Recently, multi-car elevator (MCE) system has captured attention as an effective mean for the improvement of transportation capability in a high-rise building. The MCE has two or more cars in one shaft. In this paper, we propose an algorithm for group controllers of MCE system, and show the effectiveness of our algorithm through computer simulation.

Comments on the present status of the problem in the title and an additional counterexample for Koga's Lemma 3 and Theorem 16 in (1) are presented.

As IT systems, including network systems using SDN/NFV technologies, become large-scaled and complicated, the cost of system management also increases rapidly. Network operators have to maintain their workflow in constructing and consistently updating such complex systems, and thus these management tasks in generating system update plan are desired to be automated. Declarative system update with state space search is a promising approach to enable this automation, however, the current methods is not enough scalable to practical systems. In this paper, we propose a novel heuristic approach to greatly reduce computation time to solve system update procedure for practical systems. Our heuristics accounts for structural bottleneck of the system update and advance search to resolve bottlenecks of current system states. This paper includes the following contributions: (1) formal definition of a novel heuristic function specialized to system update for A* search algorithm, (2) proofs that our heuristic function is consistent, i.e., A* algorithm with our heuristics returns a correct optimal solution and can omit repeatedly expansion of nodes in search spaces, and (3) results of performance evaluation of our heuristics. We evaluate the proposed algorithm in two cases; upgrading running hypervisor and rolling update of running VMs. The results show that computation time to solve system update plan for a system with 100 VMs does not exceed several minutes, whereas the conventional algorithm is only applicable for a very small system.

We have fabricated enhancement-mode n-channel GaN MOSFETs with overlap gate structure on a p-GaN using thick HfO2 as a gate insulator. The maximum transconductance of 23 mS/mm which is 4 times larger, to our knowledge, than the best-reported value of the normally-off GaN MOSFETs with SiO2 gate oxide has been obtained.

An optical flow processor architecture is proposed. It offers accuracy and image-size scalability for video segmentation extraction. The Hierarchical Optical flow Estimation (HOE) algorithm [1] is optimized to provide an appropriate bit-length and iteration number to realize VLSI. The proposed processor architecture provides the following features. First, an algorithm-oriented data-path is introduced to execute all necessary processes of optical flow derivation allowing hardware cost minimization. The data-path is designed using 4-SIMD architecture, which enables high-throughput operation. Thereby, it achieves real-time optical flow derivation with 100% pixel density. Second, it has scalable architecture for higher accuracy and higher resolution. A third feature is the CMOS-process compatible on-chip 2-port DRAM for die-area reduction. The proposed processor has performance for CIF 30 fr/s with 189 MHz clock frequency. Its estimated core size is 6.025.33 mm2 with six-metal 90-nm CMOS technology.

In this paper, we present a new three-dimensional (3D) virtual environment (3DVE) system named "QuViE/P", which can enhance quality of service (QoS), that users actually feel, as good as possible when resources of computers and networks are limited. To realize this, we focus on characteristics of user's perceptual quality evaluation on 3D objects. We propose an effective QoS control scheme for QuViE/P by introducing relationships between system's internal quality parameters and user's perceptual quality parameters. This scheme can appropriately maintain the QoS of the 3DVE system and it is expected to improve convenience when using 3DVE system where resources are insufficient. We designed and implemented a prototype of QuViE/P using a multiagent framework. The experiment results show that even when the computer resource is reduced to 20% of the required amount, the proposed scheme can maintain the quality of important objects to a certain level.

High output power AlGaN/GaN metal-insulator-semiconductor (MIS) hetero-junction field effect transistor (HFET) on Si substrate for millimeter-wave application has developed. High temperature chemical vapor deposition (HT-CVD) grown SiN as a gate insulator improves the breakdown characteristics which enables the operation at high drain voltage of 55 V. The device exhibits high drain current of 1.1 A/mm free from the current collapse and high RF gain of 10.4 dB. The amplifier module developed AlGaN/GaN MIS-HFET with the gate width of 5.4 mm exhibits an output power of 10.7 W and a linear gain of 4 dB at 26.5 GHz. The resultant high output power is very promising for long-distance communication at millimeter-wave in the future which would enable high speed and high density data transmission.

Network service providers need to appropriately design systems and carefully configuring the settings and parameters to ensure that the systems keep running consistently and deliver the desired services. This can be a heavy and error-prone task. Intent-based system design methods have been developed to help with such tasks. These methods receive service-level requirements and generate service configurations to fulfill the given requirements. One such method is search-based system design, which can flexibly generate systems of various architectures. However, it has difficulty dealing with constraints on the quantitative parameters of systems, e.g., disk volume, RAM size, and QoS. To deal with practical cases, intent-based system design engines need to be able to handle quantitative parameters and constraints. In this work, we propose a new intent-based system design method based on search-based design that augments search states with quantitative constraints. Our method can generate a system that meets both functional and quantitative service requirements by combining a search-based design method with constraint checking. Experimental results show that our method can automatically generate a system that fulfills all given requirements within a reasonable computation time.