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Holographic Optical Elements (HOEs) employ refractive index (RI) modulation to manipulate light, establishing their widespread application in augmented and virtual reality technologies. Despite significant strides in HOEs' fabrication, a comprehensive 3D examination and measurement of these elements remain largely unexplored. This study targets this void by conducting an in‐depth exploration of the 3D RI distributions of volume holographic gratings (VHGs), a quintessential representative of HOEs. Direct tomographic measurements of the 3D RI distributions within millimeter‐scale VHGs are performed at a spatial resolution of 156 nm × 156 nm × 1.2 µm and an RI precision of 2×10−4. This level of precision facilitates a systematic high‐resolution characterization of VHGs. The findings present a substantial evolution from traditional measurement techniques and promise to considerably advance the evaluation of intricate HOE structures and refine the corresponding fabrication processes. [ABSTRACT FROM AUTHOR]

Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite and climate data, this research aims to enhance the accuracy and resolution of soil moisture estimation, enabling more effective agricultural planning, irrigation management, and environmental monitoring. Five ML models, including linear regression, support vector machines, decision trees, random forests, and long short-term memory networks (LSTM), are evaluated and compared using real-world data from multiple geographical regions, which includes a dataset from NASA's SMAP project, supplemented by climate data, which employs both active and passive sensors for data collection. The outcomes demonstrate that the LSTM model consistently outperforms other ML algorithms across various evaluation metrics, highlighting the effectiveness of WSN-driven approaches to soil moisture estimation. The study contributes to the advancement of soil moisture monitoring technologies, offering insights into the potential of WSNs combined with ML and DL for sustainable agriculture and environmental management practices. [ABSTRACT FROM AUTHOR]

Background: The stability index estimation algorithm was derived and applied to develop and implement a balance ability diagnosis system that can be used in daily life. Methods: The system integrated an approach based on sensory function interaction, called the clinical test of sensory interaction with balance. A capacitance and resistance sensing type force mat was fabricated, and a stability index prediction algorithm was developed and applied using the center of pressure variables. The stability index prediction algorithm derived a center of pressure variable for 103 elderly people by Nintendo Wii Balance Board to predict the stability index of the balance system (Biodex SD), and the accuracy of this approach was confirmed. Results: As a result of testing with the test set, the linear regression model confirmed that the r-value ranged between 0.943 and 0.983. To confirm the similarity between the WBB and the flexible force mat, each measured center of pressure value was inputted and calculated in the developed regression model, and the result of the correlation coefficient validation confirmed an r-value of 0.96. Conclusion: The system developed in this study will be applicable to daily life in the home in the form of a floor mat. [ABSTRACT FROM AUTHOR]

This study investigates the potential of micron-sized Bi as an alloy-type anode material for lithium-ion batteries (LIBs). Compared to the limited capacity of conventional anode materials, Bi offers a high theoretical volumetric capacity of 3800 mA h cm−3. We utilized commercial micron-sized Bi powder and a conventional method to prepare Bi electrodes. Remarkably, the Bi anode exhibited excellent cycling stability with a capacity retention of 94% after 1000 cycles when using a tetrahydrofuran (THF)-based electrolyte. During charge/discharge cycling, the Bi particles initially underwent pulverization but subsequently formed a porous structure through room-temperature sintering, showcasing a self-healing phenomenon. Importantly, the pulverization of the alloy-type anode did not contribute significantly to degradation during cycling. This study presents the first evidence of self-healing from pulverization in alloy-type anodes for LIBs. We successfully fabricated a full cell by combining the Bi anode with a lithium iron phosphate (LFP; Li4FePO4) cathode. Notably, the results demonstrate the promise of micron-sized Bi without surface coating or nanostructuring as an anode material for LIBs. Additionally, the self-healing concept explored here holds potential for application to other alloy-type anodes in LIBs, providing an avenue for further advancements in next-generation battery systems. [ABSTRACT FROM AUTHOR]

