ORCID Profile
0000-0002-1928-3704
Current Organisations
ETH Zurich Department of Materials
,
Charles Darwin University
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Publisher: Wiley
Date: 03-08-2020
DOI: 10.1002/SPE.2853
Publisher: Elsevier BV
Date: 02-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-08-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Publisher: Hindawi Limited
Date: 18-11-2021
DOI: 10.1155/2021/7156420
Abstract: Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence. FL has the capability of revolutionizing machine learning (ML) but lacks in the practicality of implementation due to technological limitations, communication overhead, non-IID (independent and identically distributed) data, and privacy concerns. Training a ML model over heterogeneous non-IID data highly degrades the convergence rate and performance. The existing traditional and clustered FL algorithms exhibit two main limitations, including inefficient client training and static hyperparameter utilization. To overcome these limitations, we propose a novel hybrid algorithm, namely, genetic clustered FL (Genetic CFL), that clusters edge devices based on the training hyperparameters and genetically modifies the parameters clusterwise. Then, we introduce an algorithm that drastically increases the in idual cluster accuracy by integrating the density-based clustering and genetic hyperparameter optimization. The results are bench-marked using MNIST handwritten digit dataset and the CIFAR-10 dataset. The proposed genetic CFL shows significant improvements and works well with realistic cases of non-IID and ambiguous data. An accuracy of 99.79% is observed in the MNIST dataset and 76.88% in CIFAR-10 dataset with only 10 training rounds.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2023
Publisher: Springer International Publishing
Date: 11-08-2016
Publisher: Wiley
Date: 11-01-2022
Abstract: Controlled polymerizations have enabled the production of nanostructured materials with different shapes, each exhibiting distinct properties. Despite the importance of shape, current morphological transformation strategies are limited in polymer scope, alter the chemical structure, require high temperatures, and are fairly tedious. Herein we present a rapid and versatile morphological transformation strategy that operates at room temperature and does not impair the chemical structure of the constituent polymers. By simply adding a molecular transformer to an aqueous dispersion of polymeric nanoparticles, a rapid evolution to the next higher-order morphology was observed, yielding a range of morphologies from a single starting material. Significantly, this approach can be applied to nanoparticles produced by disparate block copolymers obtained by various synthetic techniques including emulsion polymerization, polymerization-induced self-assembly and traditional solution self-assembly.
Publisher: Springer International Publishing
Date: 2019
Publisher: MDPI AG
Date: 18-02-2023
DOI: 10.3390/ELECTRONICS12041020
Abstract: The emergence of Explainable Artificial Intelligence (XAI) has enhanced the lives of humans and envisioned the concept of smart cities using informed actions, enhanced user interpretations and explanations, and firm decision-making processes. The XAI systems can unbox the potential of black-box AI models and describe them explicitly. The study comprehensively surveys the current and future developments in XAI technologies for smart cities. It also highlights the societal, industrial, and technological trends that initiate the drive towards XAI for smart cities. It presents the key to enabling XAI technologies for smart cities in detail. The paper also discusses the concept of XAI for smart cities, various XAI technology use cases, challenges, applications, possible alternative solutions, and current and future research enhancements. Research projects and activities, including standardization efforts toward developing XAI for smart cities, are outlined in detail. The lessons learned from state-of-the-art research are summarized, and various technical challenges are discussed to shed new light on future research possibilities. The presented study on XAI for smart cities is a first-of-its-kind, rigorous, and detailed study to assist future researchers in implementing XAI-driven systems, architectures, and applications for smart cities.
Publisher: Springer International Publishing
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 04-2022
Publisher: American Chemical Society (ACS)
Date: 13-11-2019
DOI: 10.1021/ACSMACROLETT.9B00855
Abstract: Photo-ATRP has recently emerged as a powerful technique that allows for oxygen-tolerant polymerizations and the preparation of polymers with low dispersity and high end-group fidelity. However, the effect of various photo-ATRP components on oxygen consumption and polymerization remains elusive. Herein, we employ an in situ oxygen probe and UV-vis spectroscopy to elucidate the effects of ligand, initiator, monomer, and solvent on oxygen consumption. We found that the choice of photo-ATRP components significantly impacts the rate at which the oxygen is consumed and can subsequently affect both the polymerization time and the dispersity of the resulting polymer. Importantly, we discovered that using the inexpensive ligand TREN results in the fastest oxygen consumption and shortest polymerization time, even though no appreciable reduction of CuBr
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Publisher: Springer International Publishing
Date: 15-12-2020
Publisher: Cambridge University Press
Date: 21-11-1985
Publisher: Elsevier BV
Date: 02-2015
Publisher: Springer International Publishing
Date: 15-12-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: Springer International Publishing
Date: 15-12-2020
Publisher: Elsevier BV
Date: 05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Elsevier BV
Date: 06-2020
Publisher: IEEE
Date: 07-2010
DOI: 10.1109/CTC.2010.8
Publisher: Association for Computing Machinery (ACM)
Date: 14-03-2022
DOI: 10.1145/3491217
Abstract: Multi-access edge computing (MEC) and ultra-dense networking (UDN) are recognized as two promising paradigms for future mobile networks that can be utilized to improve the spectrum efficiency and the quality of computational experience (QoCE) . In this paper, we study the task offloading problem in an MEC-enabled UDN architecture with the aim to minimize the task duration while satisfying the energy budget constraints. Due to the dynamics associated with the environment and parameter uncertainty, designing an optimal task offloading algorithm is highly challenging. Consequently, we propose an online task offloading algorithm based on a state-of-the-art deep reinforcement learning (DRL) technique: asynchronous advantage actor-critic (A3C) . It is worthy of remark that the proposed method requires neither instantaneous channel state information (CSI) nor prior knowledge of the computational capabilities of the base stations. Simulations show that the our method is able to learn a good offloading policy to obtain a near-optimal task allocation while meeting energy budget constraints of mobile devices in the UDN environment.
