Coverage Performance Research Articles

Digital Twin Enhanced Multi-Agent Reinforcement Learning for Large-Scale Mobile Network Coverage Optimization

With the rapid advancement of communication technology and the exponential growth of mobile users, improving network coverage quality and throughput has become increasingly important. In particular, large-scale Base Station (BS) cooperative optimization has become a highly significant topic. BSs can adjust various parameters for high-quality communication, but automating this optimization remains challenging due to environmental sensitivity and interdependencies. Traditional methods for network optimization are constrained by the intricate nature of real-world environments. Further, Reinforcement Learning (RL) techniques, which are effective for configuration policies, encounter difficulties in intricate, high-dimensional wireless communication networks, especially in multi-agent cooperative optimization. To overcome these challenges, this article proposes the Enhanced Multi-Agent Proximal Policy Optimization (EMAPPO), which utilizes the capabilities of the UNet network to extract multi-spatial relationships among a massive number of network elements and employs the DiffPool network to efficiently depict the impact of large-scale action coordination among massive agents on coverage performance. To facilitate evaluation in communication optimization, we further introduce a high-fidelity digital twin-driven mobile network. Extensive experiments validate the effectiveness and superior performance of EMAPPO by utilizing the network digital twin. The results demonstrate significant improvements in signal coverage rate and network throughput compared to the competing methods.

A Novel Approach to Node Coverage Enhancement in Wireless Sensor Networks Using Walrus Optimization Algorithm

Wireless Sensor Networks (WSNs) are crucial components of modern technology, supporting applications like healthcare, industrial automation, and environmental monitoring. This research aims to design intelligent and adaptive sensor networks by integrating metaheuristics with node coverage optimization in WSNs. By incorporating metaheuristics and optimizing node coverage, WSNs can become more resilient and robust, leading to the development of self-adapting, self-organizing networks capable of efficiently covering dynamic and diverse environments. This research introduces the Walrus Optimization Algorithm for Node Coverage Enhancement in WSNs, called the WaOA-NCEWSN technique. The primary goal of this technique is to optimize the coverage of a target region using a limited number of Sensor Nodes (SNs) and by improving their placement. The WaOA is inspired by walrus behaviours like feeding, migrating, breeding, escaping, roosting, and gathering in response to environmental signals. The WaOA-NCEWSN technique uses an objective function that defines the coverage ratio, representing the maximum probability of coverage in a 2D-WSN monitoring area. Comparative analysis with other models using 50, 75, 100, and 200 nodes shows that the WaOA-NCEWSN technique performs better. The compilation times for the WaOA-NCEWSN technique are 5.14s, 6.48s, 6.54s, and 7.47s for 50, 75, 100, and 200 nodes, respectively. Experimental results indicate that the WaOA-NCEWSN technique offers superior coverage performance compared to other models.

Optimized uniform sampling and validation of fiber tracts from magnetic resonance tractography for in vivo architectural measurement of human forearm muscles.

In vivo muscle architectural parameters can be calculated from the fiber tracts using magnetic resonance (MR) tractography. However, the reconstructed tracts may be unevenly distributed within the muscle volume and there lacks commonly used metric to quantitatively evaluate the validity of the tracts. Our objective is to measure forearm muscle architecture by uniformly sampling fiber tracts from the candidate streamlines in MR tractography and validate the reconstructed fiber tracts qualitatively and quantitatively. We proposed farthest streamline sampling (FSS) to uniformly sample fiber tracts from the candidate streamlines. The method was evaluated on the MR data acquired from 12 healthy subjects for 17 forearm muscles and was compared with two conventional methods through uniform coverage performance. Anatomical correctness was verified by: 1. visually assessing fiber orientation, 2. checking whether architectural parameters were within physiological ranges and 3. classifying architectural types. The proposed FSS yielded optimal uniform coverage performance among the three methods (P<0.05). FSS reduced the sampling of long tracts (10% fiber length reduction, P<0.05), and the estimated architectural parameters were within the physiological ranges (P<0.05). The tractography visually matched cadaveric specimens. The architectural types of 16 muscles were correctly classified except for the palmaris longus, which exhibited a linear arrangement of fiber endpoints (R2 = 0.95±0.02, P<0.001). The proposed FSS method reconstructed uniformly distributed fiber tracts and the anatomical correctness of the reconstructed tracts was verified. The novel methods allow for accurate in vivo muscle architectural measurement, which was demonstrated through the characterization of architectural properties in human forearm muscles.

