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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Caterina Alfano Lorenzo Farina Manuela Petti PhD program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering PhD program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Colorectal cancer is the third most diagnosed cancer in the world, but it has a higher mortality rate in men compared to women. However, we are not close to understanding how and why sex influences the outcome of the disease. This study focuses on mRNA expression profiles of colon cancer patients to look for molecular differences in the development of colon cancer between men and women. We used paired expression data (i.e., data collected in pairs of normal and cancer cells, by taking samples from the same individual), we identified differentially expressed genes (cancer vs normal) and computed co-expression and differential co-expression gene networks (men vs women). Doing so, we inferred the main changes and alterations happening in cancer tissues, and specifically how these changes were different among men and women. We found that the co-expression networks of women and men affected by colon cancer are quite different and we reported the genes that show the most differences in this comparison, checking if they could also be associated to sexual dimorphism or sexual hormones. Among these genes we found a interesting presence of genes associated to the Wnt signaling pathway which has been found to be regulated by estrogen and whose activation is strongly linked with colon cancer.

关键词： Network analyzers Biochemistry Colon Bioinformatics Cancer

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A Low-overhead PUF-based Secure Scan Design

A Low-overhead PUF-based Secure Scan Design

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IEEE International Symposium on Quality Electronic Design

作者： Wei Zhou Aijiao Cui Cassi Chen Gang Qu School of Electronic and Information Engineering Harbin Institute of Technology (Shenzhen) Guangdong China University of California Berkeley USA Dept. of Electrical and Computer Engineering and Institute of Systems Research Univ. of Maryland College Park USA

Scan-based side-channel attacks have become a severe threat to the security of cryptographic chips and locking mechanisms are one of the most effective methods against these attacks. However, securing the test key that locks the scan but must be shared among test engineers arises as a new challenge. In this paper, we solve this challenge by adopting the physical unclonable function (PUF) design to generate test keys that are unique for each chip. A one-time programming structure (OTPS) is used when the PUF response is first generated to improve its reliability. The security of the PUF response is achieved by obfuscation such that it can be retrieved only when a specific validation test vector presents. We implement the proposed secure scan design by reusing the original scan chain to reduce overhead. We demonstrate that the proposed secure scan design can protect the crypto chips against all existing scan-based side-channel attacks while incurring negligibly low overhead.

关键词： Side-channel attacks Resists Programming Physical unclonable function Reliability engineering Silicon Registers

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Robust Optimal control for Demand Side Management of Multi-Carrier Microgrids

TechRxiv

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TechRxiv 2022年

作者： Carli, Raffaele Cavone, Graziana Pippia, Tomás De Schutter, Bart Dotoli, Mariagrazia The Dept. of Electrical and Information Engineering Polytechnic of Bari Bari Italy The Delft Center for Systems and Control Delft University of Technology Delft Netherlands

This paper focuses on the control of microgrids where both gas and electricity are provided to the final customer, i.e., multi-carrier microgrids. Hence, these microgrids include thermal and electrical loads, renewable energy sources, energy storage systems, heat pumps, and combined heat and power units. The parameters characterizing the multi-carrier microgrid are subject to several disturbances, such as fluctuations in the provision of renewable energy, variability in the electrical and thermal demand, and uncertainties in the electricity and gas pricing. With the aim of accounting for the data uncertainties in the microgrid, we propose a Robust Model Predictive control (RMPC) approach whose goal is to minimize the total economical cost, while satisfying comfort and energy requests of the final users. In the related literature various RMPC approaches have been proposed, focusing either on electrical or on thermal microgrids. Only a few contributions have addressed the robust control of multi-carrier microgrids. Consequently, we propose an innovative RMPC algorithm that employs on an uncertainty set-based method and that can provide better performance compared with deterministic model predictive controllers applied to multi-carrier microgrids. With the aim of mitigating the conservativeness of the approach, we define suitable robustness factors and we investigate the effects of such factors on the robustness of the solution against variations of the uncertain parameters. We show the effectiveness of the proposed RMPC approach by applying it to a realistic residential multi-carrier microgrid and comparing the obtained results with the ones of a baseline robust method. © 2022, CC BY-NC-SA.

