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arXiv 2024年

作者： Albaseer, Abdullatif Abdallah, Mohamed Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

Semantic Communication (SemCom) systems, empowered by deep learning (DL), represent a paradigm shift in data transmission. These systems prioritize the significance of content over sheer data volume. However, existing SemCom designs face challenges when applied to diverse computational capabilities and network conditions, particularly in time-sensitive applications. A key challenge is the assumption that diverse devices can uniformly benefit from a standard, large DL model in SemCom systems. This assumption becomes increasingly impractical, especially in high-speed, high-reliability applications such as industrial automation or critical healthcare. Therefore, this paper introduces a novel SemCom framework tailored for heterogeneous, resource-constrained edge devices and computation-intensive servers. Our approach employs dynamic knowledge distillation (KD) to customize semantic models for each device, balancing computational and communication constraints while ensuring Quality of Service (QoS). We formulate an optimization problem and develop an adaptive algorithm that iteratively refines semantic knowledge in edge devices, resulting in better models tailored to their resource profiles. This algorithm strategically adjusts the granularity of distilled knowledge, enabling devices to maintain high semantic accuracy for precise inference tasks, even under unstable network conditions. Extensive simulations demonstrate that our approach significantly reduces model complexity for edge devices, leading to better semantic extraction and achieving the desired QoS. © 2024, CC BY.

关键词： Adaptive algorithms

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Unraveling Fear, Cultivating Awareness: A Research Proposal for Alleviating AI Concerns and Guiding Ethical Adoption

Unraveling Fear, Cultivating Awareness: A Research Proposal ...

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International Conference on Behavior, Economic and Social computing (BESC)

作者： Mohammad Mominur Rahman Information and Computing Technology Division College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (数字)9798331531904

ISBN: (纸本)9798331531911

Artificial intelligence (AI) has the potential to revolutionize industries and transform societal operations, yet public apprehension concerning its risks poses a significant barrier to its adoption. This research leverages behavior change theories to develop strategies that mitigate perceived risks and address ethical concerns surrounding AI. By investigating the psychological underpinnings of AI-related fears and implementing intervention scenarios, this study aims to enhance informed decision-making and promote informed acceptance and ethical judgment of AI. Through a comparative analysis involving participants from the United Kingdom (UK) and Gulf Cooperation Council (GCC) countries, the research seeks to uncover demographic and cultural factors influencing perceptions of AI risks and ethics. The findings are expected to provide actionable recommendations for AI developers, policymakers, and stakeholders, focusing on transparency, ethical practices, and public trust in AI technologies. This study contributes to the broader discourse on responsible AI adoption, offering insights that could influence both academic research and practical applications in the field. As a potential approach, Inoculation Theory can be utilized within this framework to further understand and address AI-related concerns.

关键词： Industries Ethics Social computing Decision making Psychology Focusing Transforms Stakeholders Proposals Artificial intelligence

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From Collatz Conjecture to Hash Function

SSRN

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SSRN 2023年

作者： Rasool, Masrat Belhaouari, Samir Brahim Division of Information and Computing Technology Hamad Bin Khalifa University Doha Qatar

The non-linear property of Chaos is a promising approach to information security, and many accomplishments have been made by combining Chaos with several sub-security domains, including chaos-based stream ciphers, block ciphers, image encryption, and hash functions. Most Chaos-based hash functions are insecure or inefficient due to their dependence on complex, attacked multi-dimensional maps or on uncertain, weak one-dimensional maps like logistic and tent. The Collatz Conjecture is a mystery that has stumped mathematicians for decades and still has not been solved. This paper implements a generalised Collatz process to model a novel chaos-based hash function to tackle the existing security challenges by employing the unpredictable Collatz behaviour, which improves ergodicity and entropy properties that are useful in cryptographic settings. The chaotic variables are controlled by the cryptographic keys which are employed to generate data sequences that are then fed into the hashing function’s diffusion and confusion structures. The proposed chaos-hash model’s design is optimised for randomness, collision resistance, uniformity, sensitivity to initial conditions, speed, and cryptanalysis. The suggested hash function is compared to two other well-known hash algorithms (SHA-3 and SHA-2) and several more Chaos-based hash algorithms to show its effectiveness and dependability. When evaluated under various circumstances and with different data sets, the suggested hash function significantly performs better when compared to the state-of-the-art. Experiments with different inputs reveal that the proposed hash function consistently outperforms the best alternatives available right now. © 2023, The Authors. All rights reserved.

