Redesigning Historic Districts: A Study of Preservation Plans for Historic Districts of Jingzhou Ancient City in Hubei, China

Designation of historic districts is becoming a more commonly seen strategy for protecting larger environment and historic urban fabrics in China. Jingzhou, which is one of the first 24 “Historic Cultural Cities” in China, designated three historic districts in 2014. However, there are many issues with the existing preservation plans. Before the completed implementation of the plans, this thesis hopes to provide better solutions for creating more equitable and resilient historic districts through criticizing the existing plans, researching on case studies, as well as re-programming and redesigning the historic districts. The criticisms mainly focus on lacking sufficient considerations of large-scale demolition on local community, planning for superfluous amount of land use for tourism that brings negative impact on local residents’ life, and the improper designs of new buildings that mismatch the scales and form of existing buildings and erase the traces of history. Revitalization of Hutong in Beijing through “micro-circulation” and “organic-renew”, as well as the transformation from residential to commercial streets of Kuanzhai Alley in Chengdu are two case studies that are mainly researched on. The strategies of reprogram require participation of all three stakeholders that are government, residents, and developers, and propose to introduce microcirculation, community development commission, as well as transferable development rights into preservation and development of historic districts. The strategies of redesign reiterate the goal of creating an equitable and resilient neighborhood through revising demolition plan, designating distinctive spaces in neighborhood, and creating new site plan

The Impact of Hotel Service Robot Appearance and Service Attributes on Customer Experience

In the past decade, an increasing discussion has taken place regarding the employment of hotel service robots. One critical issue is the impact service robots exhibit on customer experience. However, most of the existing studies focus on service robots’ technical functions or customer’s adoption behavior instead of customers’ psychological or attitudinal reactions toward the robot. Meanwhile, the emergence of humanoid robots has raised great attention from both researchers and industry practitioners. Humanlike features (e.g. facial expressions, emotions, and motions) inherently affect customer experience in a hotel environment. Nevertheless, limited literature exists in incorporating service robots’ anthropomorphism and service attributes into customer experience and perceived brand equity. Not many studies have included both the service robots’ traits and customers’ personality traits when assessing customer experience. Therefore, the purpose of the current study is to explore and understand the impact of service robots’ appearance, service efficiency, and service customization on customer experience interacting with the service robot in the context of a hotel front desk check-in service. Customers’ personality traits such as robot anxiety, technology readiness, and self-image congruity are also taken into consideration. This study also examines the influence of service robots’ appearance and service attributes on hotel customers’ perceptions toward the hotel brand equity. The current study used experiments and online surveys to test the theoretical model and the perception changes toward the hotel brand equity. Two samples of 220 and 161 hotel customers who have completed the check-in services in person in the past 12 months were recruited for Study 1 and Study 2, respectively. Pilot studies were conducted, and hypothetical scenarios were embedded in the online surveys. The results showed that hotel service robots’ appearance (extremely humanoid vs. humanoid vs. non-humanoid) did not lead to different customers’ experiences interacting with the service robot. Service efficiency was a significant factor while service customization was not in affecting customer experiences. Customers’ levels of technology readiness and self-image congruity exerted significant impacts on customer experiences. Moreover, customers did not show obvious perception changes before and after interacting with the hypothetical service robot. Theoretical and practical contributions were discussed