关键词： Demand side management

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Comparing SWIPT Techniques for Zero-Energy RIS

Comparing SWIPT Techniques for Zero-Energy RIS

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IEEE International Conference on Communications Workshops, ICC

作者： Dimitrios Tyrovolas Vasilis K. Papanikolaou Sotiris A. Tegos Yue Xiao Panagiotis D. Diamantoulakis Sotiris Ioannidis Christos Liaskos George K. Karagiannidis Dept. of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Dept. of Electrical and Computer Engineering Technical University of Chania Chania Greece School of Information Science and Technology Southwest Jiaotong University Chengdu China Computer Science Engineering Department University of Ioannina Ioannina and Foundation for Research and Technology Hellas (FORTH) Greece Cyber Security Systems and Applied AI Research Center Lebanese American University (LAU) Lebanon

Providing enhanced quality of service (QoS) to support demanding applications in the most energy-efficient way has been identified as a primary objective of future 6G networks. Towards this direction, the concept of programmable wireless environments (PWEs) has emerged, wherein extremely high QoS can be ensured by controlling the wireless propagation through reconfigurable intelligent surfaces (RIS). To meet the demands of 6G networks in terms of energy efficiency, in this paper, zero-energy RISs (ZERISs) are introduced, which harvest the required amount of energy for their operation and then contribute to the PWE conversion. More specifically, we investigate the performance of a ZERIS-assisted communication system in terms of joint energy-data rate outage probability, which quantifies the trade-off between the harvested energy and information transmission, for three distinct simultaneous wireless information and power transfer (SWIPT) methods are investigated, namely power splitting, time switching, and element splitting. Finally, simulation results validate the derived analysis, leading to useful insights for the ZERIS-assisted network regarding which energy harvesting method achieves better performance in terms of joint energy-data rate outage probability.

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Team Precoding Towards Scalable Cell-free Massive MIMO Networks

arXiv

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arXiv 2022年

作者： Miretti, Lorenzo Björnson, Emil Gesbert, David Communication Systems Dept. EURECOM Sophia Antipolis France Dept. of Computer Science KTH Royal Institute of Technology Stockholm Sweden Dept. of Electrical Engineering Linköping University Linköping Sweden

In a recent work, we studied a novel precoding design for cell-free networks called team minimum mean-square error (TMMSE) precoding, which rigorously generalizes centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSI). Despite its flexibility in handling different cooperation regimes at the CSI sharing level, TMMSE precoding assumes network-wide sharing of the data bearing signals, and hence it is inherently not scalable. In this work, inspired by recent advances on scalable cell-free architectures based on user-centric network clustering techniques, we address this issue by proposing a novel version of the TMMSE precoding design covering partial message sharing. The obtained framework is then successfully applied to derive a variety of novel, optimal, and efficient precoding schemes for a user-centric cell-free network deployed using multiple radio stripes. Numerical simulations of a typical industrial internet-of-things scenario corroborate the gains of TMMSE precoding over competing schemes in terms of spectral efficiency under different power constraints. Although presented in the context of downlink precoding, the results of this paper may be applied also on the uplink. © 2022, CC BY.

关键词： Mean square error

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Generalized Likelyhood Ratio based Detection on Cyber-Attacks

Generalized Likelyhood Ratio based Detection on Cyber-Attack...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Hao Wu Deyu Zhang dept. of Software Henan University of Engineering Zhengzhou China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9781665465373

In this paper, a generalized likelihood ratio based detection algorithm with a statistical method for threshold setting is proposed to detect cyber-attacks on a unified remote control architecture. Based on an encoder and a decoder embedded on plant side and remote controller side, respectively, not only additive interrupted signal (only effecting output or input signal), but also multiplicative attack signal could be detected easily. Finally, three numerical examples are provided to validate our proposed scheme.

