Miracle-dz/UniFAR-FTUs huggingface dataset:
High dielectric constant microwave probes for sensing soil moisture

Implantable soil moisture sensors suitable for long-term monitoring of moisture in highway subgrades and for similar applications are needed. Two candidate designs of microwave sensors (operating range 4 to 6 GHz) have been investigated for such applications. One design uses the fringing field of a low-loss dielectric slab waveguide (relative dielectric constant of 25) to obtain good resolution for finely divided soil such as bentonite clay with moisture ranging from 10 to 50 percent by dry weight for effective sample volumes of 20 to 40 cm2. The response of the dielectric waveguide sensor has been calculated in terms of the effective dielectric constant of the soil-water mixture. A model based on index of refraction yields an effective dielectric constant in reasonable agreement with experiment when effects of ionic conduction are accounted for. Another sensor design, better adapted for coarse materials, such as crushed limestone aggregate, uses waves launched from a tapered dielectric slab. By using either frequency or spatial averaging methods, the launched wave sensor accommodated aggregate particles passed by a 0.63-cm mesh sieve, and was found to have satisfactory resolution for the range of 0- to 10-percent moisture by dry weight.
A software architecture for integrated service robot development

This paper presents a computational architecture that addresses the grand challenge problem of system integration. Robotics research has made many advances in sensory processing, control and planning, but few efforts focus on the problem of dynamically integrating the "best available" approaches into a single architecture to support development of integrated systems. The role of architecture is discussed, and a novel approach to intelligent robotic system architecture is presented. This new approach has resulted from the maturation of object-based software technology.
Achieving flexible learning through recognition of prior learning practice: a case‐study lament of the Canadian academy

Although the recognition of learners' experiential learning toward postsecondary credentials holds the promise of increased flexibility and opportunity for many, especially in the current climate of labour shortage, Canadian universities have been slow to adopt recognition of prior learning (RPL) systems. This case study of one Canadian institution showcases its RPL practice against the framework of the challenges that face RPL in traditional academic settings; and presents some of the lessons learned by Canada's foremost open and distance institution's RPL practice.
Importance of the texture features in a query from a spectral image database

A new, semantically meaningful technique for querying the images from a spectral image database is proposed. The technique is based on the use of both color- and texture features. The color features are calculated from spectral images by using the Self-Organizing Map (SOM) when methods of Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) are used for constructing the texture features. The importance of texture features in a querying is seen in experimental results, which are given by using a real spectral image database. Also the differences between the results gained by the use of co-occurrence matrix and LBP are introduced.
Semiautomatic Acquisition of Translation Templates from Monolingual Unannotated Chinese Patent Corpus

We propose a data-driven, semiautomatic and unsupervised method, which can semiautomatically extract translation templates from the unannotated Chinese patent corpus. The method includes seven steps: morphological analysis, replace, fllter, cluster, merge, sort and edit. After extracting and preforming the preliminary templates, we manually edit them and then get the ultimate templates, which are used in a template-based machine translation system. The experimental results show that the method is efiective to improve the quality of machine translation, and that the template-based machine translation system outperforms the conventional rule-based machine translation system without templates.
A method for dynamics identification for haptic display of the operating feel in virtual environments

Realistic dynamics models are important for haptic display for virtual reality systems. Such dynamic models are desirably obtained via experimental identification. However, traditional dynamics identification methods normally require large sized training data sets, which maybe difficult to meet in many practical applications. To obtain the dynamics models, we present, in this paper, an identification method using support vector machines regression algorithm which is more effective than traditional methods for sparse training data. This method can be used as a generic learning machine or as a special learning technique that can make full use of the available knowledge about the dynamics structure. The experimental results show the application of our method for identifying friction models for haptic display.
TaskPair-scheduling: an approach for dynamic real-time systems

In this paper an on-line scheduling approach called TaskPair-Scheduling is presented which merges the concepts of guaranteeing (an activity) and exception handling (due to time-outs) such that the guarantee may enclose the execution of the exception handler. An on-line scheduling algorithm is shown which plans guaranteed try-except constructs as a pair of tasks (MainTask, ExceptTask) by considering the ExceptTask as a hard real-time task (task of maximum importance) and the MainTask by its relative importance (this may depend on arbitrary criteria). This leads to timely predictable behaviour even if the MainTask of the activity has an arbitrary execution time. <<ETX>>
Generation of accurate on-chip time constants and stable transconductances

