Dielectrophoretic manipulation of nano-materials and its application to micro/nano-sensors

Dielectrophoresis is a potential technique which can be employed to align and manipulate nano-structured materials to the preset locations in fluid for electronic device applications in micro/nano-sensors and circuits. In this paper, with several home-made electrode pairs, we succeeded in manipulating the micro/nano-particles along the electric field and depositing them across the gaps between two electrodes. It is proven as a helpful experiment to assemble the nano-structures with precise arrangement. A relative humidity sensor, using the dielectrophoretically assembled self-grown nano-materials as a sensing element, was fabricated and the sensing properties were then tested. The sensitivity increased with the decline of the testing frequency. And a high humidity sensitivity of 146.90 kΩ/RH% was obtained with a testing frequency of 100 Hz. The relativity of the impedances measured at the same frequency was above −0.90. The relative standard deviations were small especially under a lower relative humidity level. The comparison between aligned and not-aligned nano-materials in the sensing structures was presented to verify the work of the dielectrophoresis. The detection result confirmed the feasibility of applying nano-materials located between the electrodes by dielectrophoresis as sensing elements to micro/nano-sensors.     

Giant-grain silicon (GGS) and its application to stable thin-film transistor

We developed a giant-grain silicon (GGS) by Ni-mediated crystallization of amorphous silicon (a-Si) with a silicon-nitride (SiN_x) cap layer. Ni particles were sputtered onto the SiN_x/a-Si layer and then it was annealed at around 600 °C. The Ni diffuses through a SiN_x cap and then forms NiSi₂ crystallites in a-Si, which is able to induce crystallization. The grain size can be controlled from a few to 100 μm. The grain size can be increased with increasing the cap layer thickness or by decreasing the Ni density on the SiN_x. The p-channel GGS poly-Si TFT exhibited a field-effect mobility of 101 cm²/Vs and a threshold voltage of −3.6 V and is very stable under gate or hot carrier bias-stress. These superior performances may be due to the smooth surface of GGS poly-Si and solid-phase crystallization of a-Si.     

Fast and Exact (Poisson) Solvers on Symmetric Geometries

In computer graphics, numerous geometry processing applications reduce to the solution of a Poisson equation. When considering geometries with symmetry, a natural question to consider is whether and how the symmetry can be leveraged to derive an efficient solver for the underlying system of linear equations. In this work we provide a simple representation‐theoretic analysis that demonstrates how symmetries of the geometry translate into block diagonalization of the linear operators and we show how this results in efficient linear solvers for surfaces of revolution with and without angular boundaries.     

A novel method to fabricate silicon nanoprobe array with ultra-sharp tip on (111) silicon wafer

Microsystem Technologies - In the work, a novel fabrication method for homogeneous and sharp nanoprobe array on (111) silicon wafer is presented. The specific spatial structure of {111} planes and...     

Exact,almost and optimal input decoupled (delayed) observers

The core of this paper deals with the construction of input-decoupled observers which seek asymptotic estimation of a desired output variable (a linear combination of state and input) of a time-invariant either continuous- or discrete-time system driven by unknown inputs and disturbances. Exact, almost, optimal (suboptimal) and constrained optimal estimation or filtering problems are formulated and studied. All the problems defined and studied here are inherently interconnected, and have a strong common thread of estimation and filtering in the face of the unknown input and external disturbance signals. They are interconnected from a variety of angles, e.g. they are motivated by one another, methods of obtaining the solvability conditions and their methods of solution rely on one another, etc. Thus, a hierarchy of problems and their solutions is built on top of one another. Some of the problems studied here are known in the literature but not in as general a form as is given here, while a majority of the problems studied here are new. A classical variation of all the above problems is also studied here by introducing an l-step delay in estimating the desired output from the measured output. The underlying philosophy throughout this work has been to study most if not all of the facets of estimation and filtering in one stretch under a single folder. Our study of all the above problems has been guided by three important perspectives: (1) obtaining the solvability conditions, both necessary and sufficient; (2) obtaining optimal performance whenever it applies; and (3) developing sound methodologies to design and construct appropriate observers or filters.     

