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International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN)

作者： Sahar Boulkaboul Djamel Djenouri Miloud Bagaa CERIST Research Center Algiers Algeria Dep. of Computer Science and Creative Technologies CSRC University of the West of England (UWE) Bristol UK Department of Electrical and Computer Engineering Universit du Qubec Trois-Rivires Trois-Rivires QC Canada

A novel distributed particle filter algorithm for target tracking is proposed in this paper. It uses new metrics and addresses the measurement uncertainty problem by adapting the particle filter to environmental changes and estimating the kinematic (motion-related) parameters of the target. The aim is to calculate the distance between the Gaussian-distributed probability densities of kinematic data and to generate the optimal distribution that maximizes the precision. The proposed data fusion method can be used in several smart environments and Internet of Things (IoT) applications that call for target tracking, such as smart building applications, security surveillance, smart healthcare, and intelligent transportation, to mention a few. The diverse estimation techniques were compared with the state-of-the-art solutions by measuring the estimation root mean square error in different settings under different conditions, including high-noise environments. The simulation results show that the proposed algorithm is scalable and outperforms the standard particle filter, the improved particle filter based on KLD, and the consensus-based particle filter algorithm.

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TIoT: A Trust by Design Architecture for Secure and Private Internet of Things (IoT)

TIoT: A Trust by Design Architecture for Secure and Private ...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： H. Alsheakh Tareq Nasser Mahdi Mustafa S. Kadhm Abeer Al Shammari Fatimah I. Abdulsahib Hazeem B Taher Waleed Algriree Marwa Q. Alobaidi Hayder Dhafer Mohammed Department of Computer Science College of Science Mustansiriyah University Baghdad Iraq Clinical Laboratory Science College of Pharmacy Mustansiriyah University Baghdad Iraq IT Directorate Ministry of Science and Technology Baghdad Iraq Department of Computer Science Szechenyi Istvan Egyetem Gyor Hungary Department of Computer Science University of Thi-Qar Thi-Qar Iraq Dep. Of Wireless Communication and Network Engineering University Putra Malaysia Selangor Malaysia National Engineering School of Sfax Sfax University Sfax Tunisia College of Pharmacy Mustansiriyah University Baghdad Iraq

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

The Internet of Things (loT) facilitates the interconnection of a vast array of devices, services, and individuals for data exchange in multi-domain loT ecosystems, the social, physical, and cyber domains. That emerges various security, privacy, and trust issues, such as vulnerabilities, threats, and attacks. Addressing these challenges requires innovative solutions. New controls (solutions) are needed. Trust by design can be one of these controls, supporting security and privacy (among other system components). This paper proposes a Trusted loT (TloT), a trust-by-design model, and highlights the author's principal contributions. First, it advocates for implementing Tlo T through trust services. Second, it outlines an architecture for using trust by design in loT, including the design of its top-level structure and activities. Minor contributions include overviews of loT and trust, as well as looking at security and privacy in terms of security services and privacy services, respectively.

关键词： Privacy Ecosystems Security Internet of Things Arrays

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An Overview of Information Hiding Techniques Challenges and Applications 23

An Overview of Information Hiding Techniques Challenges and ...

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Proceedings of the 7th International Conference on Future Networks and Distributed systems

作者： Ali Noori Kareem Omar Adil Deheyab Aws Zuhair Sameen Mohammed Hasan Alwan Yousif I Hammadi Mayssam Saad Kadhum Ahmed Aziz Muthana Ali Salem Ali Department of Computer engineering University of Diyala Iraq Department of Communications Engineering Bilad Alrafidain University College Iraq Department of Medical Instrumentation Engineering Techniques Al-Farahidi University Iraq Department of Communications Engineering University of Diyala Iraq Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Department of Computer-aided Design and Engineering Design National University of Science and Technology Russia

ISBN: (纸本)9798400709036

The internet became a common communication platform for many people. However, information transmission is not secure, and there is a high probability of copying and altering the information easily. In the public network, transmitting sensitive or private information needs some kind of protection. Unless a secure channel is utilized for the transmission. Hiding the information is one of the efficient techniques that provides a solution for transmitting confidential data over communication channels. These techniques should meet various application requirements such as high robustness against attacks, real-time, and high hiding capacity. Generally, information-hiding techniques suffer from many challenges. This paper provides an insight into these techniques, their applications, and challenges to fill the gap of missing such an overview.

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Intelligent disease detection system for greenhouse with a robotic monitoring system 2

Intelligent disease detection system for greenhouse with a r...

