20 results
Search Results
2. Impact of Sustained Supply Voltage Magnitude on Consumer Appliance Behaviour.
- Author
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Elphick, Sean, Robinson, Duane A., Perera, Sarath, Knott, Jonathan C., David, Jason, and Drury, Gerrard
- Subjects
CONSUMER behavior ,VOLTAGE ,DISTRIBUTED power generation ,HIGH voltages ,ENERGY consumption - Abstract
Voltage rise caused by high levels of distributed generation is manifesting as voltage regulation challenges for many electricity network service providers. In this environment it would be ideal to reduce supply voltage magnitudes, however, many network operators are hesitant to do so due to concerns related to consumer appliance performance at reduced supply voltage magnitudes. Voltage regulation requirements are defined by network standards and network service providers must ensure voltages remain within specified limits. Through an evaluation of domestic appliance performance when supplied at various voltage magnitudes, this paper examines the impact of varying voltage levels on residential appliances. Equipment energy demand, operation and actuation were monitored for each applied voltage magnitude. While no equipment failures were recorded, appliance behaviour varied significantly with applied voltage magnitude. Individual appliance conservation voltage reduction (CVR) factors have also been established. The results highlight the importance of good voltage regulation and provide substantiated appliance performance figures for future studies. The outcomes of this paper allow electricity network service providers to understand the implications of supply voltage magnitude on domestic appliance performance, whether it be understating of the impact of higher voltage magnitudes caused by distributed generation or implications of reducing voltage magnitudes to provide headroom for distributed generation integration. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
3. A Survey on Deep Learning Techniques for Stereo-Based Depth Estimation.
- Author
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Laga, Hamid, Jospin, Laurent Valentin, Boussaid, Farid, and Bennamoun, Mohammed
- Subjects
DEEP learning ,COMPUTER vision ,MACHINE learning ,AUGMENTED reality ,LEARNING communities ,AUTONOMOUS vehicles - Abstract
Estimating depth from RGB images is a long-standing ill-posed problem, which has been explored for decades by the computer vision, graphics, and machine learning communities. Among the existing techniques, stereo matching remains one of the most widely used in the literature due to its strong connection to the human binocular system. Traditionally, stereo-based depth estimation has been addressed through matching hand-crafted features across multiple images. Despite the extensive amount of research, these traditional techniques still suffer in the presence of highly textured areas, large uniform regions, and occlusions. Motivated by their growing success in solving various 2D and 3D vision problems, deep learning for stereo-based depth estimation has attracted a growing interest from the community, with more than 150 papers published in this area between 2014 and 2019. This new generation of methods has demonstrated a significant leap in performance, enabling applications such as autonomous driving and augmented reality. In this paper, we provide a comprehensive survey of this new and continuously growing field of research, summarize the most commonly used pipelines, and discuss their benefits and limitations. In retrospect of what has been achieved so far, we also conjecture what the future may hold for deep learning-based stereo for depth estimation research. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
4. Low-Variance Memristor-Based Multi-Level Ternary Combinational Logic.
- Author
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Wang, Xiao-Yuan, Dong, Chuan-Tao, Zhou, Peng-Fei, Nandi, Sanjoy Kumar, Nath, Shimul Kanti, Elliman, Robert G., Iu, Herbert Ho-Ching, Kang, Sung-Mo, and Eshraghian, Jason K.
- Subjects
LOGIC circuits ,LOGIC ,DATA transmission systems ,MANY-valued logic - Abstract
This paper presents a series of multi-stage hybrid memristor-CMOS ternary combinational logic stages that are optimized for reducing silicon area occupation. Prior demonstrations of memristive logic are typically constrained to single-stage logic due to the variety of challenges that affect device performance. Noise accumulation across subsequent stages can be amortized by integrating ternary logic gates, thus enabling higher density data transmission, where more complex computation can take place within a smaller number of stages when compared to single-bit computation. We present the design of a ternary half adder, a ternary full adder, a ternary multiplier, and a ternary magnitude comparator. These designs are simulated in SPICE using the broadly accessible Knowm memristor model, and we perform experimental validation of individual stages using an in-house fabricated Si-doped HfOx memristor which exhibits low cycle-to-cycle variation, and thus contributes to robust long-term performance. We ultimately show an improvement in data density in each logic block of between $5.2\times - 17.3\times $ , which also accounts for intermediate voltage buffering to alleviate the memristive loading problem. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
5. Improving Voltage Regulation and Unbalance in Distribution Networks Using Peer-to-Peer Data Sharing Between Single-Phase PV Inverters.