TestCompareR: an R package to compare two binary diagnostic tests using paired data

Background Binary diagnostic tests are commonly used in medicine to answer a question about a patient’s clinical status, most commonly, do they or do they not have some disease. Recent advances in statistical methodologies for performing inferential statistics to compare commonly used test metrics for two diagnostic tests have not yet been implemented in a statistical package. Methods Up-to-date statistical methods to compare the test metrics achieved by two binary diagnostic tests are implemented in the new R package testCompareR. The output and efficiency of testCompareR is compared to the only other available package which performs this function, DTComPair, as well as an open-source program, compbdt, using a motivating example. Results testCompareR achieves similar results to DTComPair using statistical methods with improved coverage and asymptotic performance. Further, testCompareR is faster than the currently available package and requires fewer pre-processing steps in order to produce accurate results. Conclusions testCompareR provides a new tool to compare the test metrics for two binary diagnostic tests compared with the gold standard. This tool allows flexible inputs, which minimises the need for data pre-processing, and operates in very few steps, so that it is easy to use even for those less experienced with R. testCompareR achieves results comparable to those computed by DTComPair, using optimised statistical methods and with improved computational efficiency.

Designer Electrocatalysts for the Oxygen Reduction Reaction with Controlled Platinum Nanoparticle Locality

To achieve global deployment of proton exchange membrane technologies, growing efforts in platinum group metals (PGM) recycling must be coupled with substantial improvements in the durability of PGM catalysts. This need for longevity is emphasized by the establishment of the Million Mile Fuel Cell Truck (M2FCT) Department of Energy consortium, devised with durability at its core. So far, improvements in the durability of Pt and Pt-alloy catalysts have focused on surface modifications by small organic molecules (such as melamine), formation of Pt skins (for alloys), and cell design [1–3]. However, the literature transpires a certain reluctance to exploring the interaction between the active material and the often not fully understood carbon support. A handful of studies directly address the effect of support morphology on durability, focusing on the ability of porous carbons to host nanoparticles inside (IN) and outside (OUT) of mesopores [4–7]. Still, the effect of IN vs. OUT is studied on different carbon supports—namely high surface area carbons (HSA) and solid carbons (such as Vulcan), respectively—thus coming short of decoupling nanoparticle locality from carbon support effects. Furthermore, the effects of nanoparticle locality on long-term durability remain unclear.To address these challenges, we present a new class of carbon supported Pt-based electrocatalysts with distinct nanoparticle localities. A methodology was developed to place nanoparticles at will on the inside or outside of carbon mesopores. Specialty carbon blacks from Cabot Corporation pre-production FCX series were used as supports. Synthesis protocols were tuned to ensure that nanoparticle size, crystallinity and loading were the same for IN and OUT catalysts; this way the effect of locality could be studied in isolation from all other parameters. Pt/C catalysts with nanoparticles IN or OUT of mesopores were prepared with Pt loadings of 20 and 40 wt% and shown to have ECSA and mass activity comparable to Pt/Vulcan (30 wt%) from Tanaka Kikinzoku (TKK). Pt-alloy catalysts with controlled nanoparticle locality were also prepared. We believe these materials can serve as model catalysts for long-term durability studies in membrane electrode assemblies. Specifically, given their carefully tailored structure, these catalysts can help address the question of whether placing nanoparticles in mesopores slows down their degradation. Especially for alloys, where degradation is more pronounced and complex, controlling parameters such as carbon structure and nanoparticle locality becomes even more important if we are to improve their durability.[1] H. Daimon, S.I. Yamazaki, M. Asahi, T. Ioroi, M. Inaba, A Strategy for Drastic Improvement in the Durability of Pt/C and PtCo/C Alloy Catalysts for the Oxygen Reduction Reaction by Melamine Surface Modification, ACS Catal. 12 (2022) 8976–8985. https://doi.org/10.1021/ACSCATAL.2C01942.[2] C. Wang, M. Chi, D. Li, D. Strmcnik, D. Van Der Vliet, G. Wang, V. Komanicky, K.C. Chang, A.P. Paulikas, D. Tripkovic, J. Pearson, K.L. More, N.M. Markovic, V.R. Stamenkovic, Design and synthesis of bimetallic electrocatalyst with multilayered Pt-skin surfaces, J Am Chem Soc. 133 (2011) 14396–14403. https://doi.org/10.1021/JA2047655/SUPPL_FILE/JA2047655_SI_001.PDF.[3] S. Liu, S. Hua, R. Lin, H. Wang, X. Cai, W. Ji, Improving the performance and durability of low Pt-loaded MEAs by adjusting the distribution positions of Pt particles in cathode catalyst layer, Energy. 253 (2022) 124201. https://doi.org/10.1016/J.ENERGY.2022.124201.[4] E. Padgett, N. Andrejevic, Z. Liu, A. Kongkanand, W. Gu, K. Moriyama, Y. Jiang, S. Kumaraguru, T.E. Moylan, R. Kukreja, D.A. Muller, Editors’ Choice—Connecting Fuel Cell Catalyst Nanostructure and Accessibility Using Quantitative Cryo-STEM Tomography, J Electrochem Soc. 165 (2018) F173. https://doi.org/10.1149/2.0541803JES.[5] E. Padgett, V. Yarlagadda, M.E. Holtz, M. Ko, B.D.A. Levin, R.S. Kukreja, J.M. Ziegelbauer, R.N. Andrews, J. Ilavsky, A. Kongkanand, D.A. Muller, Mitigation of PEM Fuel Cell Catalyst Degradation with Porous Carbon Supports, J Electrochem Soc. 166 (2019) F198–F207. https://doi.org/10.1149/2.0371904JES/XML.[6] Y.-C. Park, H. Tokiwa, K. Kakinuma, M. Watanabe, M. Uchida, Effects of carbon supports on Pt distribution, ionomer coverage and cathode performance for polymer electrolyte fuel cells, (2016). https://doi.org/10.1016/j.jpowsour.2016.02.091.[7] X. Tuaev, S. Rudi, P. Strasser, The impact of the morphology of the carbon support on the activity and stability of nanoparticle fuel cell catalysts, Catal Sci Technol. 6 (2016) 8276–8288. https://doi.org/10.1039/C6CY01679K. Figure 1