关键词： Additives Automation Statistical analysis Switches Decoding Detection algorithms Cyberattack

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TARGET SPECIFIC DE NOVO DESIGN OF DRUG CANDIDATE MOLECULES WITH GRAPH TRANSFORMER-BASED GENERATIVE ADVERSARIAL NETWORKS

arXiv

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arXiv 2023年

作者： Ünlü, Atabey Çevrim, Elif Sarıgün, Ahmet Yiğit, Melih Gökay Çelikbilek, Hayriye Bayram, Osman Güvenilir, Heval Ataş Koyaş, Altay Kahraman, Deniz Cansen Olğaç, Abdurrahman Rifaioğlu, Ahmet Banoğlu, Erden Doğan, Tunca Biological Data Science Lab Dept. of Computer Engineering Hacettepe University Turkey Dept. of Bioinformatics Graduate School of Health Sciences Hacettepe University Turkey Dept. of Chemistry Middle East Technical University Turkey Dept. of Physics Middle East Technical University Turkey Dept. of Computer Engineering Middle East Technical University Turkey Dept. Of Artificial Intelligence Engineering Bahcesehir University Turkey Cancer Systems Biology Lab Graduate School of Informatics Middle East Technical University Turkey Dept. of Pharmaceutical Chemistry Faculty of Pharmacy Gazi University Turkey Laboratory of Molecular Modeling Evias Pharmaceutical R&D Ltd Turkey Dept. of Electrical and Electronics Engineering Iskenderun Technical University Turkey Institute for Computational Biomedicine Heidelberg University Germany

Discovering novel drug candidate molecules is one of the most fundamental and critical steps in drug development. Generative deep learning models, which create synthetic data given a probability distribution, offer a high potential for designing de novo molecules. However, for them to be useful in real-life drug development pipelines, these models should be able to design drug-like and target-centric molecules. In this study, we propose an end-to-end generative system, DrugGEN, for the de novo design of drug candidate molecules that interact with intended target proteins. The proposed method represents molecules as graphs and processes them via a generative adversarial network comprising graph transformer layers. The system is trained using a large dataset of drug-like compounds and target-specific bioactive molecules to design effective inhibitory molecules against the AKT1 protein, which is critically important in developing treatments for various types of cancer. We conducted molecular docking and dynamics to assess the target-centric generation performance of the model, as well as attention score visualisation to examine model interpretability. Results indicate that our de novo molecules have a high potential for interacting with the AKT1 protein at the level of its native ligands. Using the open-access DrugGEN codebase, it is possible to easily train models for other druggable proteins, given a dataset of experimentally known bioactive molecules. © 2023, CC BY-NC-SA.

关键词： Generative adversarial networks

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An Architectural Approach for Enhanced Data Interoperability Across Building systems

An Architectural Approach for Enhanced Data Interoperability...

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Cloudification of the Internet of Things (CIoT)

作者： Peter Yefi Sikandar Ejaz Ramanunni Parakkal Menon Ursula Eicker Yann-Gaël Guéhéneuc Computer Science and Software Engineering Dept. Concordia University Montreal Canada Institute for Information Systems Engineering Concordia University Montreal Canada German Aerospace Center Institute for Solar Research Jülich Germany NextGen Cities Institute Concorida University Montreal Canada