KubeEdge is an open-source platform that orchestrates containerized Internet of Things (IoT) application services in IoT edge computing environments. Based on Kubernetes, it supports heterogeneous IoT device protocols on edge nodes and provides various functions necessary to build edge computing infrastructure, such as network management between cloud and edge nodes. However, the resulting cloud-based systems are subject to several limitations. In this study, we evaluated the performance of KubeEdge in terms of the computational resource distribution and delay between edge nodes. We found that forwarding traffic between edge nodes degrades the throughput of clusters and causes service delay in edge computing environments. Based on these results, we proposed a local scheduling scheme that handles user traffic locally at each edge node. The performance evaluation results revealed that local scheduling outperforms the existing load-balancing algorithm in the edge computing environment. [ABSTRACT FROM AUTHOR]

The Wii balance board (WBB) is a simplified force plate system used to evaluate the balancing ability of the elderly via a sensory interaction task to confirm a significant standing balance index. The accuracy of this system has been verified in previous studies. In this study, an instrumented and modified clinical test of sensory interaction on balance (i-mCTSIB) was performed on 84 elderly subjects, and the variables for center of pressure (CoP) were calculated using WBB for each task condition. The results indicate that the visual condition has a significant effect on the sway proprioceptive sensory variables with a foam condition as their complexity increases. In addition, the correlation between the variable and Berg Balance Scale was not confirmed since CTSIB is a sensory interaction on balance ability. Therefore, WBB can be used to evaluate balancing ability based on sensory interactions consisting of the surface condition. [ABSTRACT FROM AUTHOR]

Atherosclerotic plaques with high likelihood of rupture often show local temperature increase with respect to the surrounding arterial wall temperature. In this work, atherosclerotic plaque temperature was numerically determined during the different levels of blood flow reduction produced by the introduction of catheters at the vessel lumen. The temperature was calculated by solving the energy equation and the Navier-Stokes equations in 2D idealized arterial models. Arterial wall temperature depends on three basic factors: metabolic activity of the inflammatory cells embedded in the plaque, heat convection due to luminal blood flow, and heat conduction through the arterial wall and plaque. The calculations performed serve to simulate transient blood flow reduction produced by the presence of thermography catheters used to measure arterial wall temperature. The calculations estimate the spatial and temporal alterations in the cooling effect of blood flow and plaque temperature during the measurement process. The mathematical model developed provides a tool for analyzing the contribution of factors known to affect heat transfer at the plaque surface. Blood flow reduction leads to a nonuniform temperature increase ranging from 0.1[degrees]C to 0.25[degrees]Celsius in the plaque/lumen interface of the arterial geometries considered in this study. The temperature variation as well as the Nusselt number calculated along the plaque surface strongly depended on the arterial geometry and distribution of inflammatory cells. The calculations indicate that the minimum required time to obtain a steady temperature profile after arterial occlusion is 6 s. It was seen that in arteries with geometries involving bends, the temperature profiles appear asymmetrical and lean toward the downstream edge of the plaque. Keywords: atherosclerotic plaque, arterial wall temperature, blood flow occlusion, mathematical models

Edge/fog computing is a new computing paradigm where fully distributed fog/edge nodes located near end devices provide computing resources. The article "Distributed Agent-Based Orchestrator Model for Fog Computing" by Agnius Liutkevicius et al. [[1]] presents a distributed agent-based orchestrator model that enables flexible service provisioning in a dynamic fog computing environment, accounting for the resource constraints and security levels of fog nodes. By analyzing, filtering, and processing at local fog/edge nodes instead of transferring tremendous amounts of data to centralized cloud servers, fog/edge computing can significantly reduce processing delay and network traffic. [Extracted from the article]