UAVs Revolutionizing Efficiency: Integrating DRL and Random Walrus for Enhanced Energy and Spectral Resource Management

The improvement of energy efficiency and spectral efficiency in networks is achieved by seamlessly integrating energy harvesting, cognitive radio technologies, and Non-Orthogonal Multiple Access (NOMA) techniques. These complementary strategies optimize resource usage and address challenges related to energy consumption. Additionally, the adaptability and versatility of Unmanned Aerial Vehicles (UAVs) offer innovative solutions for enhancing coverage performance, thereby improving connectivity, efficiency, and reliability. We introduce a novel approach called the Deep Reinforcement Learning-Random Walrus (DRL-RW) algorithm, which combines Deep Reinforcement Learning (DRL) with the Random Walrus optimization (RWO) technique for efficient spectrum resource allocation and energy harvesting management in dynamic environments. The DRL-RW algorithm enables UAVs to learn optimal spectrum-sharing strategies and energy harvesting policies, while the RWO enhances the algorithm's adaptability and speed in exploring diverse solutions. Simulation results demonstrate the effectiveness of the DRL-RW algorithm, showing significant improvements in several performance metrics, including reduced energy consumption, enhanced computation time, improved convergence, increased signal-to-noise ratio, higher throughput, extended network lifetime, and increased harvested energy. These findings underscore the efficacy of the DRL-RW approach in addressing challenges associated with energy management in cognitive radio networks. The integration of UAVs, NOMA networks, and this novel algorithm represents a promising direction for developing energy-efficient communication systems.

TestCompareR: an R package to compare two binary diagnostic tests using paired data.

