RSS 1.0Computing
Recent Submissions
-
Applications of blockchain technology and related security threats: a comparative studyBlockchain is one of the emerging technology of the 21st century. It is getting familiar to the people help them by providing better financial services without any centralized medium (banks, agencies etc.). Although it has a strong backbone of cryptography that ensures data protection, security vulnerabilities are still part of this system and are continuously emerging. This chapter will explore the deep analysis of various blockchain applications, related security threats and vulnerabilities, future trends, and possible solutions that could promise the integrity of this technology.
-
Cyberstalking in India: challenges on the social side and the underlying contradictionsThe ordeal of woman victims in India has rightly been given the term - secondary victimization and its outcome in the form of deindividuation. Arguably, the positioning of a cyberstalking victim in the Indian patriarchal society only belittles her existence and leads to deindividuation. The fear of loss of reputation, poor social perception and fragility of her womanhood make her a sitting duck for any cyber stalker; and the case is the same for even a male victim. In view of the contextual realities, the present research sets itself to argue the fact that, 'conservative beliefs, lack of awareness and the patriarchal outlook seem to curtail women's sovereignty and choices; this seemingly engenders a secondary form of social punishment victims endure'. It goes on to argue why the guilt and the blameworthiness are for only the victim to endure and why the victim has to keep quiet and fall prey to negative stereotypes of the society. Most importantly, the research tries to fill the gap on existing work by finding an answer to - what can possibly prevent deindividuation and secondary victimization of Indian women based on regulation, mechanism and enforcements on the social side? The assessment would be based on an integrative contextual analysis of the contemporary realities of cyberstalking in India. A solution is sought with in the domain of behavioral studies based on - neutralization theory, sexual solicitation of the society methods of monitoring and Zero FIR for influencing the motivators of the cyber-stalkers.
-
Data protection and privacy determinants of e-government adoption in NigeriaThe global recurring news about data scandals, the sale of customer data and revealing employee records intensify concerns of citizens over protecting their privacy and personal data. This paper aims to systematically review literatures and discuss how data protection and privacy influences e-government adoption in Nigeria. Based on an extensive review of literature the paper provides a structured empirical findings and theoretical perspectives relating to impact of data protection and privacy on e-government adoption.
-
Algorithms and security concern in blockchain technology: a brief reviewIn this chapter, we will research the number of technical aspects of blockchain technology, the pace at which this technology is booming, and, most importantly, its implementation on the Bitcoin cryptocurrency, which has revolutionized the financial infrastructure of the world. We will also consider a number of security concerns, challenges, and other technical vulnerabilities associated with the Bitcoin technology. The decentralized mechanism, distributed mechanism, scripted mechanism, and the password related to blockchain have opened a new view on the rapidly developing Internet technology. There is no need for participants or any third party to know each other. The responsibility is included in the recording, transmission, and activities regarding storage by distributed technology. That is how the assurance is guaranteed by keeping these aloof from tampering and forging. With the assistance of an asymmetric cryptographic algorithm, every participant can reach a consensus on the blockchain's information. Blockchain technology can play a key role in the case of information security technology. Hence, in this chapter, we will also cover the impact of blockchain to expand the sphere of information security.
-
Road ahead for D2D communicationsDevice-to-device (D2D) is a key enabling technology for the fifth-generation Internet-of-Things, where the global number of D2D connections specifically is expected to reach 14.7 billion devices by 2023. In D2D communication, the spectrum can be shared between D2D and cellular users via two methods, namely, in-band (licensed) and out-band (unlicensed) communication. The integration of D2D in the network requires a substantial modification in both core and access networks to support the smart services in future innovative infrastructures. User equipment communicates through radio network links and core network in conventional cellular communication. Efficient discovery of the nodes in proximity is fundamental to the D2D communications. Vehicle-to-vehicle communications have attracted great interest due to the potential of improving traffic safety, reducing energy consumption, and enabling new services related to intelligent transportation systems. Visible light communication-based D2D can potentially be a venue for more structured research and development efforts in near future.
