Optical recording system using an integrated solid immersion lens

 Nobody doubts that the high area density recording and miniaturization of the devices in the data storage are in the general trend. What matters now is how to compact the data in a small area and how to decrease the device size. For the last decade, a lot of researchers engaged in the optical memory have expected the near-field recording (NFR) technology to be able to bring the remarkable results. However, they have been confronted with many obstacles including heat, contamination, dynamics of optical head in the unsealed environment, etc. In this paper, we propose the new concept of a solid immersion lens (SIL) with a potential to be able to resolve the critical issues on the way to the commercialization of the high areal density optical recording using the near-field recording technology. Received: 5 July 2001/Accepted: 17 October 2001     

Designing an integrated driver assistance system using image sensors

Road accidents cause a great loss to human lives and assets. Most of the accidents occur due to human errors, such as bad awareness, distraction, drowsiness, low training, and fatigue. Advanced driver assistance system (ADAS) can reduce the human errors by keeping an eye on the driving environment and warning a driver to the upcoming danger. However, these systems come only with modern luxury cars because of their high cost and complexity due to several sensors employed. Therefore, camera-based ADAS are becoming an option due to their lower cost, higher availability, numerous applications and ability to combine with other systems. Targeting at designing a camera-based ADAS, we have conducted an ethnographic study of drivers to know what information about the driving environment would be useful in preventing accidents. It turned out that information on speed, distance, relative position, direction, and size and type of the nearby objects would be useful and enough for implementing most of the ADAS functions. Several camera-based techniques are available for capturing the required information. We propose a novel design of an integrated camera-based ADAS that puts technologies??such as five ordinary CMOS image sensors, a digital image processor, and a thin display??into a smart system to offer a dozen advanced driver assistance functions. A basic prototype is also implemented using MATLAB. Our design and the prototype testify that all the required technologies are now available for implementing a full-fledged camera-based ADAS.     

Predicting personal information system adoption using an integrated diffusion model

The purpose of this study is to develop a research model that integrates the relationship between innovation characteristics (innovation diffusion theory) and technology characteristics (task-technology fit model). With the research model, the current study investigates the adoption of the “personal information system,” a concept that we develop in the context of mobile technologies. In this paper, we performed the first quantitative test of the model by integrating the innovation diffusion and task-technology fit models. Further, we proposed a theoretical definition of “personal information systems” by highlighting the differences in the types of tasks across individual users’ needs. To test our research model, 202 college students were surveyed. Partial least squares (PLS) structural equation modeling was employed to analyze our data, and these analyses provided empirical support for the proposed hypotheses. Quality, compatibility, cost, and relative advantage were found to be important indicators of the intention to adopt due to their impact on the intended communication, information, transaction, and entertainment tasks, while compatibility, relative advantage, and complexity had a direct impact on the intention to adopt.     

Intelligent multi-user detection using an artificial immune system

Artificial immune systems (AIS) are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multiple-access communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.     

A real-time vision system using an integrated memory array processor prototype

This paper describes a real-time vision system (RVS) architecture and performance and its use of an integrated memory array processor (IMAP) prototype. This prototype integrates eight 8-bit processors and a 144-kbit SRAM on a single chip. The RVS was developed with 64 IMAP prototypes connected in series in a 512 processor-system configuration. A host workstation can access the memory on the IMAP prototypes directly through a random access port. Images are inputted and outputted at high speed through serial access ports. The RVS performance is shown in real-time road-image processing and in a neural network simulation, as well as in low-level image processing algorithms, such as filtering, histograms, discrete cosine transform (DCT), and rotation. The RVS image processing is shown to be much faster than the video rate.     

Creep feed grinding optimization by an integrated GA-NN system

The present work is aimed to optimize creep feed grinding (CFG) process by an approach using integrated Genetic Algorithm-Neural Network (GA-NN) system. The aim of this creep feed grinding optimization is obtain the maximal metal removal rate (MRR) and the minimum of the surface roughness (R _a ). For optimization, metal removal rate is calculated with a mathematic formula and a Back Propagation (BP) artificial neural-network have been used to prediction of R _a . The parameters used in the optimization process were reduced to three grinding conditions which consist of wheel speed, workpiece speed and depth of cut. All of other parameters such as workpiece length, workpiece material, wheel diameter, wheel material and width of grinding were taken as constant. The BP neural network was trained using the scaled conjugate gradient algorithm (SCGA). The results of the neural network were compared with experimental values. It shows that the BP model can predict the surface roughness satisfactorily. For optimization of creep feed grinding process, an M-file program has been written in ‘Matlab’ software to integrate GA and NN. After generation of each population by GA, firstly, the BP network predicts R _a and then MRR has been calculated with mathematic formula. In this study, the importance of R _a and MRR is equal in the optimization process. By using this integrated GA-NN system optimal parameters of creep feed grinding process have been achieved. The obtained results show that, the integrated GA-NN system was successful in determining the optimal process parameters.     