Binary diagnostic tests are commonly used in medicine to answer a question about a patient's clinical status, most commonly, do they or do they not have some disease. Recent advances in statistical methodologies for performing inferential statistics to compare commonly used test metrics for two diagnostic tests have not yet been implemented in a robust statistical package. Up-to-date statistical methods to compare the test metrics achieved by two binary diagnostic tests are implemented in the new R package testCompareR. The output and efficiency of testCompareR is compared to the only other available package which performs this function, DTComPair, as well as an open-source program, compbdt, using a motivating example. testCompareR achieves similar results to DTComPair using statistical methods with improved coverage and asymptotic performance. Further, testCompareR is faster than the currently available package and requires fewer pre-processing steps in order to produce accurate results. testCompareR provides a new tool to compare the test metrics for two binary diagnostic tests compared with the gold standard. This tool allows flexible inputs, which minimises the need for data pre-processing, and operates in very few steps, so that it is easy to use even for those less experienced with R. testCompareR achieves results comparable to those computed by DTComPair, using optimised statistical methods and with improved computational efficiency.

TestCompareR: an R package to compare two binary diagnostic tests using paired data

Background Binary diagnostic tests are commonly used in medicine to answer a question about a patient’s clinical status, most commonly, do they or do they not have some disease. Recent advances in statistical methodologies for performing inferential statistics to compare commonly used test metrics for two diagnostic tests have not yet been implemented in a robust statistical package. Methods Up-to-date statistical methods to compare the test metrics achieved by two binary diagnostic tests are implemented in the new R package testCompareR. The output and efficiency of testCompareR is compared to the only other available package which performs this function, DTComPair, as well as an open-source program, compbdt, using a motivating example. Results testCompareR achieves similar results to DTComPair using statistical methods with improved coverage and asymptotic performance. Further, testCompareR is faster than the currently available package and requires fewer pre-processing steps in order to produce accurate results. Conclusions testCompareR provides a new tool to compare the test metrics for two binary diagnostic tests compared with the gold standard. This tool allows flexible inputs, which minimises the need for data pre-processing, and operates in very few steps, so that it is easy to use even for those less experienced with R. testCompareR achieves results comparable to those computed by DTComPair, using optimised statistical methods and with improved computational efficiency.

Letter to the Editor: Variant Coverage and Diagnostic Performance of Commercially Available DPYD Genotyping Tests in Brazil.

Letter to the Editor: Variant Coverage and Diagnostic Performance of Commercially Available DPYD Genotyping Tests in Brazil.

Based on coverage evaluation design method study of factor low-orbit infrared remote sensing constellation configuration

Abstract To satisfy the infrared detection coverage demands of Low Earth Orbit (LEO) satellites in global missile surveillance, we have devised a comprehensive evaluation system for global missile infrared remote sensing coverage performance. By referencing Walker’s extensive and uninterrupted global coverage constellation layout, we conducted a thorough analysis of various constellation configuration parameters. This analysis aimed to assess the coverage efficiency of differently configured LEO networking satellites. Following a detailed comparative analysis, we settled on an LEO infrared remote sensing constellation configuration featuring an orbit height of 1150 km and an orbit inclination of 60°. After an in-depth examination of the capabilities of the infrared remote sensing constellation and the characteristics of the detection zone, we constructed a Blind Spot Compensation Constellation. This was achieved by integrating four additional LEO satellites with a 0° orbit inclination to bolster coverage in low-latitude regions. Using our comprehensive coverage evaluation system, we rigorously evaluated the ground coverage capabilities of multiple constellations. Notably, the Blind Spot Compensation Constellation achieved impressive coverage, reaching 100%, and excelled particularly in the latitude belt of 20° or less. Although the Original Constellation performed better in the 40° latitude belt compared to the Blind Spot Compensation Constellation, it showed some deficiencies in coverage at a 50 km altitude. Specifically, it averaged 18.417 gaps per day, with a coverage rate slightly below 100%. However, it achieved full coverage at other altitudes. To validate our findings, we conducted scenario simulations. For missile targets, the Original Constellation offered a maximum coverage multiplicity of 6, with a total access duration of 4539.1 seconds. On the other hand, the Blind Spot Compensation Constellation boasted a maximum coverage multiplicity of 8, with a total access duration of 5465.9 seconds. Importantly, both constellations fully covered the missile’s entire 1056-second lifecycle, showcasing commendable performance. In conclusion, the LEO infrared remote sensing constellation and its complementary counterpart, developed and rigorously tested in this study, not only meet the demands of continuous global detection but also cater to the priority detection needs of diverse geographical regions.

