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Blockchain technology in finance industry

Transactions of the Korean Institute of Electrical Engineers 2019年第12期68卷 1601-1606页

作者： Youn, Seongwook Cho, Hyun-Chong Dept. of Software Korea National University of Transportation Korea Republic of Dept. of Electronics Engineering Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of

Blockchain is a peer-to-peer public ledger which guarantees the reliability of all the transactional record without a trusted third party. Basically, all the participants in the network create transactional record, examine the validity of the transaction, and keep the valid transactional record. The whole finance industry including banks and fintechs recognizes the value of the blockchain because of its efficiency and secure mechanism. In this paper, we explained the blockchain mechanism by providing its basic principles, strengths and weaknesses. Then, we provided what comes with it in the finance industry. Though there are still a few disadvantages such as persistence, and lack of the standard improvements and modifications in blockchain technology could overcome them and lead to the broader acceptance. Blockchain is definitely a disruptive technology in the financial system. Copyright © The Korean Institute of Electrical Engineers.

关键词： Smart contract

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

TechRxiv

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TechRxiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Software Engineering Sun Yat-Sen University Zhuhai China Department of Electrical and Computer Engineering Auburn University Auburn United States

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of large Generative AI (GAI) models presents challenges. To address this issue, we introduce an AIGC-as-a-Service (AaaS) architecture, which deploys AIGC models in wireless edge networks to ensure broad AIGC services accessibility for Metaverse users. Nonetheless, an important aspect of providing personalized user experiences requires carefully selecting AIGC Service Providers (ASPs) capable of effectively executing user tasks, which is complicated by environmental uncertainty and variability. Addressing this gap in current research, we introduce the AI-Generated Optimal Decision (AGOD) algorithm, a diffusion model-based approach for generating the optimal ASP selection decisions. Integrating AGOD with Deep Reinforcement Learning (DRL), we develop the Deep Diffusion Soft Actor-Critic (D2SAC) algorithm, enhancing the efficiency and effectiveness of ASP selection. Our comprehensive experiments demonstrate that D2SAC outperforms seven leading DRL algorithms. Furthermore, the proposed AGOD algorithm has the potential for extension to various optimization problems in wireless networks, positioning it as a promising approach for future research on AIGC-driven services. The implementation of our proposed method is available at: https://***/Lizonghang/AGOD. © 2023, CC BY.

关键词： Reinforcement learning

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Software Engineering Sun Yat-Sen University Zhuhai China The Department of Electrical and Computer Engineering Auburn University Auburn United States

关键词： Reinforcement learning

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Extracting Semantics of Predicates From Millions of Bio-Medical Abstracts for Inferencing New Biological Key Events and Relationships

Extracting Semantics of Predicates From Millions of Bio-Medi...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Chih Lai Dalma Martinović-Weigelt Aline Serrao De Filippo Stefan Krämer Carolin Poschen Graduate Program in Software University of St. Thomas St. Paul MN USA University of St. Thomas St. Paul MN USA Helmholtz Centre forEnvironmental Research GmbH UFZ / Permoserstraße 15 Leipzig Germany

ISBN: (纸本)9781665429825

Adverse outcome pathways (AOP) structure toxicological knowledge as sequential, directed chains of key events (KE) that culminate in adverse outcomes (AOs). AOP development is a laborious process that involves extensive knowledge mining and could be improved via use of machine / deep learning. In this paper, we present an artificial intelligence system that can accelerate putative AOP development process by inferencing new AOP modules based on the knowledge learned from 16-million pre-parsed PubMed abstracts. Each AOP modules is represented as a triplet that consists of antecedent and consequent biological entities connected by a relation. Users can also investigate specific types of antecedent, consequent, and relations by specifying macro/microtemplates using the MeSH semantic type hierarchy. We also provide visualizations to illustrate the hidden semantics that our system can extract from input triplets.

