Capsiate Intake with Exercise Training Additively Reduces Fat Deposition in Mice on a High-Fat Diet,but Not without Exercise Training

While exercise training (ET) is an efficient strategy to manage obesity, it is recommended with a dietary plan to maximize the antiobesity functions owing to a compensational increase in energy intake. Capsiate is a notable bioactive compound for managing obesity owing to its capacity to increase energy expenditure. We aimed to examine whether the antiobesity effects of ET can be further enhanced by capsiate intake (CI) and determine its effects on resting energy expenditure and metabolic molecules. Mice were randomly divided into four groups (n = 8 per group) and fed high-fat diet. Mild-intensity treadmill ET was conducted five times/week; capsiate (10 mg/kg) was orally administered daily. After 8 weeks, resting metabolic rate and metabolic molecules were analyzed. ET with CI additively reduced the abdominal fat rate by 18% and solely upregulated beta-3-adrenoceptors in adipose tissue (p = 0.013) but did not affect the metabolic molecules in skeletal muscles. Surprisingly, CI without ET significantly increased the abdominal fat rate (p = 0.001) and reduced energy expenditure by 9%. Therefore, capsiate could be a candidate compound for maximizing the antiobesity effects of ET by upregulating beta-3-adrenoceptors in adipose tissue, but CI without ET may not be beneficial in managing obesity.     

Design and analysis of cooperative wireless data access algorithms in multi-radio wireless networks

In the future, most mobile nodes will have multiple radio interfaces, and this feature can be exploited to reduce the transmission cost in wireless data access applications. In this work, we propose cooperative poll-each-read (CoopPER) and cooperative callback (CoopCB) wireless data access algorithms with strong consistency in multi-radio wireless networks. In addition, we investigate CoopPER and CoopCB in heterogeneous wireless networks where CoopPER and CoopCB nodes are mixed. Extensive simulations are done to show the effects of access-to-update ratio, data access pattern, cache size, and cooperation range. Simulation results demonstrate that CoopPER and CoopCB can significantly reduce the expensive transmission cost over wireless links.     

Hardware design of motion data decoding process for H.264/AVC

In H.264/AVC, motion data can be basically derived by the following two schemes: one is a typical spatial prediction scheme based on the DPCM and the other is a sophisticated spatiotemporal prediction scheme for the skipped motion data, formally referred to as a direct mode. We verified through instruction level profiling that when these schemes are combined with various H.264/AVC coding techniques, the computational burden to derive the motion data could be considerably aggravated. Specifically, its computational complexity amounts to maximally 55% of that of the overall syntax parsing process. In this paper, we aim at an efficient hardware design of the motion data decoding process for H.264/AVC, for which all the key design considerations are addressed in detail and respective rational answers are presented. As comparing the resulting hardware design with the processor-based solution, its effectiveness was clearly demonstrated. The proposed design was implemented with 43.2 K logic gates and three on-chip memories of 3584 bits using Samsung Semiconductor’s Standard Cell Library in 65 nm L6LP process technology (SS65LP), and was capable of operating the H.264/AVC high-profile video bitstream of 1080p@60fps at 100 MHz consuming 843 μW.     

Morphogenic inspired self-organization control of unmanned aerial swarm robots

A central issue in distributed formation of swarm is enabling agents with only a local view of their environment to take actions that advance global system objectives (emergence of collective behavior). This paper describes a bio-inspired control algorithm using pheromone for coordinating a swarm of identical flying agents to spatially self-organize into arbitrary shapes using local communication maintaining a certain level of density. Development of morphological features such as the fine formation of particles, hollow particles, cracks in particles, and the evolution of the structure are used as illustrative examples. Distributed formation of swarming with no coordinated agreement or positioning information is an interesting research area because the global behaviors must emerge from many diverse local interactions. Different from most existing distributed control, the proposed approach considers the topological structure of the organization, supports dynamic reconfiguration and self-organization. This paper presents the experimental results on simulating in the forming of arbitrary shape, and also describes a analytic aspect of our model comparing with behavioral performances.

     

Tunnel lane‐positioning system for autonomous driving cars using LED chromaticity and fuzzy logic system

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three‐lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.     

Advanced Hybrid Particle‐Grid Method with Sub‐Grid Particle Correction

This paper proposes a novel hybrid particle‐grid approach to liquid simulation, which uses the fluid‐implicit‐particle (FLIP) method to resolve the liquid motion and a grid‐based particle correction method to complement FLIP. The correction process addresses the high‐frequency errors in FLIP ensuring that the particles are properly distributed. The proposed approach enables the corrective procedure to avoid directly processing the particle relationships and supports flexible corrective forces. The proposed technique effectively and efficiently improves the distribution of the particles and therefore enhances the overall simulation quality. The experimental results confirm that the technique is able to conserve the liquid volume and to produce dynamic surface motions, thin liquid sheets, and smooth surfaces without disturbing artifacts such as bumpy noise.     

Modularized multimedia framework for multi-modal and multi-functional interactions

Smart Architectural Surface is a novel and highly integrated planar construct for diversified smart home services with networked smart cell units equipped with various sensing, cognition and actuation capabilities that would allow run-time polymorphism as the basis for functional changes for various event-driven operation scenarios. The SAS system can demonstrate the outcomes of collective intelligence that are mediated by various multi-modal interactions. Current SAS prototype is capable of polymorphous functional changes for dynamically adjustable electronic wallpaper, location/distance-aware video conferencing, personalized information browser, and automatic responses to various unintended events. Future applications would harness machine learning and machine vision techniques and will explore the advantages of having computational ecology of its digital modular units constituting smart wall system for multi-modal and multi-functional interactions.