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C9SC03546J
Abstract: This review explores the different synthetic methods by which dispersity and MWD shape can be tuned and discusses the different properties and applications where this variation is beneficial.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Wiley
Date: 07-08-2019
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: MDPI AG
Date: 30-04-2020
DOI: 10.3390/S20092559
Abstract: The pursuit to spot abnormal behaviors in and out of a network system is what led to a system known as intrusion detection systems for soft computing besides many researchers have applied machine learning around this area. Obviously, a single classifier alone in the classifications seems impossible to control network intruders. This limitation is what led us to perform dimensionality reduction by means of correlation-based feature selection approach (CFS approach) in addition to a refined ensemble model. The paper aims to improve the Intrusion Detection System (IDS) by proposing a CFS + Ensemble Classifiers (Bagging and Adaboost) which has high accuracy, high packet detection rate, and low false alarm rate. Machine Learning Ensemble Models with base classifiers (J48, Random Forest, and Reptree) were built. Binary classification, as well as Multiclass classification for KDD99 and NSLKDD datasets, was done while all the attacks were named as an anomaly and normal traffic. Class labels consisted of five major attacks, namely Denial of Service (DoS), Probe, User-to-Root (U2R), Root to Local attacks (R2L), and Normal class attacks. Results from the experiment showed that our proposed model produces 0 false alarm rate (FAR) and 99.90% detection rate (DR) for the KDD99 dataset, and 0.5% FAR and 98.60% DR for NSLKDD dataset when working with 6 and 13 selected features.
Publisher: Elsevier BV
Date: 09-2020
Publisher: Unpublished
Date: 2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 04-2020
Publisher: Palgrave Macmillan
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: MDPI AG
Date: 27-04-2022
DOI: 10.3390/BDCC6020047
Abstract: Smart grids (SG) are electricity grids that communicate with each other, provide reliable information, and enable administrators to operate energy supplies across the country, ensuring optimized reliability and efficiency. The smart grid contains sensors that measure and transmit data to adjust the flow of electricity automatically based on supply/demand, and thus, responding to problems becomes quicker and easier. This also plays a crucial role in controlling carbon emissions, by avoiding energy losses during peak load hours and ensuring optimal energy management. The scope of big data analytics in smart grids is huge, as they collect information from raw data and derive intelligent information from the same. However, these benefits of the smart grid are dependent on the active and voluntary participation of the consumers in real-time. Consumers need to be motivated and conscious to avail themselves of the achievable benefits. Incentivizing the appropriate actor is an absolute necessity to encourage prosumers to generate renewable energy sources (RES) and motivate industries to establish plants that support sustainable and green-energy-based processes or products. The current study emphasizes similar aspects and presents a comprehensive survey of the start-of-the-art contributions pertinent to incentive mechanisms in smart grids, which can be used in smart grids to optimize the power distribution during peak times and also reduce carbon emissions. The various technologies, such as game theory, blockchain, and artificial intelligence, used in implementing incentive mechanisms in smart grids are discussed, followed by different incentive projects being implemented across the globe. The lessons learnt, challenges faced in such implementations, and open issues such as data quality, privacy, security, and pricing related to incentive mechanisms in SG are identified to guide the future scope of research in this sector.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: MDPI AG
Date: 11-02-2022
DOI: 10.3390/S22041377
Abstract: Recent technological developments, such as the Internet of Things (IoT), artificial intelligence, edge, and cloud computing, have paved the way in transforming traditional healthcare systems into smart healthcare (SHC) systems. SHC escalates healthcare management with increased efficiency, convenience, and personalization, via use of wearable devices and connectivity, to access information with rapid responses. Wearable devices are equipped with multiple sensors to identify a person’s movements. The unlabeled data acquired from these sensors are directly trained in the cloud servers, which require vast memory and high computational costs. To overcome this limitation in SHC, we propose a federated learning-based person movement identification (FL-PMI). The deep reinforcement learning (DRL) framework is leveraged in FL-PMI for auto-labeling the unlabeled data. The data are then trained using federated learning (FL), in which the edge servers allow the parameters alone to pass on the cloud, rather than passing vast amounts of sensor data. Finally, the bidirectional long short-term memory (BiLSTM) in FL-PMI classifies the data for various processes associated with the SHC. The simulation results proved the efficiency of FL-PMI, with 99.67% accuracy scores, minimized memory usage and computational costs, and reduced transmission data by 36.73%.
Publisher: IEEE
Date: 10-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: IEEE
Date: 11-2020
DOI: 10.1109/ITHINGS-GREENCOM-CPSCOM-SMARTDATA-CYBERMATICS50389.2020.00012
Publisher: Elsevier BV
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Association for Computing Machinery (ACM)
Date: 09-06-2021
DOI: 10.1145/3425707
Abstract: The advancements in the internet of things (IoT) require specialized security protocols to provide unbreakable security along with computation and communication efficiencies. Moreover, user privacy and anonymity has emerged as an integral part, along with other security requirements. Unfortunately, many recent authentication schemes to secure IoT-based systems were either proved as vulnerable to different attacks or prey of inefficiencies. Some of these schemes suffer from a faulty design that happened mainly owing to undue emphasis on privacy and anonymity alongside performance efficiency. This article aims to show the design faults by analyzing a very recent hash functions-based authentication scheme for cloud-based IoT systems with misunderstood privacy cum efficiency tradeoff owing to an unadorned design flaw, which is also present in many other such schemes. Precisely, it is proved in this article that the scheme of Wazid et al. cannot provide mutual authentication and key agreement between a user and a sensor node when there exists more than one registered user. We then proposed an improved scheme and proved its security through formal and informal methods. The proposed scheme completes the authentication cycle with a minor increase in computation cost but provides all security goals along with privacy.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-02-2023
Publisher: Elsevier BV
Date: 03-2021
Publisher: Springer International Publishing
Date: 2019
Publisher: Springer International Publishing
Date: 2019
Publisher: Emerald
Date: 10-11-2014
DOI: 10.1108/IMCS-02-2013-0007
Abstract: – The purpose of this paper is to mitigate vulnerabilities in web applications, security detection and prevention are the most important mechanisms for security. However, most existing research focuses on how to prevent an attack at the web application layer, with less work dedicated to setting up a response action if a possible attack happened. – A combination of a Signature-based Intrusion Detection System (SIDS) and an Anomaly-based Intrusion Detection System (AIDS), namely, the Intelligent Intrusion Detection and Prevention System (IIDPS). – After evaluating the new system, a better result was generated in line with detection efficiency and the false alarm rate. This demonstrates the value of direct response action in an intrusion detection system. – Data limitation. – The contributions of this paper are to first address the problem of web application vulnerabilities. Second, to propose a combination of an SIDS and an AIDS, namely, the IIDPS. Third, this paper presents a novel approach by connecting the IIDPS with a response action using fuzzy logic. Fourth, use the risk assessment to determine an appropriate response action against each attack event. Combining the system provides a better performance for the Intrusion Detection System, and makes the detection and prevention more effective.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: IEEE
Date: 07-2020
Publisher: Elsevier BV
Date: 11-2020
Publisher: IEEE
Date: 08-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Royal Society of Chemistry (RSC)
Date: 2022
DOI: 10.1039/D1PY01331A
Abstract: A general model is developed for the distribution of polymers made with reversible deactivation. The model is applied to a range of experimental systems including RAFT, cationic and ATRP.
