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Pay Innovations in Japan : Do They Lead to High Performance Organizations?
Motohiro Morishima 한국고용노사관계학회 2000 한국노사관계학회 정책세미나 Vol.2000 No.10
Japanese innovations in pay practices are most accurately described as a shift away from basing employee evaluation and rewards on seniority and ability development, to a practice of placing more emphasis on employees’ performance and output. As a result, new pay-for-practices including performance-based evaluation and management-by-objectives are being implemented in Japanese firms. Yet, we have surprisingly little knowledge about how this shift may affect organizational effectiveness. This study examines this issue by focusing on the effects of the changes in compensation and evaluation practices on workplace effectiveness. Workplace effectiveness is examined because of its critical role in influencing such important outcomes as employee motivation, skill development, fairness in employment relations and knowledge creation. The empirical results presented in this paper show that simple introduction of “pay-for-performance” practices may have serious implications for workplace and organizational effectiveness. More specifically, pay-for-performance practices in Japanese organizations are likely to have negative impacts on the effectiveness of Japanese high performance workplaces, unless these changes are also accompanied by a practice encouraging or requiring performance feedback, providing employees with their evaluation results and the reasons for these results. In conclusion, It is proposed that Japanese employers must introduce both performance-based compensation practices and performance feedback to obtain full benefits of these pay innovations.
Generation of Super-Resolution Images from Satellite Images Based on Improved RCAN
Futa Morishima,Huimin Lu,Tohru Kamiya 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Satellite images can be analyzed and used for a variety of purposes. In the future, satellite image analysis will become more important since the number of satellites launches, and the amount of satellite data increase every year. Under these circumstances, there are some problems to be solved. One is the existence of low-resolution satellite images. To analyze the lower resolution of satellite images there are some technical issues such as reduction of noise, misclassification of object recognition. Therefore, high-resolution images are necessary. However, high-resolution satellite images are expensive, and its images may not be available in the past satellite images. Super-resolution which is introduced in image processing is a method to solve these problems. Convolutional neural network (CNN)-based methods are effective, and there is a need for models that can perform super-resolution with higher accuracy. In this paper, we propose a method for super-resolving satellite images, based on the improved the RCAN (residual channel attention network) model with SRM (style-based recalibration module). The proposed method improves the PSNR (peak signal to noise ratio) by 0.0181 dB compared to the conventional RCAN model.
An Analysis of the University Students’ Images about the Learning on the Developing Country
Ayako Morishima 한양대학교 교육공학연구소 2010 학습과학연구 Vol.4 No.1
Though it is said that the learning on the developing country through the social activities has the various possibilities, there are few case studies and few students studying in the developing country. This paper shows the factor causing this situation. After that, the authors consider the approach to promote the learning on the developing country.
Moriuchi, Takeyuki,Morishima, Keisuke,Furukawa, Yuji Korean Society for Precision Engineering 2008 International Journal of Precision Engineering and Vol.9 No.2
As a biofuel source, direct photosynthetic/metabolic biofuel cells (DPBFC) use cyanobacteria whose photosynthesis and metabolization reactions can convert light energy to electricity, In our previous work, we fabricated a prototype micro-DPBFC that could generate a peak current density of $36{\mu}A/cm^{2}$ and a maximum power density of $270nW/cm^{2}$. In this study, we improve on the previous results by using carbon micro electromechanical systems (C-MEMS), formed from the pyrolysis of patterned photoresist, to fabricate carbon electrodes of an arbitrary shape and controlled porosity to increase the surface area. With these new C-MEMS electrodes, the maximum power density of the micro-DPBFC was $516nW/cm^{2}$, a performance twice as good as the results of our previous work.
Genetic structure of wild brown sole inferred from mitochondrial DNA analysis
김상규,Kagayaki Morishima,Katsutoshi Arai 한국통합생물학회 2010 Animal cells and systems Vol.14 No.3
The population structure of brown sole was examined in a total of 308 samples collected from three geographical groups: one locality (Gangneung) on the east side of the Korean Peninsula, two localities (Erimo and Tomakomai)on the southeastern side and four localities (Onishika, Teshio, Tomamae and Yoichi) on the northwestern side of Hokkaido Island, Japan, by using sequences of 484 bp from the 5' end of the control region of mtDNA. We detected 225 haplotypes, but 183 of them were unique to an individual. A total of 116 nucleotide sites were variable. Haplotype diversity (h) was very high, ranging from 0.989 to 1.000, and nucleotide diversity (π) was detected between 0.015 and 0.022. Genetic distances (ΦST) within populations, among populations and among geographical groups were low (0.0002 to 0.0014). No significant difference was detected by the AMOVA test (PB0.05). Pairwise FST values between sampling localities were also low and not significant. Genetic differentiation was not detected among sampling localities.
The brain’s functional network architecture reveals human motives
Hein, Grit,Morishima, Yosuke,Leiberg, Susanne,Sul, Sunhae,Fehr, Ernst American Association for the Advancement of Scienc 2016 Science Vol.351 No.6277
<P>Goal-directed human behaviors are driven by motives. Motives are, however, purely mental constructs that are not directly observable. Here, we show that the brain's functional network architecture captures information that predicts different motives behind the same altruistic act with high accuracy. In contrast, mere activity in these regions contains no information about motives. Empathy-based altruism is primarily characterized by a positive connectivity from the anterior cingulate cortex (ACC) to the anterior insula (AI), whereas reciprocity-based altruism additionally invokes strong positive connectivity from the AI to the ACC and even stronger positive connectivity from the AI to the ventral striatum. Moreover, predominantly selfish individuals show distinct functional architectures compared to altruists, and they only increase altruistic behavior in response to empathy inductions, but not reciprocity inductions.</P>