A Graph-Based Approach to Power-Constrained SOC Test Scheduling

The test scheduling problem is one of the major issues in the test integration of system-on-chip (SOC), and a test schedule is usually influenced by the test access mechanism (TAM). In this paper we propose a graph-based approach to power-constrained test scheduling, with TAM assignment and test conflicts also considered. By mapping a test schedule to a subgraph of the test compatibility graph, an interval graph recognition method can be used to determine the order of the core tests. We then present a heuristic algorithm that can effectively assign TAM wires to the cores, given the test order. With the help of the tabu search method and the test compatibility graph, the proposed algorithm allows rapid exploration of the solution space. Experimental results for the ITC02 benchmarks show that short test length is achieved within reasonable computation time.     

基于并行机制的边界扫描技术

在SoC测试时,测试功耗和测试成本是其可测性设计中最重要的一点要求.在分析了常见测试结构的测试功耗的基础上,提出了一种并行扫描机制的测试结构,包括访问机制的设计和测试控制器的设计.该方法可根据测试成本和测试功耗的要求,选择不同的构造方法.     

Toward an Understanding of Consumer Attitudes on Online Review Usage

ABSTRACT

With the rapid e-commerce growth and changes in consumers’ behaviors, many businesses are forced to adapt their business model to match their target customers’ needs. To provide consumers with more product details and increase their confidence in making online purchases, online businesses offer an online review as an alternative to physically interacting with a product. Although consumers have become familiar with the use of online product reviews, many aspects of user behavior toward the usage of online reviews are still not well understood. This study explores the factors underlying the acceptance of consumers’ online review usage when considering purchasing an item. The study results provide insight into the factors that affect customers’ use of online reviews prior to a purchase. This study furthers the body of knowledge that deals with online reviews and system usage, providing results that allow e-commerce businesses to adapt their business model to better fit consumers’ expectations.     

Deep learning diffusion by infusion into preexisting technologies – Implications for users and society at large

Artificial Intelligence (AI) in the form of Deep Learning (DL) technology has diffused in the consumer domain in a unique way as compared to previous general-purpose technologies. DL has often spread by infusion, i.e., by being added to preexisting technologies that are already in use. We find that DL-algorithms for recommendations or ranking have been infused into all the 15 most popular mobile applications (apps) in the U.S. (as of May 2019). DL-infusion enables fast and vast diffusion. For example, when a DL-system was infused into YouTube, it almost immediately reached a third of the world's population. We argue that existing theories of innovation diffusion and adoption have limited relevance for DL-infusion, because it is a process that is driven by enterprises rather than individuals. We also discuss its social and ethical implications. First, consumers have a limited ability to detect and evaluate an infused technology. DL-infusion may thus help to explain why AI's presence in society has not been challenged by many. Second, the DL-providers are likely to face conflicts of interest, since consumer and supplier goals are not always aligned. Third, infusion is likely to be a particularly important diffusion process for DL-technologies as compared to other innovations, because they need large data sets to function well, which can be drawn from preexisting users. Related, it seems that larger technology companies comparatively benefit more from DL-infusion, because they already have many users. This suggests that the value drawn from DL is likely to follow a Matthew Effect of accumulated advantage online: many preexisting users provide a lot of behavioral data, which bring about better DL-driven features, which attract even more users, etc. Such a self-reinforcing process could limit the possibilities for new companies to compete. This way, the notion of DL-infusion may put light on the power shift that comes with the presence of AI in society.     

E-Learning during COVID-19 Outbreak: Cloud Computing Adoption in Indian Public Universities