Publisher: IEEE
Date: 08-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Hindawi Limited
Date: 02-12-2018
DOI: 10.1155/2018/1728303
Abstract: With the explosion of Internet of Things (IoT) worldwide, there is an increasing threat from malicious software (malware) attackers that calls for efficient monitoring of vulnerable systems. Large amounts of data collected from computer networks, servers, and mobile devices need to be analysed for malware proliferation. Effective analysis methods are needed to match with the scale and complexity of such a data-intensive environment. In today’s Big Data contexts, visualisation techniques can support malware analysts going through the time-consuming process of analysing suspicious activities thoroughly. This paper takes a step further in contributing to the evolving realm of visualisation techniques used in the information security field. The aim of the paper is twofold: ( 1 ) to provide a comprehensive overview of the existing visualisation techniques for detecting suspicious behaviour of systems and ( 2 ) to design a novel visualisation using similarity matrix method for establishing malware classification accurately. The prime motivation of our proposal is to identify obfuscated malware using visualisation of the extended x86 IA-32 (opcode) similarity patterns, which are hard to detect with the existing approaches. Our approach uses hybrid models wherein static and dynamic malware analysis techniques are combined effectively along with visualisation of similarity matrices in order to detect and classify zero-day malware efficiently. Overall, the high accuracy of classification achieved with our proposed method can be visually observed since different malware families exhibit significantly dissimilar behaviour patterns.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 07-2020
Publisher: No publisher found
Date: 2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: IEEE
Date: 05-2019
Publisher: Springer Science and Business Media LLC
Date: 06-2009
Publisher: Wiley
Date: 29-10-2019
DOI: 10.1002/DAC.4228
Publisher: IEEE
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2021
Publisher: Inderscience Publishers
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: Elsevier BV
Date: 12-2020
Publisher: Royal Society of Chemistry (RSC)
Date: 2012
DOI: 10.1039/C1CC12869H
Abstract: More usually thought of as a base, the sodium zincate [(TMEDA)·Na(μ-TMP)(μ-(t)Bu)Zn((t)Bu)] 1 can undergo single electron transfer with TEMPO to give [(TMEDA)·Na(μ-TMP)(μ-TEMPO(-))Zn((t)Bu)] 2 and [(TMEDA)·Na(μ-TEMPO(-))(2)Zn((t)Bu)] 3 and with chalcone [PhCOCH=CHPh] gives [{(TMEDA)·Na(μ-TMP)Zn((t)Bu)}(2)(μ-OCPhCH=CHPhCHPhCH=CPh-μ-O)] which contains two chalcone units C-C coupled though their benzylic C atoms.
Publisher: Elsevier BV
Date: 09-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Publisher: IEEE
Date: 12-2016
Publisher: American Chemical Society (ACS)
Date: 22-03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 06-2021
Publisher: IEEE
Date: 11-2015
DOI: 10.1109/CTC.2014.11
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-08-2022
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C9CC03825F
Abstract: While lithium alkyls and lithium amides do not metallate the scandium compound [(η 5 -C 5 H 5 )Sc(η 8 -C 8 H 8 )], a synergistic lithium–aluminium base-trap partnership cannot resist taking a bite with one C–H bond selectively cleaved from both Cp and COT rings.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 2015
DOI: 10.2139/SSRN.2594624
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Wiley
Date: 04-09-2023
Publisher: American Chemical Society (ACS)
Date: 10-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: IEEE
Date: 11-2013
DOI: 10.1109/CTC.2013.16
Publisher: Elsevier BV
Date: 07-2022
Publisher: Wiley
Date: 10-01-2022
Abstract: Controlled polymerizations have enabled the production of nanostructured materials with different shapes, each exhibiting distinct properties. Despite the importance of shape, current morphological transformation strategies are limited in polymer scope, alter the chemical structure, require high temperatures, and are fairly tedious. Herein we present a rapid and versatile morphological transformation strategy that operates at room temperature and does not impair the chemical structure of the constituent polymers. By simply adding a molecular transformer to an aqueous dispersion of polymeric nanoparticles, a rapid evolution to the next higher‐order morphology was observed, yielding a range of morphologies from a single starting material. Significantly, this approach can be applied to nanoparticles produced by disparate block copolymers obtained by various synthetic techniques including emulsion polymerization, polymerization‐induced self‐assembly and traditional solution self‐assembly.