关键词： Measurement Deep learning Visualization Databases Conferences Semantics Unified modeling language

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Analyzing Morphological Changes in Zebrafish Embryos Exposed to Toxic Chemicals

Analyzing Morphological Changes in Zebrafish Embryos Exposed...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Akhil Ambekar Carolin Poschen Chih Lai Stefan Scholz Elisabet Teixidó Graduate Program in Software University of St. Thomas St. Paul MN USA Data Science Fellow on AI Healthcare Duke University NC USA Helmholtz Centre for Environmental Research GmbH - UFZ Leipzig Germany University of Barcelona Barcelona Spain

ISBN: (纸本)9781665429825

Subtle morphological changes caused by toxic chemicals in different regions of organs in small zebrafish embryos can be difficult to detect by human eyes or even by traditional image processing tools. Without brute force testing arbitrary parameters and thresholds in various combinations of imaging algorithms, we present our systematic approach in which we first train convolutional neural networks (CNNs) to recognize which organs of which zebrafish embryos contain significant morphological differences so they can be reliably classified as being exposed to either the fresh water or the toxic water contaminated with chemicals. From the training results, the organ images in each identified image subset were then analyzed by the technique, occlusion sensitivity map, to allocate the exact locations and the scales of morphological changes caused by different chemicals. In the experiment section of this paper, we use multiple chemical exposure scenarios to demonstrate the morphological differences in organs that can be detected by our approach.

关键词： Training Embryo Systematics Sensitivity Toxic chemicals Biological systems Water pollution

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Impact of design variations of a micro-perforated panel on psychoacoustic metrics of transmitted sound

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The Journal of the Acoustical Society of America 2024年第4_SUPPLEMENT期156卷 A22-A22页

作者： Jiahua Zhang Jacques Cuenca Laurent De Ryck Lucas Van Belle Elke Deckers Test Div. Siemens Digital Industry Software 110 8th St. Graduate Program in Architectural Acoustics Troy NY 12180 (email protected) Test Division Siemens Digital Industry Software Leuven Belgium Test Div. Siemens Digital Industry Software Leuven Belgium Dept. of Mech. Eng. KU Leuven Heverlee Belgium Dept. of Mech. Eng. KU Leuven Campus Diepenbeek Leuven Belgium

Recent work reveals that sound travelling through metamaterials can lead to changes in sound perception [L. De Ryck et al., Proceedings of ISMA and USD, pp. 1147–1162 (2018)]. As a starting point unravelling the impact of intricate vibro-acoustic design on perception, this study investigates the relationship between the intrinsic physical properties of micro-perforated panels (MPP) and several psychoacoustic metrics (loudness, sharpness, prominence ratio, and speech intelligibility index) in sound transmission conditions. A Sobol global sensitivity analysis is performed to quantify the impact of variations in MPP design parameters—panel thickness, perforation rate, hole diameter, and air cavity depth between panels—on these sound quality metrics [I. M. Sobol, MATCOM 55, 271–280 (2001)]. The analysis is conducted using both broadband and narrowband noise stimuli. The data trends suggest that the psychoacoustic effects of MPP acoustic treatments exhibit a non-trivial dependence on specific parameters of the panel setup. This also provides a framework towards innovative material design, where desired psychoacoustic metrics can help guide the manufacturing of metamaterials in order to meet specific sound quality targets. [The European Commission is gratefully acknowledged for its support of the Marie Sklodowska Curie program through the Horizon Europe DN METAVISION project (GA 101072415).]

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Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch 22

Accelerating Real-Time Imaging for Radiotherapy: Leveraging ...

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22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Obe, Ruth Kaufmann, Brandt Baird, Kaelen Kadel, Sam Soltani, Yasmin Cham, Mostafa Gobbert, Matthias K. Barajas, Carlos A. Jiang, Zhuoran Sharma, Vijay R. Ren, Lei Peterson, Stephen W. Poif, Jerimy C. U. of Houston-Clear Lake Dept. of Computer Science and of Software Engineering United States U. of San Francisco Dept. of Mathematics and Statistics United States Skidmore College Dept. of Computer Science and of Mathematics United States Mount Holyoke College Dept. of Computer Science and of Psychology United States U. of Houston Dept. of Biomedical Engineering United States U. of Maryland Dept. of Information Systems Baltimore County United States U. of Maryland Dept. of Mathematics and Statistics Baltimore County United States Medical Physics Graduate Program Duke University United States U. of Maryland School of Medicine Dept. of Radiation Oncology United States U. of Maryland School of Medicine Department of Radiation Oncology United States U. of Cape Town Dept. of Physics South Africa H3D Inc. United States

