东芝 （Toshiba），是日本最大的半导体制造商，也是第二大综合电机制造商，隶属于三井集团。公司创立于1875年7月，原名东京芝浦电气株式会社，1939年由东京电气株式会社和芝浦制作所合并而成。 东芝业务领域包括数码产品、电子元器件、社会基础设备、家电等。20世纪80年代以来，东芝从一个以家用电器、重型电机为主体的企业，转变为包括通讯、电子在内的综合电子电器企业。进入90年代，东芝在数字技术、移动通信技术和网络技术等领域取得了飞速发展，成功从家电行业的巨人转变为IT行业的先锋。 2019年5月，ICinsghts发布了2019年Q1季度全球半导体市场报告，东芝公司营收下滑了31%，排名从2018年的第八降至现在的第九。
Nonlinear dynamical systems with continuous variables can be used for solving combinatorial optimization problems with discrete variables. Numerical simulations of them are also useful as heuristic algorithms with a desirable property, namely, parallelizability, which allows us to execute them in a massively parallel manner, leading to ultrafast performance. However, the dynamical-system approaches with continuous variables are usually less accurate than conventional approaches with discrete variables such as simulated annealing. To improve the solution accuracy of a quantum-inspired algorithm called simulated bifurcation (SB), which was found from classical simulation of a quantum nonlinear oscillator network exhibiting quantum bifurcation, here we generalize it by introducing nonlinear control of individual bifurcation parameters and show that the generalized SB (GSB) can achieve surprisingly high performance, namely, almost 100% success probabilities for some large-scale problems. As a result, the time to solution for a 2000-variable problem is shortened to 10 ms by a GSB-based machine, which is 2 orders of magnitude shorter than the best known value, 1.3 s, previously obtained by an SB-based machine. To examine the reason for the ultrahigh performance, we investigated chaos in the GSB changing the nonlinear-control strength and found that the dramatic increase of success probabilities happens near the edge of chaos. That is, the GSB can find a solution with high probability by harnessing the edge of chaos. This finding suggests that dynamical-system approaches to combinatorial optimization will be enhanced by harnessing the edge of chaos, opening a broad possibility for physics-inspired approaches to combinatorial optimization.
This paper proposes a warm-start design optimization method based on potential-shaped latent representations learned by a variational autoencoder (VAE). The latent space is structured so that objective function values correspond to a quadratic potential, concentrating high-performance designs near the origin without explicit latent-space optimization. Candidate designs are generated by sampling the latent space around the origin and subsequently refined using level-set-based optimization. The effectiveness of the proposed method is demonstrated through rotor flux-barrier shape optimization of a synchronous reluctance motor.
We introduce latest power electronics technologies for adjustable-speed pumped-storage hydropower systems based on the converter renewal of Unit 2 at the Electric Power Development Co., Ltd. Okukiyotsu No. 2 Hydropower Station. The system includes a doubly-fed induction machine and a secondary excitation converter. Controlling the excitation converter provides fast and flexible system output/input in generation and pump operations. While pre-renewal excitation converter employed Gate-Turn-Off thyristor as the switching device, the renewed one employed Injection Enhanced Gate Transistors. This change reduced the loss and the volume of the excitation converter by approximately 26% and 37%, respectively, compared to the pre-renewal converter. Moreover, the total self-startup time of the doubly-fed induction machine was reduced by approximately 18%.