Antenna Deployment Optimization for Coverage Performance Improvement in High-Speed Railway Communications

Antenna Deployment Optimization for Coverage Performance Improvement in High-Speed Railway Communications

Multi-Path Data Transmission System Based on 5G Communication Technology

Due to the current problems of 5G(5th Generation Mobile Communication Technology) networks such as discontinuous coverage, poor coverage performance, and insufficient uplink rate, the real-time transmission performance of 5G networks has been greatly affected, and cannot meet the growing needs of high-speed communication and applications based on the Internet of Things. This paper aims to improve the transmission effect of 5G communication technology by improving the algorithm. By analyzing the problems of existing 5G bandwidth estimation algorithm, this paper proposes a Westwood-based coupling adaptive bandwidth estimation algorithm, and describes the algorithm ideas involved in the algorithm point-by-point. Moreover, this paper uses adaptive bandwidth estimation algorithm to update the slow start threshold in the fast retransmission phase, which makes the congestion window size of path transmission more reasonable. Simulation results show that the congestion control algorithm proposed in this paper improves the accuracy of link bandwidth estimation to a certain extent, improves the link congestion situation and improves the throughput of multipath transmission links. This article can be applied to the algorithm in multipath data transmission to further improve data processing efficiency and processing speed.Therefore, the improved method in this paper can be used in the practice of 5G communication to further improve the efficiency of 5G communication.

Evaluating 4G Network Performance at UTeM Campus to Facilitate 5G Implementation in Malaysia

As Malaysia transitions to 5G technology, evaluating 4G coverage performance is essential for preparing the groundwork for advanced networks. This project focuses on assessing the radio communication link performance of 4G systems at the University Technical Malaysia Malacca (UTeM) campus. The goal is to assist Mobile Broadband (MBB) service providers in developing efficient long-term strategies for Malaysian university campuses and enhancing 4G coverage. The study conducted measurement campaigns and real-time performance analysis using the G-Net Track app, recording key metrics such as minimum RSRP (-115 dBm off-peak, -117 dBm peak), RSRQ (-18 dB off-peak, -17 dB peak), and average SNR (11.178 dB off-peak, 11.003 dB peak). Signal quality varied with 25.3% excellent and 4.5% poor in normal weather, and 21.8% excellent and 5.8% poor in rainy conditions. Proximity to the base station showed the best RSRP of -68 dBm at 56m and the worst at -110 dBm around 915m away. The study concludes that mobile network operator (MNO) performance is influenced by traffic load, weather conditions, and distance from the base station. Understanding these dynamics can help MBB service providers enhance coverage, reliability, and overall user experience on university campuses and beyond. Future research considering additional KPIs and environmental factors will further enrich these insights, supporting robust network planning and management.

Long-Term Outcomes of Collagen Matrix versus Subepithelial Connective Tissue in Root Coverage for Multiple Teeth: A Systematic Review and Meta-Analysis

Background: This study aimed to conduct a meta-analysis to assess the differences in the performance of root coverage between collagen matrix and subepithelial connective tissue. Methods: A comprehensive search using a combination of controlled vocabulary (MeSH) and free-text terms was undertaken by two reviewers to identify published systematic reviews. Three major electronic databases (Medline via PubMed, Cochrane database, and Embase) were searched up to October 2023. Results: Initially, five hundred and seventy-six articles were identified, but only nine studies met the criteria for inclusion in the meta-analysis. Meta-analysis showed that the pooled mean difference in mean root coverage of collagen matrix compared with subepithelial connective tissue was −0.48 (95% confidence interval of −0.69 to −0.26). The relative risk of complete root coverage of collagen matrix compared with subepithelial connective tissue was 0.68 (95% confidence interval, 0.49 to 0.94). The pooled mean difference in width of keratinized tissue of collagen matrix compared with subepithelial connective tissue was −0.75 (95% confidence interval of −1.25 to −0.26). Conclusions: The outcomes of this study revealed that subepithelial connective tissue generally exhibited superior performance. Nonetheless, the utilization of the coronally advanced flap with collagen matrix may yield comparable results in terms of the percentage of complete root coverage.