ISBN: (纸本)9798350345346

Proton beam therapy is an advanced form of cancer radiotherapy that uses high-energy proton beams to deliver precise and targeted radiation to tumors. This helps to mit-igate unnecessary radiation exposure in healthy tissues. Real-time imaging of prompt gamma rays with Compton cameras has been suggested to improve therapy efficacy. However, the camera's non-zero time resolution leads to incorrect interaction classifications and noisy images that are insufficient for accurately assessing proton delivery in patients. To address the challenges posed by the Compton camera's image quality, machine learning techniques are employed to classify and refine the generated data. These machine-learning techniques include recurrent and feedforward neural networks. A PyTorch model was designed to improve the data captured by the Compton camera. This decision was driven by PyTorch's flexibility, powerful capabilities in handling sequential data, and enhanced G PU usage. This accelerates the model's computations on large-scale radiotherapy data. Through hyperparameter tuning, the validation accuracy of our PyTorch model has been improved from an initial 7 % to over 60 %. Moreover, the PyTorch Distributed Data Parallelism strategy was used to train the RNN models on multiple G PU s, which significantly reduced the training time with a minor impact on model accuracy. © 2023 IEEE.

关键词： Clas-sification Compton camera Distributed Data Parallelism Proton beam therapy PyTorch Recurrent neural network

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Assessment of postural control with deprivation of visual system and somatosensorial perturbation in child with autism: case report

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Gait & Posture 2023年 106卷 S145-S145页

作者： Mendes, Juliana D.O.H. Cordeiro, Lorraine B. Santos, Grazielly N. Carvalho, Fernanda B.D. Grecco, Luanda A.C. Ribeiro, Pedro A.S. Moraes, Priscilla M. Oliveira, Claudia Evangelical University of Goiás- UniEVANGÉLICA Postgraduate Program Anápolis Brazil Evangelical University of Goiás- UniEVANGÉLICA Graduate Course in Physiotherapy Anápolis Brazil Center of Pediatric Neurostimulation CENEPE – REAB Pediatric Neurostimulation São Paulo Brazil Evangelical University of Goiás- UniEVANGÉLICA Graduate Course in Software engineering Anápolis Brazil Evangelical University of Goiás- UniEVANGÉLICA Psychology Clinical- Post-Graduate Program Anápolis Brazil School of Medical Sciences- Santa Casa de São Paulo Health Sciences Program São Paulo Brazil

IntroductionMental maturity is a state of preparation for physical, mental and social aspects of life.1 Individuals with autism spectrum disorder (ASD) have low mental maturity and deficits with regards to social interactions, language,1 motor skills and postural control.2 Postural control is achieved by the integration of three systems: visual, vestibular and somatosensorial.3 Postural perturbation increases the risk of falls and can exert a negative impact on the development of communication skills and social interactions.4 Children with autism are more susceptible due to deficits related to visual and somatosensorial feedback.5 Research questionDo deprivation of the visual system and somatosensorial perturbation alter postural control variables in a child with autism compared to a child with neurotypical development? MethodsThis case report involved two male children aged seven years and four months – one with a diagnosis of ASD (22 kg, 132 cm) and another with neurotypical development (26.4 kg, 129 cm). The psychological evaluation (general reasoning capacity) was performed using the Columbia Mental Maturity Scale (CMMS-3). The motor assessment was performed using the SMART-D 140® system (BTS Engineering), which has two force plates (Kistler Platform, model 9286BA). Postural control was investigated under the following conditions: eyes open, eyes closed, without a mat and with a 5-cm foam rubber mat. ResultsTable 1 lists the results of the CMMS-3 and force plate variables. The child with ASD had average reasoning capacity. Both children exhibited oscillations in postural control, but the child with autism had poorer results in the occurrence of visual deprivation and somatosensorial perturbation. Table 1- Results of Columbia Mental Maturity Scale-3 and force plate variables DiscussionThis study investigated whether mental maturity exerts an influence on postural control in a child with autism and whether the deprivation of the visual system and sensorial perturb

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Effect of different knee protheses on functional mobility assessed using an inertial sensor

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Gait & Posture 2023年 106卷 S143-S144页