Publisher: Elsevier BV
Date: 08-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: MDPI AG
Date: 05-02-2020
DOI: 10.3390/ELECTRONICS9020274
Abstract: Diabetic Retinopathy is a major cause of vision loss and blindness affecting millions of people across the globe. Although there are established screening methods - fluorescein angiography and optical coherence tomography for detection of the disease but in majority of the cases, the patients remain ignorant and fail to undertake such tests at an appropriate time. The early detection of the disease plays an extremely important role in preventing vision loss which is the consequence of diabetes mellitus remaining untreated among patients for a prolonged time period. Various machine learning and deep learning approaches have been implemented on diabetic retinopathy dataset for classification and prediction of the disease but majority of them have neglected the aspect of data pre-processing and dimensionality reduction, leading to biased results. The dataset used in the present study is a diabetes retinopathy dataset collected from the UCI machine learning repository. At its inceptions, the raw dataset is normalized using the Standardscalar technique and then Principal Component Analysis (PCA) is used to extract the most significant features in the dataset. Further, Firefly algorithm is implemented for dimensionality reduction. This reduced dataset is fed into a Deep Neural Network Model for classification. The results generated from the model is evaluated against the prevalent machine learning models and the results justify the superiority of the proposed model in terms of Accuracy, Precision, Recall, Sensitivity and Specificity.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Elsevier BV
Date: 02-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: American Chemical Society (ACS)
Date: 05-2023
DOI: 10.1021/JACS.3C00589
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2021
Publisher: IOP Publishing
Date: 02-2021
DOI: 10.1088/1742-6596/1798/1/011001
Abstract: It is highly delighted to introduce the proceedings dedicated to the 2020 International Conference on Applied Mechanics and Mechanical Engineering (ICAMME 2020), which was successfully held on Sep. 25-27, 2020 in Hulun Buir, China, and hosted by AEIC Academic Exchange Information Centre. ICAMME 2020 is to bring together innovative academics and industrial experts in the field of applied mechanics, mechanical engineering, electrical and automation engineering to a common forum. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. An ideal platform for seeking global partners had been established. About 60 participants from academic, high-education institutes and other organizations took part in the Conference. The conference model was ided into two sessions, including oral presentations and keynote speeches. In the first part, some scholars, whose submissions were selected as the excellent papers, were given 15 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. We were very honored to have Prof. Simon X. Yang from University of Guelph, Canada and Prof. Wei Min Huang from Nanyang Technological University, Singapore as our Chairman. In the keynote presentation part, we invited three professors as our keynote speakers. The first keynote speaker, Prof. Simon X. Yang, our beloved Chairman, shared a speech: Bioinspired Intelligent Approaches to Various Mechatronic Systems. In this talk, he started with a very brief introduction to biologically inspired computation and learning, and some bio-inspired computational techniques. After that, he presented several practical applications in engineering systems. The second keynote speaker, Prof. Wei Min Huang from Nanyang Technological University, Singapore. He delivered a speech: Morphing Via Shape Memory Materials and Technology. In this talk, he presented a brief introduction of various shape memory phenomena firstly. After that, he showed a range of morphing applications in aero/space missions, biomedical devices etc. utilizing shape memory alloy and shape memory polymer. Our finale keynote speaker, Prof. Junxi Bi, from Inner Mongolia University of Technology, China shared a speech on Reliability Analysis and Optimization of Key Parts of Low Pressure Cantilever Casting Machine. The proceedings present a selection of high-quality papers submitted to the conference by researchers from universities, research institutes, and industry. All papers were subjected to peer-review by conference committee members and international reviewers. The papers were selected based on their quality and their relevance to the conference. The proceedings present recent advances in the fields of Applied Mechanics and Engineering Mechanics, Mechanical Engineering, Materials Science, Electrical and Automation Engineering and Other related research. I would like to express special gratitude to members of the conference committee and organizers of the conference. I would also like to thank the reviewers for their valuable time and advice which helped in improving the quality of the papers selected for presentation at the conference and for publication in the proceedings. Finally, I want to thank the authors, the members of the organizing committee, the reviewers, the chairpersons, sponsors, and all other conference participants for their support of ICAMME 2020. The Organizing Committee of ICAMME 2020 List of Committee member is available in this pdf.
Publisher: Wiley
Date: 11-08-2022
Abstract: A series of group 1 hydrocarbon-soluble donor free aluminates [AM(
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-01-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2021
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 06-2020
Publisher: American Chemical Society (ACS)
Date: 12-02-2020
DOI: 10.26434/CHEMRXIV.11836137.V1
Abstract: Dispersity ( Ɖ ) can significantly affect polymer properties and is a key parameter in materials design however, current methods do not allow for the comprehensive control of dispersity. They are limited in monomer scope, may require the use of flow-based systems and/or additional reagents ( e.g. termination agents or co-monomers), and are often accompanied by multimodal molecular weight distributions, low initiator efficiencies or poor end-group fidelity. Herein, we report a straightforward and versatile batch method based on reversible addition-fragmentation chain transfer (RAFT) polymerization which enables good control over Ɖ of a wide range of monomer classes, including acrylates, acrylamides, methacrylates and styrene. In addition, our methodology is compatible with more challenging monomers such as methacrylic acid, vinyl ketone and vinyl acetate. Control over Ɖ is achieved by mixing two RAFT agents with sufficiently different transfer activities in various ratios, affording polymers with monomodal molecular weight distributions over a broad dispersity range ( Ɖ ~ 1.09-2.10). Our findings were further supported by simulations through the use of deterministic kinetic modelling which was fully in line with our experimental data, further confirming the power of our methodology. The robustness of the concept is further demonstrated by the preparation of well-defined block copolymers via chain extension of all polymers regardless of the initial Ɖ .
Publisher: Elsevier BV
Date: 06-2020
Publisher: ACM
Date: 25-09-2020
Publisher: American Chemical Society (ACS)
Date: 12-02-2020
DOI: 10.26434/CHEMRXIV.11836137
Abstract: Dispersity ( i Ɖ /i ) can significantly affect polymer properties and is a key parameter in materials design however, current methods do not allow for the comprehensive control of dispersity. They are limited in monomer scope, may require the use of flow-based systems and/or additional reagents ( i e.g. /i termination agents or co-monomers), and are often accompanied by multimodal molecular weight distributions, low initiator efficiencies or poor end-group fidelity. Herein, we report a straightforward and versatile batch method based on reversible addition-fragmentation chain transfer (RAFT) polymerization which enables good control over i Ɖ /i of a wide range of monomer classes, including acrylates, acrylamides, methacrylates and styrene. In addition, our methodology is compatible with more challenging monomers such as methacrylic acid, vinyl ketone and vinyl acetate. Control over i Ɖ /i is achieved by mixing two RAFT agents with sufficiently different transfer activities in various ratios, affording polymers with monomodal molecular weight distributions over a broad dispersity range ( i Ɖ /i ~ 1.09-2.10). Our findings were further supported by simulations through the use of deterministic kinetic modelling which was fully in line with our experimental data, further confirming the power of our methodology. The robustness of the concept is further demonstrated by the preparation of well-defined block copolymers via chain extension of all polymers regardless of the initial i Ɖ /i .
