The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.
Imaging is a keystone for the understanding and delivery of craniofacial health care and recent developments have led to many diverse technologies and approaches. This paper reviews new developments in three-dimensional imaging, as well as three-dimensional facial image acquisition. Visualization and convergence of the data from these technologies are also described for construction of patient-specific models.
Chlorophyll-a concentrations (mg/l) in surface waters of Songsong Islands were mapped using an optically derived remote sensing model. Landsat TM imagery dated 8 October 2008 was used in the classification process and in situ measurements made on 19 May 2012 during spring tidal condition (HW: 2.6 m, LW: 0.9 m) served as ground truthing data. The temporal difference between data used will be useful to review the robustness of the model. Three classes of chlorophyll-a concentrations were mapped: Class 1: 10 mg/l. Considering the dynamic nature of coastal and marine waters particularly the shallow region, and the temporal difference between the Landsat TM imagery used in classification and the field data, results of chlorophyll-a mapping using the developed remote sensing model was high at 83.3%, with producer’s accuracy of 50%–100% and user’s accuracy of 80%–100%. Kappa coefficient of agreement, Kˆ , calculated was 57.1%.
Covering as much as 25% to 35% of the development cost, software testing is an integral part of the software development lifecycle. Despite its importance, the current software testing practice is still based on highly manual processes from the generation of test cases (i.e. from specifications) up to the actual execution of the test. These manually generated tests are sometimes executed using ad hoc approaches, typically requiring the construction of a test driver for the particular application under test. In addition, test engineers are also under pressure to test increasing lines of code in order to meet market demands for more software functionalities. While there are significant proliferations of helpful testing tools or research prototypes in the market, much of them do not adequately provide the right level of abstraction and automation as required by test engineers. In order to facilitate and address some of the aforementioned issues, an automated testing tool was developed, called SFIT, based on Java® technology. This paper describes the development, implementation and evaluation of SFIT. Two case studies involving the robustness assessment of an adder module and a Linda-based distributed shared memory implementation are described in order to demonstrate the applicability of SFIT as a helpful automated testing tool.
The majority of the Wireless Sensor Network (WSN) localization methods utilize a large number of nodes to achieve high localization accuracy. However, there are many unnecessary data redundancies that contributes to high computation, communication, and energy cost between these nodes. Therefore, we propose the Intersection and Complement Set (IACS) method to reduce these redundant data by selecting the most significant neighbor nodes for the localization process. Through duplication cleaning and average filtering steps, the proposed IACS selects the normal nodes with unique intersection and complement sets in the first and second hop neighbors to localize the unknown node. If the intersection or complement sets of the normal nodes are duplicated, IACS only selects the node with the shortest distance to the blind node and nodes that have total elements larger than the average of the intersection or complement sets. The proposed IACS is tested in various simulation settings and compared with MSL* and LCC. The performance of all methods is investigated using the default settings and a different number of degree of irregularity, normal node density, maximum velocity of sensor node and number of samples. From the simulation, IACS successfully reduced 25% of computation cost, 25% of communication cost and 6% of energy consumption compared to MSL*, while 15% of computation cost, 13% of communication cost and 3% of energy consumption compared to LCC.
Electrical Discharge Machining, EDM is one of the technologies used for surface
texturing such as the embedded micro-dimples on the metallic acetabular cup. During
the machining process, changes in the gap distance may lead to load changes from
open to short circuit. Limiting the load current under short circuit conditions and load
voltage under open circuit conditions is the requirement in this system. Power supply
is one of the elements that controls the process parameters which is related to improve
the machining condition as well as Material Removal Rate (MRR). A considerable
number of power supply design method were proposed for various EDM application.
This research proposed a Switch Mode Power Supply method implementing new
design of Flyback power supply which can stabilize the voltage during open circuit
condition as well as during discharge condition. Experimental studies were conducted
to verify the capability of Flyback power supply by machining eight micro-dimples in
lower position and twelve micro-dimples in upper position, both in circular
arrangement on metallic acetabular cup. Research conducted shows that the Flyback
power supply improve the consistency of MRR when compared to Linear power supply.