-
Interference mitigation in D2D communication underlaying LTE-A network [2022]This chapter focuses on underlay in-band device-to-device (D2D) communication. The applicability of D2D spans across many areas including, but not limited to proximity-based services, e.g. social application, smart communication between vehicles, content distribution, multicasting, peer-to-peer communication, location aware advertisement, and public safety. There are two types of D2D communication, namely, in-band and out-band. The major difference between the two is the frequency spectrum band in which the D2D communication is operating. D2D communications can provide higher spectral efficiency and network throughput, which are the two main requirements for the long term evolution-advanced (LTE-A) network. D2D communication underlaying cellular network is expected to operate within the same coverage area of an existing cell of LTE-A network and share the same cellular spectrum. Various interference mitigation schemes such as power control, efficient resource allocation, and multi-antenna beam forming among others have been reviewed and critically analyzed.
-
River Project, an innovative way to reduce pollution on riverboatsConsidering the EU environmental standards for non-road mobile machinery (NRMM), reducing pollutant emissions from inland waterway vessels is becoming increasingly important. The RIVER research project aims to find solutions to achieve nitrogen-free combustion in waterways transportation systems while also emitting zero CO2 emission. RIVER addresses these issues using Carbon Capture and Storage (CCS) technology and Oxy-fuel combustion (OFC). The project is co-financed by the European Union, as part of the Interreg North-West Europe program. There are ten partners involved in this project (FR, UK, GE, NL, LU). In OFC technology, pure oxygen is used instead of air. Due to the absence of N2 in the intake charge, NOx emissions will be eliminated. Consequently, the only products of combustion are CO2 and water vapor. To have a stable combustion process and avoid overheating problems caused by using pure oxygen, some part of the exhaust CO2 will be recirculated to the engine to create an oxygen-CO2 mixture for being fed into the engine. A detailed CFD simulation carried out in this project has revealed that 21% oxygen and 79% carbon dioxide is the ideal mixture for the engine to run at maximum efficiency. The remaining CO2 from the exhaust is collected. It is then condensed, compressed, and stored in a tank to be valorized later. It will be transformed into cosmetics, skincare products, and formic acid. These types of acids are used by the medical sector as an anti-rheumatic product. River's final demonstration will take place in Crewe, UK in July 2022.
-
Artificial intelligence based early diagnosis of sepsisSepsis is a major killer of those who are already in a serious condition. The morbidity and death rates in this field remain high, despite the fact that medical technology has been advancing steadily over the last several years. This is due mostly to people not beginning therapy quickly enough and doctors not following best practices. Medical decision support solutions have advanced greatly with the help of artificial intelligence (AI), a rapidly developing sector in the medical industry. Great promise has been shown in its ability to anticipate patients' clinical conditions and aid clinical decision-making. Early prediction, prognosis evaluation, mortality prediction, and optimum treatment are just few of the areas where algorithms developed using artificial intelligence may be put to use. This article summarizes the most recent research on AI based clinical decision support in sepsis as well as explains how this cutting-edge technology might aid in sepsis prediction, identification, sub phenotyping, prognostic evaluation, and clinical treatment. We also spoke about the difficulties of using this non-conventional approach in clinical practice.
-
Exploration and assessment of critical covariates of breast cancer outcomes via between-group test of survival rates at Sir Run Run Shaw HospitalBreast cancer, being the most pervasive malignancy globally, poses a substantial threat to the well-being of the female population. Given the pronounced heterogeneity in survival times among affected individuals, a comprehensive examination of the factors governing treatment outcomes becomes imperative. Leveraging a sizable dataset comprising 2,757 breast cancer patients from Sir Run Run Shaw Hospital, the current study endeavors to assess the foremost covariates influencing the survival outcomes in breast cancer through survival analysis. The analytical framework commences with the application of Kendall analysis to effectuate dimensionality reduction on the dataset. Subsequently, an overarching survival analysis encompassing the pertinent factors is carried out, followed by a series of individual factor-specific survival assessments. Lastly, the results are visualised and discussed. The primary objective of this study is to evaluate the crucial covariates by employing a between-group test of survival rates.
-
Influence of artificial intelligence in higher education; impact, risk and counter measureArtificial Intelligence (AI) is an emerging field that seeks to replicate or emulate human-like cognitive abilities using artificial means. As the world changes, the development and application of AI tools and technologies in areas such as agriculture, medicine, healthcare, and education are growing at an unprecedented pace. This chapter presents a review study on the impact, risks, and countermeasures of artificial intelligence in higher education (AIHE). The chapter begins by discussing the journey of AI in education from its beginning to the present day. It then examines the existing AI tools and technologies in education and explores their potential applications. The chapter goes on to analyze the influences of these tools in education and the challenges and risks they face in higher education. Additionally, it highlights the limitations of AI tools and proposes ways to overcome these gaps. The purpose of this study is to provide updated information to students, teachers, professors, national policymakers, and researchers, as well as to explore the scope of research on AI in higher education. By offering a comprehensive analysis of the impact of AI on higher education (HE), this chapter aims to inform and inspire the academic community to embrace AI as a transformative technology in education.