作者： Trindade, Andrei M.V. Cordeiro, Lorraine B. Silva, Bruno O. Ribeiro, Pedro A.S. Toledo, Roberta C. Cardoso, Deborah C.D.S. Torres, Marcelo R. Araújo, Helder R.D.S. Borges, Rodolfo P. Oliveira, Claudia Evangelical University of Goiás- UniEVANGÉLICA Postgraduate Program Anápolis Brazil State Center for Rehabilitation and Readaptation Rehabilitation Goiânia Brazil Evangelical University of Goiás- UniEVANGÉLICA Graduate Course in Physiotherapy Anápolis Brazil Evangelical University of Goiás- UniEVANGÉLICA Graduate Course in Software engineering Anápolis Brazil School of Medical Sciences- Santa Casa de São Paulo Health Sciences Program São Paulo Brazil

IntroductionKnee arthrosis is a progressive, disabling, degenerative, musculoskeletal condition in patients with an advanced age.1,2 The aim of total knee arthroplasty (TKA) is to relieve pain and rehabilitate function with the use of different types of prostheses, such as a fixed bearing (FB) prosthesis and mobile bearing (MB) prosthesis, which enables greater joint mobility.3 Spatiotemporal gait variables and functional mobility are altered in older people compared to younger people and such alterations are aggravated by the progression of knee arthrosis.4 Research questionDiferentes tipos de próteses para o tratamento da artrose do joelho influenciam nas variáveis da marcha e mobilidade funcional? MethodsFifty-four subjects who underwent unilateral knee arthroplasty for the treatment of advanced knee arthrosis were selected. The assessment of functional mobility was performed using the Timed Up and Go (TUG) Test with an inertial sensor (G-sensor, BTS Bioengineering) to quantify the time in seconds required for the individual to perform the task of standing up from a standard chair without arm support, walking three meters, turning around, going back to the chair and sitting down again. ResultsThe normality of the data was determined using the Kolmogorov-Smirnov test, which demonstrated non-normal distribution. Thus, the Mann-Whitney test was used for the comparison of prosthesis type (FB vs. MB) and TUG test variables. The effect size of variables with statistically significant differences between groups was also determined. The SPSS program (v.19, IBM) was used for all statistical tests. The median postoperative time was 14.5 months (p > 0.05). Table 1 shows the median and p-values for the TUG test variables between groups. Interestingly, the only variables with significant differences were those related to turns. Although the participants with MB executed the TUG test faster than those with FB (i.e., sit-to-stand and stand-to-sit phases), no significant differe

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Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization

arXiv

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arXiv 2022年

作者： Grisci, Bruno Iochins Kuhn, Gabriela Colombelli, Felipe Matter, Vítor Kehl Lima, Leomar Heinen, Karine Pegoraro, Mauricio Borges, Marcio Rigo, Sandro José Barbosa, Jorge Luis Victória da Rosa Righi, Rodrigo da Costa, Cristiano André de Oliveira Ramos, Gabriel Software Innovation Laboratory - Softwarelab Graduate Program in Applied Computing Universidade do Vale do Rio dos Sinos Av. Unisinos 950 RS São Leopoldo93022-750 Brazil Institute of Informatics Federal University of Rio Grande do Sul Av. Bento Gonçalves 9500 RS Porto Alegre91501-970 Brazil Dell Technologies Brazil Av. Industrial Belgraf 400 Eldorado do Sul RS 92990-000 Brazil

Nowadays, data has become an invaluable asset to entities and companies, and keeping it secure represents a major challenge. Data centers are responsible for storing data provided by software applications. Nevertheless, the number of vulnerabilities has been increasing every day. Managing such vulnerabilities is essential for building a reliable and secure network environment. Releasing patches to fix security flaws in software is a common practice to handle these vulnerabilities. However, prioritization becomes crucial for organizations with an increasing number of vulnerabilities since time and resources to fix them are usually limited. This review intends to present a survey of vulnerability ranking techniques and promote a discussion on how multi-objective optimization could benefit the management of vulnerabilities risk prioritization. The state-of-the-art approaches for risk prioritization were reviewed, intending to develop an effective model for ranking vulnerabilities in data centers. The main contribution of this work is to point out multi-objective optimization as a not commonly explored but promising strategy to prioritize vulnerabilities, enabling better time management and increasing security. Copyright © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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