Exact and Robust (Self‐)Intersections for Polygonal Meshes

We present a new technique to implement operators that modify the topology of polygonal meshes at intersections and self‐intersections. Depending on the modification strategy, this effectively results in operators for Boolean combinations or for the construction of outer hulls that are suited for mesh repair tasks and accurate mesh‐based front tracking of deformable materials that split and merge. By combining an adaptive octree with nested binary space partitions (BSP), we can guarantee exactness (= correctness) and robustness (= completeness) of the algorithm while still achieving higher performance and less memory consumption than previous approaches. The efficiency and scalability in terms of runtime and memory is obtained by an operation localization scheme. We restrict the essential computations to those cells in the adaptive octree where intersections actually occur. Within those critical cells, we convert the input geometry into a plane‐based BSP‐representation which allows us to perform all computations exactly even with fixed precision arithmetics. We carefully analyze the precision requirements of the involved geometric data and predicates in order to guarantee correctness and show how minimal input mesh quantization can be used to safely rely on computations with standard floating point numbers. We properly evaluate our method with respect to precision, robustness, and efficiency.     

Biological Data Analysis Program (BDAP): a multitasking biological sequence analysis program

Neural Computing and Applications - Exploration of mysterious facts from the sequences and structures of biomolecules of an organism is the essential requirement for understanding their molecular...     

(2+1)维KD方程的解及分岔行为

通过行波变换,将非线性偏微分方程化为常微分方程,利用辅助常微分方程的解来构造偏微分方程的精确解,获得了(2+1)维Konopelchenko-Dubrovsky方程的孤波解和周期解.然后直接研究变换以后的常微分方程,揭示该方程控制的动力系统的鞍结分岔行为,画出了系统的分岔图.     

Exact scheduling analysis of non-accumulatively monotonic multiframe tasks

In this paper, we present exact analysis for the worst case response time of the general multiframe (MF) task model executing on a uniprocessor according to the fixed priority scheduling scheme. The analysis is developed in four stages. Firstly, we present the basic response time analysis where we optimize the number of frames that have to be considered in such analysis; we show how their number can be significantly reduced by eliminating non critical frames that are dominated by other frames. Secondly, we extend this analysis to be applicable to MF tasks with arbitrary deadlines. Thirdly, the basic analysis is extended to cope with frame specific deadlines. Lastly, the two models of frame specific deadlines and arbitrary deadlines are combined and the relative analysis is presented. An optimal priority assignment scheme for the frame specific deadline scenario is also presented in this paper.     

A silicon transconductance light emitting device (TRANSLED)

A novel multi-terminal silicon light emitting device (TRANSLED) is described where both the light intensity and spatial light pattern of the device are controlled by an insulated MOS gate voltage. This presents a major advantage over two terminals Si-LEDs, which require direct modulation of the relatively high avalanche current. It is found that, depending on the bias conditions, the light intensity is either a linear or a quadratic function of the applied gate voltage. The nonlinear relationship facilitates new applications such as the mixing of electrical input signals and modulating the optical output signal, which cannot readily be achieved with two terminal Si-LEDs, since they exhibit a linear relationship between diode avalanche current and light intensity. Furthermore, the control gate voltage can also modulate the emission pattern of the light emitting regions, for example, changing the TRANSLED from an optical line source to two point sources.     

SELECT: A computer program to identify associationally rich words for content analysis

Conclusions An overview of these results indicates that SELECT is, in general, producing results in which elicited themes parallel those produced by frequency-based word selection. More importantly —and consonant with the impetus for development of the method — SELECT is delivering factors which are larger, more easily interpretable, and more discriminable than these available from frequency data and is doing so within the constraint of basic thematic identities.     

Concept drift and how to identify it

This paper studies concept drift over time. We first define the meaning of a concept in terms of intension, extension and label. Then we study concept drift over time using two theories: one based on concept identity and one based on concept morphing. A qualitative toolkit for analysing concept drift is proposed to detect concept shift and stability when concept identity is available, and concept split and strength of morphing chain if using the morphing theory. We apply our framework in four case-studies: a political vocabulary in SKOS, the DBpedia ontology in RDFS, the LKIF-Core ontology in OWL and a few biomedical ontologies in OBO. We describe ways of identifying interesting changes in the meaning of concept within given application contexts. These case-studies illustrate the feasibility of our framework in analysing concept drift in knowledge organisation schemas of varying expressiveness.     