Kubernetes (K8s) is expected to be a key container orchestration tool for edge computing infrastructures owing to its various features for supporting container deployment and dynamic resource management. For example, its horizontal pod autoscaling feature provides service availability and scalability by increasing the number of replicas. kube-proxy provides traffic load-balancing between replicas by distributing client requests equally to all pods (replicas) of an application in a K8s cluster. However, this approach can result in long delays when requests are forwarded to remote workers, especially in edge computing environments where worker nodes are geographically dispersed. Moreover, if the receiving worker is overloaded, the request-processing delay can increase significantly. To overcome these limitations, this paper proposes an enhanced load balancer called resource adaptive proxy (RAP). RAP periodically monitors the resource status of each pod and the network status among worker nodes to aid in load-balancing decisions. Furthermore, it preferentially handles requests locally to the maximum extent possible. If the local worker node is overloaded, RAP forwards its requests to the best node in the cluster while considering resource availability. Our experimental results demonstrated that RAP could significantly improve throughput and reduce request latency compared with the default load-balancing mechanism of K8s. [ABSTRACT FROM AUTHOR]

In handwriting recognition research, a public image dataset is necessary to evaluate algorithm correctness and runtime performance. Unfortunately, in existing Thai language script image datasets, there is a lack of variety of standard handwriting types. This paper focuses on a new offline Thai handwriting image dataset named Burapha-TH. The dataset has 68 character classes, 10 digit classes, and 320 syllable classes. For constructing the dataset, 1072 Thai native speakers wrote on collection datasheets that were then digitized using a 300 dpi scanner. De-skewing, detection box and segmentation algorithms were applied to the raw scans for image extraction. The experiment used different deep convolutional models with the proposed dataset. The result shows that the VGG-13 model (with batch normalization) achieved accuracy rates of 95.00%, 98.29%, and 96.16% on character, digit, and syllable classes, respectively. The Burapha-TH dataset, unlike all other known Thai handwriting datasets, retains existing noise, the white background, and all artifacts generated by scanning. This comprehensive, raw, and more realistic dataset will be helpful for a variety of research purposes in the future. [ABSTRACT FROM AUTHOR]

Among the flooding-based time synchronization protocols in wireless sensor networks, rapid-flooding outperforms slow-flooding in terms of synchronization speed. However, sometimes it is not realistic to apply rapid-flooding in dense or low-duty cycle networks due to its operational constraint that timing messages must be forwarded immediately after being received. On the contrary, slow-flooding protocols are free from this operational constraint, but they have a fundamental limitation that their convergence time increases with the size of the network. In this letter, we prove that this limitation can be overcome by sharing the compensated skew and timing information to the next hop nodes so that they can all be synchronized in the same round. The evaluation results demonstrate that we can achieve a comparable convergence speed of rapid-flooding protocols with the slow-flooding-based mechanism and can provide better accuracy for network-wide and per-hop synchronization. [ABSTRACT FROM AUTHOR]

With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices. EdgeX Foundry is a representative open-source-based IoT gateway platform, providing various IoT protocol services and interoperability between them. However, due to the absence of container orchestration technology, such as automated deployment and dynamic resource management for application services, EdgeX Foundry has fundamental limitations of a potential edge computing platform. In this paper, we propose EdgeX over Kubernetes, which enables remote service deployment and autoscaling to application services by running EdgeX Foundry over Kubernetes, which is a product-grade container orchestration tool. Experimental evaluation results prove that the proposed platform increases manageability through the remote deployment of application services and improves the throughput of the system and service quality with real-time monitoring and autoscaling. [ABSTRACT FROM AUTHOR]