A Novel Two-dimensional Low-redundancy Array Design for Solar Radio Imaging

The radioheliograph is an extensive array of antennas operating on the principle of aperture synthesis to produce images of the Sun. The image acquired by the telescope results from convoluting the Sun’s true brightness distribution with the antenna array’s directional pattern. The imaging quality of the radioheliograph is affected by a multitude of factors, with the performance of the “dirty beam” being simply one component. Other factors such as imaging methods, calibration techniques, clean algorithms, and more also play a significant influence on the resulting image quality. As the layout of the antenna array directly affects the performance of the dirty beam, the design of an appropriate antenna configuration is critical to improving the imaging quality of the radioheliograph. Based on the actual needs of observing the Sun, this work optimized the antenna array design and proposed a two-dimensional low-redundancy array. The proposed array was compared with common T-shaped arrays, Y-shaped arrays, uniformly spaced circular arrays, and three-arm spiral arrays. Through simulations and experiments, their performance in terms of sampling point numbers, UV coverage area, beam-half width, sidelobe level, and performance in the absence of antennas are compared and analyzed. It was found that each of these arrays has its advantages, but the two-dimensional low-redundancy array proposed in this paper performs best in overall evaluation. It has the shortest imaging calculation time among the array types and is highly robust when antennas are missing, making it the most suitable choice.

Design and Implementation of Long Range Wide Area Networks for Future Industrial IoT Applications

Background: The evolution of Long Range Wide Area Networks (LoRaWAN) is a potential candidate for next generation networks for managing the massive number of devices in the Industrial Internet of Things (IIoT). LoRaWAN is more suitable for transmitting smaller intermittent data but using smaller bandwidth over a long distance. Objective: This research paper proposes to design a Low Power Wide Area Network (LPWAN) to provide long-range data transfer for Industrial IoT applications, especially for industrial sensor data. Methods: This research work deploys the experimental setup of LoRaWAN devices using LoRa gateways and Internet of Things network server to evaluate its performance for IIOT applications. Results: The deployment of this LoRaWAN has demonstrated its long range, low power, stability and low deployment cost through extensive performance evaluation carried out. LoRaWAN has been analyzed for its coverage and throughput performance. Conclusion: Through performance analysis, potential enhancements have been identified to overcome its shortcomings. This paper concludes the feasibility of deploying LoRaWAN technology for the future generation IIOT applications.

Dynamic switched crowding-based multi-objective particle swarm optimization algorithm for solving multi-objective AC-DC optimal power flow problem

In this paper, the multi-objective AC-DC optimal power flow (MO/AC-DC OPF) problem in the presence of renewable energy sources (RESs), flexible AC transmission system (FACTS) devices and multi-terminal direct current (MTDC) systems is introduced for the first time. Conflicting objective functions and the high complexity of the objective and constraint spaces are the main challenges in finding optimal solutions for MO/AC-DC OPF. To overcome these challenges, twelve different versions of the dynamic switched crowding-based multi-objective particle swarm optimization (DSC-MOPSO) algorithm are introduced in this paper. Studies on multimodal optimization problems have shown that all DSC-MOPSO versions have better performance metrics than the MOPSO algorithm. Using the developed DSC-MOPSO and its strong competitors, the Pareto-optimal solution sets of the MO/AC-DC OPF problem are investigated. In these investigations, the performances of the algorithms are tested for the minimization of dual and triple objectives such as fuel cost, voltage level deviation, emission and power loss in a modified IEEE 30-bus power grid. According to the simulation results, the proposed DSC-MOPSO achieved an improvement in fuel cost between 0.02 % and 5.05 % and a reduction in active power loss between 0.44 % and 30.74 % compared to its competitors. The Hypervolume (HV) performance metric was used to evaluate the Pareto-front coverage performance of DSC-MOPSO and other optimizers. The results from nine case studies of the MO/AC-DC OPF were statistically analyzed by the Friedman test according to the 1/HV metric. According to the Friedman test results, the rankings of DSC-MOPSO and MOMA are 1.984 and 3.079, respectively, ranking first and second among all competitors. Finally, in this study, feasible solutions for MO/AC-DC OPF problem are identified for the first time and the stability of competitive algorithms in finding these solutions is analyzed for the first time. The success rates and search times of DSC-MOPSO and MOMA algorithms in finding feasible solutions for MO/AC-DC OPF are 91.01 % (30.641 s) and 82.01 % (46.038 s), respectively.

