A hybrid performance evaluation system for notebook computer ODM companies

[[abstract]]The aim of the paper is to fulfill this need by building a conceptual framework for measuring the business performance of notebook computer ODM (Original Design Manufacturer) companies carried out to investigate how performance is understood and to identify the potential dimensions to improvement. In the process, a multiple criteria procedure is used to assess the performance in these companies. We explore the performance-evaluation systems by using fuzzy AHP and VIKOR techniques. The evidence from the investigation showed that supply chain capability and manufacturing capability are the top two indicators for the notebook computer ODM companies’ performance. Furthermore, it was found that Quanta and Compal have the relative high business performance among these companies. The research provides evidence which establishes whether benchmarking provides a real and lasting benefit to notebook computer ODM companies. A series of managerial implications are set forth and discussed.[[journaltype]]國外[[incitationindex]]SSCI[[booktype]]紙本[[countrycodes]]NG

Assessing Taiwan financial holding companies’ performance using window analysis and Malmquist productivity index

[[abstract]]Performance evaluation is the important approach for enterprises to give incentive and restraint to their operators and it is also an important channel for enterprise stakeholders to get the performance information. The purpose of this study is to analyze current evaluation system for Taiwan Financial Holding Companies. This research tries to measure the performance on thirteen financial holding companies in Taiwan for the period 2003 to 2009. The result presented the proposed method is practical and useful. Also the study result represented that the combined method had certain scientific and rationality. The evaluation model indicates that this method be more reasonable and easier to grasp than other methods. As a result, it is easier to popularize this evaluation method in enterprises. The study thus presents a complete assessment model that helps managers to identify items for improvement, while simultaneously promoting cost and time efficiencies in financial Holding Companies.[[journaltype]]國外[[incitationindex]]SSCI[[booktype]]電子版[[countrycodes]]NG

Path Planning on Quadric Surfaces and Its Application

In this chapter, recent near-shortest path-planning algorithms with O(nlog n) in the quadric plane based on the Delaunay triangulation, Ahuja-Dijkstra algorithm, and ridge points are reviewed. The shortest path planning in the general three-dimensional situation is an NP-hard problem. The optimal solution can be approached under the assumption that the number of Steiner points is infinite. The state-the-art method has at most 2.81% difference on the shortest path length, but the computation time is 4216 times faster. Compared to the other O(nlog n) time near-shortest path approach (Kanai and Suzuki, KS’s algorithm), the path length of the Delaunay triangulation method is 0.28% longer than the KS’s algorithm with three Steiner points, but the computation is about 31.71 times faster. This, however, has only a few path length differences, which promises a good result, but the best computing time. Notably, these methods based on Delaunay triangulation concept are ideal for being extended to solve the path-planning problem on the Quadric surface or even the cruise missile mission planning and Mars rover

Repulsive Guidance Molecule (RGM) Family Proteins Exhibit Differential Binding Kinetics for Bone Morphogenetic Proteins (BMPs)

Bone morphogenetic proteins (BMPs) are members of the transforming growth factor beta superfamily that exert their effects via type I and type II serine threonine kinase receptors and the SMAD intracellular signaling pathway to regulate diverse biologic processes. Recently, we discovered that the repulsive guidance molecule (RGM) family, including RGMA, RGMB, and RGMC/hemojuvelin (HJV), function as co-receptors that enhance cellular responses to BMP ligands. Here, we use surface plasmon resonance to quantitate the binding kinetics of RGM proteins for BMP ligands. We show that among the RGMs, HJV exhibits the highest affinity for BMP6, BMP5, and BMP7 with KD 8.1, 17, and 20 nM respectively, versus 28, 33, and 166 nM for RGMB, and 55, 83, and 63 nM for RGMA. Conversely, RGMB exhibits preferential binding to BMP4 and BMP2 with KD 2.6 and 5.5 nM respectively, versus 4.5 and 9.4 nM for HJV, and 14 and 22 nM for RGMA, while RGMA exhibits the lowest binding affinity for most BMPs tested. Among the BMP ligands, RGMs exhibit the highest relative affinity for BMP4 and the lowest relative affinity for BMP7, while none of the RGMs bind to BMP9. Thus, RGMs exhibit preferential binding for distinct subsets of BMP ligands. The preferential binding of HJV for BMP6 is consistent with the functional role of HJV and BMP6 in regulating systemic iron homeostasis. Our data may help explain the mechanism by which BMPs exert cell-context specific effects via a limited number of type I and type II receptors