- Author
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Gerdroodbari, Yasin Zabihinia, Razzaghi, Reza, and Shahnia, Farhad
- Subjects
INFORMATION sharing ,VOLTAGE ,PEER-to-peer architecture (Computer networks) ,REACTIVE power - Abstract
This paper proposes a novel reactive power-based control strategy for single-phase PV inverters (PVIs) to simultaneously improve voltage unbalance (VU) and voltage regulation (VR) in low-voltage distribution networks. The proposed strategy relies on communication links between neighboring PVIs to exchange limited data. In this strategy, each PVI finds communication paths between itself and the closest neighboring ones connected to other phases. Then, using the obtained paths and the maximum and the minimum voltage magnitude of the grid, PVIs improve both VU and VR at the same time. The performance of the proposed control strategy is evaluated by various simulation studies using the IEEE European low-voltage test feeder and considering different operational conditions. In addition, the impacts of moving clouds and a failure in the communication links have been assessed. The simulation results exhibit that using the proposed control strategy, the voltage magnitude of all the nodes will remain within the allowed limits and at the same time, the phase voltage unbalance factor will be also significantly improved. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
6. Pseudo-Pair Based Self-Similarity Learning for Unsupervised Person Re-Identification.
- Author
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Wu, Lin, Liu, Deyin, Zhang, Wenying, Chen, Dapeng, Ge, Zongyuan, Boussaid, Farid, Bennamoun, Mohammed, and Shen, Jialie
- Subjects
VIDEO surveillance ,BASE pairs ,LEARNING ,IMAGE registration ,SUPERVISED learning - Abstract
Person re-identification (re-ID) is of great importance to video surveillance systems by estimating the similarity between a pair of cross-camera person shorts. Current methods for estimating such similarity require a large number of labeled samples for supervised training. In this paper, we present a pseudo-pair based self-similarity learning approach for unsupervised person re-ID without human annotations. Unlike conventional unsupervised re-ID methods that use pseudo labels based on global clustering, we construct patch surrogate classes as initial supervision, and propose to assign pseudo labels to images through the pairwise gradient-guided similarity separation. This can cluster images in pseudo pairs, and the pseudos can be updated during training. Based on pseudo pairs, we propose to improve the generalization of similarity function via a novel self-similarity learning:it learns local discriminative features from individual images via intra-similarity, and discovers the patch correspondence across images via inter-similarity. The intra-similarity learning is based on channel attention to detect diverse local features from an image. The inter-similarity learning employs a deformable convolution with a non-local block to align patches for cross-image similarity. Experimental results on several re-ID benchmark datasets demonstrate the superiority of the proposed method over the state-of-the-arts. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
7. CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification.
- Author
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Liao, Zhibin, Liao, Kewen, Shen, Haifeng, van Boxel, Marouska F., Prijs, Jasper, Jaarsma, Ruurd L., Doornberg, Job N., Hengel, Anton van den, and Verjans, Johan W.
- Subjects
CONVOLUTIONAL neural networks ,ORTHOPEDICS ,INTRAMEDULLARY fracture fixation - Abstract
Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A common criticism of CNNs is their opaque learning and reasoning process, making it difficult to trust machine diagnosis and the subsequent adoption of such algorithms in clinical setting. This is especially true when the CNN is trained with limited amount of medical data, which is a common issue as curating sufficiently large amount of annotated medical imaging data is a long and costly process. While interest has been devoted to explaining CNN learnt knowledge by visualizing network attention, the utilization of the visualized attention to improve network learning has been rarely investigated. This paper explores the effectiveness of regularizing CNN network with human-provided attention guidance on where in the image the network should look for answering clues. On two orthopedics radiographic fracture classification datasets, through extensive experiments we demonstrate that explicit human-guided attention indeed can direct correct network attention and consequently significantly improve classification performance. The development code for the proposed attention guidance is publicly available on https://github.com/zhibinliao89/fracture_attention_guidance. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