Abstract Background This paper presents calculations of the temperature distribution in an atherosclerotic plaque experiencing an inflammatory process; it analyzes the presence of hot spots in the plaque region and their relationship to blood flow, arterial geometry, and inflammatory cell distribution. Determination of the plaque temperature has become an important topic because plaques showing a temperature inhomogeneity have a higher likelihood of rupture. As a result, monitoring plaque temperature and knowing the factors affecting it can help in the prevention of sudden rupture. Methods The transient temperature profile in inflamed atherosclerotic plaques is calculated by solving an energy equation and the Navier-Stokes equations in 2D idealized arterial models of a bending artery and an arterial bifurcation. For obtaining the numerical solution, the commercial package COMSOL 3.2 was used. The calculations correspond to a parametric study where arterial type and size, as well as plaque geometry and composition, are varied. These calculations are used to analyze the contribution of different factors affecting arterial wall temperature measurements. The main factors considered are the metabolic heat production of inflammatory cells, atherosclerotic plaque length lp, inflammatory cell layer length lmp, and inflammatory cell layer thickness dmp. Results The calculations indicate that the best location to perform the temperature measurement is at the back region of the plaque (0.5 ≤ l/lp ≤ 0.7). The location of the maximum temperature, or hot spot, at the plaque surface can move during the cardiac cycle depending on the arterial geometry and is a direct result of the blood flow pattern. For the bending artery, the hot spot moves 0.6 millimeters along the longitudinal direction; for the arterial bifurcation, the hot spot is concentrated at a single location due to the flow recirculation observed at both ends of the plaque. Focusing on the thermal history of different points selected at the plaque surface, it is seen that during the cardiac cycle the temperature at a point located at l/lp = 0.7 can change between 0.5 and 0.1 degrees Celsius for the bending artery, while no significant variation is observed in the arterial bifurcation. Calculations performed for different values of inflammatory cell layer thickness dmp indicate the same behavior reported experimentally; that corresponds to an increase in the maximum temperature observed, which for the bending artery ranges from 0.6 to 2.0 degrees Celsius, for dmp = 25 and 100 micrometers, respectively. Conclusion The results indicate that direct temperature measurements should be taken (1) as close as possible to the plaque/lumen surface, as the calculations show a significant drop in temperature within 120 micrometers from the plaque surface; (2) in the presence of blood flow, temperature measurement should be performed in the downstream edge of the plaque, as it shows higher temperature independently of the arterial geometry; and (3) it is necessary to perform measurements at a sampling rate that is higher than the cardiac cycle; the measurement should be extended through several cardiac cycles, as variations of up to 0.7 degrees Celsius were observed at l/lp = 0.7 for the bending artery.

Container-based virtualization has recently been flourishing due to its ease of deployment and flexibility of resource provisioning. Kubernetes, a well-known open source project, is an orchestration platform for containerized applications. Herein, applications can have multiple replicas to provide high scalability and availability, but some applications for stateful service require a leader to be elected to maintain consistency and coordinate tasks among the replicas. In this article, the Kubernetes architecture is first analyzed by focusing on load balancing, a leader election algorithm, and a leader-based consistency maintenance mechanism. Then we address the following challenges: the leader has heavy loads due to its inherent design, and the Kubernetes leader election algorithm cannot evenly distribute the leader throughout nodes. Finally, experimental results are provided to prove the importance of leader distribution throughout nodes in the cluster for highly scalable load balancing. [ABSTRACT FROM AUTHOR]

Byline: Taehong Kim, Wonkyu Moon, Sungsoo Kim Influences of the shapes of spring leaves in a progressive multi-leaf spring were investigated using the semi-analytic model based on the Euler beam theory and the FEM model using ABAQUS. The trends in shifting of the locations of the contact point are found to change with the shapes of spring leaves. A change in the shapes of the spring leaves causes a change in the transition load of the stiffness of a progressive multi-leaf spring. If there is a quantum jump of the contact point locations, a noise, which was absent, can be generated. It is suggested from the analyses based on the models and verified experimentally that the noise is generated by a small collision between the main and the help spring leaves when the contact point between them is shifted to a location at a finite distance. The influences of the leaf shape can be predicted more efficiently with the Euler beam model used in this investigation.

Air pollution has become a serious environmental problem causing severe consequences in our ecology, climate, health, and urban development. Effective and efficient monitoring and mitigation of air pollution require a comprehensive understanding of the air pollution process through a reliable database carrying important information about the spatiotemporal variations of air pollutant concentrations at various spatial and temporal scales. Traditional analysis suffers from the severe insufficiency of data collected by only a few stations. In this study, we propose a rigorous framework for the integration of air pollutant concentration data coming from the ground-based stations, which are spatially sparse but temporally dense, and mobile sensors, which are spatially dense but temporally sparse. Based on the integrated database which is relatively dense in space and time, we then estimate air pollutant concentrations for given location and time by applying a two-step local regression model to the data. This study advances the frontier of basic research in air pollution monitoring via the integration of station and mobile sensors and sets up the stage for further research on other spatiotemporal problems involving multi-source and multi-scale information. [ABSTRACT FROM AUTHOR]

