ジシュ キョウソウ ノ セイシン ニ モトズク カガク ギジュツ リテラシー ノ コウチク

The object of the Center for Innovation and Creativity Development of University of Tokushima is to develop a creative learning method, to practice it for ensuring the effectiveness and doing the science literacy dissemination activities in the regions through experiment course of the science class for elementary and junior high school students. Students who joined as teacher at almost all activities got something from those experience. Reaction of children and high school students participated in this activity is in good condition, and increased concern and interest in science and technology seen from the post-test questionnaire. Also seen from surveys of students was responsible self-change for teacher about teaching contents and teaching methods

ジシュ キョウソウ ノ セイシン ニ モトズク カガク ギジュツ リテラシー ノ コウチク

The object of the Center for Innovation and Creativity Development of University of Tokushima is to develop a creative learning method, to practice it for ensuring the effectiveness and doing the science literacy dissemination activities in the regions through experiment course of the science class for elementary and junior high school students. Students who joined as teacher at almost all activities got something from those experience. Reaction of children and high school students participated in this activity is in good condition, and increased concern and interest in science and technology seen from the post-test questionnaire. Also seen from surveys of students was responsible self-change for teacher about teaching contents and teaching methods

ジッセンテキ ナ ギジュツシャ イクセイ ノ タメ ノ ソウセイガタ キャリア キョウイク プロジェクト

The purposes of the this project using long-term internship programs is that students of master or doctoral course learn skills to communicate to the engineers of a client on equal terms as well as their expertise, in order to create pai-type practical engineers. By this program, we expect students to acquire skills for time management, communication and enterprising ability. From 2011 to 2012, 62 graduate students (58 master’s students and 4 doctoral students) joined this program. The students joined internship program at companies or governments for a period of 180~270 hours with their training goals for the collaborative research, as well as lectures on MOT. We tried joint internship with under-graduate students for MC or DC students, and introduction of intellectual property education during this project. We summarized the outcome of this project on this paper and future issues to be considered in order to develop the program

Preference Analysis Method Applying Relationship between Electroencephalogram Activities and Egogram in Prefrontal Cortex Activities : How to collaborate between engineering techniques and psychology

This paper introduces a method of preference analysis based on electroencephalogram (EEG) analysis of prefrontal cortex activity. The proposed method applies the relationship between EEG activity and the Egogram. The EEG senses a single point and records readings by means of a dry-type sensor and a small number of electrodes. The EEG analysis adapts the feature mining and the clustering on EEG patterns using a self-organizing map (SOM). EEG activity of the prefrontal cortex displays individual difference. To take the individual difference into account, we construct a feature vector for input modality of the SOM. The input vector for the SOM consists of the extracted EEG feature vector and a human character vector, which is the human character quantified through the ego analysis using psychological testing. In preprocessing, we extract the EEG feature vector by calculating the time average on each frequency band: θ, low-β, and high-β. To prove the effectiveness of the proposed method, we perform experiments using real EEG data. These results show that the accuracy rate of the EEG pattern classification is higher than it was before the improvement of the input vector

Experimental observations on the optimal layout of orientation blocks for safe road crossing by the visually impaired

For people with visual impairments who face difficulties when crossing the road, in urban areas of Japan the infrastructure designed to provide an indication of crossing direction and the curbstones at sidewalk-roadway boundaries often varies in reliability from one crossing to another. If anything, this promotes stress for users and is an issue for which improvement is urgently needed. The authors have proposed new orientation blocks to be installed at crosswalk entrances as a means of more accurately indicating to people with visual impairments the trajectory to follow when crossing the road, and in prior research have derived desirable specifications for the profile of these blocks and their position relative to tactile walking surface indicators (TWSI). For this paper, in order to examine in greater detail the desirable position of orientation blocks relative to TWSI, the authors conducted an experiment using totally blind subjects to evaluate conditions on a 10 m walk that simulated an actual crossing. The results, based on observations of the trajectories walked by participants in the experiment and interviews eliciting their subjective evaluations, showed that separating orientation blocks and blister tactile blocks by about 8–12 cm is effective in constraining lateral deviation at a point 5 m from the start of crossing and that an 8 cm separation was desirable in order to maintain an effective reduction of mental stress while crossing

Method to Classify Matching Patterns between Music and Human’s Mood Using EEG Analysis Technique Considering Personality

In this paper we introduce a method to classify matching patterns between music and human mood using an electroencephalogram (EEG) analysis technique and considering personality. We analyse the EEG of the left prefrontal cortex by single-point sensing. The EEG recording device uses dry-type sensors. The feature vector is created by connecting the personality quantification results and the EEG features. Egograms—the Yatabe-Guilford personality inventory and a Kretschmer-type personality inventory are used to quantify personality. The EEG features are extracted using fast Fourier transform. Then, the matching patterns are classified using the k -nearest neighbour method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data

