better than $3/2$, $8/7$, and $3/2$-approximation is possible (unless P=NP) for the 3 resource, 2 resource, and rank 3 variant, respectively. Both the approximation result for the interval case and the inapproximability result for the rank 3 variant are solutions to open challenges stated in previous works. Lastly, we also consider the reverse objective, that is, maximizing the minimal load any machine receives, and achieve similar results.","PeriodicalId":201778,"journal":{"name":"Embedded Systems and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115862763","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

Turbocharging Heuristics for Weak Coloring Numbers 弱着色数的涡轮增压启发式

Embedded Systems and Applications Pub Date : 2022-03-07 DOI: 10.48550/arXiv.2203.03358

Alexander Dobler, Manuel Sorge, Anaïs Villedieu

引用次数: 2