Using function-based patent analysis to identify potential application areas of technology for technology transfer

Under the open innovation paradigm, identification of application areas of the internally developed technologies is important to maximize the profits from them. However, many companies have failed to identify opportunity for additional applications. The fundamental reason is that companies have insufficient understanding of the potential applications of their technologies, because different industries use far different technologies and technological terminologies. However, technologies can be linked with outside industries by analyzing them from the functional perspective, because functions used in different industries are generally similar. Therefore, this article proposes a function-based patent analysis to identify the potential application areas of a technology. In general, technologies in a patent are invented for use in a specific industry, and thus a patent can be categorized into a specific industry. By identifying patents which contain a specific function, industries that use the function can be identified. Industries in which the importance of the function is relatively high can be considered as areas in which technologies performing the function have potential to be applied, and the proposed indexes evaluate the relative importance of the function within each industry. Finally, the practical usefulness of the proposed method was verified by identifying the potential areas in which vortex reduction technology can be applied.     

High aspect-ratio combined poly and single-crystal silicon (HARPSS)MEMS technology

This paper presents a single-wafer high aspect-ratio micromachining technology capable of simultaneously producing tens to hundreds of micrometers thick electrically isolated poly and single-crystal silicon microstructures. High aspect-ratio polysilicon structures are created by refilling hundreds of micrometers deep trenches with polysilicon deposited over a sacrificial oxide layer. Thick single-crystal silicon structures are released from the substrate through the front side of the wafer by means of a combined directional and isotropic silicon dry etch and are protected on the sides by refilled trenches. This process is capable of producing electrically isolated polysilicon and silicon electrodes as tall as the main body structure with various size capacitive air gaps ranging from submicrometer to tens of micrometers. Using bent-beam strain sensors, residual stress in 80-μm-thick 4-μm-wide trench-refilled vertical polysilicon beams fabricated in this technology has been measured to be virtually zero. 300-μm-long 80-μm-thick polysilicon clamped-clamped beam micromechanical resonators have shown quality factors as high as 85 000 in vacuum. The all-silicon feature of this technology improves long-term stability and temperature sensitivity, while fabrication of large-area vertical pickoff electrodes with submicrometer gap spacing will increase the sensitivity of micro-electromechanical devices by orders of magnitude     

基于荧光法和多元回归分析的混合海藻识别方法研究

钱对单一海藻和混合海藻进行荧光激发光谱的二阶导数分析,发现它们的峰值点和谷点有很强的相似性.因此,用二阶导数荧光发射光谱的谷点和峰值点为特征点,取特征点对应的荧光发射光谱的相对强度的归一化数据为特征参数,进行混合海藻的线性多元回归分析,得到分配系数矩阵.去掉分配矩阵中的负分配系数和相对很小的分配系数,重新进行多元线性回归分析,直到达到目标模型为止,这样可以根据剩余的分配系数得到混合海藻中的单一海藻类目.     

Empirical analysis of search based algorithms to identify change prone classes of open source software

There are numerous reasons leading to change in software such as changing requirements, changing technology, increasing customer demands, fixing of defects etc. Thus, identifying and analyzing the change-prone classes of the software during software evolution is gaining wide importance in the field of software engineering. This would help software developers to judiciously allocate the resources used for testing and maintenance. Software metrics can be used for constructing various classification models which can be used for timely identification of change prone classes. Search based algorithms which form a subset of machine learning algorithms can be utilized for constructing prediction models to identify change prone classes of software. Search based algorithms use a fitness function to find the best optimal solution among all the possible solutions. In this work, we analyze the effectiveness of hybridized search based algorithms for change prediction. In other words, the aim of this work is to find whether search based algorithms are capable for accurate model construction to predict change prone classes. We have also constructed models using machine learning techniques and compared the performance of these models with the models constructed using Search Based Algorithms. The validation is carried out on two open source Apache projects, Rave and Commons Math. The results prove the effectiveness of hybridized search based algorithms in predicting change prone classes of software. Thus, they can be utilized by the software developers to produce an efficient and better developed software.     

Social learning network analysis model to identify learning patterns using ontology clustering techniques and meaningful learning

Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need some centroid for the cluster initialization. Furthermore, the other researcher tried to apply ontology for the cluster on social network domain. This paper tries to reveal the behavior of students from all activities in Moodle e-learning system by putting ontology on domain social learning network (Moodle) which is not explored in the prior study. The activities such as forum, quiz, assignment, etc. are placed as clustering parameter according to the ontology model. The ontology of Moodle e-learning system is created to capture the activities of the student inside Moodle e-learning. Five meaningful attributes are used as group cluster for classifying the students' behaviour. According to the result, most of the students belong to the intentional group while some of the students belong to the constructive and active group. The constructed cluster is calculated based on the e-learning hits during the learning process inside Moodle e-learning. The result on the classification of students' behaviour using ontology cluster is comparable to their final achievement grade. It is believed that this study can bring immense benefit to the development of e-learning system in the future.