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2nd International Conference on Advancements in Computing, ICAC 2020

作者： Fernando, Sandunika Nethmi, Ranusha Silva, Ashen Perera, Ayesh De Silva, Rajitha Abeygunawardhana, Pradeep K.W. Dep. of Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe10115 Sri Lanka

ISBN: (纸本)9781728184128

Greenhouse farming plays a significant role in the agricultural industry because of its controlled climatic features. Recent examinations have stated that the mean creation of the yields under greenhouses is lessening due to disease events in the plants. These foods have become an imposing undertaking because these plants are being assaulted by different bacterial diseases, micro-organisms, and pests. The chemicals are applied to the plants intermittently without thinking about the necessity of each plant. Several problems have occurred in the greenhouse environment due to these causes. Therefore, there is a huge necessity for a system to detect diseases at an early stage. This research focused on designing a system to detect disease, which causes yellowish in greenhouse plants. Plant yellowing can be considered a significant problem of plants that grow under greenhouse-controlled environments. Through this research is focused on the most important and one of the most attention-grabbing crop tomato. There are specific diseases that cause yellowish the tomato plant, and they have been identified. The techniques utilized for early recognition of infection are image processing, machine learning, and deep learning. Index Terms-Greenhouses, Disease diagnosis, Image processing, Machine Learning, Deep Learning, Tomato Farming. © 2020 IEEE.

关键词： Greenhouses

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AI based greenhouse farming support system with robotic monitoring

AI based greenhouse farming support system with robotic moni...

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2020 IEEE Region 10 Conference, TENCON 2020

作者： Fernando, Sandunika Nethmi, Ranusha Silva, Ashen Perera, Ayesh Silva, Rajitha De Abeygunawardhana, Pradeep W. K. Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Malabe10115 Sri Lanka

ISBN: (纸本)9781728184555

Greenhouses plays a major role in today's agriculture since farmers can grow plants under controlled climatic conditions and can optimize production. The greenhouses are usually built in areas where the climatic conditions for the growth of plants are not optimal so requires some artificial setups to bring about productivity. Automating process of a greenhouse requires monitoring and controlling of the climatic parameters. This paper is an attempt to minimize the cost of maintaining greenhouse environments using new technologies. The end goal of this research an automated system to optimally monitor and control the environmental factors inside greenhouse by monitoring temperature, soil moisture, humidity and pH through a cloud connected mobile robot which can detect unhealthy plants using image processing and machine learning. The mobile robot navigates through a predefined map of greenhouse. Database server has created to store gathered real-time data. And the necessary accurate data represent by using proper application for analyzing. © 2020 IEEE.

关键词： Greenhouses

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Consistent Event-Triggered Consensus on Complete Graphs

Consistent Event-Triggered Consensus on Complete Graphs

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IEEE Conference on Decision and Control

作者： Duarte J. Antunes David Meister Toru Namerikawa Frank Allgöwer W.P.M.H. Heemels Dep. of Mechanical Eng. Eindhoven Control Systems Technology Group University of Technology the Netherlands Institute for Systems Theory and Automatic Control University of Stuttgart Germany School of Integrated Design Engineering Graduate School of Science and Technology Keio University Japan

This paper starts by considering an optimal control formulation of the consensus problem on complete graphs with a cost capturing disagreement and agents modeled by integrators. An optimal control policy for this problem is shown to be the well-known consensus algorithm by which each agent resets its state to the average of its and other agents' state values received at every time step. The framework is extended to the case where agents can only exchange information periodically, with a period larger than one. Then an event-triggered control strategy is proposed that results in a better cost than that of the optimal periodic one with the same average transmission rate, that is, it is consistent. According to this strategy, each agent distributedly transmits its state if the error between its current state and a common consensus estimate based on previously transmitted agents' data exceeds a threshold. Simulation results are presented to illustrate the proposed strategy.

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Automating Public Announcement Logic with Relativized Common Knowledge as a Fragment of HOL in LogiKEy

arXiv

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arXiv 2021年

作者： Benzmüller, Christoph Reiche, Sebastian University of Bamberg AI Systems Engineering Bamberg Germany FU Berlin Dep. of Mathematics and Computer Science Berlin Germany

A shallow semantical embedding for public announcement logic with relativized common knowledge is presented. This embedding enables the first-time automation of this logic with off-the-shelf theorem provers for classical higher-order logic. It is demonstrated (i) how meta-theoretical studies can be automated this way, and (ii) how non-trivial reasoning in the target logic (public announcement logic), required e.g. to obtain a convincing encoding and automation of the wise men puzzle, can be realized. Key to the presented semantical embedding is that evaluation domains are modeled explicitly and treated as an additional parameter in the encodings of the constituents of the embedded target logic;in previous related works, e.g. on the embedding of normal modal logics, evaluation domains were implicitly shared between meta-logic and target logic. The work presented in this article constitutes an important addition to the pluralist LogiKEy knowledge engineering methodology, which enables experimentation with logics and their combinations, with general and domain knowledge, and with concrete use cases - all at the same *** Codes 03B42, 03B60, 03B62, 68T27, 68T30 Copyright © 2021, The Authors. All rights reserved.