Publisher: Wiley
Date: 13-06-2018
Publisher: ACM
Date: 25-09-2020
Publisher: Springer Science and Business Media LLC
Date: 04-2021
DOI: 10.1038/S41561-021-00714-3
Abstract: Global climate is thought to be modulated by the supply of minerals to Earth’s surface. Whereas silicate weathering removes carbon dioxide (CO 2 ) from the atmosphere, weathering of accessory carbonate and sulfide minerals is a geologically relevant source of CO 2 . Although these weathering pathways commonly operate side by side, we lack quantitative constraints on their co-variation across erosion rate gradients. Here we use stream-water chemistry across an erosion rate gradient of three orders of magnitude in shales and sandstones of southern Taiwan, and find that sulfide and carbonate weathering rates rise with increasing erosion, while silicate weathering rates remain steady. As a result, on timescales shorter than marine sulfide compensation (approximately 10 6 –10 7 years), weathering in rapidly eroding terrain leads to net CO 2 emission rates that are at least twice as fast as CO 2 sequestration rates in slow-eroding terrain. We propose that these weathering reactions are linked and that sulfuric acid generated from sulfide oxidation boosts carbonate solubility, whereas silicate weathering kinetics remain unaffected, possibly due to efficient buffering of the pH. We expect that these patterns are broadly applicable to many Cenozoic mountain ranges that expose marine metasediments.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-1970
Publisher: IEEE
Date: 11-2010
Publisher: Wiley
Date: 06-09-2023
DOI: 10.1002/POL.20230479
Publisher: Royal Society of Chemistry (RSC)
Date: 2023
DOI: 10.1039/D2PY01563C
Abstract: In the vast majority of atom transfer radical polymerizations, alkyl bromides or alkyl chlorides are commonly employed as initiators. Herein, alkyl iodides are demonstrated as ATRP initiators.
Publisher: IGI Global
Date: 2014
DOI: 10.4018/978-1-4666-4719-0.CH006
Abstract: Improving the efficiency, effectiveness, and quality of public services has become a growing concern for many governments across the world, and more so with recent popularity of online services, widely referred as e-government services. The application of quality approaches for measuring and improving e-government services has been the subject of much research within the academic world over the last two decades. This chapter discusses the use of key quality approaches to improve services in Jordan's e-government initiatives. As more and more developing countries are adopting e-services as a means of providing quality services to their community and people through the Web, the necessary benchmarking plays an important role. Many traditional quality benchmarking performance measurements have proved futile in improving e-government services due to their quantitative focus. Though qualitative frameworks and measurement approaches such as Six Sigma and Balanced Scorecard have found their success in certain industry sectors, their relevance in the service sector has drawn attention only recently. While some studies have employed such approaches for evaluating projects in information and communication technologies, literature lacks investigations in the e-government sector. To fill this gap, this chapter investigates the application of Six Sigma and Balanced Scorecard approaches to improve quality in Jordanian e-government services.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Publisher: Royal Society of Chemistry (RSC)
Date: 2020
DOI: 10.1039/D0PY00823K
Abstract: Here we report a simple and versatile batch methodology to tailor polymer dispersity utilizing PET-RAFT polymerization.
Publisher: Wiley
Date: 20-09-2018
Abstract: A series of dialkylphenylphosphines and their analogous aniline substrates have been metallated with the synergistic mixed-metal base [(TMEDA)Na(TMP)(CH
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: MDPI AG
Date: 10-04-2020
DOI: 10.3390/ELECTRONICS9040629
Abstract: Internet of Things (IoT) forms the foundation of next generation infrastructures, enabling development of future cities that are inherently sustainable. Intrusion detection for such paradigms is a non-trivial challenge which has attracted further significance due to extraordinary growth in the volume and variety of security threats for such systems. However, due to unique characteristics of such systems i.e., battery power, bandwidth and processor overheads and network dynamics, intrusion detection for IoT is a challenge, which requires taking into account the trade-off between detection accuracy and performance overheads. In this context, we are focused at highlighting this trade-off and its significance to achieve effective intrusion detection for IoT. Specifically, this paper presents a comprehensive study of existing intrusion detection systems for IoT systems in three aspects: computational overhead, energy consumption and privacy implications. Through extensive study of existing intrusion detection approaches, we have identified open challenges to achieve effective intrusion detection for IoT infrastructures. These include resource constraints, attack complexity, experimentation rigor and unavailability of relevant security data. Further, this paper is envisaged to highlight contributions and limitations of the state-of-the-art within intrusion detection for IoT, and aid the research community to advance it by identifying significant research directions.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 2013
DOI: 10.2139/SSRN.2345525
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Inderscience Publishers
Date: 2012
Publisher: Springer Science and Business Media LLC
Date: 30-10-2020
Publisher: IEEE
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: IEEE
Date: 05-2019
Publisher: Association for Computing Machinery (ACM)
Date: 14-11-2022
DOI: 10.1145/3412353
Abstract: The Intelligent Transportation System (ITS) is said to revolutionize the travel experience by making it safe, secure, and comfortable for the people. Although vehicles have been automated up to a certain extent, it still has critical security issues that require thorough study and advanced solutions. The security vulnerabilities of ITS allows the attacker to steal the vehicle. Therefore, the identification of drivers is required in order to develop a safe and secure system so that the vehicles can be protected from theft. There are two ways in which a driver can be identified: 1) face recognition of the driver, and 2) based on driving behavior. Face recognition includes image processing of 2-D images and learning of the features, which require high computational power. Drivers are known to have unique driving styles, whose data can be captured by the sensors. Therefore, the second method identifies drivers based on the analysis of the sensor data and it requires comparatively lesser computational power. In this paper, an optimized deep learning model is trained on the sensor data to correctly identify the drivers. The Long Short-Term Memory (LSTM) deep learning model is optimized for better performance. The novelty of the approach in this work is the inclusion of hyperparameter tuning using a nature-inspired optimization algorithm, which is an important and essential step in discovering the optimal hyperparameters for training the model which in turn increases the accuracy. The CAN-BUS dataset is used for experimentation and evaluation of the training model. Evaluation parameters such as accuracy, precision score, F1 score, and ROC AUC curve are considered to evaluate the performance of the model.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2020
Publisher: SAGE Publications
Date: 27-03-2017