A tool breakage detection system using an accelerometer sensor

An on-line and in-process based monitoring system to detect tool breakage via an accelerometer was developed and successfully evaluated in an end milling operation. Prior to testing and evaluation of the tool breakage condition, a simulation model was developed. Transfer of the on-line vibration signal to the frequency domain employed the fast fourier transfer function, and set thresholds were used to determine the tool condition after various experimental tests. In comparison to other in-process methods, such as those that employ dynamometers and acoustic emission sensors, the proposed system is easy to set up and does not require changing of the mechanism. Additional benefits of the system are its high reliability and low cost. Thus, the new monitoring system is potentially useful for untended milling operations in on-line and real-time tool breakage detection in linked-cell manufacturing systems (L-CMS).     

An integrated microfluidic system using mannose-binding lectin for bacteria isolation and biofilm-related gene detection

Molecular diagnosis of biofilm-related genes (BRGs) in common bacteria that cause periprosthetic joint infections may provide crucial information for clinicians. In this study, several BRGs, including ica, fnbA, and fnbB, were rapidly detected (within 1 h) with a new integrated microfluidic system. Mannose-binding lectin (MBL)-coated magnetic beads were used to isolate these bacteria, and on-chip nucleic acid amplification (polymerase chain reaction, PCR) was then performed to detect BRGs. Both eukaryotic and prokaryotic MBLs were able to isolate common bacterial strains, regardless of their antibiotic resistance, and limits of detection were as low as 3 and 9 CFU for methicillin-resistant Staphylococcus aureus and Escherichia coli, respectively, when using a universal 16S rRNA PCR assay for bacterial identification. It is worth noting that the entire process including bacteria isolation by using MBL-coated beads for sample pre-treatment, on-chip PCR, and fluorescent signal detection could be completed on an integrated microfluidic system within 1 h. This is the first time that an integrated microfluidic system capable of detecting BRGs by using MBL as a universal capturing probe was reported. This integrated microfluidic system might therefore prove useful for monitoring profiles of BRGs and give clinicians more clues for their clinical judgments in the near future.     

An integrated edge detection method using mathematical morphology

This paper presents an edge detection method based on mathematical morphology. The proposed scheme consists of four steps: preprocessing, edge extraction, edge decision, and postprocessing. In the preprocessing step, a morphological central transformation is applied to remove noise. In the edge extraction and decision steps, a morphological edge extractor is designed to estimate the edge information of an image, and an edge decision criterion is followed to determine whether a pixel is an edge or not. In the postprocessing step, the morphological hit-or-miss transformation is utilized to improve the correctness of the detected edges. It is proved theoretically for the correctness and effectiveness for detecting ideal edges. Experimental results show that the proposed method works well on both artificial and real images. The text was submitted by the authors in English. Chin-Pan Huang was born in 1959 in Taiwan, Republic of China. He received the B.S. and M.S. degrees in electrical engineering from Chung Cheng Institute of Technology, Taiwan, in 1981 and in 1985, respectively. In 1996, he received the Ph.D. degree in electrical engineering from the University of Pittsburgh in the United States. From 1996 to 2002, he was an associate scientist of the Electronic System Division in Chung Shan Institute of Science and Technology. He then joined the Department of Computer and Communication Engineering at Ming Chuan University in August 2002 and is currently an assistant professor there. His recent research interests include data compression, computer vision, digital image processing, and pattern recognition. Ran-Zan Wang was born in 1972 in Fukien, Republic of China. He received his B.S. degree in computer engineering and science in 1994 and M.S. degree in electrical engineering and computer science in 1996, both from Yuan-Ze University. In 2001, he received his Ph.D. degree in computer and information science from National Chiao Tung University. In 2001–2002, he was an assistant professor at the Department of Computer Engineering at the Van Nung Institute of Technology. He joined the Department of Computer and Communication Engineering at Ming Chuan University in August 2002 and is currently an assistant professor there. His recent research interests include data hiding and digital watermarking, image processing, and pattern recognition. Dr. Wang is a member of the Phi Tau Phi Scholastic Honor Society.     

An integrated automatic face detection and recognition system

This paper proposes an integrated system for unconstrained face recognition in complex scenes. The scale and orientation tolerant system comprises a face detector followed by a recognizer. Given a color input image of a person, the face detector encloses the face from the complex scene within a circular boundary, and locates the position of the nose. A radial grid mapping centered on the nose is then performed to extract a feature vector within the boundary. The feature vector is input to a radial basis function neural network classifier for face identification. The proposed face detector achieved an average detection rate of 95.8% while the face recognizer achieved an average recognition rate of 97.5% on a database of 21 persons with variations in scale, orientation, natural illumination and background. The two modules were combined to form an automatic face recognition system that was evaluated in the context of a security system using a video database of 21 users and 10 intruders, acquired in an unconstrained environment. A recognition rate of 93.5% with 0% false acceptance rate was achieved.     