Patient-oriented simulation based on Monte Carlo algorithm by using MRI data

<p>Abstract</p> <p>Background</p> <p>Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with <it>in vivo </it>MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation.</p> <p>Methods</p> <p>In this study, an individualized brain is modeled based on <it>in vivo </it>MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system.</p> <p>Results</p> <p>Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement.</p> <p>Conclusions</p> <p>In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.</p

Clinical meaning of age-related expression of fecal cytokeratin 19 in colorectal malignancy

<p>Abstract</p> <p>Background</p> <p>Colorectal cancer (CRC) is one of the leading causes of malignant death worldwide. Because young age of onset is often considered a poor prognostic factor for CRC, it is important to identify the poor outcomes of CRC in a younger population and to consider an aggressive approach by implementing early treatment. Our aim was to specifically quantify the fecal cytokeratin 19 (CK19) transcript from CRC patients and investigate its correlation with clinical stage, tumor malignancy, and age.</p> <p>Methods</p> <p>The quantitation of fecal CK19 transcript was determined by a quantitative real-time reverse transcription polymerase chain in 129 CRC patients (45 younger than 60 years at diagnosis) and 85 healthy controls. The levels of CK19 protein were examined both in colonic cell lines and tissues.</p> <p>Results</p> <p>The analysis of 45 younger CRC patients (age ≤ 60 years) revealed that patients at the M1 stage had significantly higher expression levels of fecal CK19 mRNA when compared with healthy controls (<it>p </it>< 0.001) and patients at the M0 stage (<it>p </it>= 0.004). Additionally, the degree of consistency between the mean level of fecal CK19 mRNA and the distant metastatic rate in each age interval was up to 89% (<it>p </it>= 0.042).</p> <p>Conclusion</p> <p>These results indicate that high levels of fecal CK19 mRNA represent a potential marker for colorectal malignancy and for aggressive treatment of younger CRC patients.</p

Location-based Data Analysis of Visitor Structure for Recreational Area Management

This work presents a location-based data analysis framework for profiling visitors structures. In terms of recreational area management, understanding visitors’ structure and popularity is important. Traditionally, visitors monitoring with automatic counting devices has drawbacks of inaccurate visitors counting. In this work, compared to automatic counting devices, we use Wi-Fi tracking as the main method to count visitors, which provides a fairly precise picture of visitor structures. Moreover, we deliver rich analytic functions in this framework and we present the functionality with visitor data collected from Guanyinshan Visitor Center. This framework not only standardizes visitor counting process but also facilitates a profound analysis of visitor structures. Key Words: Guanyinshan Visitor Center, Wi-Fi trackin

Acquiring Authentic Data in Unattended Wireless Sensor Networks

An Unattended Wireless Sensor Network (UWSN) can be used in many applications to collect valuable data. Nevertheless, due to the unattended nature, the sensors could be compromised and the sensor readings would be maliciously altered so that the sink accepts the falsified sensor readings. Unfortunately, few attentions have been given to this authentication problem. Moreover, existing methods suffer from different kinds of DoS attacks such as Path-Based DoS (PDoS) and False Endorsement-based DoS (FEDoS) attacks. In this paper, a scheme, called AAD, is proposed to Acquire Authentic Data in UWSNs. We exploit the collaboration among sensors to address the authentication problem. With the proper design of the collaboration mechanism, AAD has superior resilience against sensor compromises, PDoS attack, and FEDoS attack. In addition, compared with prior works, AAD also has relatively low energy consumption. In particular, according to our simulation, in a network with 1,000 sensors, the energy consumed by AAD is lower than 30% of that consumed by the existing method, ExCo. The analysis and simulation are also conducted to demonstrate the superiority of the proposed AAD scheme over the existing methods

DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms. Connecting diseases with similar pathological mechanisms could inspire novel strategies on the effective repositioning of existing drugs and therapies. Although there have been several studies attempting to generate disease connectivity networks, they have not yet utilized the enormous and rapidly growing public repositories of disease-related omics data and literature, two primary resources capable of providing insights into disease connections at an unprecedented level of detail. Our DiseaseConnect, the first public web server, integrates comprehensive omics and literature data, including a large amount of gene expression data, Genome-Wide Association Studies catalog, and text-mined knowledge, to discover disease–disease connectivity via common molecular mechanisms. Moreover, the clinical comorbidity data and a comprehensive compilation of known drug–disease relationships are additionally utilized for advancing the understanding of the disease landscape and for facilitating the mechanism-based development of new drug treatments