Abstract: The optimal provision of thermal comfort and energy efficiency for residential housing in the hot and humid tropics presents challenges and opportunities for housing and sub ision designs. Climatic challenges come in the form of high ambient temperature and humidity, especially during the wet season and transition periods. On the other hand, climatic advantages come in the form of breezes coupled with relatively dry air during the dry season, enabling thermal comfort attainment through natural ventilation that employs prevailing breezes. This paper discusses existing design practices for housing and sub isions in the hot and humid tropics with particular reference to the city of Darwin in Australia’s Northern Territory. This includes several research issues and gaps that have been identified and need to be addressed. The paper also critically assesses how air speed, air temperature and humidity – three of the thermal comfort parameters – play a key role in housing and sub ision design consideration in the hot and humid tropics. In doing so, the paper sheds light on the inadequacy of the current residential energy rating methodology as a tool for assessing tropical housing performance and proposes a new direction for future research to ameliorate these issues for the tropics.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-08-2021
Publisher: IEEE
Date: 12-2020
Publisher: American Chemical Society (ACS)
Date: 22-06-2022
Publisher: IGI Global
Date: 2013
DOI: 10.4018/978-1-4666-2083-4.CH011
Abstract: Detecting malicious software or malware is one of the major concerns in information security governance as malware authors pose a major challenge to digital forensics by using a variety of highly sophisticated stealth techniques to hide malicious code in computing systems, including smartphones. The current detection techniques are futile, as forensic analysis of infected devices is unable to identify all the hidden malware, thereby resulting in zero day attacks. This chapter takes a key step forward to address this issue and lays foundation for deeper investigations in digital forensics. The goal of this chapter is, firstly, to unearth the recent obfuscation strategies employed to hide malware. Secondly, this chapter proposes innovative techniques that are implemented as a fully-automated tool, and experimentally tested to exhaustively detect hidden malware that leverage on system vulnerabilities. Based on these research investigations, the chapter also arrives at an information security governance plan that would aid in addressing the current and future cybercrime situations.
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 02-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: IEEE
Date: 05-2019
Publisher: IEEE
Date: 11-2013
DOI: 10.1109/CTC.2013.11
Publisher: Inderscience Publishers
Date: 2018
Publisher: IEEE
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: MDPI AG
Date: 11-06-2019
DOI: 10.3390/APP9112375
Abstract: In recent years, the botnets have been the most common threats to network security since it exploits multiple malicious codes like a worm, Trojans, Rootkit, etc. The botnets have been used to carry phishing links, to perform attacks and provide malicious services on the internet. It is challenging to identify Peer-to-peer (P2P) botnets as compared to Internet Relay Chat (IRC), Hypertext Transfer Protocol (HTTP) and other types of botnets because P2P traffic has typical features of the centralization and distribution. To resolve the issues of P2P botnet identification, we propose an effective multi-layer traffic classification method by applying machine learning classifiers on features of network traffic. Our work presents a framework based on decision trees which effectively detects P2P botnets. A decision tree algorithm is applied for feature selection to extract the most relevant features and ignore the irrelevant features. At the first layer, we filter non-P2P packets to reduce the amount of network traffic through well-known ports, Domain Name System (DNS). query, and flow counting. The second layer further characterized the captured network traffic into non-P2P and P2P. At the third layer of our model, we reduced the features which may marginally affect the classification. At the final layer, we successfully detected P2P botnets using decision tree Classifier by extracting network communication features. Furthermore, our experimental evaluations show the significance of the proposed method in P2P botnets detection and demonstrate an average accuracy of 98.7%.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Elsevier BV
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
Publisher: Springer International Publishing
Date: 2018
Publisher: Hindawi Limited
Date: 29-05-2021
DOI: 10.1002/INT.22489
Publisher: MDPI AG
Date: 29-10-2019
DOI: 10.3390/ELECTRONICS8111235
Abstract: Electronic Health Records (EHR) are a rich repository of valuable clinical information that exist in primary and secondary care databases. In order to utilize EHRs for medical observational research a range of algorithms for automatically identifying in iduals with a specific phenotype have been developed. This review summarizes and offers a critical evaluation of the literature relating to studies conducted into the development of EHR phenotyping systems. This review describes phenotyping systems and techniques based on structured and unstructured EHR data. Articles published on PubMed and Google scholar between 2013 and 2017 have been reviewed, using search terms derived from Medical Subject Headings (MeSH). The popularity of using Natural Language Processing (NLP) techniques in extracting features from narrative text has increased. This increased attention is due to the availability of open source NLP algorithms, combined with accuracy improvement. In this review, Concept extraction is the most popular NLP technique since it has been used by more than 50% of the reviewed papers to extract features from EHR. High-throughput phenotyping systems using unsupervised machine learning techniques have gained more popularity due to their ability to efficiently and automatically extract a phenotype with minimal human effort.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 04-2020
Publisher: IGI Global
DOI: 10.4018/978-1-4666-9461-3.CH070
Abstract: Improving the efficiency, effectiveness, and quality of public services has become a growing concern for many governments across the world, and more so with recent popularity of online services, widely referred as e-government services. The application of quality approaches for measuring and improving e-government services has been the subject of much research within the academic world over the last two decades. This chapter discusses the use of key quality approaches to improve services in Jordan's e-government initiatives. As more and more developing countries are adopting e-services as a means of providing quality services to their community and people through the Web, the necessary benchmarking plays an important role. Many traditional quality benchmarking performance measurements have proved futile in improving e-government services due to their quantitative focus. Though qualitative frameworks and measurement approaches such as Six Sigma and Balanced Scorecard have found their success in certain industry sectors, their relevance in the service sector has drawn attention only recently. While some studies have employed such approaches for evaluating projects in information and communication technologies, literature lacks investigations in the e-government sector. To fill this gap, this chapter investigates the application of Six Sigma and Balanced Scorecard approaches to improve quality in Jordanian e-government services.
