Practical I-Voting on Stellar Blockchain

In this paper, we propose a privacy-preserving i-voting system based on the public Stellar Blockchain network. We argue that the proposed system satisfies all requirements stated for a robust i-voting system including transparency, verifiability, and voter anonymity. The practical architecture of the system abstracts a voter from blockchain technology used underneath. To keep user privacy, we propose a privacy-first protocol that protects voter anonymity. Additionally, high throughput and low transaction fees allow handling large scale voting at low costs. As a result we built an open-source, cheap, and secure system for i-voting that uses public blockchain, where everyone can participate and verify the election process without the need to trust a central authority. The main contribution to the field is a method based on a blind signature used to construct reliable voting protocol. The proposed method fulfills all requirements defined for i-voting systems, which is challenging to achieve altogether.The work was supported partially by founds of Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, and Conselleria of Innovation, Universities, Science and Digital Society, of the Community of Valencia, Spain, under project AICO/2020/206. The development of the project has been also supported by the grant founded by Stellar Community Found

リチウムイオン電池材料における異相界面構造解析

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 幾原 雄一, 東京大学教授 山田 淳夫, 東京大学教授 枝川 圭一, 東京大学准教授 阿部 英司, 東京大学准教授 柴田 直哉University of Tokyo(東京大学

State of the art on ethical, legal, and social issues linked to audio- and videobased AAL solutions

Working Group 1. Social responsibility: Ethical, legal, social, data protection and privacy issuesAbstract Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressing. AAL poses many ethical challenges raising questions that will affect immediate acceptance and long-term usage. Furthermore, ethical issues emerge from social inequalities and their potential exacerbation by AAL, accentuating the existing access gap between high-income countries (HIC) and low and middle-income countries (LMIC). Legal aspects mainly refer to the adherence to existing legal frameworks and cover issues related to product safety, data protection, cybersecurity, intellectual property, and access to data by public, private, and government bodies. Successful privacy-friendly AAL applications are needed, as the pressure to bring Internet of Things (IoT) devices and ones equipped with artificial intelligence (AI) quickly to market cannot overlook the fact that the environments in which AAL will operate are mostly private (e.g., the home). The social issues focus on the impact of AAL technologies before and after their adoption. Future AAL technologies need to consider all aspects of equality such as gender, race, age and social disadvantages and avoid increasing loneliness and isolation among, e.g. older and frail people. Finally, the current power asymmetries between the target and general populations should not be underestimated nor should the discrepant needs and motivations of the target group and those developing and deploying AAL systems. Whilst AAL technologies provide promising solutions for the health and social care challenges, they are not exempt from ethical, legal and social issues (ELSI). A set of ELSI guidelines is needed to integrate these factors at the research and development stage. Keywords Ethical principles, Privacy, Assistive Living Technologies, Privacy by Design, General Data Protection Regulation.publishedVersio

State of the art on ethical, legal, and social issues linked to audio- and video-based AAL solutions - Uploaded on December 29, 2021

Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressing. AAL poses many ethical challenges raising questions that will affect immediate acceptance and long-term usage. Furthermore, ethical issues emerge from social inequalities and their potential exacerbation by AAL, accentuating the existing access gap between high-income countries (HIC) and low and middle-income countries (LMIC). Legal aspects mainly refer to the adherence to existing legal frameworks and cover issues related to product safety, data protection, cybersecurity, intellectual property, and access to data by public, private, and government bodies. Successful privacy-friendly AAL applications are needed, as the pressure to bring Internet of Things (IoT) devices and ones equipped with artificial intelligence (AI) quickly to market cannot overlook the fact that the environments in which AAL will operate are mostly private (e.g., the home). The social issues focus on the impact of AAL technologies before and after their adoption. Future AAL technologies need to consider all aspects of equality such as gender, race, age and social disadvantages and avoid increasing loneliness and isolation among, e.g. older and frail people. Finally, the current power asymmetries between the target and general populations should not be underestimated nor should the discrepant needs and motivations of the target group and those developing and deploying AAL systems. Whilst AAL technologies provide promising solutions for the health and social care challenges, they are not exempt from ethical, legal and social issues (ELSI). A set of ELSI guidelines is needed to integrate these factors at the research and development stage

Framework for Integration Decentralized and Untrusted Multi-Vendor IoMT Environments