This may help to predict the machining time, thus improving the production of microdimples
in required time.
This is a review of studies on various types of paper-based epoxy composites currently being designed and developed for technological use. The concept of designing composite materials is very significant for small to large industry and it is important where initiation of repairing work is now being considered for engineering applications. This composite material is of interest due to its advantages compared with others, including low environmental effects and low cost for a wide range of works. This review aims to provide an overview of morphological, physical and mechanical properties of various paper sheetsbased epoxy composites and details of achievements made. From this approach, this paper also presents the preliminary study of SEM results of paper sheets-based epoxy composites designed for repairing work applications. It has been found that a well-arranged laminated paper sheet layers could help the bond strength with epoxy matrix. Thus, this paper sheet-based epoxy composite can be considered as an easiest way, cheap and biodegradable that can be used for various small repairing works in structural and automotive applications.
Vehicular ad hoc networks (VANET) are also known as intelligent transportation systems. VANET ensures timely and accurate communications between vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) to improve road safety and enhance the efficiency of traffic flow. Due to its open wireless boundary and high mobility, VANET is vulnerable to malicious nodes that could gain access into the network and carry out serious medium access control (MAC) layer threats, such as denial of service (DoS) attacks, data modification attacks, impersonation attacks, Sybil attacks, and replay attacks. This could affect the network security and privacy, causing harm to the information exchange within the network by genuine nodes and increase fatal impacts on the road. Therefore, a novel secure trust-based architecture that utilizes blockchain technology has been proposed to increase security and privacy to mitigate the aforementioned MAC layer attacks. A series of experiment has been conducted using the Veins simulation tool to assess the performance of the proposed solution in the terms of packet delivery ratio (PDR), end-to-end delay, packet loss, transmission overhead, and computational cost.
This paper attempts to give a detailed review and provide a complete description on the technology, physics and modeling of various Multi-Gate MOSFETs. It consists of a synopsis of mathematical depiction of the potential distribution along the channel of various MG-MOSFETS which can be made to enable fast computer analysis of device behavior. This serves a link between process technology and circuit design. This review demonstrates that this technology is strongly desired in nanoscale domain and there is a plenty demand for analytical model which can explain the physics and operation of the devices perfectly.
A printed compact monopole antenna based on a single negative (SNG) metamaterial is proposed for ultra-wideband (UWB) applications. A low-profile, key-shaped structure forms the radiating monopole and is loaded with metamaterial unit cells with negative permittivity and more than 1.5 GHz bandwidth of near-zero refractive index (NZRI) property. The antenna offers a wide bandwidth from 3.08 to 14.1 GHz and an average gain of 4.54 dBi, with a peak gain of 6.12 dBi; this is in contrast to the poor performance when metamaterial is not used. Moreover, the maximum obtained radiation efficiency is 97%. A reasonable agreement between simulation and experiments is realized, demonstrating that the proposed antenna can operate over a wide bandwidth with symmetric split-ring resonator (SSRR) metamaterial structures and compact size of 14.5 × 22 mm2 (0.148 λ0 × 0.226 λ0) with respect to the lowest operating frequency.
Identification of appropriate clean technologies for industrial implementation requires systematic evaluation based on a set of criteria that normally reflect economic, technical, environmental and other aspects. Such multiple attribute decision-making (MADM) problems involve rating a finite set of alternatives with respect to multiple potentially conflicting criteria. Conventional MADM approaches often involve explicit trade-offs in between criteria based on the expert's or decision maker's priorities. In practice, many experts arrive at decisions based on their tacit knowledge. This paper presents a new induction approach, wherein the implicit preference rules that estimate the expert's thinking pathways can be induced. P-graph framework is applied to the induction approach as it adds the advantage of being able to determine both optimal and near-optimal solutions that best approximate the decision structure of an expert. The method elicits the knowledge of experts from their ranking of a small set of sample alternatives. Then, the information is processed to induce implicit rules which are subsequently used to rank new alternatives. Hence, the expert's preferences are approximated by the new rankings. The proposed induction approach is demonstrated in the case study on the ranking of Negative Emission Technologies (NETs) viability for industry implementation.