关键词： Hash functions

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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm

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Computers, Materials & Continua 2022年第5期71卷 3513-3531页

作者： Saima Hassan Mojtaba Ahmadieh Khanesar Nazar Kalaf Hussein Samir Brahim Belhaouari Usman Amjad Wali Khan Mashwani Institute of Computing Kohat University of Science and TechnologyKohatPakistan Department of Mechanical Materials and Manufacturing EngineeringFaculty of EngineeringUniversity of NottinghamUK College of Computer Sciences and Mathematics Tikrit UniversityIraq Division of Information and Computing Technology College of Science and EngineeringHamad Bin Khalifa UniversityQatar Department of Computer Science Sir Syed University of Engineering and TechnologyPakistan Institute of Numerical Sciences Kohat University of Science and TechnologyKohatPakistan

The estimation of the fuzzy membership function parameters for interval type 2 fuzzy logic system(IT2-FLS)is a challenging task in the presence of uncertainty and *** optimization algorithm(GOA)is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature,which has good convergence ability towards *** main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an *** antecedent part parameters(Gaussian membership function parameters)are encoded as a population of artificial swarm of grasshoppers and optimized using its *** of the consequent part parameters are accomplished using extreme learning *** optimized IT2-FLS(GOAIT2FELM)obtained the optimal premise parameters based on tuned consequent part parameters and is then applied on the Australian national electricity market data for the forecasting of electricity loads and *** forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization *** of the performance,on the same data-sets,reveals that the proposed GOAIT2FELM could be a better approach for improving the accuracy of the IT2-FLS as compared to other variants of the optimized IT2-FLS.

关键词： Parameter optimization grasshopper optimization algorithm interval type-2 fuzzy logic system extreme learning machine electricity market forecasting

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Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4322-4343页

作者： Al-Maliki, Shawqi Qayyum, Adnan Ali, Hassan Abdallah, Mohamed Qadir, Junaid Hoang, Dinh Thai Niyato, Dusit Al-Fuqaha, Ala Division College of Science and Engineering Doha34110 Qatar Information Technology University Lahore54000 Pakistan University of New South Wales Sydney Sydney2052 Australia Qatar University Department of Computer Science and Engineering College of Engineering Doha34110 Qatar University of Technology Sydney School of Electrical and Data Engineering Sydney2052 Australia Nanyang Technological University College of Computing and Data Science 639798 Singapore

Deep neural networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial examples - input samples that have been perturbed to force DNN-based models to make errors. As a result, adversarial machine learning (AdvML) has gained a lot of attention, and researchers have investigated these vulnerabilities in various settings and modalities. In addition, DNNs have also been found to incorporate embedded bias and often produce unexplainable predictions, which can result in antisocial AI applications. The emergence of new AI technologies that leverage large language models (LLMs), such as ChatGPT and GPT-4, increases the risk of producing antisocial applications at scale. AdvML for social good (AdvML4G) is an emerging field that repurposes the AdvML bug to invent prosocial applications. Regulators, practitioners, and researchers should collaborate to encourage the development of prosocial applications and hinder the development of antisocial ones. In this work, we provide the first comprehensive review of the emerging field of AdvML4G. This paper encompasses a taxonomy that highlights the emergence of AdvML4G, a discussion of the differences and similarities between AdvML4G and AdvML, a taxonomy covering social good-related concepts and aspects, an exploration of the motivations behind the emergence of AdvML4G at the intersection of ML4G and AdvML, and an extensive summary of the works that utilize AdvML4G as an auxiliary tool for innovating prosocial applications. Finally, we elaborate upon various challenges and open research issues that require significant attention from the research community. © 2020 IEEE.

关键词： Taxonomies

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Image Reconstruction for Lensless Imaging Using a Phase Congruency Perception Model

Image Reconstruction for Lensless Imaging Using a Phase Cong...

