Mitsubishi

About: Mitsubishi is a company organization based out in Tokyo, Japan. It is known for research contribution in the topics: Layer (electronics) & Signal. The organization has 53115 authors who have published 54821 publications receiving 870150 citations. The organization is also known as: Mitsubishi Group of Companies & Mitsubishi Companies.

Inverter apparatus and method therefor

Abstract: An inverter apparatus having a compact design and a changeable heat sink. The apparatus includes a power module formed in a case having pairs of parallel sides and containing the respective main circuit semiconductor devices for converting an alternating current input into a direct current and then further into an alternating current of variable frequency. The heat sink also has pairs of parallel sides and interfaces with the case in a plane whereon the projections of the sink and the case are coextensive. The apparatus also has a body with pairs of parallel sides that fasten to the case and constitute part of the enclosure of the inverter apparatus. The body, case, heat sink and associated circuit elements have alignment structures that permit easy and reliable disassembly and assembly of the apparatus.

Scalable Active Learning for Multiclass Image Classification

Abstract: Machine learning techniques for computer vision applications like object recognition, scene classification, etc., require a large number of training samples for satisfactory performance. Especially when classification is to be performed over many categories, providing enough training samples for each category is infeasible. This paper describes new ideas in multiclass active learning to deal with the training bottleneck, making it easier to train large multiclass image classification systems. First, we propose a new interaction modality for training which requires only yes-no type binary feedback instead of a precise category label. The modality is especially powerful in the presence of hundreds of categories. For the proposed modality, we develop a Value-of-Information (VOI) algorithm that chooses informative queries while also considering user annotation cost. Second, we propose an active selection measure that works with many categories and is extremely fast to compute. This measure is employed to perform a fast seed search before computing VOI, resulting in an algorithm that scales linearly with dataset size. Third, we use locality sensitive hashing to provide a very fast approximation to active learning, which gives sublinear time scaling, allowing application to very large datasets. The approximation provides up to two orders of magnitude speedups with little loss in accuracy. Thorough empirical evaluation of classification accuracy, noise sensitivity, imbalanced data, and computational performance on a diverse set of image datasets demonstrates the strengths of the proposed algorithms.

Imaging Mass Spectrometry Technology and Application on Ganglioside Study; Visualization of Age-Dependent Accumulation of C20-Ganglioside Molecular Species in the Mouse Hippocampus

Abstract: Gangliosides are particularly abundant in the central nervous system (CNS) and thought to play important roles in memory formation, neuritogenesis, synaptic transmission, and other neural functions. Although several molecular species of gangliosides have been characterized and their individual functions elucidated, their differential distribution in the CNS are not well understood. In particular, whether the different molecular species show different distribution patterns in the brain remains unclear. We report the distinct and characteristic distributions of ganglioside molecular species, as revealed by imaging mass spectrometry (IMS). This technique can discriminate the molecular species, raised from both oligosaccharide and ceramide structure by determining the difference of the mass-to-charge ratio, and structural analysis by tandem mass spectrometry. Gangliosides in the CNS are characterized by the structure of the long-chain base (LCB) in the ceramide moiety. The LCB of the main ganglioside species has either 18 or 20 carbons (i.e., C18- or C20-sphingosine); we found that these 2 types of gangliosides are differentially distributed in the mouse brain. While the C18-species was widely distributed throughout the frontal brain, the C20-species selectively localized along the entorhinal-hippocampus projections, especially in the molecular layer (ML) of the dentate gyrus (DG). We revealed development- and aging-related accumulation of the C-20 species in the ML-DG. Thus it is possible to consider that this brain-region specific regulation of LCB chain length is particularly important for the distinct function in cells of CNS.