Software defined networking controller platforms support clustering architectures to provide scalability and availability to large-scale carrier-grade networks. OpenDaylight, a well-known open source project, provides a clustering and distributed datastore architecture. The datastore is distributed into shards such that a subset of the shards can be located in any cluster member. To guarantee strong consistency in the datastore so all shard replicas have the same value, only the shard leader is responsible for accepting data updates. Even though OpenDaylight supports a distributed shard leader election algorithm, elected leaders are not distributed over the cluster members due to a lack of centralized control. Since update requests for the datastore are inherently concentrated in the leader, this results in unbalanced CPU usage of the controller cluster, as well as degradation of throughput in the distributed datastore. In this paper, we propose a shard leader distribution algorithm that maximizes the throughput of the distributed datastore by distributing the shard leaders to cluster members as evenly as possible. The shard leader distribution algorithm restricts the maximum number of leaders that a cluster member may have by monitoring the status of the shards within the cluster members. In the performance evaluation, we prove that shard leader distribution significantly improves the throughput of the datastore by load balancing data update requests to the cluster. [ABSTRACT FROM AUTHOR]

Although gallium-based liquid metals are attracting growing interest thanks to its potential applications in deformable, flexible electronic devices, challenges in fabrication associated with the high surface tension and oxide skin remain to be overcome. We report a novel fabrication technique for liquid metal circuits using dewetting. An excessively thin liquid film spontaneously shrinks on a substrate to reduce surface free energy. In the case of a thin liquid metal film on a substrate with microgrooves, the oxide on the microgroove wall and the additional viscous resistance delay the shrinkage in the grooves, which separates the liquid volume inside the microgrooves from the external volume. Utilizing this mechanism, we successfully produced 20- \mu \textm -thick conductive lines of eutectic gallium indium (EGaIn) on polydimethylsiloxane. This fabrication technique is simple, fast, and cost-effective and requires no top covering layer. The resultant metal lines show potentially applicable electrical resistance to flexible and stretchable electronic devices. [2017-0082] [ABSTRACT FROM PUBLISHER]

Software-defined networking is moving from its initial deployment in small-scale data center networks to large-scale carrier-grade networks. In such environments, high availability and scalability are two of the most prominent issues, and thus extensive work is ongoing. In this article, we first review the state of the art on high availability and scalability issues in SDN and investigate relevant open source activities. In particular, two well-known open source projects, OpenDaylight (ODL) and Open Network Operating System (ONOS), are analyzed in terms of high availability (i.e., network state database replication/synchronization and controller failover mechanisms) and scalability (i.e., network state database partition/ distribution and controller assignment mechanisms) issues. We also present experimental results on the flow rule installation/read throughput and the failover time upon a controller failure in ONOS and ODL, and identify open research challenges. [ABSTRACT FROM PUBLISHER]

The shortcut tree routing has been proposed to provide near optimal routing path as well as maintaining the advantages of the ZigBee tree routing, such as resource-free multi-hop routing capability. However, in spite of the efforts to provide an efficient and reliable protocol, the unicast routing itself has the fundamental limitation in wireless environment due to lossy, time-varying, and broadcast nature of wireless medium. For example, even one lossy link on a path may result in the failure of end-to-end packet delivery in wireless network environment. In this paper, we propose the opportunistic shortcut tree routing that combines the shortcut tree routing and the opportunistic routing. Instead of specifying a next hop node, the opportunistic shortcut tree routing allows the receiving nodes to compete to forward a packet with the priority of remaining hops. Since it has inherited advantages of both routing protocols, it can provide reliable packet delivery service without any resources for multi-hop routing and forwarder candidate selection for opportunistic routing. The performance evaluation proves that the opportunistic approach significantly enhances diverse network performances, while suppressing duplicate forwarding effectively with a metric of the remaining hops and the one-hop neighbor table. [ABSTRACT FROM PUBLISHER]