A Method to Optimize Deployment of Directional Sensors for Coverage Enhancement in the Sensing Layer of IoT

Directional sensor networks are a widely used architecture in the sensing layer of the Internet of Things (IoT), which has excellent data collection and transmission capabilities. The coverage hole caused by random deployment of sensors is the main factor restricting the quality of data collection in the IoT sensing layer. Determining how to enhance coverage performance by repairing coverage holes is a very challenging task. To this end, we propose a node deployment optimization method to enhance the coverage performance of the IoT sensing layer. Firstly, with the goal of maximizing the effective coverage area, an improved particle swarm optimization (IPSO) algorithm is used to solve and obtain the optimal set of sensing directions. Secondly, we propose a repair path search method based on the improved sparrow search algorithm (ISSA), using the minimum exposure path (MEP) found as the repair path. Finally, a node scheduling algorithm is designed based on MEP to determine the optimal deployment location of mobile nodes and achieve coverage enhancement. The simulation results show that compared with existing algorithms, the proposed node deployment optimization method can significantly improve the coverage rate of the IoT sensing layer and reduce energy consumption during the redeployment process.

Experimental and numerical studies on spray cooling of a downward-facing surface under partial coverage of multi-nozzle sprays

A new experimental study (aka SPAYCOR-S2) on multi-nozzle spray cooling of a downward-facing heater surface is conducted on the SPAYCOR facility at KTH, to provide data assessing the feasibility of spray cooling for in-vessel melt retention (IVR) in light water reactors. It is intended to investigate the potential for reducing the number of nozzles for spray cooling of an 80 mm × 120 mm surface, from the 2 × 3 nozzle array in the previous study (Bandaru, 2021) to a 2 × 2 nozzle array in the present study. Given the same heater surface, the pitch-to-diameter ratio is enlarged in a 2 × 2 nozzle array, resulting a partial coverage of the spray cones of four nozzles, in contrast with the 2 × 3 nozzle array where the heater surface was fully covered by six-nozzle spray. The tests focus on the cooling performance of such partial coverage of multi-nozzle spray and the effects of heater surface’s inclination angle. The experimental results reveal that the inclination angle of the heat surface has a negligible impact on cooling capacity, although it is slightly higher on the surface inclined at 90° than on the surfaces inclined at 45° or 60°. The maximum steady heat flux of the 2 × 2 nozzle array at its minimum spray flowrate is determined as 1.96 MW/m2. A numerical study on the spray cooling of the 2 × 2 nozzle array is also performed with models in OpenFOAM, which are extended from our previous development (Fang, 2023) by adding models for thin-film boiling and conjugate heat transfer in solid. For validation of the numerical study, the spray cooling of the heater surface inclined at various degrees is simulated, and the results are compared with those of experiment. The simulation generally shows good correspondence with experiments.

A Comparative study of the Basel III liquidity framework’s “Liquidity Coverage Ratio”: Compliance and Performance between Islamic Banks and Conventional banks in the State of Kuwait

Aim of the Paper: To propose some recommendations based on the finding for the conventional and Islamic banks in the sample of the study and to submit the experience of the research sample, first, to all the relevant regulatory authorities who deal with the supervision and control of conventional and Islamic banks in their banking system and second, to the decision makers in the conventional and Islamic banks to gain their bank’s compliance and better performance of Liquidity Coverage Ratio.Study Design: Comparative study of Liquidity Coverage Ratio’s compliance and performance between 4 national Islamic banks and 4 national conventional banks.Sample and Data: The sample contains of 4 conventional and 4 Islamic banks in the Kuwaiti national banking system. The data were quantitative “LCR figures” of the sampled banks and were gathered from their official websites (secondary data).Results: Both the conventional and the Islamic banks showed that were compliant and had the same efficient and effective level of LCRs performanceConclusion: the paper presented recommendation on bank solo level, banking sector level, regulatory authority level and international organizations level.