关键词： Formal logic

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Analysis and Design of Terahertz Elliptical Slot Antenna Based on Photonic Crystal Substrate

Analysis and Design of Terahertz Elliptical Slot Antenna Bas...

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Antennas and Propagation Society International Symposium

作者： Mohamed Nasreddine Temmar Mourad Nedil Abdellah Chehri School of Engineering Université du Québec en Abitibi-Témiscamingue (UQAT) Val-d'Or QC Canada Dep. of Math. and Computer Science Royal Military College of Canada Kingston ON Canada

This paper aims to develop a photonic band gap substrate-based slot microstrip patch antenna for terahertz applications. The proposed antenna is based on an elliptical slotted patch placed on the top of a photonic crystal structure to improve the conventional microstrip patch antenna in terms of the undesirable surface waves and its electrical properties. As a result, good radiation characteristics are achieved. Besides, an enhancement of more than 35% and 91% are observed for a total bandwidth of 203.5 GHz and a realized gain of 9.1 dBi, respectively.

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Designing Participatory AI: Creative Professionals’ Worries and Expectations about Generative AI

arXiv

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arXiv 2023年

作者： Inie, Nanna Falk, Jeanette Tanimoto, Steven IT University of Copenhagen Copenhagen Denmark Dep. of Artificial Intelligence and Human Interfaces University of Salzburg Salzburg Austria Paul G. Allen School of Computer Science & Engineering University of Washington Seattle United States

Generative AI, i.e., the group of technologies that automatically generate visual or written content based on text prompts, has undergone a leap in complexity and become widely available within just a few years. Such technologies potentially introduce a massive disruption to creative fields. This paper presents the results of a qualitative survey (N = 23) investigating how creative professionals think about generative AI. The results show that the advancement of these AI models prompts important reflections on what defines creativity and how creatives imagine using AI to support their workflows. Based on these reflections, we discuss how we might design participatory AI in the domain of creative expertise with the goal of empowering creative professionals in their present and future coexistence with AI. © 2023, CC BY.

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Cybersecurity Threats in the Era of AI: Detection of Phishing Domains Through Classification Rules 2

Cybersecurity Threats in the Era of AI: Detection of Phishin...

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2nd International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Aljaidi, Mohammad Alsarhan, Ayoub Al-Fraihat, Dimah Al-Arjan, Ahmed Igried, Bashar El-Salhi, Subhieh M. Khalid, Muhammad Al-Na'amneh, Qais Zarqa University Faculty of Information Technology Department of Computer Science Zarqa13110 Jordan The Hashemite University Department of Information Technology Jordan Isra University Faculty of Information Technology Department of Software Engineering Amman11622 Jordan The Hashemite University Faculty of Prince AL-Hussein Bin Abdullah Ii of Information Technology Department of Information Technology Jordan The Hashemite University Department of Computer Science and Applications Zarqa Jordan The Hashemite University P. O Box 330127 Zarqa13133 Jordan University of Hull Department of Computer Sciences and Technology Kingston upon Hull United Kingdom Applied Science Private University Dep. of Cyber Security Amman Jordan

ISBN: (纸本)9798350373363

Phishing is a cyber threat where attackers create deceptive websites or emails to exploit individuals for fraudulent purposes such as providing sensitive information like usernames, passwords, or financial details. Hence, detecting phishing emails is of paramount importance to protect sensitive information, preventing financial losses, protecting against identity theft, and maintaining trust. This study employs machine learning techniques to classify and categorize websites that are used for phishing attacks. To achieve this, we proposed a classification model for the detection of phishing domains based on classification rules. These rules were formulated based on analyzing and distributing them into three classifiers: domain name features, search engine opinion (SEO) information of the domain, and security scans by security vendors. A total of eleven classification rules were formulated which were distributed as follows: six rules for the first classifier, four rules for the second classifier, and one rule for the third classifier. Each classifier feeds its results to the main classifier, which then evaluates the received results based on its rules. Domain names from 222 confirmed phishing URLs were used to test the suggested model. The model demonstrated exceptional performance, achieving an impressive accuracy rate of 99.1% during testing. © 2023 IEEE.

关键词： Websites

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