-
Privacy-preserving patient-centric electronic health records exchange using blockchainThe global electronic health records (EHRs) market is expected to reach USD 38.5 billion by 2030. This growth is expected owing to reasons, such as the digitalization of healthcare systems, and wearable healthcare devices. However, this raises the challenge to preserve the privacy of EHRs when massive amounts of data are created, retrieved, and circulated daily. Furthermore, it is vital that the patient's EHRs that are controlled by the medical industry are transited to a patient-centric model, where patients are fully authorized to control their data. It is widely acknowledged that distributed ledger technologies (DLTs), particularly blockchain enable the storage and exchange of data in a decentralized, trusted, pseudonymous, and immutable fashion. This chapter explores adapting blockchain technologies toward patient-centric and privacy-preserving EHR exchange. Furthermore, the concept of patient-centric EHR is introduced while exploring existing methods on privacy-preserving and patient-centric EHR exchange using blockchain, and possible research directions.
-
Injecting commonsense knowledge into prompt learning for zero-shot text classificationThe combination of pre-training and fine-tuning has become a default solution to Natural Language Processing (NLP) tasks. The emergence of prompt learning breaks such routine, especially in the scenarios of low data resources. Insufficient labelled data or even unseen classes are frequent problems in text classification, equipping Pre-trained Language Models (PLMs) with task-specific prompts helps get rid of the dilemma. However, general PLMs are barely provided with commonsense knowledge. In this work, we propose a KG-driven verbalizer that leverages commonsense Knowledge Graph (KG) to map label words with predefined classes. Specifically, we transform the mapping relationships into semantic relevance in the commonsense-injected embedding space. For zero-shot text classification task, experimental results exhibit the effectiveness of our KG-driven verbalizer on a Twitter dataset for natural disasters (i.e. HumAID) compared with other baselines.
-
Design of energy-efficient approximate arithmetic circuits for error tolerant medical image processing applicationsMedical image processing encompasses the use and investigation of human body image collections, usually from a Computed Tomography (CT) to diagnose pathologies for disease detection. Energy efficiency is one of the key parameters in the design of very large-scale integrated circuits. For more power consuming circuits, the traditional methodologies deal with limited approaches. In recent years, approximate computing techniques improve the design metrics power, delay, and area with a limitation on accuracy. High performance computing and Error tolerant applications are preferred to implement Approximation techniques. Many multimedia applications, such as digital image and video processing, can introduce minor errors in the processed output. For these applications, approximate computational approach offers good performance in terms of low power consumption at a trade-off of accuracy. This is best suited for arithmetic circuits. Several improved versions of Approximate adders (PAA_s) and Approximate Subtractors (APSC8-APSC10) have been proposed in this paper for basic operations. Based on these designs, multipliers and dividers have developed and also performance is compared with previous designs. The proposed designs achieve a better peak signal-to-noise ratio (PSNR).
-
Optimization of shark groove drag reduction based on CFD and genetic algorithmAn optimization of shark scale flake groove structure by genetic algorithm is proposed to enhance its drag reduction performance. The microstructure of shark scales has been shown to play a key role in reducing frictional drag and enhancing hydrodynamic efficiency. Therefore, a genetic algorithm was used to optimize the design of the groove shape of the scales to exhibit optimal performance in the fluid environment. Genetic algorithms of selection, crossover and mutation are used to find the optimal solution in the design space. The optimized design is validated by Computational Fluid Dynamics (CFD) technique. The CFD simulation results demonstrate the improved hydrodynamic performance of the optimized groove design and confirm the effectiveness of genetic algorithms in complex engineering design problems. This study provides a new research avenue to improve the hydrodynamic efficiency.
-
PGC-Arctan demodulation method based on improved IKEFThe proposed method is an improvement on the traditional PGC demodulation technique, specifically addressing the impact of carrier phase delay, modulation depth drift, and low-frequency ambient noise on phase demodulation accuracy in phase-modulated homodyne interferometers. It utilises an improved iterative extended Kalman filtering (IEKF) approach. The algorithm enhances the iterative updating process by incorporating a damping factor into the traditional IEKF. This enables optimal estimation and correction of the parameters of the PGC quadrature signals, resulting in reduced nonlinear error in the demodulation process. Additionally, the improved algorithm achieves higher demodulation accuracy. Simulation results demonstrate the method's effectiveness in eliminating nonlinear error in phase generation carrier.