The inherent complexities of Industrial Internet of Things (IIoT) architecture make its security and privacy issues becoming critically challenging. Numerous surveys have been published to review IoT security issues and challenges. The studies gave a general overview of IIoT security threats or a detailed analysis that explicitly focuses on specific technologies. However, recent studies fail to analyze the gap between security requirements of these technologies and their deployed countermeasure in the industry recently. Whether recent industry countermeasure is still adequate to address the security challenges of IIoT environment are questionable. This article presents a comprehensive survey of IIoT security and provides insight into today's industry countermeasure, current research proposals and ongoing challenges. We classify IIoT technologies into the four-layer security architecture, examine the deployed countermeasure based on CIA+ security requirements, report the deficiencies of today's countermeasure, and highlight the remaining open issues and challenges. As no single solution can fix the entire IIoT ecosystem, IIoT security architecture with a higher abstraction level using the bottom-up approach is needed. Moving towards a data-centric approach that assures data protection whenever and wherever it goes could potentially solve the challenges of industry deployment.
Medication reviews are effective in improving the quality of medication use among older people. However, they are conducted to various standards resulting in a wide range of outcomes which limit generalisability of findings arising from research studies. There also appear to be funding and time constraints, lack of data storage for quality improvement purposes, and non-standardised reporting of outcomes, especially clinically relevant outcomes. Furthermore, the coronavirus disease-19 (COVID-19) pandemic has restricted many face-to-face activities, including medication reviews. This article introduces a technology-enabled approach to medication reviews that may overcome some limitations with current medication review processes, and also make it possible to conduct medication reviews during the COVID-19 pandemic by providing an alternate platform. The possible advantages of this technology-enabled approach, legislative considerations and possible implementation in practice are discussed.
The valorization and conversion of biomass into various value-added products and bioenergy play an important role in the realization of sustainable circular bioeconomy and net zero carbon emission goals. To that end, microwave technology has been perceived as a promising solution to process and manage oil palm waste due to its unique and efficient heating mechanism. This review presents an in-depth analysis focusing on microwave-assisted torrefaction, gasification, pyrolysis and advanced pyrolysis of various oil palm wastes. In particular, the products from these thermochemical conversion processes are energy-dense biochar (that could be used as solid fuel, adsorbents for contaminants removal and bio-fertilizer), phenolic-rich bio-oil, and H2-rich syngas. However, several challenges, including (1) the lack of detailed study on life cycle assessment and techno-economic analysis, (2) limited insights on the specific foreknowledge of microwave interaction with the oil palm wastes for continuous operation, and (3) effects of tunable parameters and catalyst's behavior/influence on the products' selectivity and overall process's efficiency, remain to be addressed in the context of large-scale biomass valorization via microwave technology.
LoRa is an ISM-band based LPWAN communication protocol. Despite their wide network penetration of approximately 20 kilometers or higher using lower than 14 decibels transmitting power, it has been extensively documented and used in academia and industry. Although LoRa connectivity defines a public platform and enables users to create independent low-power wireless connections while relying on external architecture, it has gained considerable interest from scholars and the market. The two fundamental components of this platform are LoRaWAN and LoRa PHY. The consumer LoRaWAN component of the technology describes the network model, connectivity procedures, ability to operate the frequency range, and the types of interlinked gadgets. In contrast, the LoRa PHY component is patentable and provides information on the modulation strategy which is being utilized and its attributes. There are now several LoRa platforms available. To create usable LoRa systems, there are presently several technical difficulties to be overcome, such as connection management, allocation of resources, consistent communications, and security. This study presents a thorough overview of LoRa networking, covering the technological difficulties in setting up LoRa infrastructures and current solutions. Several outstanding challenges of LoRa communication are presented depending on our thorough research of the available solutions. The research report aims to stimulate additional research toward enhancing the LoRa Network capacity and allowing more realistic installations.