HMC-Based Accelerator Design For Compressed Deep Neural Networks

Deep Neural Networks (DNNs) offer remarkable performance of classifications and regressions in many high dimensional problems and have been widely utilized in real-word cognitive applications. In DNN applications, high computational cost of DNNs greatly hinder their deployment in resource-constrained applications, real-time systems and edge computing platforms. Moreover, energy consumption and performance cost of moving data between memory hierarchy and computational units are higher than that of the computation itself. To overcome the memory bottleneck, data locality and temporal data reuse are improved in accelerator design. In an attempt to further improve data locality, memory manufacturers have invented 3D-stacked memory where multiple layers of memory arrays are stacked on top of each other. Inherited from the concept of Process-In-Memory (PIM), some 3D-stacked memory architectures also include a logic layer that can integrate general-purpose computational logic directly within main memory to take advantages of high internal bandwidth during computation. In this dissertation, we are going to investigate hardware/software co-design for neural network accelerator. Specifically, we introduce a two-phase filter pruning framework for model compression and an accelerator tailored for efficient DNN execution on HMC, which can dynamically offload the primitives and functions to PIM logic layer through a latency-aware scheduling controller. In our compression framework, we formulate filter pruning process as an optimization problem and propose a filter selection criterion measured by conditional entropy. The key idea of our proposed approach is to establish a quantitative connection between filters and model accuracy. We define the connection as conditional entropy over filters in a convolutional layer, i.e., distribution of entropy conditioned on network loss. Based on the definition, different pruning efficiencies of global and layer-wise pruning strategies are compared, and two-phase pruning method is proposed. The proposed pruning method can achieve a reduction of 88% filters and 46% inference time reduction on VGG16 within 2% accuracy degradation. In this dissertation, we are going to investigate hardware/software co-design for neural network accelerator. Specifically, we introduce a two-phase filter pruning framework for model compres- sion and an accelerator tailored for efficient DNN execution on HMC, which can dynamically offload the primitives and functions to PIM logic layer through a latency-aware scheduling con- troller. In our compression framework, we formulate filter pruning process as an optimization problem and propose a filter selection criterion measured by conditional entropy. The key idea of our proposed approach is to establish a quantitative connection between filters and model accuracy. We define the connection as conditional entropy over filters in a convolutional layer, i.e., distribution of entropy conditioned on network loss. Based on the definition, different pruning efficiencies of global and layer-wise pruning strategies are compared, and two-phase pruning method is proposed. The proposed pruning method can achieve a reduction of 88% filters and 46% inference time reduction on VGG16 within 2% accuracy degradation

International capital flows : do short-term investment and direct investment differ?

The authors examine the behavior of four major components of international capital flows in 15 developing and industrial countries. Striking differences in the behavior of the component flows arise in general specifications that allow the flows to interact. For example, the behavior of international short-term investment appears to be sensitive to changes in all the other types of international capital flows, including direct investment, but direct investment appears to be insensitive to such changes. In finding that short-term investment appears to respond more dramatically to disturbances in other capital flows and in other countries than does direct investment, the authors provide empirical support for the conventional notion that short-term investment is"hot money"and direct investment is not.International Terrorism&Counterterrorism,Economic Theory&Research,Payment Systems&Infrastructure,Fiscal&Monetary Policy,Capital Markets and Capital Flows,Financial Intermediation,International Terrorism&Counterterrorism,Economic Theory&Research,Banks&Banking Reform,Capital Flows

Equity and bond flows to Asia and Latin America : the role of global and country factors

The authors investigate what has motivated the large portfolio flows to several developing countries in recent years. Using monthly data on U.S. capital flows to nine Latin American and nine Asian countries (instead of monthly reserves data), they analyze the behavior of bond and equity flows to those countries. Using panel data, they find that global factors - such as a drop in U.S. interest rates and the slowdown in U.S. industrial production - are important in explaining capital inflows. But country developments are at least as important in determining those flows, especially for Asia. They also find that equity flows are more sensitive than bond flows to global factors, but that bond flows are generally more sensitive to a country's credit rating and to the secondary market price of debt.Economic Theory&Research,Banks&Banking Reform,Financial Intermediation,Environmental Economics&Policies,Macroeconomic Management

Two Moons

People may think that they can better understand the world through convenient technology in this Internet age. The fact is that even though we can search almost everything on Google, we still live and are confined to a small world. What\u27s worse, big smart data will provide you with privately customized information services based on your specific situation. People gradually become accustomed to a voice and are more inclined to think that the world is what they see. This has also led to the fact that people of different social classes and cultural environments may be very different, and they believe too much in the world they perceive and tend to reject and deny other voices