A method for generating accurately known on-chip time constants and less accurate but stable transistor transconductances over process, power-supply, and temperature variations is presented. The technique uses a constant-g/sub m/ bias circuit, which has a resistor that is tuned with a fully integrated CMOS phase-locked loop (PLL) locked to an external frequency reference (normally present in most systems). Other on-chip analog circuits biased using the same constant-g/sub m/ bias circuit are also stabilized. The PLL uses a charge-pump structure with three control loops (two digital and one analog) having overlapping ranges with hysteresis to minimize tuning glitches in the steady state. The PLL has a lock range of 135 to 300 MHz, and displays an RMS jitter of 15.6 ps. The transconductances generated from the circuit display a 2.2% variation for a 60/spl deg/C change in temperature, and a 1.3% variation for a 10% variation in power-supply voltage. The design has been fabricated in a 0.35-/spl mu/m CMOS process, using an active area of 1200/spl times/1200 /spl mu/m/sup 2/ and draws 5.8 mA from a 3.3-V supply.
The Optimization Design of I-Beam Based on Multi-Objective Cellular Genetic Algorithm

Multi-objective cellular genetic algorithm is obviously superior to the traditional multi-objective evolutionary algorithms in terms of testing performance of algorithm. However, the algorithm still needs to be used in practical engineering problems. In consideration of the above, this paper tries to apply the multi-objective cellular genetic algorithm to solve the problem of design of I-beam. Finally, the results show that multi-objective cellular genetic algorithm has more advantages than the traditional multi-objective evolutionary algorithms in solving this kind of multi-objective problems, no matter in uniformity or expansibility of best solutions.
Design of digital audio input output chip

The design of a digital audio input output (DAIO) chip that interfaces a standard 16/32-bit microprocessor bus with audio devices based on the AES protocol is described. This novel design provides general-purpose microprocessor systems with the ability to communicate with compact-disk and digital-audio-tape players. The chip is designed, using high-level and logic synthesis tools, from a function description in a hardware description language
An Information Propagation Scheme for VANETs

A goal in Vehicular Ad hoc Networks (VANETs) is to enable the dissemination of traffic and road conditions such as local congestion and surface ice as detected by independently moving vehicles. This activity known as Information Warning Functions is useful for vehicles on the highway and enables early reaction. This problem can be described as the direc- tional propagation of information originating from linearly- distributed mobile nodes on a rectilinear plane. By using limited-range packet radios and attribute-based routing, we are able to isolate vehicular from network traffic and permit directional propagation of messages outward from the point of origin. For example, it is desirable to propagate the occurrence of congestion created by an accident in both the forward and backward directions on a highway. We assume the use of multi-hop routing in clusters of connected vehicles to achieve a propagation rate that exceeds the speeds of individual carrier vehicles. We characterize the bounds of information propagation under various traffic patterns and describe a new technique and algorithm that can achieve these limits. We also show an implementation of the dissemination algorithm as a routing protocol using a combination of MANET (mobile ad hoc networking) and DTN (delay tolerant networking) methodologies.
Information-enhanced sparse binary matrix in compressed sensing for ECG

An information-enhanced sparse binary matrix (IESBM) is proposed to improve the quality of the recovered ECG signal from compressed sensing. With the detection of the area of interest and the enhanced measurement model, the IESBM increases the information entropy of the compressed signal and preserves more information during compression; thus, it guarantees a high-quality recovery. The experimental results indicate that the proposed matrix is suitable for compressed sensing of the ECG signal with small distortions in both overall and the concerned diagnostic segments.
HRTF Measurements of a KEMAR Dummy-Head Microphone