8. Computing K-Cores in Large Uncertain Graphs: An Index-Based Optimal Approach.
- Author
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Wen, Dong, Yang, Bohua, Qin, Lu, Zhang, Ying, Chang, Lijun, and Li, Rong-Hua
- Subjects
PROTEIN-protein interactions ,UNCERTAIN systems ,CHARTS, diagrams, etc. ,HEURISTIC algorithms - Abstract
Uncertain graph management and analysis have attracted many research attentions. Among them, computing $k$ k -cores in uncertain graphs (aka, $(k,\eta)$ (k , η) -cores) is an important problem and has emerged in many applications such as community detection, protein-protein interaction network analysis and influence maximization. Given an uncertain graph, the $(k,\eta)$ (k , η) -cores can be derived by iteratively removing the vertex with an $\eta$ η -degree of less than $k$ k . However, the results heavily depend on the two input parameters $k$ k and $\eta$ η . The settings for these parameters are unique to the specific graph structure and the user's subjective requirements. In addition, computing and updating the $\eta$ η -degree for each vertex is the most costly component in the algorithm, and the cost is high. To overcome these drawbacks, we propose an index-based solution for computing $(k,\eta)$ (k , η) -cores. The size of the index is well bounded by $O(m)$ O (m) , where $m$ m is the number of edges in the graph. Based on the index, queries for any $k$ k and $\eta$ η can be answered in optimal time. We propose an algorithm for index construction with several different optimizations. We also propose a new algorithm for index construction in external memory. We conduct extensive experiments on eight real-world datasets to practically evaluate the performance of all proposed algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
9. Curbing Poor-Quality in Large-Scale Transport Infrastructure Projects.
- Author
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Love, Peter E. D., Ika, Lavagnon A., Matthews, Jane, and Fang, Weili
- Subjects
INFRASTRUCTURE (Economics) ,GREY literature ,PRODUCT life cycle assessment ,RISK sharing ,WORK sharing - Abstract
Poor-quality remains a pervasive challenge for the delivery of large-scale transport infrastructure projects. Typically, it manifests as nonconformance and often requires rework. If, however, a nonconformance goes unidentified, then an asset's integrity can be jeopardized and put people's lives at risk. Hence, governments should shoulder the responsibility for quality. In practice, however, there has been a proclivity for governments to place fixed-price contracts and high-level quality risks on contractors. Yet, there is a dearth of research that has addressed the issue of poor-quality within large-scale transport infrastructure projects. In this article, we attempt to fill this gap and adopt an illustrative case-study approach to garner an understanding as to why poor-quality manifests during the construction of large-scale transport projects. We examine the issue of poor-quality in three high-profile rail transit projects using the gray literature: 1) Delhi Airport Metro Express (India); 2) Honolulu Rail Transit (United States); and 3) Sydney Skytrain (Australia). Then, drawing on empirical observations from two road projects, a highway corridor and a busway, we bring to the fore the poor-quality issue that pervades practice. To curb poor-quality, we suggest that the public and private sectors work collaboratively and share risks to ensure the benefits and value of an asset can be realized. To facilitate the process of collaboration and sharing of quality risks, we propose a Standard Life-cycle Quality Assessment system that can be used to ensure projects conform to standards and requirements. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
10. Does the Planning Fallacy Prevail in Social Infrastructure Projects? Empirical Evidence and Competing Explanations.
- Author
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Love, Peter E. D., Ika, Lavagnon A., and Sing, Michael C. P.
- Subjects
INFRASTRUCTURE (Economics) ,COST overruns ,EXTERNALITIES ,COST estimates ,EXPLANATION ,PESSIMISM - Abstract
The planning fallacy is at play in projects when optimism bias and/or strategic misrepresentation are present. We examine the cost performance of approximately US$ 6.5 billion worth of social infrastructure projects that were procured in Hong Kong and specifically the differences between their final accounts and the various types of estimates that were prepared prior to construction. We focus on the (honest) planning fallacy and hence aim to determine whether estimates are more optimistic than actual costs. Our data shows that 43% of projects incurred a cost underrun from their contract award. We therefore infer that at best 57% of projects may be explained by the presence of the planning fallacy. Based on our findings, we argue that optimism and pessimism bias coexist. Likewise, the planning fallacy and competing explanations can simultaneously account for cost deviations in social infrastructure projects. We submit that the prevalence of the planning fallacy has been exaggerated and hence provide an explanation as to why this has occurred. We finally suggest there is a need for additional empirical work to test the claim that the planning fallacy is the underlying cause of cost overruns and thus the best “theory” to explain “how projects work.” [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
11. Imaging Breast Microcalcifications Using Dark-Field Signal in Propagation-Based Phase-Contrast Tomography.
- Author
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Aminzadeh, A., Arhatari, B. D., Maksimenko, A., Hall, C. J., Hausermann, D., Peele, A. G., Fox, J., Kumar, B., Prodanovic, Z., Dimmock, M., Lockie, D., Pavlov, K. M., Nesterets, Y. I., Thompson, D., Mayo, S. C., Paganin, D. M., Taba, S. T., Lewis, S., Brennan, P. C., and Quiney, H. M.
