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A Tentative Assumption on Catch-up-oriented Innovation : The Implication from China’s Industrial Catch-up
Get PDFSince the beginning of 21st century, the competitive power of many industries in advanced countries began to decline while China’s industrial power got greatly improved. What happened in traditional advanced countries? What can we find behind China’s industrial success? This paper investigates the secrets of China’s industrial Catch-up by using the hypothesis of “catch-up-oriented innovation”. Some certain facts have been found through the analysis- (1) most catch-up in China is based on transferred technological source from the west, (2) the existence of foresighted entrepreneurs, (3) the existence of potential R&D capability, (4) the happening of “new combination”. Furthermore, 2 points-(1) the happening of technological paradigm shift, (2) independent R&D after technological source introduction-are responsible for the late-comers’ taking over the frontrunners
Capitalism in the Post-genomic Age : The Main Issue of Life Science and Family Form in America
Get PDFThe aim of this paper is to study the main factor taking industrial capital another stage forward and, consequently, finding a new concept in social relations.Firstly, studying the “Cultural War” between Pro-Choice and Pro-Life in American history, the base of capitalist society is given as the family form, in particular, the genesis-form of life.The latest revolution in life science, namely, bio-technology develops “bio-capital” and leads to the critical point beyond human nature: Post-humanism.As a result, the family form is now transformed into the “intimate sphere” free from sex, blood, and property. That signifies an “association of free individuals”, from where a new human history begins
The Rise of China and A Reconsideration of the Stages Theory of Capitalism : Focusing on Global Production and Finance Networks
Get PDFThe rapid rise of China since the 2000s has made a great impact not only on the world economy but also on studies of capitalism, including the stages theory of capitalism that defines the stages of historical development of world capitalism. It is thought critical to recognize that China has risen during a stage of global capitalism, since the country has been affected greatly by globalization.Examined in this paper is what global capitalism is, and it is argued that the backbone of global capitalism is formed by global production networks （GPNs） and global finance networks （GFNs）. China’s rise has been largely brought about by GPNs and GFNs entering the country. On the other hand, China also attracted these with its “reform and opening-up” policy. How the stages theory of capitalism can be rebuild is examined by considering and incorporating China’s rise
Single Mothers and Multiple Jobs
Get PDFThe aim of this paper is to examine the issue of holding multiple jobs. Prime Minister Shinzo Abe’s Government has changed Japanese labor policy from prohibiting employed workers from holding secondary jobs to allowing them to do so in principle. The reason for the policy shift was explained to be to promote flexible work arrangements. However, according to Nobuko Hara’s work on welfare reform since the 1980s, work flexibility leads to low working hours, with insufficient and unstable income, and makes it difficult for single mothers to live and care for their children. In this paper, I review a general study of multiple job holders along with the work of single mothers and their childcare. I then examine the survey data collected by the Single Mother Research Project. The data from July 2020 to July 2021 suggest that some single mothers are holding secondary jobs because one job alone fails to provide enough income to rear children. It is also suggested that through holding secondary jobs, single mothers are protecting themselves from the risks of leave of absence due to COVID-19, reduced working hours, and unemployment. Holding multiple jobs for single mothers, however, has a negative impact on childcare due to time input to their children being reduced
Relationships in the Marketing Channels : A Review
Get PDFAlthough there is a vast amount of research on cooperative relationships in marketing channels, there is a few review articles that follow up the recent studies. Therefore, this paper examines the background of the emergence of the cooperative relationship research, and then summarizes the development of the cooperative relationship theory since 1980s based on five theoretical backgrounds: (1) social exchange, (2) relational contracts, (3) power-conflict, (4) transaction cost analysis, (5) trust-commitment. Furthermore, as a more contemporary development, this paper examines the development of cooperative relationship research based on transaction cost analysis. The paper provides an integrative guide to the literature and suggests some promising future research directions
A study on consumer shopping value : understanding consumer behavior in the omni-channel
Get PDF博士(経営学)法政大学 (Hosei University
Paralinguistic and Nonverbal Information Extraction from Speech Signal towards Empathetic Dialogue Systems