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2023 China Automation Congress, CAC 2023

作者： Tian, Yibin Lu, Dajiang Deng, Hong Zhang, Zhiyuan Zhong, Xiaopin Wu, Zongze College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Litemaze Technology R&D Division Hangzhou China School of Computing and Information Systems Singapore Management University Singapore Singapore

ISBN: (纸本)9798350303759

Lensless imaging systems capture images without the need for traditional lenses. Instead, they employ flat and thin micro-optical devices, such as masks, diffusers, Fresnel zone plates, and other diffractive optical elements, to capture information-encoded images of imaging targets, and rely on advanced computational methods to reconstruct regular images from the encoded ones. Typical image reconstructions in lensless imaging utilize compressive sensing and sophisticated iterative optimization algorithms. Recently such iterative methods have been replaced by deep neural networks. However, in both approaches the cost (or loss) functions usually are defined on certain simple mathematical distance metric, without considering the inherent perceptive properties of images. In this report, a new method is proposed to construct cost functions for image reconstruction in lensless imaging. It is based on a visual perception model of image phase congruency, a measure of the consistency of the phase information across different spatial orientations and scales in images. The proposed method is demonstrated to provide improved image reconstruction quality using more than 200 encoded images from a virtual lensless imaging system with a Fresnel zone plate, as well a small number of encoded images from a physical one with an optical diffuser. © 2023 IEEE.

关键词： Image reconstruction

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Fully Inkjet-Printed Soft Wearable Strain Sensors Based on Metal/Polymer Composite Sensing Films 5

Fully Inkjet-Printed Soft Wearable Strain Sensors Based on M...

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5th IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Khan, Arshad Ali, Shawkat Nittala, Aditya Shekhar Riaz, Kashif Bermak, Amine College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Doha Qatar Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia University of Calgary Department of Computer Science Calgary Canada

ISBN: (纸本)9781665457330

In this paper, we present a high-performance soft strain sensor that uses composite sensing layers made of metal and polymer. This strain sensor is entirely developed by inkjet-printing the composite films on a highly stretchable thermoplastic polyurethane (TPU) substrate and a textile-compatible polymer film, which makes the process easy, affordable, energy-efficient, and scalable. The sensing patches are made up of two films: a PEDOT:PSS-based conductive polymer top film and a metal bottom film composed of silver nanoparticles. The sensor has a decent sensing range (≈10% strain), high sensitivity (GF ≈ 12), and outstanding mechanical stability (>1000 cycles), making it suitable for both stretching and bending deformation detection. As application examples, the soft sensors are used to track the highly deformed human body motions, displaying excellent performance. The outcomes demonstrate the attractiveness and potential of our low-cost soft strain sensors for real-world uses, such as the wide-range tracking of human movements. © 2023 IEEE.

关键词： Polymer films

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Multi-Agent DRL for Queue-Aware Task Offloading in Hierarchical MEC-Enabled Air-Ground Networks

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Hevesli, Muhammet Seid, Abegaz Mohammed Erbad, Aiman Abdallah, Mohamed Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Qatar University College of Engineering Doha Qatar

Mobile edge computing (MEC)-enabled air-ground networks advance 6G wireless networks by utilizing aerial base stations (ABSs) such as unmanned aerial vehicles (UAVs) and high altitude platform stations (HAPS) to provide dynamic services to ground IoT devices (IoTDs). These IoTDs support real-time applications like multimedia and Metaverse services, which demand high computational resources and strict quality of service (QoS) guarantees, specifically in terms of latency and efficient task queue management. However, IoTDs often face constraints in energy and computational power, requiring efficient queue management and task scheduling to maintain QoS. To address these challenges, UAVs and HAPS are deployed to supplement the computational limitations of IoTDs by offloading tasks for distributed processing. Due to UAVs' resource limitations, particularly in terms of power and coverage area, HAPS are used to enhance their capabilities and extend coverage. Overloaded UAVs may relay tasks to HAPS, creating a multi-tier computing system. This paper addresses the overall energy minimization problem in the MEC-enabled air-ground integrated network (MAGIN) by optimizing UAV trajectories, computing resource allocation, and queue-aware task offloading decisions. The optimization problem is highly complex due to the nonconvex and nonlinear nature of this hierarchical system, which traditional methods cannot effectively solve. To tackle this, we reformulate the problem as a multi-agent Markov decision process (MDP) with continuous action spaces and heterogeneous agents. We propose a novel variant of multi-agent proximal policy optimization (MAPPO) with Beta distribution (MAPPO-BD) to solve this problem. Extensive simulations show that MAPPO-BD significantly outperforms other baselines, achieving superior energy savings and efficient resource management in MAGIN, while adhering to constraints related to queue delays and edge computing capabilities. © 2025 IEEE.