Publisher: IEEE
Date: 10-2012
DOI: 10.1109/CTC.2012.15
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D1PY01044A
Abstract: Herein we present a simple batch method to control polymer dispersity using a mixture of two ATRP initiators with different reactivities.
Publisher: IEEE
Date: 08-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.3042174
Publisher: Royal Society of Chemistry (RSC)
Date: 2022
DOI: 10.1039/D1CC05379E
Abstract: Rubidium and caesium aluminyls [M{Al(NON Dipp )}] 2 have been synthesised but only the caesium compound can oxidatively cleave an aromatic C–H bond of benzene.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Elsevier BV
Date: 11-2020
Publisher: World Scientific Pub Co Pte Lt
Date: 2021
DOI: 10.1142/S021962202050042X
Abstract: Ranking the strengths and weaknesses of software engineering students in software development life cycle (SDLC) process level is a challenging task owing to (1) data variation, (2) multievaluation criteria, (3) criterion importance and (4) alternative member importance. According to the existing literature, no specified procedure can rank the ability of software engineering students based on SDLC process levels to figure out the strengths and weaknesses of each student. This study aims to present a novel triplex procedure for ranking the ability of software engineering students to address the literature gap. The methodology of the proposed work is presented on the basis of three phases. In the identification phase, four steps are implemented, namely, processing dataset, identifying the criteria, distributing the courses to the software engineering body of knowledge and proposing the pre-decision matrix (DM). The data comprise the GPA and soft skills from 60 software engineering students who graduated from Universiti Pendidikan Sultan Idris in 2016. In the pre-processing phase, three steps are involved as follows. Analytic hierarchy process (AHP) is first used to assign weights to the courses and then multiply the assigned weight by courses, which is the first procedure in the proposed work. In this phase, the construction of DM is presented based on multimeasurement criteria (GPA and soft skills), with SDLC process levels as alternatives. In the development phase, AHP is used again to weight the multimeasurement criteria, and this is the second procedure. In such case, the coordinator and head of the software engineering department are consulted to obtain subjective judgments for each criterion. Technique for order performance by similarity to ideal solution (TOPSIS) is then used to rank the students, which is the third procedure. In the validation, statistical analysis is performed to validate the results by checking the accuracy of the systematic ranking. Results show that (1) integrating AHP and group TOPSIS is suitable for ranking the ability of students. (2) The 60 students are categorized into five ranking groups based on their strength level: 14 collector requirements, 13 designers, 5 programmers, 13 testers and 15 maintenances. (3) Significant differences are observed between the groups’ scores for each level of SDLC, indicating that the ranking results are identical for all levels.
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.2984101
Publisher: MDPI AG
Date: 08-08-2023
DOI: 10.3390/ELECTRONICS12163382
Abstract: Detecting anomalies, intrusions, and security threats in the network (including Internet of Things) traffic necessitates the processing of large volumes of sensitive data, which raises concerns about privacy and security. Federated learning, a distributed machine learning approach, enables multiple parties to collaboratively train a shared model while preserving data decentralization and privacy. In a federated learning environment, instead of training and evaluating the model on a single machine, each client learns a local model with the same structure but is trained on different local datasets. These local models are then communicated to an aggregation server that employs federated averaging to aggregate them and produce an optimized global model. This approach offers significant benefits for developing efficient and effective intrusion detection system (IDS) solutions. In this research, we investigated the effectiveness of federated learning for IDSs and compared it with that of traditional deep learning models. Our findings demonstrate that federated learning, by utilizing random client selection, achieved higher accuracy and lower loss compared to deep learning, particularly in scenarios emphasizing data privacy and security. Our experiments highlight the capability of federated learning to create global models without sharing sensitive data, thereby mitigating the risks associated with data breaches or leakage. The results suggest that federated averaging in federated learning has the potential to revolutionize the development of IDS solutions, thus making them more secure, efficient, and effective.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2023
Publisher: Elsevier BV
Date: 02-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: Wiley
Date: 15-12-2009
Publisher: IEEE
Date: 10-2015
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D1SC04241F
Abstract: The dispersity of polymers is efficiently controlled in aqueous atom transfer radical polymerization by modulating the reversible dissociation of the bromide ion from the copper deactivator.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2020
Publisher: American Chemical Society (ACS)
Date: 23-11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: IEEE
Date: 11-2017
DOI: 10.1109/CCC.2017.13
Publisher: IEEE
Date: 11-2017
DOI: 10.1109/CCC.2017.11
Publisher: Elsevier BV
Date: 03-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Royal Society of Chemistry (RSC)
Date: 2016
DOI: 10.1039/C5DT04224K
Abstract: Transmetallation of lithiodihydropyridines with Group 1 alkoxides provides facile access to reactive MH (M = Na, K) sources, which show significant structural ersity due in part to the distinct ways that Na/K engage with the σ (green) and π (red) donor systems of the DHP ligands.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: IGI Global
Date: 04-2012
Abstract: This paper investigates the application of the Six Sigma approach to improve quality in electronic services (e-services) as more countries are adopting e-services as a means of providing services to their people through the Web. This paper presents a case study about the use of Six Sigma model to measure customer satisfaction and quality levels achieved in e-services that were recently launched by public sector organisations in a developing country, such as Jordan. An empirical study consisting of 280 customers of Jordan’s e-services is conducted and problems are identified through the DMAIC phases of Six Sigma. The service quality levels are measured and analysed using six main criteria: Website Design, Reliability, Responsiveness, Personalization, Information Quality, and System Quality. The study indicates a 74% customer satisfaction with a Six Sigma level of 2.12 has enabled the Greater Amman Municipality to identify the usability issues associated with their e-services offered by public sector organisations. The aim of the paper is not only to implement Six Sigma as a measurement-based strategy for improving e-customer service in a newly launched e-service programme, but also widen its scope in investigating other service dimensions and perform comparative studies in other developing countries.