In the COVID-19 pandemic situation, the need to adopt cloud computing (CC) applications by education institutions, in general, and higher education (HE) institutions, in particular, has especially increased to engage students in an online mode and remotely carrying out research. The adoption of CC across various sectors, including HE, has been picking momentum in the developing countries in the last few years. In the Indian context, the CC adaptation in the HE sector (HES) remains a less thoroughly explored sector, and no comprehensive study is reported in the literature. Therefore, the aim of the present study is to overcome this research vacuum and examine the factors that impact the CC adoption (CCA) by HE institutions (HEIs) in India. The scope of the study is limited to public universities (PUs) in India. There are, in total, 465 Indian PUs and among these 304 PUs, (i.e., 65% PUs) are surveyed using questionnaire-based research. The study has put forth a novel integrated technology adoption framework consisting of the Technology Acceptance Model (TAM), Technology-Organization-Environment (TOE), and Diffusion of Innovation (DOI) in the context of the HES. This integrated TAM-TOE-DOI framework is utilized in the study to analyze eleven hypotheses concerning factors of CCA that have been tested using structural equation modelling (SEM) and confirmatory factor analysis (CFA). The findings reveal that competitive advantage (CA), technology compatibility (TC), technology readiness (TR), senior leadership support, security concerns, government support, and vendor support are the significant contributing factors of CCA by Indian PUs. The study contends that whereas the rest of the factors positively affect the PUs’ intention towards CCA, security concerns are a significant reason for the reluctance of these universities against adopting CC. The findings demonstrated the application of an integrated TAM-TOE-DOI framework to assess determining factors of CCA in Indian PUs. Further, the study has given useful insights into the successful CCA by Indian PUs, which will facilitate eLearning and remote working during COVID-19 or similar outbreak.     

APP动效设计中的用户专注沉浸度模型研究

目的基于MaterialDesign的交互动效理论,通过拓展TAM的三个维度研究用户对APP使用的专注沉浸度,并对比研究不同的交互动画在不同的应用中对用户专注沉浸度的影响,从而得出动效设计中用户专注沉浸度的理论假设模型,以补充TAM模型理论在交互设计方面的扩展研究。方法分析运用TAM和专注沉浸度模型的相关理论,综合扩展APP中交互动画研究测度,构建出新的假设理论模型,再通过两类典型交互动画对其动效做专注沉浸度实验,实验主要利用SPSS对由用户研究和体验测度组成的调查问卷进行数据统计和分析,最终检验本文的假设理论模型。结论实验结果表明H1-H7呈正相关,理论假设模型成立。验证了在一定条件下,运用本文构建的假设理论模型设计的交互动画在APP设计实践中能够更加有效地提高用户的专注沉浸度,能给用户带来更好的体验。     

Cultural Effects on Use of Online Social Media for Health-Related Information Acquisition and Sharing in Taiwan

The aims of this study were to use the technology acceptance model to examine how the cultural characteristics of social media users in Taiwan affect their use of social media for acquiring and sharing health-related information and to examine how their use of online social media benefits their social relationships and health self-efficacy. The research model in this quantitative cross-sectional study was tested with data collected from 321 active Facebook users in Taiwan. All three cultural characteristics/dimensions considered in the research model (masculinity, collectivism, and uncertainty avoidance) significantly affected the perceived usefulness and the perceived ease of using the online social media platform. However, masculinity had a significant positive effect on perceived usefulness but not on perceived ease of use. These results imply that technology tools for people in high masculinity cultures should be designed to maximize the effectiveness of the technology for achieving goals rather than to maximize the ease of using the technology. On the other hand, the use of online social media for acquiring and sharing health-related information significantly affected the social relationships of users but not their health self-efficacy. The results of this study imply that participants in online communities share health-related information not only to enhance their health but also to form strong social connections. This study proposes a new construct of technology acceptance, acquisition, and sharing of health-related information and investigates its effects on social relationships and health self-efficacy.     

Word of Mouth impact on the adoption of mobile banking in Iran

Purpose

The purpose of this paper is to explore word of mouth impact on the adoption of mobile banking in Iran. This study provides insights into factors affecting the adoption of mobile banking in Iran.

Modelling the Roles of Cewebrity Trust and Platform Trust in Consumers’ Propensity of Live-Streaming: An Extended TAM Method

Live streaming is a booming industry in China, involving an increasing number of Internet users. Previous studies show that trust is a cornerstone to develop e-commerce. Trust in the streaming industry is different from that of other e-commerce areas. There are two major dimensions of trust in the live streaming context: platform trust and cewebrity trust, which are both important for customers to adopt and reuse a specific live streaming service. We collected questionnaire data from 520 participates who have used live streaming services in China. We model the collected data and identified factors that can influence users’ propensity by an extended technology acceptance model (TAM) method. According to our analysis, both cewebrity trust and platform trust will greatly influence users’ intention to reuse a certain platform. Moreover, results also indicate that cewebrity trust is far more important than platform trust. These findings can lead to several management strategies to improve the adherence of users to streaming platforms.     

基于IP核的芯片级测试结构研究

分析了芯片级测试的特点以及与传统板级测试区别,对SOC测试结构的核心部分测试访问机制(TAM)和Wrapper进行了详细的论述,分析了系统级芯片的测试结构及其优化.