A rough set based approach to patent development with the consideration of resource allocation

Patent strategy is the overriding mechanism that helps direct investment, resource allocation, expectations, and policy development within an organization. Much studies of patent, for example, patent classification, patent analysis, patent management, patent strategy planning have been made. Due to the high cost of devoting to the research and development for a new patent application, it is essential for a company to develop the patent portfolio based on analyzing related information for fitting with cost constraint and maximizing the benefit. However, only few research attempts to develop new patents with the consideration of resource allocation, for example, optimizing budget utilization. In addition, the previous studies did not derive significant technologies and induct rules for resource allocation through patent analysis. In some cases, the patent analysis may process qualitative information that is difficult to analyze by standard statistical techniques. The rough set approach, which is suitable for processing qualitative information, is required to induct decision rules to derive critical technologies of patents. In this paper, a systematic approach to analyze existing patent information based on rough set theory with the consideration of resource allocation is developed. A case study is presented to demonstrate the contribution of the proposed approach which assists on decision-making in patent reform or invention with constraint resource.     

Detection of viable antibiotic‐resistant/sensitive Acinetobacter baumannii in indoor air by propidium monoazide quantitative polymerase chain reaction

Acinetobacter baumannii represents a significant cause of nosocomial infections. Therefore, we combined real‐time quantitative polymerase chain reaction (PCR) with the propidium monoazide (PMA‐qPCR) to assess the feasibility of detecting viable, airborne A. baumannii. The biological collection efficiencies of three samplers for collecting airborne A. baumannii were evaluated by PMA‐qPCR in a chamber study. After sampling, the effects of storage in collection fluid on A. baumannii were evaluated. The results showed that the culturable ratio of A. baumannii measured using the culture method was significantly correlated with the viable ratio measured using PMA‐qPCR, but was not significantly correlated with the qPCR results. It was indicated that the AGI‐30 impinger and the BioSampler were much more effective than the Nuclepore filter sampler for collecting airborne A. baumannii. The storage temperature was critical for aerosol samples, as the loss of viable A. baumannii was minimized when the PMA‐bound DNA was stored at ?20°C or if the collected cells were stored at 4°C and subsequently processed by PMA‐qPCR within 1 month. The PMA‐qPCR method was also to distinguish between colistin‐sensitive and colistin‐resistant A. baumannii, and no colistin‐sensitive A. baumannii was detected by PMA‐qPCR upon treatment of the BioSampler collection medium with 2 μg/ml colistin for 5 min.     

Localised heating of tumours utilising injectable magnetic nanoparticles for hyperthermia cancer therapy

This study reports an investigation of hyperthermia cancer therapy utilising an alternating magnetic field to induce a localised temperature increase on tumours by using injectable magnetic nanoparticles. In-vitro and in-vivo experiments represent the feasibility of hyperthermia cancer therapy. A feedback temperature control system was first developed to keep the nanoparticles at a constant temperature to prevent overheating in the tumours such that a safer and more precise cancer therapy becomes feasible. By using the feedback temperature control system, magnetic nanoparticles can be heated up to the specific constant temperatures, 37, 40, 42, 45, 46 and 47degC, respectively, with a variation less than 0.2degC. With this approach, the in-vitro survival rate of tumour cells at different temperatures can be systematically explored. It was experimentally found that the survival rate of cancer cells can be greatly reduced while CT-26 cancer cells were heated above 45degC. Besides, localised temperatures increase as high as 59.5degC can be successfully generated in rat livers by using the proposed method. Finally, complete regression of tumour was achieved. The developed method used injectable magnetic nanoparticles and may provide a promising approach for hyperthermia cancer therapy.     

Numerical simulation of protein stamping process driven by capillary force

Numerical simulations based on first-principle conservation laws of mass and momentum are performed to observe flow characteristics during the stamping process. The protein solution is transferred by a new design of microstamps with microchannels and printed on a bottom substrate. Furthermore, key physics of the stamping process and the control factors achieving uniform spot size can be identified and optimized after these simulations.     

A Genetic Algorithm for Assessing Flatness in Automated Manufacturing Systems

The measurement of flatness for manufactured parts is one of the most frequently used procedures in automated manufacturing systems. Measuring instruments are commonly utilized in taking measurement data from manufactured surfaces for inspection purposes. The measurement data is then used to evaluate the geometric information, from errors associated with its surface. The study proposes the computational approaches for flatness with respect to ASME Y14.5M-1994 standard. The proposed methods consider the trade-off between the accuracy of flatness and the efficiency of inspection. Two approaches of computational metrology based on genetic algorithms are proposed to explore the optimality of flatness measurement and the flatness feasibility analysis. The results show that the optimization algorithms provide exact flatness errors and adequate tolerance size. Received: February 2004 / Accepted: September 2005     

A novel manufacturing defect detection method using association rule mining techniques

In recent years, manufacturing processes have become more and more complex, and meeting high-yield target expectations and quickly identifying root-cause machinesets, the most likely sources of defective products, also become essential issues. In this paper, we first define the root-cause machineset identification problem of analyzing correlations between combinations of machines and the defective products. We then propose the Root-cause Machine Identifier (RMI) method using the technique of association rule mining to solve the problem efficiently and effectively. The experimental results of real datasets show that the actual root-cause machinesets are almost ranked in the top 10 by the proposed RMI method.     