An extensive set of head-related transfer function (HRTF 1) measurements of a KEMAR dummy head microphone has recently been completed. The measurements consist of the left and right ear impulse responses from a Realistic Optimus Pro 7 loudspeaker mounted 1.4 meters from the KEMAR. Maximum length (ML) pseudo-random binary sequences were used to obtain the impulse responses at a sampling rate of 44.1 kHz. In total, 710 diierent positions were sampled at elevations from-40 degrees to +90 degrees. Also measured were the impulse response of the speaker in free eld and several headphones placed on the KEMAR. This data is being made available to the research community on the Internet via anonymous FTP and the World Wide Web. 1 Measurement technique Measurements were made using a Macintosh Quadra computer equipped with an Audiomedia II DSP card, which has 16-bit stereo A/D and D/A converters that operate at a 44.1 kHz sampling rate. One of the audio output channels was sent to an ampliier which drove a Realistic Optimus Pro 7 loudspeaker. This is a small two way loudspeaker with a 4 inch woofer and 1 inch tweeter. The KEMAR, Knowles Electronics model DB-4004, was equipped with model DB-061 left pinna, model DB-065 (large red) right pinna, Etymotic ER-11 microphones, and Etymotic ER-11 preampliiers. The outputs of the microphone preampliiers were connected to the stereo inputs of the Audiomedia card. From the standpoint of the Audiomedia card, a signal sent to the audio outputs results in a corresponding signal appearing at the audio inputs. Measuring the impulse response of this system yields the impulse response of the combined system consisting of the Audiomedia D/A and A/D converters and anti-alias lters, the ampliier, the speaker, the room in which the measurements are made, and most importantly, the response of the KEMAR with its associated microphones and preamps. We can avoid interference due to room reeections by ensuring that any reeections occur well after the head response time, which is several milliseconds. We can compensate for a non-uniform speaker response by measuring the speaker response separately and creating an inverse lter. The inverse lter, when applied to an HRTF measurement, equalizes the speaker response to be at. 1 In this document, we use the acronym HRTF to refer to head related impulse responses. The impulse response and transfer function are related in the obvious way by the Fourier transform.
Design and implementation of parallel approximate inverse classes using OpenMP

A new parallel normalized optimized approximate inverse algorithm, based on the concept of antidiagonal wave pattern, for computing classes of explicitly approximate inverses, is introduced for symmetric multiprocessor systems. The parallel normalized explicit approximate inverses are used in conjunction with parallel normalized explicit preconditioned conjugate gradient schemes for the efficient solution of finite element sparse linear systems. The parallel design and implementation issues of the new algorithm are discussed and the parallel performance is presented using OpenMP. Copyright © 2008 John Wiley & Sons, Ltd.
Consideration of building a common platform of collaborative learning environment

This paper reports on considerations about a common and basic functions/components for building a collaborative learning environment. We make efforts to specify the technological issues towards the future standardization of this environment through our research experiences. The problem of standardization includes many embarrassed aspects, however it will extend and widen the field of applications possible within the collaborative learning paradigm, and will make possible the usage of the fruits of years of research and individual implementations of the concept of collaborative learning, from many researches, developments and experiences. So we would like to locate this problem as building a common platform.
Efficient implementation of the two dimensional discrete cosine transform for image coding applications on the DSP96002 processor

This paper describes the efficient implementation of the 2D DCT for image coding on the DSP96002 processor. The DSP96002 is a general purpose, dual-bus IEEE floating point digital signal processor. Utilizing the DSP96002's inherent parallel processing capabilities, the execution of a 8/spl times/8 fast 2D DCT takes 133 microseconds. The recently proposed 2D and 1D fast DCT algorithms are employed in this implementation. Transform coefficient zigzag ordering, used in the image coding process, executes in less than 28 microseconds. The fast DSP96002 routines, incorporated within this implementation, can be applied in a number of image coding applications such as video and still image coding as well as the newer JPEG still image and MPEG video standards. <<ETX>>
Years of Chaos : Applied and Theoretical Theory and experiments of fast non-deterministic random bit generation using on-chip chaos lasers

We report physical random bit generation with on-chip chaos lasers. The design of the laser device is based on a theoretical model for non-deterministic random bit generation by amplification of microscopic noise. It is shown that the bit sequences generated at rates up to 2.08 gigabit per second (Gbit/s) pass a standard statistical test suite of randomness. © 2012 Published by Elsevier Ltd. Peer-review under responsibility of Takashi Hikihara and Tsutomu Kambe Keyword: Random bit generation; chaos; semiconductor laser
[Paper] Using Trajectory Features to Recognize Human Actions Within Crowd Sequences of Real Surveillance Video