Lack of standardization is highly visible while we use historical data sets or compare our model with others that use IoMT devices from different vendors. The problem also concerns the trust in highly decentralized and anonymous environments where sensitive data are transferred through the Internet and then are analyzed by third-party companies. In our research we propose a standard that has been implemented in the form of framework that allows describing requirements for methods and platforms that collect, manage, share, and perform data analysis form the Internet of Medical Things in order to increase trust. Further, we can distinguish two types of IoMT devices: passive and active. Passive devices measure some parameters of the body and save them in databases. Active devices have the functionality of passive devices and moreover, they can act in a defined way, eg.: inject directly into the patient’s body some elements such as a medicament, electric signals to the nervous system, stimulus pacemaker, etc. Nevertheless how to create a safe and transparent environment for using data active sensors, developing safe ML models, performing medical decisions based on the created models and finally deploy this decision to the specified device. While the IoMT devices are used in real-life, professional healthcare the control system should offer tools for backtracking decisions, allowing e.g. to find who made a mistake, or which event caused a particular decision. Our framework provides backtracking in the IoMT environment in which for each medical decision supported by ML models we can prove which sensor sends the data, which data was used to create prediction/recommendation, what prediction was produced, who and when use it, what medical decision was made by who. We propose a vendor transparency framework for each IoMT devices and ML models that will process the medical data in order to increase patient’s privacy and prevent for eventual data leaking.This work was supported in part by the Department of Computer Architecture, Gdansk University of Technology, in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under Project CloudDriver4Industry TIN2017-89266-R, and in part by Grant RTI2018-094283-B-C32, ECLIPSE-UA (Spanish Ministry of Education and Science)

Smart shop services for building customer-oriented scenarios

The shops of today mostly support the customer by offering him or her products based on basic relationships between products viewed or ordered by users with similar tastes. This common approach may fail in many cases especially when the user does not have sufficient knowledge about the market, or when he or she wants to build a set of products in more than one shop. New categories of smart shop services are proposed in order to execute such customer-oriented scenarios where recommended products do meet mutual dependencies with products previously ordered by the customer. An attempt is made to collect additional information about the behavior of users (from past and current contexts) and represent it in a targeted graph called the customer-oriented scenario. Four types of such scenarios are distinguished depending on how many shops have been visited by the user before buying the expected products and how many products the user wants to buy. Moreover, the proposed scenario model provides the possibility of showing which services had been used by the user before the selection was made. Customer-oriented scenarios may be created post factum based on event data logs or before the user will use the shop, which means that it can be arranged which information, knowledge sources (internal or external), products or categories should be suggested in some context of the user's decision. The possibility of leveraging additional smart services into a traditional trading platform may help users, especially when they want to implement a complex scenario and order many products with mutual dependencies or in a situation when the user wants to understand the market before buying something. Using internal and external services allows creating a network for distributing knowledge focused on the actual customer context in a shop

The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process

This paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in the fermentation sludge. The analyses revealed that the implementation of artificial neural networks allowed the prediction of the values of odor intensity and the hedonic tone of the post-fermentation sludge at the level of 30% mean absolute percentage error. Application of the decision tree made it possible to determine what input parameters the fermentation feed should have in order to arrive at the post-fermentation sludge with an odor intensity <2 and hedonic tone >−1. It was shown that the aforementioned phenomenon was influenced by the following factors: concentration of p-xylene, pH, concentration of volatile fatty acids, and concentration of p-cresol

Mobile Cloud computing architecture for massively parallelizable geometric computation

Cloud Computing is one of the most disruptive technologies of this century. This technology has been widely adopted in many areas of the society. In the field of manufacturing industry, it can be used to provide advantages in the execution of the complex geometric computation algorithms involved on CAD/CAM processes. The idea proposed in this research consists in outsourcing part of the load to be computed in the client machines to the cloud through the Mobile Cloud Computing paradigm. This practice gives substantial benefits to both the clients and the software-provider in terms of costs, flexibility, ubiquity and performance. In this document, an outsourcing architecture is proposed based on this paradigm. Extensive experiments have been done using highly parallelizable computational geometry operations to show the strengths and weaknesses of the proposal in combination of specialized computing platforms in the cloud. The results suggest that there are some issues that affect the overall performance and the stability of the QoS: the network communication delay, and the number of simultaneous clients and multiple requests. Some solutions have been proposed to face these challenges.This work was supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under project CloudDriver4Industry TIN2017-89266-R, and by the Conselleria of Innovation, Universities, Science and Digital Society of the Community of Valencia, Spain, within the program of support for research under project AICO/2020/206