对一种集成应用系统的研究

针对企业现存对外交流的信息平台所存在的不足,提出了将计算机电话集成技术系统与客户关系管理系统进行集成的方案,阐述了计算机电话集成技术系统与客户关系管理系统的原理及相关技术,给出了集成间的数据接口的定义,阐述了计算机电话集成系统智能路由的数据传榆协议。利用该集成技术,可为企业改善服务,提高用户的满意度,促进企业经济效益的提高。     

Accommodating larger container vessels using an integrated laser system for approach and berthing

Various activities such as dredging and pier lengthening have made it possible for ports to receive larger container vessels, though in many cases this has made berthing the vessels more difficult, necessitating advanced ranging and docking systems. For example, in Koper, Slovenia, navigation through a narrow and bending channel has been made safer through the implementation of a laser-ranging system; a laser docking system is in place so that once the ship is positioning alongside where, say, inadequate fenders await and ship-to-shore (STS) cranes are near, special care is required and parameters such as precise vessel position, transversal speed, and vessel-approaching angle are of great importance. This paper will present the layout of the system and the first results related to the observed docking of large container vessels calling at the Port of Koper.     

Development of an integrated reflow soldering control system using incremental hybrid process knowledge

In this paper, we present an industrial application of intelligent knowledge-based reflow soldering control system to economically determine process parameters and assess the outputs for surface mount assembly. The system performance of surface mounting is significantly affected by three major interconnected process segments (including solder paste application, component placement, and solder reflow) and in combination. Many surface mount manufacturers have suffered both quality and productivity losses due to the lacks of effective line setup procedures, rapid process troubleshooting, and appropriate corrective action. This proposed system develops an integrated process control scheme, the framework of hybrid process knowledge extraction through neuro-fuzzy data training, and a knowledge-based system with a GUI man–machine interface for predicting and controlling the given system performance. The efficiency and effectiveness of the proposed system are illustrated using DPMO measurement and productivity analysis.     

Development of an integrated CMOS DNA detection biochip

This paper presents a CMOS DNA detection biochip using an electrical detection method with self-assembly multilayer gold nanoparticles (AuNPs). Each measuring spot of this biochip consists of three major parts; a pair of electrodes with a nanogap, a current amplifier circuit, and a heater with an embedded temperature sensor. The biochip is first fabricated by a TSMC (Taiwan Semiconductor Manufacturing Company Ltd.) 0.35 μm 2P4M standard CMOS process. Then, post-CMOS micromachining etch processes are used to expose the surface of the nanogap to test samples for the establishment of multilayer AuNPs through hybridization between single strand DNAs in the samples. The gap distance between a pair of electrodes is 350 nm. Before taking DNA detection measurements, self-assembly monolayer AuNPs is established on the nanogap surface between two microelectrodes. Multilayer AuNPs can be observed if hybridization between single strand DNAs occurs. An approximately 1000-fold increase in electric current between the multilayer AuNPs over the monolayer AuNPs serves an indication of the presence of target DNA in test samples. After integrating the electrodes with an embedded current amplifier, the electric current of multilayer AuNPs is amplified to the order of mA that can be easily measured by a commercial Volt-Ohm-Milliammeter. The heating system with a heating element and a temperature sensor can be used to distinguish single base-pair mismatch hybridization from complementary hybridization for the establishment of multilayer AuNPs. The lowest detectable concentration of target DNA on this biochip is 0.1 nM.     

基于PSO算法集成神经网络的多元有害气体检测系统

针对目前常见的多元有害气体检测问题,搭建了一套基于传感器阵列和集成神经网络相结合的多元有害气体检测系统。为了提高该系统的稳定性和预测精度,提出使用粒子群算法( PSO)优化集成神经网络的权重系数的方法,即利用PSO的全局搜索能力,对该系统的集成神经网络权重系数进行全局优化,再以优化后的权重系数实现多个神经网络的结论结合。该系统对传感器阵列的4种混合有害气体的响应信号进行回归分析。结果显示,该系统PSO算法的集成神经网络预测的平均相对误差小于1%,网络具有更强的稳定性和泛化能力。     

New production method of convex microlens arrays for integrated fluorescence microfluidic detection systems

A new method for producing microlens array with large sag heights is proposed for integrated fluorescence microfluidic detection systems. Three steps in this production technique are included for concave microlens array formations to be integrated into microfluidic systems. First, using the photoresist SU-8 to produce hexagonal microchannel array is required. Second, UV curable glue is injected into the hexagonal microchannel array. Third, the surplus glue is rotated by a spinner at high velocity and exposed to a UV lamp to harden the glue. The micro concave lens molds are then finished and ready to produce convex microlens in poly methsiloxane (PDMS) material. This convex microlens in PDMS can be used for detecting fluorescence in microfluidic channels because a convex microlens plays the light convergence role for optical fiber detection.