- Subjects
CALCIFICATIONS of the breast ,BREAST ,BREAST imaging ,COMPUTED tomography ,DIGITAL mammography ,TOMOGRAPHY ,IMAGE processing - Abstract
Breast microcalcifications are an important primary radiological indicator of breast cancer. However, microcalcification classification and diagnosis may be still challenging for radiologists due to limitations of the standard 2D mammography technique, including spatial and contrast resolution. In this study, we propose an approach to improve the detection of microcalcifications in propagation-based phase-contrast X-ray computed tomography of breast tissues. Five fresh mastectomies containing microcalcifications were scanned at different X-ray energies and radiation doses using synchrotron radiation. Both bright-field (i.e. conventional phase-retrieved images) and dark-field images were extracted from the same data sets using different image processing methods. A quantitative analysis was performed in terms of visibility and contrast-to-noise ratio of microcalcifications. The results show that while the signal-to-noise and the contrast-to-noise ratios are lower, the visibility of the microcalcifications is more than two times higher in the dark-field images compared to the bright-field images. Dark-field images have also provided more accurate information about the size and shape of the microcalcifications. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
12. Rework, Failures, and Unsafe Behavior: Moving Toward an Error Management Mindset in Construction.
- Author
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Love, Peter E. D., Ika, Lavagnon, Luo, Hanbin, Zhou, Ying, Zhong, Botao, and Fang, Weili
- Subjects
CONSTRUCTION management ,DEVIANT behavior ,SENIOR leadership teams ,SEMI-structured interviews ,TEAMS in the workplace - Abstract
In this article, we aim to address the following research question: How can a construction organization reduce and contain errors in its projects and mitigate rework and failures? We adopt an organizing sense-making perspective to acquire a sense of order of quality (e.g., rework) and to understand its relationship with safety (e.g., unsafe behavior) in construction. We undertook semistructured interviews from a range of employees involved with delivering a construction organization's projects. Also, documentary sources were accessed to supplement the rework and safety incidents that were referenced during the interviewing process. We found that the construction organization's prevailing culture focused on error prevention, which stymied its ability to learn and reduce rework in projects. The organization consciously enacted a trade-off between quality and safety. The upshot of this either/or framing of competing values was the suppression by senior management of nonconformances, which then led to deviant behavior manifesting in projects. We also revealed that safety incidents tended to arise when people engaged in unsafe behaviors while performing rework. The empirical evidence supports our call for construction organizations to engage in error management so that they can cultivate mindfulness where individuals and project teams can improvise and better handle errors, so they are not repeated. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
13. The Effects of External Auditors and Certification Bodies on the Operational and Market-Oriented Outcomes of ISO 9001 Implementation.
- Author
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Prajogo, Daniel, Nair, Anand, and Castka, Pavel
- Subjects
AUDITORS ,CERTIFICATION ,REPUTATION ,QUALITY standards - Abstract
Many studies on ISO 9001 have been focused on the motivation, the implementation process, and the outcomes of the implementation of the standard. This article seeks to advance the knowledge on ISO 9001 implementation by examining two research issues. First, we investigate the relationship between external auditors, certification bodies, and the operational and market-oriented outcomes from the ISO 9001 certification. Second, we study the different roles played by external auditors and certification bodies in affecting the outcomes achieved from the quality of implementation of the standard. Using a dataset comprising 537 firms from Australia and New Zealand that are ISO 9001 certified, our findings show that the quality of external auditors enhances operational outcomes as well as strengthens the relationship between ISO 9001 implementation and operational outcomes. This affirms the role of external auditors in the implementation of the standard. On the other hand, the reputation of certification bodies has a positive direct effect on market-oriented outcome, and its effect is strengthened by the quality of ISO 9001 implementation. The findings, therefore, show the contrasting roles between external auditors and certification bodies in enhancing different outcomes of ISO 9001 adoption in terms of operational and market-oriented ones. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
14. Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor.