Evaluation of initiating characteristics of osteoblastic calcium signaling responses to stretch by video rate time-course observation

Osteoblasts change their intracellular calcium ion concentration in response to mechanical stimuli. Although it has been reported that osteoblasts sense and respond to stretching of a substrate on which osteoblastic cells have adhered, the details of the dynamic characteristics of their calcium signaling response remain unclear. Motion artifacts such as loss of focus during stretch application make it difficult to conduct precise time-course observations of calcium signaling responses. Therefore, in this study, we observed intracellular calcium signaling responses to stretch in a single osteoblastic cell by video rate temporal resolution. Our originally developed cell-stretching microdevice enables in situ observation of a stretched cell without excessive motion artifacts such as focus drift. Residual minor effects of motion artifacts were corrected by the fluorescence ratiometric method with fluorescent calcium indicator Fluo 8H and fluorescent cytoplasm dye calcein red-orange. We succeeded to detect the intracellular calcium signaling response to stretch by video rate temporal resolution. The results revealed a time lag from stretch application to initiation of the intracellular calcium signaling response. We compared two time lags measured at two different cell areas: central and peripheral regions of the cell. The time lag in the central region of the cell was shorter than that in the peripheral region. This result suggests that the osteoblastic calcium signaling response to stretching stimuli initiates around the central region of the cell

In Situ Observation and Measurement of Actin Stress Fiber Deformation in Stretched Osteoblast like Cell

It is believed that mechanical stimuli, such as stretching of the extracellular matrix, are transmitted into cells via focal adhesion complexes and the actin cytoskeleton. Transmission dynamics of strain from the extracellular matrix into intracellular organelles is crucial to clarify the mechanosensing mechanisms of cells. In this study, we observed deformation behavior of actin stress fibers under uniaxial stretch using an originally developed cell-stretching microelectromechanical system (MEMS) device. It was difficult to conduct in situ observation of cells under stretch using conventional cell stretching devices, because motion artifacts such as rigid displacement during stretch application were not negligible. Our novel cell-stretching MEMS device suppressed rigid displacement while stretching, and we succeeded in obtaining time-lapse images of stretched cells. Uniaxial strain with a 10% magnitude and strain rate of 0.5%/sec was applied to cells. Deformation behaviors of the cells and actin stress fibers were recorded using a confocal laser scanning microscope. In time-lapse images of stretched cells, strains along each stress fiber were measured manually. As a result, in cells with a relatively homogeneous stress fiber structure oriented in one direction, distribution of the axial strain on stress fibers generally corresponded to deformation of the stretching sheet on which the cells had adhered. However, in cells with a heterogeneous stress fiber structure oriented in several directions, we found that the strain distribution along stress fibers was not homogeneous. In regions around the cell nucleus, there was a more complicated strain distribution compared with other regions. Our results suggest the cell nucleus with a stiff mechanical resistance yields such a complicated strain distribution in stress fibers

Preference Classification Method Using EEG Analysis Based on Gray Theory and Personality Analysis

This paper introduces a method to classify the preference patterns of sounds on the basis of an electroencephalogram (EEG) analysis and a personality analysis. We analyze the EEG of the left prefrontal cortex by single-point sensing. For EEG recording, a dry-type sensor and few electrodes were used. The proposed feature extraction method employs gray relational grade detection on the frequency bands of EEG and egogram. The gray relational grade is used for extracting the EEG feature. The egogram is extracted for quantifying the subject’s personality. The preference patterns generated when the subject is hearing a sound are classified using the nearest neighbor method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data. These results show that the accuracy rate of the preference classification using the proposed method is better than that using the method that does not to consider the subject’s personality

Preference Classification Method Using EEG Analysis Based on Gray Theory and Personality Analysis

This paper introduces a method to classify the preference patterns of sounds on the basis of an electroencephalogram (EEG) analysis and a personality analysis. We analyze the EEG of the left prefrontal cortex by single-point sensing. For EEG recording, a dry-type sensor and few electrodes were used. The proposed feature extraction method employs gray relational grade detection on the frequency bands of EEG and egogram. The gray relational grade is used for extracting the EEG feature. The egogram is extracted for quantifying the subject’s personality. The preference patterns generated when the subject is hearing a sound are classified using the nearest neighbor method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data. These results show that the accuracy rate of the preference classification using the proposed method is better than that using the method that does not to consider the subject’s personality