A Novel Financial Market Dynamics Analytic Framework against the Black Swans Effect

Inevitably the turbulence of social events, the Black Swans, will impact the economic growth and stability significantly. The polarized media and the populism amplify this impact during the survival period of the social event. To observe the impact of the event, using the leading indices such as the volatility of the financial market is a common approach of reflecting the sensitivity of the event. In the democratic society, the presidential election is the most significant social event that gives the uncertainty of the existing political courses in many perspectives. Arguably, especially when this election occurs in a divided society, the public opinions of the major media collide with the “silent” populism, will magnify the financial turbulence drastically. Mr. Donald Trump has been considered as a black swan since he became the president candidate of the Republicans Party (GOP). Many pessimistic people speculated he would jeopardize the economy if he won the election. This paper examined the poll statistics and the stock indices; not only be this paper able to disclose how the controversial election impacted the financial market, but also to show the deviation between the polls conducted by the major media and the result of the election by rigorous analytical processes. Lastly, the proposed analytic framework can be applied to any critical social events that has financial impact or no

Yeast cytochrome c oxidase: a model system to study mitochondrial forms of the haem-copper oxidase superfamily.

The known subunits of yeast mitochondrial cytochrome c oxidase are reviewed. The structures of all eleven of its subunits are explored by building homology models based on the published structures of the homologous bovine subunits and similarities and differences are highlighted, particularly of the core functional subunit I. Yeast genetic techniques to enable introduction of mutations into the three core mitochondrially-encoded subunits are reviewed

THE RECOMMENDATIONS FOR OPEN HARBOR INITIATIVE

The efficiency of harbor management plays a significant economic role to a nation in various aspects, including trading business, logistics and the manufacturing. The visibility of harbor activities and management determines the performance of the whole logistic chain. The harbor agencies continuously strive to provide better operation models to the stakeholders by collecting and analyzing these data populated from the activities. To expedite this improvement, an Open Innovation Model is called to encourage more special interest groups to contribute their works; the harbor agencies disclose the datasets derived from those servicing activities through the government Open Data platforms. Since there is no clear picture of how these contributors would utilize the datasets for their researches, there is a considerable requirement gap between the dataset provider - the harbor agencies and the consumers - the interest groups. This paper surveyed the open datasets provided by the advanced harbors using the textual analysis and the text mining approaches to emerge the potential requirements for the Open Harbor initiative followers such as Taiwan. By taking the example of Taiwan Open Harbor initiative, it reexamined the potential meaning against the already opened datasets and tangibly identified where they could be further enhanced to bring more value to the interest groups. Based on these findings, this paper presents the initiative realization models through the Enterprise Architecture - a methodology of defining the information systems from the strategic planning to the realization -processes as the recommendations to those pursuing operation eminence harbor agencies

Explorations in engagement for humans and robots

This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.Comment: 31 pages, 5 figures, 3 table

Smart Material Planning Optimization Problem Analysis

Mostly, the concept of smart manufacturing is addressed based upon how to effectively facilitate the production activities by using the automation equipment; however, causing the fluctuation of production may frequently root to the uncertain incoming sales orders. These uncertain factors may be influenced by various economic parameters, such as changes within trade regulations, competitor innovations, and changes within the market. In order to reduce the difference between the forecasted demand versus actual demand and to minimize risk, these factors need to be taken into account and be fully investigated. The current widely applied forecast methods are factory capacity-driven and based on the trend against the activity history. When the uncertainty comes from the external, then the forecasts derived from these models cannot provide convincing insights to let the firms make decisions confidently. Many previous prestigious studies focused on the problem-solving optimization mathematic methods and articulated the causality among latent factors; few have addressed to a holistic framework that the firms can practice on. This study presents a clear operable step-by-step framework to manage and cushion the impact from the external uncertain factors. It also introduces three novel and feasible production planning models with the consideration of the economic parameters. The empirical case was a multi-nation machinery-making firm who has adopted the proposed framework to optimize the material forecasts pursuing their smart manufacturing goals

Better age estimations using UV-optical colours: breaking the age-metallicity degeneracy

We demonstrate that the combination of GALEX UV photometry in the FUV (~1530 angstroms) and NUV (~2310 angstroms) passbands with optical photometry in the standard U,B,V,R,I filters can efficiently break the age-metallicity degeneracy. We estimate well-constrained ages, metallicities and their associated errors for 42 GCs in M31, and show that the full set of FUV,NUV,U,B,V,R,I photometry produces age estimates that are ~90 percent more constrained and metallicity estimates that are ~60 percent more constrained than those produced by using optical filters alone. The quality of the age constraints is comparable or marginally better than those achieved using a large number of spectrscopic indices.Comment: Published in MNRAS (2007), 381, L74 (doi: 10.1111/j.1745-3933.2007.00370.x