Simulations of the dielectric constant of bonding materials and field emission properties of CNT cathodes

The effect of the dielectric constant (k) of bonding materials in a screen-printed carbon nanotube (CNT) cathode on the field enhancement factor was investigated for high-efficiency CNT cathodes using the ANSYS software. The values obtained by a simulation study were compared to the experimental results obtained for screen-printed CNT cathodes. The field enhancement factor increased as the dielectric constant decreased, reaching a maximum value at a dielectric constant of 1, the value for a vacuum. The findings indicate that the larger sheet resistance of the bonding materials, after the firing process, can be attributed to the larger emission current of the CNT cathode. From these results, it was concluded that the best bonding materials for screen-printed CNT cathodes should have a low dielectric constant and a high sheet resistance. This finding can be used as criteria for selecting bonding materials for use in CNT pastes for highly efficient CNT cathodes.     

Effect of change management capability in real-time environment: an information orientation perspective in supply chain management

Supply chain management (SCM) is an important strategic tool that requires careful planning and management. While the availability of real-time information is a critical aspect of an SCM system, it possesses a potential to disrupt supply chain participants. Thus, the success of an SCM system hinges on how well participants deal with changes taking place in a real-time environment. This study adopts the concept of the real-time enterprise to understand the role of change management on SCM performance based on the concept of the information orientation. The study empirically validated the role of change management on SCM performance.     

Protection of quantum correlations against decoherence

The protection of different quantum correlations, such as Bell nonlocality, quantum discord, and geometric quantum discord as trace distance against noise, is explored. By weak measurement and quantum measurement reversal, we show that the mentioned quantum correlations can be effectively preserved probabilistically from the decoherence due to amplitude damping. The results will play an important role in the experiments using the quantum correlations as resource.     

Effective pedestrian detection using deformable part model based on human model

Recently, pedestrian detection systems have become an important technology in the development of the advanced driver assistance system (ADAS) for the autonomous car. The histogram of oriented gradients (HOG) is currently the most basic algorithm for detecting pedestrians, but it treats the entire body of the pedestrian as one single feature. In other words, if the entire body of the pedestrian is not visible, the detection rate under HOG decreases markedly. To solve this problem, we propose a detection system using a deformable part model (DPM) that divides the pedestrian data into two parts using a latent support vector machine (SVM)-based machine-learning technique. Experimental results show that our approach achieves better performance in a detection system than the existing method. In practice, there are many occlusions in the environment in front of the vehicle. For example, the surrounding transport facilities, such as a car or another obstacle, can occlude a pedestrian. These occlusions can increase the false detection rate and cause difficulties during the detection process. Our proposed method uses a different approach and can easily be applied in real-world scenarios, regardless of occlusions.

     

Range image denoising using a constrained local Gaussian model for 3D object query service in the smart space

A position and direction is a fundamental information for U-Business as an anywhere service. A mobile device camera image can increase an accuracy of the positioning, and a range image provides significant information in an occlusion scene. U-Business service queries the information with the range image for a precision position or a target object. We present a method for smoothing heavy noisy surfaces acquired by mobile 3D imaging devices to obtain the stable curvature. The smoothing is performed in a way that finds centers of probability distributions, which maximizes the likelihood of observed points with smooth constraints. The smooth constraints are derived from the unit tangent vector equality. This provides a way of obtaining smooth surfaces and stable curvatures. We achieve the smoothing by solving the regularized linear system. The unit tangent vector equality involves consideration of geometric symmetry, and it minimizes the variation of differential values that are a factor of curvatures. The proposed algorithm has two apparent advantages. The first thing is that the surfaces in a scene with various signals-to-noise ratio are smoothed, and then they can earn suitable curvatures. The second is that the proposed method works on heavy noisy surfaces, for example, a stereo camera image. Experiments on range images demonstrate that the proposed method yields the smooth surfaces from the input with various signals-to-noise ratio and the stable curvatures obtained from the smooth surfaces.     

Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies

In this paper, we propose a distributed agent model that applies belief-desire-intention (BDI) reasoning and negotiation for addressing the linear assignment problem (LAP) collaboratively. In resource allocation, LAP is viewed as seeking a concurrent allocation of one different resource for every task to optimize a linear sum objective function. The proposed model provides a basic agent-based foundation needed for efficient resource allocation in a distributed environment. A distributed agent algorithm that has been developed based on the BDI negotiation model is examined both analytically and experimentally. To improve performance in terms of average negotiation speed and solution quality, two initialization heuristics and two different reasoning control strategies are applied, with the latter yielding different variants of the basic algorithm. Extensive simulations suggest that all the heuristic-algorithm combinations can produce a near optimal solution soon enough in some specific sense. The significance and applicability of the research work are also discussed.     

Ambient‐light sensor system with wide dynamic range enhanced by adaptive sensitivity control

Abstract— A new digital ambient‐light sensor system is presented which employs two linear light sensors with different sensitivities and automatically adjusts the sensitivity based on the illumination condition. The adaptation mechanism allows a very wide range of light intensity to be detected, and the input dynamic range of the system is substantially improved from 22.5 to 45.1 dB. The proposed method does not require any additional precision bits for output data. Due to the small number of the output bits and the simple conversion process, the system can be easily integrated on the display panel.     

12.1‐in. WXGA AMOLED display driven by InGaZnO thin‐film transistors

Abstract— A full‐color 12.1‐in.WXGA active‐matrix organic‐light‐emitting‐diode (AMOLED) display was, for the first time, demonstrated using indium‐gallium‐zinc oxide (IGZO) thin‐film transistors (TFTs) as an active‐matrix backplane. It was found that the fabricated AMOLED display did not suffer from the well‐known pixel non‐uniformity in luminance, even though the simple structure consisting of two transistors and one capacitor was adopted as the unit pixel circuit, which was attributed to the amorphous nature of IGZO semiconductors. The n‐channel a‐IGZO TFTs exhibited a field‐effect mobility of 17 cm²/V‐sec, threshold voltage of 1.1 V, on/off ratio >10⁹, and subthreshold gate swing of 0.28 V/dec. The AMOLED display with a‐IGZO TFT array is promising for large‐sized applications such as notebook PCs and HDTVs because the a‐IGZO semiconductor can be deposited on large glass substrates (larger than Gen 7) using the conventional sputtering system.     

Dynamic Multiple Swarms in Multiobjective Particle Swarm Optimization

A multiple-swarm multiobjective particle swarm optimization (PSO) algorithm, named dynamic multiple swarms in multiobjective PSO, is proposed in which the number of swarms is adaptively adjusted throughout the search process via the proposed dynamic swarm strategy. The strategy allocates an appropriate number of swarms as required to support convergence and diversity criteria among the swarms. Additional novel designs include a PSO updating mechanism to better manage the communication within a swarm and among swarms and an objective space compression and expansion strategy to progressively exploit the objective space during the search process. Comparative study shows that the performance of the proposed algorithm is competitive in comparison to the selected algorithms on standard benchmark problems. In particular, when dealing with test problems with multiple local Pareto fronts, the proposed algorithm is much less computationally demanding. Sensitivity analysis indicates that the proposed algorithm is insensitive to most of the user-specified design parameters.