Calibrating parametric exponential Lévy models to option market data by incorporating statistical moments priors

We investigate a parametric method for calibrating European option pricing using the state-of-art exponential Lévy models. We propose a derivative-free calibration method constrained by four observable statistical moments (mean, variance, skewness and kurtosis) from underlying time series to conquer the ill-posed inverse problem and to incorporate priors on observable statistical moments. We present a numerical implementation scheme for calibrating the exponential Lévy models and show that it can resolve the instability of the inverse problems empirically and can produce good calibration results. In particular, we apply our approach to real market data sets of S&P 500 call options with significantly better performance.     

A fact-oriented ontological approach to human process modeling for knowledge-intensive business services

Modern business environment emphasizes the role of knowledge-intensive business services (KIBS). As well as the enterprises in any other kinds of industries, business process management (BPM) can be a source of core competency for the enterprises in KIBS industry. However, most of the business processes in KIBS are human processes which are collaborative, innovative, and dynamic, which cannot be supported well by current BPM technologies. Human interaction management (HIM) has emerged as an alternative theory to deal with human processes in KIBS. But, the current ways of process modeling and management in HIM have a problem of complexity, especially in terms of realizing its principle of ‘supportive activity management’. This research adopts fact-oriented ontological approach to address this problem. Based on fact-oriented approach, human-friendly condition modeling and state management during supportive activity management can be achieved.     

A scrape-through piezoelectric MEMS energy harvester with frequency broadband and up-conversion behaviors

We propose a MEMS piezoelectric energy harvester with a wide operating frequency range by incorporating a high-frequency piezoelectric cantilever and a metal base as the top and bottom stoppers with a low-frequency piezoelectric cantilever. Frequency up-conversion of the piezoelectric energy harvester is realized when the low-frequency piezoelectric cantilever impacts and scrapes through the high-frequency piezoelectric cantilever. For an input acceleration of 0.6?g, with top and bottom stopper distances of 0.75 and 1.1?mm, respectively, the operating frequency ranges from 33 to 43?Hz. The output voltage and power up to 95?mV and 94 nW can be achieved. Experimental results indicate that the frequency up-conversion mechanism significantly improves the effective power.     

Modeling analysis of a triaxial microaccelerometer with piezoelectric thin-film sensing using energy method

This study applies energy method to derive the system modeling of a triaxial microaccelerometer that consists of a quadri-beam suspension, a seismic mass, and displacement transducers using piezoelectric thin films. Two suspension beams support both ends of the seismic mass, which is fabricated by anisotropic etching of silicon. An out-of-plane acceleration will result in a symmetric bend, and in-plane accelerations will produce asymmetric bend and torsion of the suspension beams. Two piezoelectric thin-film transducers are arranged at both ends of each suspension beam. Eight transducers in total are interconnected such that triaxial accelerations can be measured selectively. The structure stiffness of the suspension beams considers both the silicon beams and piezoelectric films by the use of the laminated beam theory. Therefore, the analytical model is applicable to the accelerometers with thick piezoelectric films. The model is based on the anisotropic material properties of Silicon and PZT and Euler’s beam equation with the assumptions that smaller strains and stresses are negligible. The analytical results of the resonant frequencies and sensor sensitivities to triaxial accelerations are presented and confirmed by finite element analysis.     

Iteratively constrained selection of word alignment links using knowledge and statistics

Word alignment is a crucial component in applications that use bilingual resources. Statistical methods are widely used because they are portable and allow simple system building. However, pure statistical methods often incorrectly align functional words in the English–Korean language pair due to differences in the typology of the languages and a lack of knowledge. Knowledge is inevitably required to correct errors and to improve word alignment quality. In this paper, we introduce an effective method that uses an iterative process to incorporate knowledge into the word alignment system. The method achieved significant improvements in word alignment and its application: statistical machine translation.     

Low-complexity joint transmit and receive antenna selection for MIMO systems

In this paper, we present a low-complexity algorithm for real-time joint transmit and receive antenna selection in MIMO systems. The computational complexity of exhaustive search in this problem grows exponentially with the number of transmit and receive antennas. We apply Binary Particle Swarm Optimization (BPSO) to the joint transmit and receive antenna selection problem. In addition, applying the general BPSO to joint antenna selection, we also present a specific improvement to this population-based heuristic algorithm, namely, we feed cyclically shifted initial population so that the average convergence time (the number of iterations until reaching an acceptable solution) is reduced. The proposed BPSO for joint antenna selection problem has a low computational complexity, and its effectiveness is verified through simulation results.     

Deriving industrial logistics hub reference models for manufacturing based economies

Global enterprises require extended logistics operations that integrate channel intermediaries into the network. The method for deriving integrated models for logistics hubs that improve the efficiency of manufacturers’ global operations is the focus of this paper. Under government sponsorship, six industrial logistics hubs were implemented by leading manufacturing sectors across Taiwan over a five year period from 2004 until 2008. Each industry sector had unique industry characteristics, business strategies, and logistics models. Therefore, this paper describes how generalized and quick to implement integrated logistics hubs are developed by studying the successful reference models and systems used by six independent industrial sectors. The research results provide a field tested method for deriving integrated logistics hub models in different manufacturing economies with notes that provide sufficient methodological detail for repeating the construction of logistics hubs in other manufacturing economies.     

Measuring the degree of eyestrain caused by watching LCD and PDP devices

In this paper, we propose a new way of measuring the degree of eyestrain caused by watching LCD (Liquid Crystal Display) and PDP (Plasma Display Panel) devices. In the experiments, we used a head-mounted eye capturing device and an illumination setup that was designed to avoid specular reflections caused by glasses or contact lenses. Using the captured eye images, we analyzed the eye blinking and changes of pupil sizes (pupil accommodation), using a real-time image processing algorithm. Then we analyzed the degree of eyestrain based on the calculated blinking rate and the pupil accommodation speed. The proposed method offers five improvements over previous methods. First, we perform a comparative analysis of LCD and PDP devices based on the degree of eyestrain. Second, to analyze the degree of eyestrain, we use quantitative data such as the blinking rate and the pupil accommodation speed. Third, we measure the accurate eye blinking and changes of pupil sizes by using high-resolution and zoomed eye image sequences. Fourth, since the camera and illuminative system are based on a specular reflective model, the proposed method can be used with subjects that wear glasses or contact lenses. Fifth, the proposed method is performed at real-time speed.Experimental results showed that the degree of eyestrain when watching LCD devices was greater than that when watching PDP devices.

Relevance to industry

In the large display industry, LCD and PDP devices have become more and more prevalent. In the past, LCD devices have been compared to PDP devices in terms of factors such as spatial resolution, brightness, contrast levels, etc. To perform more accurate comparisons based on human factor, we are proposing a new way of comparing LCD to PDP devices based on the degree of eyestrain.     

Asymmetric information distances for automated taxonomy construction

A novel method for automatically constructing taxonomies for specific research domains is presented. The proposed methodology uses term co-occurrence frequencies as an indicator of the semantic closeness between terms. To support the automated creation of taxonomies or subject classifications we present a simple modification to the basic distance measure, and describe a set of procedures by which these measures may be converted into estimates of the desired taxonomy. To demonstrate the viability of this approach, a pilot study on renewable energy technologies is conducted, where the proposed method is used to construct a hierarchy of terms related to alternative energy. These techniques have many potential applications, but one activity in which we are particularly interested is the mapping and subsequent prediction of future developments in the technology and research.     

Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.