National Institute of Technology, Yuge College

Abstract Let be an arbitrary monomial algebra. We investigate the stable category of graded Gorenstein‐projective ‐modules and the orbit category induced by and the degree shift functor (1). We prove that is triangle equivalent to the bounded derived category of a path algebra of Dynkin type and that is triangle equivalent to the stable module category of a self‐injective Nakayama algebra. Both the path algebra and the self‐injective Nakayama algebra will be given explicitly. The latter result provides an explicit description of the stable category of (ungraded) Gorenstein‐projective ‐modules.

Cognitive dysfunction is a major symptom in schizophrenia associated with social skills. It has been reported that cognitive rehabilitation can improve cognitive dysfunction. The Brief Assessment of Cognition in Schizophrenia-Japanese version (BACS-J) is often used as an outcome measure to assess the effectiveness of cognitive rehabilitation. However, the minimal clinically important difference (MCID) in the BACS-J composite score has not been reported. Therefore, we conducted this study to calculate a preliminary MCID in the BACS-J composite score and confirm the feasibility of retrospective data collection and analysis for future large-scale studies. The medical records of patients with schizophrenia who underwent cognitive rehabilitation were retrospectively surveyed. BACS-J data were collected at the beginning and end of the cognitive rehabilitation, and Clinical Global Impression-Improvement (CGI-I) data obtained at the end of the cognitive rehabilitation were evaluated retrospectively. To calculate the MCID in the BACS-J composite score using distribution-based methods, the standard error of measurement was calculated as a characteristic of the scale itself. To calculate the MCID using anchor-based methods, the mean change in BACS-J score corresponding to "minimally improved" on the CGI-I was determined. Twenty-eight patients were included in this study, and BACS-J data were collected from all patients. The CGI-I was completed by 11 patients, 3 of whom showed "minimally improved" according to their CGI scores. Distribution-based methods applied to the data of 28 patients revealed an MCID of 0.735 for the BACS-J composite score. Anchor-based methods were ultimately not applied because the sample size was insufficient. This study confirmed that CGI and BACS-J data can be collected and analyzed retrospectively. According to distribution-based methods, an increase of approximately 0.7 in the BACS-J composite score can be considered clinically meaningful. Future studies with larger sample sizes using both calculation methods could provide more accurate MCID.

In a water channel as an internal flow, the velocity is increasing in where the cross-sectional area is small according to Bernoulli's law. Because of this strong impression, many students of KOSEN misunderstand that the specific energy of flow through a channel with a wide cross-section area on the upstream side is larger than that of it through a channel with a wide cross-sectional area on the downstream side in the internal/external mixed flow.

GPS-based navigation systems have been developed to support the walking of visually impaired people. However, their use in station premises and malls presented difficulties due to radio wave interference. In such places, an indoor navigation system (IDNS) was indispensable. Recently, an IDNS using geomagnetism that did not require the installation of new infrastructure attracted our attention. It incorporated technology to detect self-position by association with a geomagnetic fingerprint (GMFP) database, which included the geomagnetic vector of the current position, stored in advance on the cloud. However, to realize navigation over an entire floor, a detailed geomagnetic map of the floor was needed, taking a lot of time and labor to measure the geomagnetic field. In this research, we proposed a novel method that limited the area of the GMFP to places above braille blocks and linked the geometric maps to braille block maps. The main features of our system were as follows: (1) Reduction of labor and time required to make the GMFP; (2) Realization of a real-time navigation system with little error in estimated position; (3) A high-resolution geomagnetic map database could be easily made by walking with a nearly fixed stride length without any specific equipment. To confirm the principal operation of our system, we made a prototype system. We then evaluated the performance of our system under various experimental conditions. Finally, we demonstrated a simple navigation system. As a result, we were able to confirm that our system could estimate self-position in real-time with little error and provide simple navigation for visually impaired people.

In recent years, the number of visually impaired people in Japan has exceeded 300,000 including those with low vision, and accidental falls on the station platform involving them have not been eliminated. Persons having acquired visual impairment make up one third of all cases of blindness in Japan. It is known that they often cannot walk alone with only a white cane or guide dog. The main cause of platform accidents was misidentification of braille blocks. Therefore, it was necessary to develop an auxiliary device for accurately identifying braille blocks that the acquired visually impaired could also use easily. In this research, we developed an automatic identification system for braille blocks using foot pressure data acquired by a multi-channel pressure sensor array. First, we devised a new foot pressure data acquisition device using a multi-channel pressure sensor array. Our proposed device had excellent features such as being light weight, low cost, and easy to extend to multi-channel. Second, in order to accurately identify the braille blocks, the foot pressure data acquired under various conditions was learned by neural network, and identification performance evaluated. As a result of the experiment, the braille blocks could be identified with a high rate of at least 98% accuracy by neural network, with a very simple structure of an input layer (16 neurons), a hidden layer (5 neurons), and an output layer (4 neurons).

This study analyzes the recognition process of examining the texture of fine particles through tactile sensing using human fingers and aims at establishing the structure of texture recognition. Characteristic values of the tactile sensing are studied in order to investigate a relationship between tactile sensing and its verbal response. In this study, the SD method (Semantic Differential method) is used to execute the language estimation (the evaluation value) of fine particles. This paper is intended as an investigation of a feature of Kansei Evaluation in around 60 years old using multivariate analysis.