- Author
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Ngo, Thang, Nguyen, Dinh C., Pathirana, Pubudu N., Corben, Louise A., Delatycki, Martin B., Horne, Malcolm, Szmulewicz, David J., and Roberts, Melissa
- Subjects
DEEP learning ,CEREBELLAR ataxia ,DATA privacy ,EQUILIBRIUM testing ,MOTION capture (Cinematography) ,MOTION detectors - Abstract
Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been used to objectively diagnose and quantify the severity of CA. Although these approaches achieved high accuracy, large scale deployment will require large clinics and raises privacy concerns. In this study, we propose an image transformation-based approach to leverage the advantages of state-of-the-art deep learning with federated learning in diagnosing CA. We use motion capture sensors during the performance of a standard neurological balance test obtained from four geographically separated clinics. The recurrence plot, melspectrogram, and poincaré plot are three transformation techniques explored. Experimental results indicate that the recurrence plot yields the highest validation accuracy (86.69%) with MobileNetV2 model in diagnosing CA. The proposed scheme provides a practical solution with high diagnosis accuracy, removing the need for feature engineering and preserving data privacy for a large-scale deployment. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
15. Unraveling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks.
- Author
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John, Alka Rachel, Singh, Avinash K., Do, Tien-Thong Nguyen, Eidels, Ami, Nalivaiko, Eugene, Gavgani, Alireza Mazloumi, Brown, Scott, Bennett, Murray, Lal, Sara, Simpson, Ann M., Gustin, Sylvia M., Double, Kay, Walker, Frederick Rohan, Kleitman, Sabina, Morley, John, and Lin, Chin-Teng
- Subjects
HEART beat ,AIR traffic control ,PSYCHOLOGICAL typologies ,FORECASTING - Abstract
Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload. Air traffic control operators routinely work in such complex environments, and we designed tracking and collision prediction tasks to emulate their elementary tasks. The physiological response to the workload variations in these tasks was elucidated to untangle the impact of workload variations experienced by operators. Electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. Our findings indicate that variations in task load in both these tasks are sensitively reflected in EEG, eye activity and HRV data. Multiple regression results also show that operators’ performance in both tasks can be predicted using the corresponding EEG, eye activity and HRV data. The results also demonstrate that the brain dynamics during each of these tasks can be estimated from the corresponding eye activity, HRV and performance data. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just “when” but also “what” to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in complex work environments. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
16. Scenario and Sensitivity Based Stability Analysis of the High Renewable Future Grid.
- Author
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Marzooghi, Hesamoddin, Garmroodi, Mehdi, Verbic, Gregor, Ahmadyar, Ahmad Shabir, Liu, Ruidong, and Hill, David J.
- Subjects
RENEWABLE energy sources ,IMPACT strength - Abstract
It can be expected that the power systems of the future will be significantly different from today’s, especially due to increasing renewable energy sources (RESs), storage systems, and price-responsive users leading to large uncertainty and complexity. The operation of these future grids (FGs) at levels of renewable energy approaching 100% will require all the usual stability analysis along with new issues in a much more complex situation than has been encountered in the past. In fact, how close we can get to this desired level will likely be dependent on the assessed stability limits. Therefore, in this study, we use a novel scenario-sensitivity-contingency based framework to evaluate the system stability along possible evolution pathways towards high renewable FGs. As a case study, we carry out our studies based on proposed future scenarios and sensitivities for the Australian FG. Using a simulation platform that encompasses market simulation, load flow calculation and stability assessment altogether, the impact of grid strength, level of prosumers, and utility storage on the stability of the FG is studied and quantified indices for long term stability have been devised. The results of this study enable us to address the underlying stability issues of the FGs. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
17. Embroidered Ground Planes for Wearable Antennas.
- Author
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Pinapati, Sree Pramod, Chen, Shengjian Jammy, Brittain, Joshua, Caldow, Adrian, and Fumeaux, Christophe
- Subjects
WEARABLE antennas ,EMBROIDERY ,ANTENNAS (Electronics) - Abstract
Various embroidered structures with differing amounts of stitch spacing, stitch density, and various stitching patterns are characterized through scattering experiments. From the scattering measurements, an effective sheet resistance is determined for a variety of embroidery parameters. Based on observations from the characterization procedure, several hybrid ground planes incorporating both computerized embroidery and metallized fabric are then realized and compared in view of their applications to textile antennas. The main contribution of the current study is then to provide a practical means of realizing selectively embroidered antenna structures that can serve as a viable, if not equivalent, replacement to purely metallized fabric-based antennas. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