Low-frequency noise in TaSiN/HfO/sub 2/ nMOSFETs and the effect of stress-relieved preoxide interfacial layer

Low-frequency noise characteristics are reported for TaSiN-gated n-channel MOSFETs with atomic-layer deposited HfO/sub 2/ on thermal SiO/sub 2/ with stress-relieved preoxide (SRPO) pretreatment. For comparison, control devices were also included with chemical SiO/sub 2/ resulting from standard Radio Corporation of America clean process. The normalized noise spectral density values for these devices are found to be lower when compared to reference poly Si gate stack with similar HfO/sub 2/ dielectric. Consequently, a lower oxide trap density of /spl sim/4/spl times/10/sup 17/ cm/sup -3/eV/sup -1/ is extracted compared to over 3/spl times/10/sup 18/ cm/sup -3/eV/sup -1/ values reported for poly Si devices indicating an improvement in the high-/spl kappa/ and interfacial layer quality. In fact, this represents the lowest trap density values reported to date on HfO/sub 2/ MOSFETs. The peak electron mobility measured on the SRPO devices is over 330 cm/sup 2//V/spl middot/s, much higher than those for equivalent poly Si or metal gate stacks. In addition, the devices with SRPO SiO/sub 2/ are found to exhibit at least /spl sim/10% higher effective mobility than RCA devices, notwithstanding the differences in the high-/spl kappa/ and interfacial layer thicknesses. The lower Coulomb scattering coefficient obtained from the noise data for the SRPO devices imply that channel carriers are better screened due to the presence of SRPO SiO/sub 2/, which, in part, contributes to the mobility improvement.     

Exploiting locality for irregular scientific codes

Irregular scientific codes experience poor cache performance due to their irregular memory access patterns. In this paper, we present two new locality improving techniques for irregular scientific codes. Our techniques exploit geometric structures hidden in data access patterns and computation structures. Our new data reordering (GPART) finds the graph structure within data accesses and applies hierarchical clustering. Quality partitions are constructed quickly by clustering multiple neighbor nodes with priority on nodes with high degree and repeating a few passes. Overhead is kept low by clustering multiple nodes in each pass and considering only edges between partitions. Our new computation reordering (Z-SORT) treats the values of index arrays as coordinates and reorders corresponding computations in Z-curve order. Applied to dense inputs, Z-SORT achieves performance close to data reordering combined with other computation reordering but without the overhead involved in data reordering. Experiments on irregular scientific codes for a variety of meshes show locality optimization techniques are effective for both sequential and parallelized codes, improving performance by 60-87 percent. GPART achieved within 1-2 percent of the performance of more sophisticated partitioning algorithms, but with one third of the overhead. Z-SORT also yields the performance improvement of 64 percent for dense inputs, which is comparable with data reordering combined with computation reordering.     

Proactive DAD: A Fast Address-Acquisition Strategy for Mobile IPv6 Networks

The increasing number of Wi-Fi-compatible mobile devices highlights various wireless access challenges, including the need for smooth hand offs between Internet attachment points in mobile IPv6 networks. To confirm address uniqueness in a new domain, mobile nodes must run duplicate address detection (DAD), which is a time-consuming process. The Proactive DAD approach uses topology information and layer-2 signals to predict the new network domains prior to or in parallel with layer-3 hand offs. Experimental results show that P-DAD can significantly reduce both hand-off latency and packet loss     

Characterization of closed-loop measurement accuracy in precision CNC milling

This study investigates the closed-loop measurement error in computer numerical controlled (CNC) milling as they relate to the different inspection techniques. The on-line inspection of machining accuracy using a spindle probe has an inherent shortcoming because the same machine-produced parts are used for inspection. In order to use the spindle probe measurement as a means of correcting deviations in machining, the magnitude of measurement errors needs to be quantified. The empirical verification was made by conducting three sets of cutting experiments, followed by a design of experiment with three levels and three factors on a state-of-the-art CNC machining center. Three different material types and parameter settings were selected to simulate a diverse cutting condition. During the cutting, the cutting force and spindle vibration sensor signals were collected and a tool wear was recorded using a computer vision system. The bore tolerance was gauged by a spindle probe as well as a coordinate-measuring machine. The difference between the two measurements was defined as a closed-loop measurement error and the subsequent analysis was performed to determine the significant factors affecting the errors. The analysis results showed the potential of improving production efficiency and improved part quality.