AI Design to Innovation

Artificial intelligence (AI) is expected to create various innovations for changing human workplaces. AI is characterized by features of learning and self-growth. Efficient AI learning should depend on human inputs, particularly from human professionals (e.g., doctors and nurses). Hence, professionals’ intention to facilitate AI innovation is critical. However, little is known about how to design AI to strengthen such intention, warranting our research to answer this question. We use expectancy-value theory to identify three potential AI design elements and examine how they enhance the perception that AI enhances professionals’ capabilities and their intention to facilitate AI innovation. These elements are contextual-specific features of AI, extending the expectancy-value theory to the novel AI technologies. We will test our model by using two-wave data of nursing professionals’ responses. The results are expected to assist AI designs that effectively motivate professionals to facilitate AI innovations

Predicting effects of blood flow rate and size of vessels in a vasculature on hyperthermia treatments using computer simulation

<p>Abstract</p> <p>Background</p> <p>Pennes Bio Heat Transfer Equation (PBHTE) has been widely used to approximate the overall temperature distribution in tissue using a perfusion parameter term in the equation during hyperthermia treatment. In the similar modeling, effective thermal conductivity (K_eff) model uses thermal conductivity as a parameter to predict temperatures. However the equations do not describe the thermal contribution of blood vessels. A countercurrent vascular network model which represents a more fundamental approach to modeling temperatures in tissue than do the generally used approximate equations such as the Pennes BHTE or effective thermal conductivity equations was presented in 1996. This type of model is capable of calculating the blood temperature in vessels and describing a vasculature in the tissue regions.</p> <p>Methods</p> <p>In this paper, a countercurrent blood vessel network (CBVN) model for calculating tissue temperatures has been developed for studying hyperthermia cancer treatment. We use a systematic approach to reveal the impact of a vasculature of blood vessels against a single vessel which most studies have presented. A vasculature illustrates branching vessels at the periphery of the tumor volume. The general trends present in this vascular model are similar to those shown for physiological systems in Green and Whitmore. The 3-D temperature distributions are obtained by solving the conduction equation in the tissue and the convective energy equation with specified Nusselt number in the vessels.</p> <p>Results</p> <p>This paper investigates effects of size of blood vessels in the CBVN model on total absorbed power in the treated region and blood flow rates (or perfusion rate) in the CBVN on temperature distributions during hyperthermia cancer treatment. Also, the same optimized power distribution during hyperthermia treatment is used to illustrate the differences between PBHTE and CBVN models. K_eff(effective thermal conductivity model) delivers the same difference as compared to the CBVN model. The optimization used here is adjusting power based on the local temperature in the treated region in an attempt to reach the ideal therapeutic temperature of 43°C. The scheme can be used (or adapted) in a non-invasive power supply application such as high-intensity focused ultrasound (HIFU). Results show that, for low perfusion rates in CBVN model vessels, impacts on tissue temperature becomes insignificant. Uniform temperature in the treated region is obtained.</p> <p>Conclusion</p> <p>Therefore, any method that could decrease or prevent blood flow rates into the tumorous region is recommended as a pre-process to hyperthermia cancer treatment. Second, the size of vessels in vasculatures does not significantly affect on total power consumption during hyperthermia therapy when the total blood flow rate is constant. It is about 0.8% decreasing in total optimized absorbed power in the heated region as γ (the ratio of diameters of successive vessel generations) increases from 0.6 to 0.7, or from 0.7 to 0.8, or from 0.8 to 0.9. Last, in hyperthermia treatments, when the heated region consists of thermally significant vessels, much of absorbed power is required to heat the region and (provided that finer spatial power deposition exists) to heat vessels which could lead to higher blood temperatures than tissue temperatures when modeled them using PBHTE.</p

Media Richness and User Continuance to Instant Messaging

Media richness determines adoption of information systems. Insufficient research was done for investigating its influence on user continuance of using instant messaging applications. This study used classic IS and psychological theories to construct a research framework. This study gathered more than 200 responses by using an online form. LISREL software was used to conduct structural equation modeling technique to test the research framework. The findings indicated that various but not all dimensions of media richness positively contribute to users’ continuance to use instant messaging applications. Specific dimensions provide insights for managers to design their applications to effectively retain their users

The effect of enforcement intensity on illegal insider trading volume: the case of Taiwan

In this paper, the authors examine the illegal insider trading volume and cumulative abnormal return by the relative variables of the amendment, the change of the securities price, the number of defendants, the penalty and the fine for insider who committed a crime, and the quality of concealed important information. Illegal insider trading is prohibited by the article 157-1 of Securities and Exchange Act in Taiwan. It has been amended three times to provide a sound and rigorous law and completely protect investors. The authors examine the illegal insider trading volume after the amendment to explore whether the Securities and Exchange Act is efficient enough to lower illegal insider trading. The authors find that the change of the securities price and the quality of concealed important information are the critical factors which affect the illegal insider trading volume and cumulative abnormal returns. Nevertheless, the relative variables of the amendment do not show significant effect

On Scalable Service Function Chaining with O(1) Flowtable Entries

The emergence of Network Function Virtualization (NFV) enables flexible and agile service function chaining in a Software Defined Network (SDN). While this virtualization technology efficiently offers customization capability, it however comes with a cost of consuming precious TCAM resources. Due to this, the number of service chains that an SDN can support is limited by the flowtable size of a switch. To break this limitation, this paper presents CRT-Chain, a service chain forwarding protocol that requires only constant flowtable entries, regardless of the number of service chain requests. The core of CRT-Chain is an encoding mechanism that leverages Chinese Remainder Theorem (CRT) to compress the forwarding information into small labels. A switch does not need to insert forwarding rules for every service chain request, but only needs to conduct very simple modular arithmetic to extract the forwarding rules directly from CRT-Chain's labels attached in the header. We further incorporate prime reuse and path segmentation in CRT-Chain to reduce the header size and, hence, save bandwidth consumption. Our evaluation results show that, when a chain consists of no more than 5 functions, CRT-Chain actually generates a header smaller than the legacy 32-bit header defined in IETF. By enabling prime reuse and segmentation, CRT-Chain further reduces the total signaling overhead to a level lower than the conventional scheme, showing that CRT-Chain not only enables scalable flowtable-free chaining but also improves network efficiency