A new dimmer for alternating-current directly driven light-emitting-diode lamp

A new dimmer using a mental-oxide-semiconductor field-effect transistor (MOSFET) for alternating-current (AC) directly driven light-emitting-diode (LED) lamp was presented. The control method of proposed dimmer is pulse width control (PWM) method. Compared with the conventional phase-controlled dimmer, the proposed PWM dimmer can produce sine wave and did not cause harmonics problem. Furthermore, the proposed control method did not amplify the light flicker due to the independence of input voltage. Therefore, the PWM dimmer can be used as the dimmer of the AC LED lamp instead of the conventional phase-controlled dimmer. The experimental result shows that the proposed PWM dimmer has good performances.     

Design and compensation of second-order sub-sampling digital frontend

The problem of designing a digital frontend (DFE) was considered which can dynamically access or sense dual bands in any radio frequency (RF) regions without requiring hardware changes. In particular, second-order bandpass sampling (BPS) as a technique that enables to realize the multiband reception function was discussed. In a second-order BPS system, digital reconstruction filters were utilized to eliminate the interferences generated while down converting arbitrarily positioned RF-band signals by using the direct digitization method. However, the inaccuracy in the phase shift or the amplitude mismatch between the two sample streams may cause insufficient rejection of interference. Practical problems were studied, such as performance degradation in signal-to-interference ratio (SIR) and compensation methods to overcome them. In order to demonstrate the second-order BPS as a flexible DFE suitable for software-defined radio (SDR) or cognitive radio (CR), a DFE testbed with a reconfigurable structure was implemented. Moreover, with a view to further demonstrate the proposed compensation algorithms, experimental results show that dual bands are received simultaneously.     

Design of small-area and high-efficiency DC-DC converter for 1 T SRAM

The direct current-direct current (DC-DC) converter is designed for 1 T static random access memory (SRAM) used in display driver integrated circuits (ICs), which consists of positive word-line voltage (V _PWL), negative word-line voltage (V _NWL) and half-V _DD voltage (V _HDD) generator. To generate a process voltage temperature (PVT)-insensitive V _PWL and V _NWL, a set of circuits were proposed to generate reference voltages using bandgap reference current generators for respective voltage level detectors. Also, a V _PWL regulator and a V _NWL charge pump were proposed for a small-area and low-power design. The proposed V _PWL regulator can provide a large driving current with a small area since it regulates an input voltage (VCI) from 2.5 to 3.3 V. The V _NWL charge pump can be implemented as a high-efficiency circuit with a small area and low power since it can transfer pumped charges to V _NWL node entirely. The DC-DC converter for 1 T SRAM were designed with 0.11 μm mixed signal process and operated well with satisfactory measurement results.     

The effects of safety handrails and the heights of scaffolds on the subjective and objective evaluation of postural stability and cardiovascular stress in novice and expert construction workers

Work performed on scaffolds carries the risk of falling that disproportionately threatens the safety and health of novice construction workers. Hence, objective measures of the postural stability, cardiovascular stress, and subjective difficulty in maintaining postural balance were evaluated for four expert and four novice construction workers performing a manual task in a standing posture on a scaffold with and without safety handrails at two different elevation heights. Based on a multivariate analysis of variance, the experience, scaffold height, and presence of a handrail were found to significantly affect measures of the postural stability and cardiovascular stress. At a lower level of worker experience, a higher scaffold height, and in the absence of a handrail (which may correspond to higher risk of a fall), postural stability was significantly reduced, while cardiovascular stress and subjective difficulties in maintaining postural balance increased. We emphasize the importance of training and handrails for fall prevention at construction sites.     

Integration of evolutional BOMs for design of ship outfitting equipment

PLM (Product Lifecycle Management) as well as enterprise information systems commonly use the BOM (Bill of Material) as a means of communication during product development. BOM has been used for product design, production scheduling, procurement, manufacturing and maintenance as it contains the part list of a subassembly or assembly product. BOM currently plays a key role in the PLM environment because it is an essential product information platform in the industry. In practice, product data should be arranged based on the BOM and product structure. Many shipyards or PLM vendors have attempted to develop a PLM adequate for shipbuilding. However, it is always the premise of the successful PLM implementation to prepare the efficient product structure and BOM.This paper suggests an enterprise BOM which addresses the hierarchy of parts and assembly, product structure and product information of outfitting equipment in marine vessel design. In order to express the evolution of product structures and outfitting information during the ship design, the enterprise BOM is modeled by the structure BOM and the display BOM. Concepts are developed for modeling all levels of product relations with a uniform set of relationships supported by the enterprise BOM. It is shown that the architecture of the structure BOM can be used to define the relationships between assemblies, parts, and a multi-view of an evolutional BOM in ship design. The architecture of the outfitting BOM is also presented using an example of a piping system.     

Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing

Since semiconductor manufacturing consists of hundreds of processes, a faulty wafer detection system, which allows for earlier detection of faulty wafers, is required. statistical process control (SPC) and virtual metrology (VM) have been used to detect faulty wafers. However, there are some limitations in that SPC requires linear, unimodal and single variable data and VM underestimates the deviations of predictors. In this paper, seven different machine learning-based novelty detection methods were employed to detect faulty wafers. The models were trained with Fault Detection and Classification (FDC) data to detect wafers having faulty metrology values. The real world semiconductor manufacturing data collected from a semiconductor fab were tested. Since the real world data have more than 150 input variables, we employed three different dimensionality reduction methods. The experimental results showed a high True Positive Rate (TPR). These results are promising enough to warrant further study.     

A literature review and classification of recommender systems research

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. Although academic research on recommender systems has increased significantly over the past 10 years, there are deficiencies in the comprehensive literature review and classification of that research. For that reason, we reviewed 210 articles on recommender systems from 46 journals published between 2001 and 2010, and then classified those by the year of publication, the journals in which they appeared, their application fields, and their data mining techniques. The 210 articles are categorized into eight application fields (books, documents, images, movie, music, shopping, TV programs, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). Our research provides information about trends in recommender systems research by examining the publication years of the articles, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this paper helps anyone who is interested in recommender systems research with insight for future research direction.     

Uniformly subsampled ensemble (USE) for churn management: Theory and implementation

The present paper explores the possible application of a new ensemble model. The model, which is based on multiple SVM classifiers, is employed to address churner identification problems in the mobile telecommunication industry, a sector in which the role of customer retention program becomes increasingly important due to its very competitive business environment. In particular, the current study introduces a uniformly subsampled ensemble (USE) model of SVM classifiers, not only to reduce the computational complexity of large-scale data, but also to boost the reliability and accuracy of calibrated models on data sets with highly skewed class distributions. According to our experiments, the performance of the USE SVM model is superior compared to all single and ensemble models. It is more scalable than well-known ensemble models as well.