Publisher: American Chemical Society (ACS)
Date: 22-09-2023
DOI: 10.1021/JACS.3C05632
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2020
Publisher: IEEE
Date: 08-2016
DOI: 10.1109/CCC.2016.34
Publisher: Elsevier BV
Date: 03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2023
Publisher: Elsevier BV
Date: 07-2020
Publisher: Wiley
Date: 21-12-2016
Publisher: AICIT
Date: 31-03-2010
Publisher: Emerald
Date: 05-07-2013
Abstract: The purpose of this paper is to emphasise on a balance between quantitative and qualitative measures, and examine the use of Balanced Scorecard to evaluate and estimate the performance of information and communication technologies (ICT) in delivering valuable e‐government services through the internet. This study tests the hypotheses of e‐government effectiveness using Balanced Scorecard technique by incorporating qualitative measures within a quantitative research methodology with data collected by means of a survey questionnaire. The survey s le of 383 stakeholders includes common customers, employees of e‐government, and employees from the IT sector. The survey data were analysed to test the hypothesis in measuring e‐government effectiveness from Balanced Scorecard's four dimensions: customer perspective, financial perspective, internal business process perspective, and innovation and learning perspective. The results show that the Balanced Scorecard factors fit very well with monitoring and measuring the performance of e‐government in Jordan, and also in evaluating their success in IT project investments. This study attempts to address this gap in the literature and would benefit future studies in applying Balanced Scorecard for performance evaluation of various IT projects that are gaining huge investments from governments and organisations.
Publisher: Royal Society of Chemistry (RSC)
Date: 2023
DOI: 10.1039/D2PY01383E
Abstract: Eosin Y is used as a photocatalyst for the acceleration of the depolymerization of polymethacrylates.
Publisher: Elsevier BV
Date: 08-2017
Publisher: Springer Netherlands
Date: 2010
Publisher: Elsevier
Date: 2016
Publisher: American Chemical Society (ACS)
Date: 10-01-2023
DOI: 10.1021/JACS.2C11757
Publisher: Springer International Publishing
Date: 15-12-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Springer Science and Business Media LLC
Date: 05-09-2020
Publisher: Academy Publisher
Date: 31-12-1969
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-08-2021
Publisher: AICIT
Date: 31-12-2009
Publisher: Wiley
Date: 07-08-2019
Abstract: Dispersity significantly affects the properties of polymers. However, current methods for controlling the polymer dispersity are limited to bimodal molecular weight distributions, adulterated polymer chains, or low end-group fidelity and rely on feeding reagents, flow-based, or multicomponent systems. To overcome these limitations, we report a simple batch system whereby photoinduced atom transfer radical polymerisation is exploited as a convenient and versatile technique to control dispersity of both homopolymers and block copolymers. By varying the concentration of the copper complex, a wide range of monomodal molecular weight distributions can be obtained (Đ=1.05-1.75). In all cases, high end-group fidelity was confirmed by MALDI-ToF-MS and exemplified by efficient block copolymer formation (monomodal, Đ=1.1-1.5). Importantly, our approach utilises ppm levels of copper (as low as 4 ppm), can be tolerant to oxygen and exhibits perfect temporal control, representing a major step forward in tuning polymer dispersity for various applications.
Publisher: Hindawi Limited
Date: 05-11-2020
DOI: 10.1002/INT.22322
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Elsevier BV
Date: 05-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Elsevier BV
Date: 04-2021
Publisher: Royal Society of Chemistry (RSC)
Date: 2018
DOI: 10.1039/C7CC08214B
Abstract: Cooperativity between the Li and Al centres is implicated in catalytic hydroboration reactions of aldehydes and ketones with pinacolborane via heteroleptic lithium diamidodihydridoaluminates.
Publisher: Elsevier BV
Date: 04-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 12-06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: IEEE
Date: 11-2017
DOI: 10.1109/CCC.2017.4
Publisher: IEEE
Date: 08-2016
DOI: 10.1109/CCC.2016.10
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 10-2020
Publisher: IEEE
Date: 08-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: Association for Computing Machinery (ACM)
Date: 31-10-2020
DOI: 10.1145/3421276
Abstract: The significant growth of the Internet of Things (IoT) takes a key and active role in healthcare, smart homes, smart manufacturing, and wearable gadgets. Due to complexness and difficulty in processing multimedia data, the IoT based scheme, namely Internet of Multimedia Things (IoMT) exists that is specialized for services and applications based on multimedia data. However, IoMT generated data are facing major processing and privacy issues. Therefore, tensor-based deep computation models proved a better platform to process IoMT generated data. A differentially private deep computation method working in the tensor space can attest to its efficacy for IoMT. Nevertheless, the deep computation model comprises a multitude of parameters thus, it requires large units of memory and expensive computing units with higher performance levels, which hinders its performance for IoMT. Motivated by this, therefore, the paper proposes a deep private tensor train autoencoder (dPTTAE) technique to deal with IoMT generated data. Notably, the compression of weight tensors to manageable tensor train format is achieved through Tensor Train (TT) network. Moreover, TT format parameters are trained through higher-order back-propagation and gradient descent. We applied dPTTAE on three representative datasets. Comprehensive experimental evaluations and theoretical analysis show that dPTTAE enhances training time efficiency, and greatly improve memory utilization efficiency, attesting its potential for IoMT.
Publisher: ACM
Date: 02-12-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Hindawi Limited
Date: 04-10-2021
DOI: 10.1002/INT.22699
Publisher: IEEE
Date: 12-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Location: Greece
No related grants have been discovered for Mamoun Alazab.