The importance of human action recognition technology has been increasing1). Action recognition techniques based on video analysis have many applications, such as for motion-based video searches or video summarization. In particular, with the rapid spread of surveillance cameras, there is growing interest in developing a system that not only detects people but also automatically tracks and identifies their actions. However, it is very difficult to analyze real surveillance videos. Video taken by surveillance cameras is typically low quality and low resolution. Noisy background regions make it hard to perform motion analysis. Luminance changes and occlusions also interrupt the image regions that show people's actions. The diversity of human actions is another big issue. The speeds or joint movements for a certain action will differ greatly between individuals. Even the movements of the same person will strongly depend on the circumstance. For the above reasons, automatic recognition of such actions in a real video sequence has been viewed as a challenging task. In this paper, we discuss a method to robustly recognize specific human actions from video sequences taken in crowded places. Fig.1 shows sample images in the dataset of the TRECVID Surveillance Event Detection (SED) task2)3). TRECVID is an international workshop using real video corpora for evaluating information retrieval technologies. The task uses real surveillance videos that were shot in a crowded airport. The images contain many occlusions and variety Abstract There is growing interest in automatic recognition of human actions in video sequences shot by surveillance cameras. However, it's difficult to analyze human actions in real environments. That is, almost all of the current techniques can only detect simple actions within video sequences showing controlled environments. We propose action recognition methods based on multiple trajectories that can identify human actions within crowd sequences of real surveillance video. The methods use novel techniques for detecting diverse actions: a motion-speed invariant feature descriptor made from a key-point trajectory, and a weighting and clustering for the trajectory features. We conducted several experiments on the proposed methods, in which our previously proposed single-trajectory method was used as a baseline for comparison and the dataset was that of the TRECVID Surveillance Event Detection task. We discuss how to select the proper method to detect actions in crowd situations through an analysis of these experimental results.
Estimating object depth using a vertical gradient metal detector

Object depth is a simple characteristic that can indicate an object's type. Popular instruments like radar, metal detectors, and magnetometers are often used to detect the presence of a subsurface object. The next question is often, "How deep is it? " Determining the answer, however, is not as straight forward as might be expected. This paper explores the determination of depth using metal detectors. More specifically, it looks at a popular metal detector (the Geonics EM61) and makes use of its vertically separated coils to generate a depth estimate. Estimated depths are shown for UXO and small surface clutter from flush buried down to 48". Ultimately a statistical depth resolution is determined. An alternative approach is then considered that casts the depth determination problem as one of classification. Only two classes are considered important "deep" and "shallow". Results are shown that illustrate the utility of the classifier approach. The traditional estimator can provide a depth estimate of the object, but the classifier approach can distinguish between small shallow, large deep, and large shallow object classes.
A general method for automated simulation of non-linear dynamical systems using a new fuzzy-fractal-genetic approach

We describe in this paper a new method for automated simulation of non-linear dynamical systems. This method is based on a hybrid fuzzy-fractal-genetic approach to achieve, in an efficient way, automated simulation of a particular dynamical system given its mathematical model. The use of genetic algorithms is to achieve automated parameter selection for the mathematical models. The use of fuzzy logic is to simulate the process of expert behavior identification, by implementing the knowledge of identification by a set of fuzzy rules. We also use the concept of the fractal dimension of a time series to help make this identification more accurate. Experimental results for the case of robotic dynamic systems show the efficiency and accuracy of this new method for the simulation of complex non-linear dynamical systems.
Examining public librarians? information literacy, self-directed learning readiness, and e-learning

The purpose of this study was to explore the current situation of public librarians’ information literacy, self-directed learning readiness and e-learning attitudes in Taiwan. It also sought to identify the relationships among the three variables and the predictive ability of information literacy and self-directed learning readiness on e-learning attitudes. This study employed a survey questionnaire that contained the following: information literacy scale, self-directed learning readiness scale and e-learning attitude scale. The subjects were 385 public librarians from three cities: Taipei, Taichung and Kaohsiung. The research results showed that, public librarians’ perceptions toward information literacy, self-directed learning readiness, and e-learning attitudes were positive. Statistical analysis revealed that public librarians’ who hold a library science degree performed significantly better than those who had graduated from non-library science departments on three sub-factors of information literacy (information querying, information organisation and information evaluation). Respondents who had received more training had better information evaluations and love of learning scores. The stepwise regression analysis indicated that the information evaluation was the strongest predictor in determining public librarians’ e-learning attitudes followed by creative learning, love of learning, and independent learning.
The Architectural Organization of a Mobile Radio Network via a Distributed Algorithm

In this paper we consider the problem of organizing a set of mobile, radio-equipped nodes into a connected network. We require that a reliable structure be acquired and maintained in the face of arbitrary topological changes due to node motion and/or failure. We also require that such a structure be achieved without the use of a central controller. We propose and develop a self-starting, distributed algorithm that establishes and maintains such a connected architecture. This algorithm is especially suited to the needs of the HF Intra-Task Force (ITF) communication network, which is discussed in the paper.