This study aims to give a comprehensive analysis of customers' acceptance and use of AI gadgets and its relevant ethical issues in the tourism and hospitality business in the era of the Internet of Things. Adopting a PRISMA methodology for Systematic Reviews and Meta-Analyses, the present research reviews how tourism and hospitality scholars have conducted research on AI technology in the field of tourism and the hospitality industry. Most of the journal articles related to AI issues published in Web of Science, ScienceDirect.com and the journal websites were considered in this review. The results of this research offer a better understanding of AI implementation with roboethics to investigate AI-related issues in the tourism and hospitality industry. In addition, it provides decision-makers in the hotel industry with practical references on service innovation, participation in the design of AI devices and AI device applications, meeting customer needs, and optimising customer experience. The theoretical implications and practical interpretations are further identified.
Health Technology Assessment (HTA) is a multidisciplinary tool to inform healthcare decision-making. HTA has been implemented in high-income countries (HIC) for several decades but has only recently seen a growing investment in low- and middle-income countries. A scoping review was undertaken to define and compare the role of HTA in least developed and lower middle-income countries (LLMIC). MEDLINE and EMBASE databases were searched from January 2015 to August 2021. A matrix comprising categories on HTA objectives, methods, geographies, and partnerships was used for data extraction and synthesis to present our findings. The review identified 50 relevant articles. The matrix was populated and sub-divided into further categories as appropriate. We highlight topical aspects of HTA, including initiatives to overcome well-documented challenges around data and capacity development, and identify gaps in the research for consideration. Those areas we found to be under-studied or under-utilized included disinvestment, early HTA/implementation, system-level interventions, and cross-sectoral partnerships. We consider broad practical implications for decision-makers and researchers aiming to achieve greater interconnectedness between HTA and health systems and generate recommendations that LLMIC can use for HTA implementation. Whilst HIC may have led the way, LLMIC are increasingly beginning to develop HTA processes to assist in their healthcare decision-making. This review provides a forward-looking model that LLMIC can point to as a reference for their own implementation. We hope this can be seen as timely and useful contributions to optimize the impact of HTA in an era of investment and expansion and to encourage debate and implementation.
Blockchain has become a well-known, secured, decentralized datastore in many domains, including medical, industrial, and especially the financial field. However, to meet the requirements of different fields, platforms that are built on blockchain technology must provide functions and characteristics with a wide variety of options. Although they may share similar technology at the fundamental level, the differences among them make data or transaction exchange challenging. Cross-chain transactions have become a commonly utilized function, while at the same time, some have pointed out its security loopholes. It is evident that a secure transaction scheme is desperately needed. However, what about those nodes that do not behave? It is clear that not only a secure transaction scheme is necessary, but also a system that can gradually eliminate malicious players is of dire need. At the same time, integrating different blockchain systems can be difficult due to their independent architectures, and cross-chain transactions can be at risk if malicious attackers try to control the nodes in the cross-chain system. In this paper, we propose a dynamic reputation management scheme based on the past transaction behaviors of nodes. These behaviors serve as the basis for evaluating a node's reputation to support the decision on malicious behavior and enable the system to intercept it in a timely manner. Furthermore, to establish a reputation index with high precision and flexibility, we integrate Particle Swarm Optimization (PSO) into our proposed scheme. This allows our system to meet the needs of a wide variety of blockchain platforms. Overall, the article highlights the importance of securing cross-chain transactions and proposes a method to prevent misbehavior by evaluating and managing node reputation.
Greenhouse gas emissions and global warming are recent issues of upward trend. This study sought to underline the causal relationships between engagement modes with green technology, environmental, social, and governance (ESG) ratio, and circular economy. Our investigation also captured benchmarking of energy companies' circular economy behaviors. A hybrid-stage partial least squares structural equation modeling (PLS-SEM) and multi-criteria decision-making (MCDM) analysis have been adopted. This study collected 713 questionnaires from heads of departments and managers of energy companies. The findings of this study claimed that engagement modes with green technology affect the circular economy and sustainability. The findings revealed that ESG ratings have a mediating role in the nexus among engagement modes with green technology and circular economy. The results of the MCDM application revealed the identification of the best and worst energy companies of circular economy behaviours. This study is exceptional because it is among the first to address the issues of greenhouse gas emissions by providing decisive evidence about the level of circular economy behaviors in energy companies.