Get PDFIn this research, we aim to extract paralinguistic and nonverbal information such as emotions, speaking style, and speaker attributes towards a human-like empathetic dialogue system. Empathy is the ability to project the other person’s feelings and thoughts onto the other person’s knowledge. It plays an important role in human communication. In particular, personalization and understanding emotion are essential for an advanced dialogue system. This research focuses on methods for estimating speaker attributes, personal speaking-style and emotion category that are related to personalization and emotion in real-time from a small amount of speech information like a human agent. By integrating the methods proposed in this paper, it is possible to realize more human-like recognition of paralinguistic and nonverbal information for automatic dialogue systems using speech. This doctoral dissertation consists of five chapters. In chapter 1, the introduction is described.In chapter 2, we propose a method for identifying speaker attributes, which are nonverbal information in speech. We specially focus on the identification of male and female speeches as speaker attributes in this chapter. In order to extract speaker attributes, it is necessary to first detect a speech segment from a sound signal sequence, which is a mixture of speech and non-speech segments, and then to identify them in the speech segment. In conventional speaker attribute identification, the endpoint of speech with a certain length of continuous speech is detected, and then the features to identify speaker attributes are extracted, and an identification process is performed for the segment. However, a delay time occurs to identify speaker attributes since the process starts after the end of speech is detected. In our method, the speaker attributes and the probabilities for the speech and non-speech segments are calculated simultaneously for each time frame using a single neural network. The framework can identify speaker attributes sequentially based on their accumulated probabilities. This method made it possible to classify male and female speech with high accuracy while maintaining the accuracy of speech segment detection.In Chapter 3, we propose a phoneme identification method that leads to the extraction of low-intelligibility speech. When low-intelligibility speech occurs, phonemes in a relevant part of a speech are unclear and differ significantly from the nature of phonemes in ordinary speech. Since features of the phonemes depend on a relative phoneme position, it is necessary to cluster them depending on the phoneme position, and a discriminative model for each cluster is trained to determine whether the phoneme is clearly uttered or not. Therefore, we propose a discriminator that contains phoneme environment-dependent clusters inside, which enables to discriminate phonemes without pre-clustering and to calculate a score for the intelligibility.In chapter 4, we propose a method for extracting paralinguistic and nonverbal information, such as fillers and word fragments. There are many variations of fillers and word fragments, and it is not easy to keep all patterns as a dictionary of language in advance. Therefore, existing methods use two-pass decoding to detect fillers and word fragments based on a confusion network output from first-pass recognition and sub-word language model to deal with various fillers and word fragments. However, this method is unsuitable for real-time applications because it can only start processing after decoding the end of the utterance. To solve this problem, we propose a method of learning filler and word fragment acoustic patterns as filler symbols and word fragment symbols, respectively, and incorporating a detection process using filler symbols and word fragment symbols into a WFST decoder for speech recognition, thereby processing them in a single pass of the decoder.There is no need to register all speech patterns of filler, and word fragment in a language dictionary since the proposed method treats filler and word fragment as a single acoustic symbol. By this method, fillers and word fragments can be detected in real-time. Simultaneously, the speech is recognized in one pass without degrading the accuracy. As for fillers, the number of occurrences can be controlled by using a confidence score based on the number of occurrences of filler symbols.In chapter 5, we propose a method for recognizing emotions, which are paralinguistic and nonverbal information. At present, the accuracy of emotion classification for 7 or 8 emotions is only 70 or 80%, even when the emotions are uttered intentionally. Therefore, performance improvement is desired. Emotional features in speech are contained in both a short speech signal and a long speech signal. Therefore, many efforts have been made to improve the performance of emotion classification by incorporating features of various temporal resolutions. Conventional emotion recognition methods tried to improve the performance by using a single neural network encompassing multiple temporal resolutions. However, they have not been able to significantly improve the performance due to the small emotional speech database.We consider that the performance of emotion classification methods using high-level statistical functions (HSFs), which show high accuracy in emotion classification, can be improved by extracting and combining HSFs from windows with multiple temporal resolutions instead of a single fixed window length. In this paper, we aim to improve the accuracy by extending the HSFs extracted from a single fixed window in the existing methods to HSFs generated from multiple windows with temporal resolutions of 30 or more. In addition, to reduce the number of parameters to be learned simultaneously for a small amount of data, stacking with Gradient Boosting Decision Trees (GBDT) is applied when combining features of multiple temporal resolutions. As a result, we obtained the highest emotion classification performance for the American emotional speech database. In addition, although the method initially uses multiple temporal resolutions of more than 30, it is found that the same classification performance can be obtained with only 15 temporal resolution features based on analyzing by GBDT.博士(理学)法政大学 (Hosei University