Image Fusion with Contrast Improving and Feature Preserving

The goal of image fusion is to obtain a fused image that contains most significant information in all input images which were captured by different sensors from the same scene. In particular, the fusion process should improve the contrast and keep the integrity of significant features from input images. In this paper, we propose a region-based image fusion method to fuse spatially registered visible and infrared images while improving the contrast and preserving the significant features of input images. At first, the proposed method decomposes input images into base layers and detail layers using a bilateral filter. Then the base layers of the input images are segmented into regions. Third, a region-based decision map is proposed to represent the importance of every region. The decision map is obtained by calculating the weights of regions according to the gray-level difference between each region and its neighboring regions in the base layers. At last, the detail layers and the base layers are separately fused by different fusion rules based on the same decision map to generate a final fused image. Experimental results qualitatively and quantitatively demonstrate that the proposed method can improve the contrast of fused images and preserve more features of input images than several previous image fusion methods

The Literature Review of Technology Acceptance Model: A Study of the Bibliometric Distributions

Technology acceptance model plays a signified issue in the information systems field since this theory was introduced by Davis in 1989. This paper investigates the features of technology acceptance model literature based on bibliometric method. By searching the ISI Web of knowledge database under the keyword of “technology acceptance model,” 689 articles were retrieved and analyzed though growth of the literatures and citation, document type, publication countries, subject area, keyword analysis are addressed. The distribution of journal paper was also examined using Bradford’s law and Lotka’s law. As the result, this research found that technology acceptance model literature has a steady growth as well as the citations. Relevant articles were concentrating on computer science, information systems, management, information science, and library science. The author productivity distribution data in technology acceptance literature was consistent with Lotka’s law. Furthermore, eight core journals were identified utilizing the Bradford’s law

Examining The Factors That Affect ERP Assimilation

The aim of this study is to identify the factors that influence the assimilation of enterprise resource planning (ERP) systems in the post-implementation stage. Building on organizational information processing theory (OIPT) and absorptive capacity (AC), we propose an integrated model, which examines the relationship among organizational fit, absorptive capacity, environmental uncertainty, and ERP assimilation. Based on the survey data from 98 firms that have implemented ERP, most of the proposed hypotheses were supported, showing that initial fit, potential AC, realized AC, and heterogeneity jointly affect ERP assimilation. Task uncertainty (hostility and heterogeneity) negatively moderates the relationship between initial fit and ERP assimilation. The implications for both theory and practice are discussed

Clinical applicability of quantitative nailfold capillaroscopy in differential diagnosis of connective tissue diseases with Raynaud's phenomenon

Background/PurposeNailfold capillaroscopy is a useful tool to distinguish primary from secondary Raynaud's phenomenon (RP) by examining the morphology of nailfold capillaries but its role in disease diagnosis is not clearly established. The purpose of this study was to evaluate the roles of quantitative nailfold capillaroscopy in differential diagnosis of connective tissue diseases (CTDs) with RP.MethodsThe data between the year 2005 and 2009 were retrieved from the nailfold capillaroscopic database of National Taiwan University Hospital (NTUH). Only the data from the patients with RP were analyzed. The criteria for interpretation of capillaroscopic findings were predefined. The final diagnoses of the patients were based on the American College of Rheumatology classification criteria for individual diseases, independent of nailfold capillaroscopic findings. The sensitivity and the specificity of each capillaroscopic pattern to the diseases were determined.ResultsThe data from a total of 67 patients were qualified for the current study. We found the sensitivity and specificity of scleroderma pattern for systemic sclerosis (SSc) were 89.47% and 80%, and the specificity of the early, active, and late scleroderma patterns for SSc reached 87.5%, 97.5%, and 95%, respectively. The sensitivity/specificity of systemic lupus erythematosus (SLE) pattern for SLE and polymyositis/dermatomyositis (PM/DM) pattern for PM/DM were 33.33%/95.45% and 60%/96.3%, respectively. The sensitivity/specificity of mixed connective tissue disease (MCTD) pattern for MCTD were 20%/100%.ConclusionThe nailfold capillaroscopic (NC) patterns may be useful in the differential diagnosis of CTDs with RP. The NC patterns for SSc and PM/DM are both sensitive and specific to the diseases, while the SLE and MCTD patterns exhibit high specificity but relatively low sensitivity

