What can Analysis of the Organizations’ Web Sites tell us about AI? Comparative Study of the Online Resources operated at Google, Yandex, and Baidu

The current social and cultural debates on AI and how it is being embedded into the reality of social life have reignited scientific debates on how to study AI, what counts as data, and the conditions under which information and data pertaining AI turn into knowledge. In this paper the authors’ focus was exploring new sources of data on AI and methods of AI phenomena examination. The paper presents the results of a comparative analysis of Google, Yandex, and Baidu’s websites. Contrary to these companies commonly being perceived as online search engines, Google, Baidu, and Yandex have multiple offerings across mobile products and services, knowledge products, translation services, open platforms for startups, PC client software and AI technologies. In the first part of the paper the authors compare information presented on these companies’ websites about their goals, their technologies, how they define AI, the proclaimed social problems associated with using AI, and the forms of interaction between these companies and their audiences. The second part of the paper analyzes 20 projects that won the Google AI Impact Challenge contest. Analyzing these projects allowed for identifying areas of application of AI technologies inside and outside organizations, for characterizing AI’s potential roles as a mediator in relations between people, and finally for highlighting utopian and dystopian scenarios associated with implementing AI in social relations. In the conclusion the authors formulate a set of broader questions for social analytics concerning artificial intelligence grounded in the results of their analysis.

CHIMERA

Wearable technologies draw on a range of disciplines, including fashion, textiles, HCI, and engineering. Due to differences in methodology, wearables researchers can experience gaps or breakdowns in values, goals, and vocabulary when collaborating. This situation makes wearables development challenging, even more so when technologies are in the early stages of development and their technological and cultural potential is not fully understood. We propose a common ground to enhance the accessibility of wearables-related resources. The objective is to raise awareness and create a convergent space for researchers and developers to both access and share information across domains. We present CHIMERA, an online search interface that allows users to explore wearable technologies beyond their discipline. CHIMERA is powered by a Wearables Taxonomy and a database of research, tutorials, aesthetic approaches, concepts, and patents. To validate CHIMERA, we used a design task with multidisciplinary designers, an open-ended usability study with experts, and a usability survey with students of a wearables design class. Our findings suggest that CHIMERA assists users with different mindsets and skillsets to engage with information, expand and share knowledge when developing wearables. It forges common ground across divergent disciplines, encourages creativity, and affords the formation of inclusive, multidisciplinary perspectives in wearables development.

A Narrative Review of Clinical researches of Acupuncture treatment for Depression using Neuroimaging method: Focusing on SCI papers

Objectives: The purpose of this article was to investigate the current status of clinical studies of acupuncture treatment for depression using neuroimaging method, focusing on SCI papers.Methods: We searched for clinical trial studies of acupuncture treatment for depression using neuroimaging method in the MEDLINE (Pubmed), OASIS, and RISS database. Once the online search was finished, studies were selected manually by the inclusion criteria. Finally, we analyzed the characteristics of selected articles and reviewed the neural substrates of acupuncture treatment in depression.Results: Total eight studies were included in this study. The most frequently utilized modality was functional MRI. The most frequently selected acupoint for depression was GV20. Several studies revealed that acupuncture treatment could improve the symptoms of depression. In this manuscript, we demonstrated that neuroimaging techniques could capture the neural substrates associated with depression and acupuncture treatment may modulate the activation of brain areas which were impaired in depression in a different way from sham acupuncture.Conclusions: Utilizing neuroimaging methods to explore neural mechanism of acupuncture treatment on depression would be helpful in clinical trials and more efforts should be needed in this fields.

Real-time analysis and predictability of the health functional food market using big data

This study conducted a real-time analysis of the health functional food market using big data. To assess the scope of big data in market analysis, big data of the health food category were compared and analyzed with actual market data. Data were first collected using a program to obtain data, through application programming interfaces, followed by SPSS to compare and analyze the actual market index and shopping search word data. The correlation between the online search data and the actual market was high, indicating that online search data can be used to predict the trend of the actual market. Various types of data, such as items and major functional ingredients, can be collected and analyzed through the program developed for this study, which is also used to predict the market trend. The results demonstrate how APIs can be used to predict market size in the food industry effectively.

Identification of School Leadership Strategy In Supporting Students Learning From Home During Pandemics

Identifying school leadership strategies to support students learning from home during the pandemic is the core objective of this study. To answer the problem above, we have reviewed dozens of publications interested in discussing educational disruption during the outbreaks where the effect of the disruption forces students to study from home with all the problems that arise. We get the data from an online search, and we study it with a phenomenological approach. We evaluate the data with a coding system to know what and how school leadership responds to the pandemic. Based on the data and the discussion, we found that many things must and have been done by the school that does not have to wait for the direction of policy superiors from the central state. The support provided is, for example, teachers and school boards assisting students and guiding how to prevent students and parents from panicking through the disrupted period of the pandemic. Schools do not force students with assignments and work, but teachers should encourage collaborative learning with parents while maintaining progress. Thus, we hope this study is helpful to many parties.

How does Online Engagement Drive Consumers’ Webrooming Intention?

Based on the cognitive-motivational-relational (CMR) theory, this study empirically investigates the mechanisms through which consumers' online engagement impacts their channel switching intention. The present study examines the mediating effects of perceived value and the ways in which these mediating effects are moderated by online risk perception. Data were collected from 428 online Indian consumers using systematic random sampling. The results of the structural and process macro analyses indicated that consumer online engagement has a significant impact on consumer online search benefits which in turn leads to webrooming intention. Also, perceived value mediated the effects of online search benefits and offline purchase benefits on webrooming intention. The results advance the theory of CMR by explaining consumer channel switching behaviour and are expected to help multi-channel retailers to identify the key drivers that help engage consumers online.