关键词： Quality of service

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Flexible Paper-Based Capacitive Touchpad for Wireless Switching Control Fabricated via Facile and Solvent-Free Method

Flexible Paper-Based Capacitive Touchpad for Wireless Switch...

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Conference on Technologies for Sustainability (Sustech)

作者： Muhammad Mateen Fawad Kashif Riaz Muhammad Hamza Zulfiqar Muhammad Nasir Arshad Khan Bo Wang Amine Bermak Electrical Engineering Department Information Technology University Lahore Pakistan Division of Computing and Information Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (数字)9798350394344

ISBN: (纸本)9798350394351

Due to the substantial growth in the use of electronic devices in our daily lives, the demand for flexible and green input interfaces has increased as a mean to accommodate more sustainable Human Machine Interface (HMI) options for consumers. Furthermore, capacitive touch sensors are more fabrication-friendly, sensitive, and responsive than traditional physical tactile buttons input interfaces. In this regard we have presented a flexible paper-based capacitive touchpad input interface fabricated through a facile, solvent-free eco-friendly method. Considering greenhouse gases and electronic waste conventionally associated with the electronic device lifecycle, non-toxic and recyclable materials in particular copper and paper are used to fabricate the touchpad. Copper tape is used as touch sensing electrodes, while cellulose-based printing paper is used as a substrate to support the electrodes. Furthermore, the touchpad implementation is facile and only requires off-the-shelf materials readily available easily in a home or laboratory settings. The touchpad flexibility allows bending, warping, twisting, and tugging to desired shape and size without causing a signal change in the functionality. The electrodes of the touchpad are touch-sensitive and sense the capacitance change caused by the effective capacitance of the skin with the help of a microcontroller. The touch-sensitive electrodes have very little intrinsic capacitance, and the response time of the implemented touchpad is excessive. Wireless digital switch control is also interfaced with the touchpad using the Wi-Fi equipped microcontroller. An RGB LED analogy successfully demonstrates the touchpad's functionality reported for controlling digital switches wirelessly. According to the study's findings, there is a very promising application scope for such a touchpad interface system in environment friendly, low cost, disposable HMI(s) that have a facile fabrication method. People with impairments, the elderly, edu

关键词： Fabrication Electrodes Wireless communication Wireless sensor networks Microcontrollers Switches Capacitance

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Accessible Remote Electronic Education: Affordable DIY Paper-based Tunable RC Oscillator Circuits

Accessible Remote Electronic Education: Affordable DIY Paper...

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Conference on Technologies for Sustainability (Sustech)

作者： Muhammad Nasir Kashif Riaz Muhammad Hamza Zulfiqar Muhammad Mateen Fawad Arshad Khan Bo Wang Amine Bermak Electrical Engineering Department Information Technology University Lahore Pakistan Division of Computing and Information Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (数字)9798350394344

ISBN: (纸本)9798350394351

Paper-based electronics are gaining popularity for their affordability, abundant availability in household settings, biodegradability, recyclability, disposability, facile fabrication, eco-friendliness, and sustainability. This aligns with the UN's Sustainable Development Goals, promoting sustainable, responsible, and environmentally conscious production practices. Given the current economic and pandemic scenario, which restricts students' access to traditional physical labs, there is a pressing need to develop cost-effective, do-it-yourself (DIY), and eco-friendly sustainable electronic solutions for remote learning from home. This study introduces an economical and DIY approach wherein a graphite pencil drawn resistor and copper tape capacitor are integrated with a 74HC14 IC on paper to form an RC oscillator circuit. The 74HC14 IC, acting as a Schmitt trigger, exhibits oscillatory behavior when connected to the RC bridge. The frequency achieved from the RC oscillator was up to 250 kHz. Furthermore, the circuit's tunability is demonstrated by varying the resistance of the circuit either by increasing or decreasing the graphite flakes. Furthermore, these circuits can be reused and recycled again in performing the same or other electronic labs. The study showcases the feasibility and practicality of making circuits on paper in home-based settings, laying a foundation for incorporating basic electronics lab experiments on paper substrates, particularly required in the pandemic and economic context. This approach not only addresses the immediate need for remote learning solutions but also sets a transformative precedent for sustainable and accessible electronic education.

关键词： Economics Resistors Distance learning Pandemics Education Graphite Copper

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