Driving Control Technologies of New High-Efficient Motors

Although switched-reluctance machine (SRM) possesses many structural advantages and application potential, it is rather difficult to successfully control with high performance being comparable to other machines. Many critical affairs must be properly treated to obtain the improved operating characteristics. This chapter presents the basic and key technologies of switched-reluctance machine in motor and generator operations. The contents in this chapter include: (1) structures and governing equations of SRM; (2) some commonly used SRM converters; (3) estimation of key parameters and performance evaluation of SRM drive; (4) commutation scheme, current control scheme, and speed control scheme of SRM drive; (5) some commonly used front-end converters and their operation controls for SRM drive; (6) reversible and regenerative braking operation controls for SRM drive; (7) some tuning issues for SRM drive; (8) operation control and some tuning issues of switched-reluctance generators; and (9) experimental application exploration for SRM systems: (a) wind generator and microgrid; (b) EV SRM drive

Decision Support System For Safety Warning Of Bridge – A Case Study In Central Taiwan

This study aims at developing the decision support system (DSS) for safety warning of bridge. In the DSS, real-time and forecasted radar rainfalls are used to predict flood stage, velocity and scouring depth around bridge piers for one to three hours ahead. The techniques adopted in the DSS include (1) measurement and correction models of radar rainfall, (2) a grid-based distributed rainfall-runoff model for simulating reservoir inflows, (3) models for predicting flood stages, velocities and scouring depths around bridge piers, and (4) ultimate analysis approaches for evaluating safety of pier foundation. The DSS can support the management department to decide whether they should close bridges or not during floods. The proposed DSS gave a test-run during Typhoon Morakot in 2009 in Dajia River Basin, central Taiwan. The results show the DSS has reasonable performances during floods

Automatic Finger Interruption Detection in Electroluminescence Images of Multicrystalline Solar Cells

This study provides an automatic method for detecting finger interruptions in electroluminescence (EL) images of multicrystalline solar cells. The proposed method is a supervised classification method. We obtain regions of interest (ROI) by separating the EL image to several regions. The fingers within each ROI are candidates for defect detection. We horizontally scan each ROI region and extract features from each finger pixel. In the training stage, we record a set of features which are extracted from interrupted fingers and noninterrupted fingers. These features are represented as points in a spectral embedding space produced by spectral clustering method. These points will be classified into two clusters: interrupted fingers and noninterrupted fingers. In the classification stage, we firstly detect the position of fingers in an EL image and obtain features from each finger. The set of features in each finger combined with known features in the training stage will be represented as points in the spectral embedding space and then will be classified to the cluster with nearer cluster centroid of known features. Experimental results show that the proposed method can effectively detect finger interruptions on a set of EL images of various solar cells

UNDERSTANDING COMPETITIVE PERFORMANCE OF SOFTWARE-AS-A-SERVICE (SAAS)—THE COMPETITIVE DYNAMICS PERSPECTIVE

Understanding the antecedents and consequences of a firm’s agility in cloud software applications is important. This papers draws on the competitive dynamics perspective to develop a model that explains the relationships between collaboration with vendors, agility, and competitive performance in software-as-a-service (SaaS) context. Collaboration reflects a firm’s ability to leverage interfirm resources, characterized as knowledge sharing and process alignment. Agility is measured by a firm’s strategy-oriented agility and service-oriented agility. This study also investigates the moderating effect of environmental turbulence. The proposed hypotheses are supported by the empirical data. The results show that competitive performance is affected by ability, which, in turn, is impacted by collaboration. Environmental turbulence positively moderates the relationship between agility and performance. Finally, we discuss the implications of our results