ISBN: (数字)9798350356717

ISBN: (纸本)9798350356724

Access to building data is crucial for creating portable applications and improving building operation and energy efficiency. Ensuring data transmutability is essential for facilitating research and overcoming the diverse data representation, management, and collection methods across various building management systems (BMSs). Different BMSs use multiple interfaces for data exchange. Some BMSs provide Application Programming Interfaces (APIs) for data exchanges, while others have gateways connecting to cloud services for application subscription and data access. This study introduces a five-layered architecture that describes how client applications, researchers, and other interested stakeholders can exchange data with different BMSs. Our objective is to help researchers and practitioners understand the various ways of accessing transmutable (capable of being transformed into a compatible format) data from BMSs, regardless of the building management system a building uses. Through transmutable access to building systems’ data, we aim to enable transferable energy-efficient-related applications for buildings. We evaluate our work with a building model of the Varennes Library in Varennes, QC, Canada. The building model includes information about the building, floors, rooms, electric meter and historical time series data of the meter, weather station and its historical time series data. The model also has carbon dioxide concentration sensors, temperature sensors, humidity sensors, and historical time series data of the sensors. We include two test client programs to show how they access the transmutable data of the building through a model. We conclude that the five-layered architecture facilitates the exchange of transmutable data across diverse BMSs, making it a valuable tool for researchers and practitioners.

关键词： Temperature sensors Meters Architecture Buildings Time series analysis Data models Energy efficiency Sensors Stakeholders Building management systems

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TangiGuru: Tangible E-Learning Solution for Early Childhood Development

TangiGuru: Tangible E-Learning Solution for Early Childhood ...

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Advancements in Computing (ICAC), International Conference on

作者： Thiwanka Cholitha Hettiarachchi Lakisuru Sathyajith Semasinghe Shashika Lokuliyana Narmada Gamage Rajitha De Silva Dept. Computer Systems Engineering Sri Lanka Institute of Information Technology Lincoln Institute for Agri-Food Technology University of Lincoln

ISBN: (纸本)9798350398106

Exploration and manipulation of physical objects are essential for early childhood learning. Previous investigations found several TUI uses in other fields. Less research has been done on tangible learning for youngsters; thus, it is unclear if they are more collaborative, playful, or functional. TangiGuru consists of 12 tangible, manipulative objects known as TangiCubes, which are used as a tangible user interface between children and the e-Learning application. It can carry out cognitive learning activities related to colors, languages, shapes and basic math by dynamically varying assigned values by changing the external appearance of TangiCubes. This dynamic nature of the TangiCubes makes it possible to use the same tangibles with endless possibilities compared to traditional tangible learning solutions with static value for each tangible. After the prototyping phase, children were evaluated with the traditional tangible learning solutions compared to TangiGuru. They concluded that the more interactive tangible interfaces could make the children perform activities more engagingly.

关键词： Performance evaluation Human computer interaction Electronic learning Shape Toy manufacturing industry Collaboration Games

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AI in Agriculture: Yield Optimization and Food Security

AI in Agriculture: Yield Optimization and Food Security

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Technological Advancements in Computational Sciences (ICTACS), International Conference on

作者： Lavanya Chavan Rishikesh Kumbhalkar Poorva Agrawal Nitin Rakesh R. Parvathi Mohammad Shahid Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Dept. of Smart Computing School of Computer Science Engineering and Information Systems Vellore Institute of Technology (VIT) Vellore India Noida Institute of Engineering and Technology Greater Noida India

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

Artificial Intelligence (AI) is remarkably automating the agricultural methods. In this process, AI is helping to optimize yield, and improving food security in a world with growing population and environmental concern(s). AI technology integration in agriculture is the focus of this paper which includes predictive analytics, machine learning and IoT. These applications led to precision farming and resource management which lead to efficient use of resources. The discussion on the benefits of AI in increasing productivity and sustainability is based on the summarization of the latest literature and empirical studies. Yet, these technologies bring along their own issues such as initial capital investment to implement the systems in emergence economies as well as the need for the rapid upgrading of the infrastructure and human capital. This research demonstrates that AI has the potential to change agriculture radically, while at the same time acknowledging the pending problems that hinder full-fledged implementation.

关键词： Training Food security Agriculture Resource management Artificial intelligence Sustainable development Socioeconomics Optimization Farming Investment

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