-
Periodic silicon metasurfaces for high performance structural colorStructural color can be divided into plasmonic structural color and all-dielectric structural color, and dielectric structural color is becoming the first choice for making structural color because of its high color saturation and low cost. In this work, a large area of silicon-based structural color was fabricated using the Taber effect based on laser interference theory from commercial silicon-on-insulator (SOI) substrates on the basis of FDTD simulation. Consequently, periodic grating silicon metasurfaces with a width of 106 nm can achieve a maximum spectral reflectance of up to 91% at 650-700 nm, which can produce bright red structural color, providing a reliable way for the fabrication of low cost and high performance dielectric structural color at low cost.
-
A dedicated consensus algorithm for improving performance of futuristic energy blockchainIntegrating renewable energy generation in the consumer end has transformed users acting as both buyers and sellers. Uncoordinated interconnections lead to degraded power quality, which demands for continuous network monitoring. This study evaluates the applicability of the network monitoring process to develop a novel consensus protocol, customized for blockchain platforms integrated with smart grids. The motivation for integrating grid monitoring with the blockchain consensus mechanism lies in the significance of decentralized architectures such as distributed ledger technologies for future energy grids. Existing blockchain consensus mechanisms have exhibited excessive energy usage and low scalability due to the additional workload associated. Hence, the study proposes a customised solution, which has the advantage of combining grid monitoring with the blockchain consensus protocol. This eliminates the additional computation burden, reduces the cost of execution, and improves the transaction throughput of the blockchain consensus mechanism.
-
Divide and control: generation of multiple component comic illustrations with diffusion models based on regressionDiffusion-based text-to-image generation has achieved huge success in creative image generation and editing applications. However, when applied to comic illustrations, it still struggles to deliver predictable high-quality productions with multiple characters due to the interference of the text prompts. In this paper, we propose a practicable method to use ControlNet and stable diffusion to generate controllable outputs of multiple components. The method first generates images for individual components separately and then degenerates those images to a regressed form, such as line drawings or Canny edges. Those regressed forms of individual components are then merged and fed into ControlNet to generate the final image. Experiments show that this method is highly controllable and can produce high-quality comic illustrations with multiple components.
-
Towards continuously programmable networksWhile programmability has been a feature of network devices for a long time, the past decade has seen significant enhancement of programming capability for network functions and nodes, spearheaded by the ongoing trend towards softwarization and cloudification. In his context, new design principles and technology enablers are introduced (Section 7.2) which reside2 at: (i) service/application provisioning level, (ii) network and resource management level, as well as (iii) network deployment and connectivity level.
-
Observation of gallium droplets directly formed on GaAs substrate by in-situ laser irradiationIn this study, following the deposition of a 500nm GaAs buffer layer, the GaAs substrate was irradiated in MBE with an in situ laser shooting at a very low temperature of around 12°C. We carefully observed the morphology evolution of the irradiated surface with different pulse energy varying from 20mJ to 50mJ. After being pulsed-irradiated with 20mJ, a density of Ga droplets as high as 7.2×1010/cm2 was directly formed on the surface. The droplets have a height range of 1.0nm to 4.1nm (averaging at 2.4nm) and a width range of 15.7nm to 39.2nm (averaging at 28.1nm). With increasing irradiation energy, it is observed the droplet density will gradually decrease from 2.2 × 1010/cm2, 1.2 × 1010/cm2 to 5.2 × 109/cm2 while the size (average width/height) will continue to grow up from 64.1nm/8.2nm, 63.3/9.2nm to 76.1nm/12.2nm, respectively corresponding to exposure energy from 30mJ, 40mJ to 50mJ. The results demonstrate the successful provision of a new technology to generate Ga droplets on the surface of GaAs directly through in-situ pulsed laser irradiation without the need of epitaxial growth. Furthermore, both the resulting density and size can be easily and effectively adjusted by varying the laser energy. Additionally, this technique offers significant advantages such as low cost, free of contamination and defects and high controllability. Therefore, we believe this technology may find great application prospects for nano-fabrication of semiconductor quantum structures and devices.