18. Two-Tier Cache-Aided Full-Duplex Hybrid Satellite–Terrestrial Communication Networks.
- Author
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Ngo, Quynh Tu, Phan, Khoa Tran, Xiang, Wei, Mahmood, Abdun, and Slay, Jill
- Subjects
TELECOMMUNICATION systems ,CACHE memory ,FEMTOCELLS ,TELECOMMUNICATION satellites ,LOW earth orbit satellites ,INTERNET of things ,INTERNET access ,EARTH stations - Abstract
Enabling global Internet access is challenging for cellular-based Internet of Things (IoT) due to the limited range of terrestrial network services. One viable solution is to deploy IoT over satellite systems for coverage extension. However, operating a hybrid satellite–terrestrial network might incur high satellite bandwidth consumption and excessive service latency. Aiming to reduce the content delivery latency from the Internet-connected gateway to the users, this article proposes a two-tier cache-enabled model with full-duplex transmissions where content caches are deployed at the satellite and ground station. A closed-form solution for the successful delivery probability (SDP) of the files is derived considering the requested content distributions and channel statistics. Then, the SDP performance under common caching policies can be evaluated. The results are also used to optimize cache placement under caching capacity constraints. Numerical results demonstrate the performance improvements of the proposed system over those of single-tier cache-aided and half-duplex transmission systems. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
19. A Novel Optical Assay System for Bilirubin Concentration Measurement in Whole Blood.
- Author
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Ndabakuranye, Jean Pierre, Rajapaksa, Anushi E., Burchall, Genia, Li, Shiqiang, Prawer, Steven, and Ahnood, Arman
- Subjects
BILIRUBIN ,ELECTRONIC equipment ,HEALTH facilities ,DIAGNOSTIC imaging - Abstract
As a biomarker for liver disease, bilirubin has been utilized in prognostic scoring systems for cirrhosis. While laboratory-based methods are used to determine bilirubin levels in clinical settings, they do not readily lend themselves to applications outside of hospitals. Consequently, bilirubin monitoring for cirrhotic patients is often performed only intermittently; thus, episodes requiring clinical interventions could be missed. This work investigates the feasibility of measuring bilirubin concentration in whole porcine blood samples using dual-wavelength transmission measurement. A compact and low-cost dual-wavelength transmission measurement setup is developed and optimized to measure whole blood bilirubin concentrations. Using small volumes of whole porcine blood (72 µL), we measured the bilirubin concentration within a range corresponding to healthy individuals and cirrhotic patients (1.2–30 mg/dL). We demonstrate that bilirubin levels can be estimated with a positive correlation (R-square > 0.95) and an accuracy of ±1.7 mg/dL, with higher reliability in cirrhotic bilirubin concentrations (> 4 mg/dL) – critical for high-risk patients. The optical and electronic components utilized are economical and can be readily integrated into a miniature, low-cost, and user-friendly system. This could provide a pathway for point-of-care monitoring of blood bilirubin outside of medical facilities (e.g., patient's home). [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
20. Scaled Tracking Consensus in Discrete-Time Second-Order Multiagent Systems With Random Packet Dropouts.
- Author
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Shi, Lei, Zheng, Wei Xing, Shao, Jinliang, and Cheng, Yuhua
- Subjects
ARTIFICIAL satellite tracking ,RANDOM matrices ,INDEPENDENT variables ,COMPUTER simulation ,MULTIAGENT systems - Abstract
This article focuses on the issue of scaled tracking consensus for discrete-time second-order multiagent systems under random packet dropouts, where the cases with a static leader and a dynamic leader are considered, respectively. The scaled tracking consensus means that all agents reach a consensus value determined by the leader but with different scales, and the phenomenon of packet dropout on each communication link is described as a Bernoulli variable independent of other communication links. By virtue of random environment-based scaled consensus algorithms, it is shown how to reconstruct the original system into augmented error systems with random coefficient matrices. With the kind assistance of substochastic matrix and super-stochastic matrix, sufficient conditions for the cases with a static leader and a dynamic leader are derived, respectively. Moreover, computer simulations are performed to demonstrate the dynamics of network agents under random packet dropouts. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
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