Miracle-dz/UniFAR-FTUs huggingface dataset:
Compression for reduction of off-chip video bandwidth

The architecture for block-based video applications (e.g. MPEG/JPEG coding, graphics rendering) is usually based on a processor engine, connected to an external background SDRAM memory where reference images and data are stored. In this paper, we reduce the required memory bandwidth for MPEG coding up to 67% by identifying the optimal block configuration and applying embedded data compression up to a factor four. It is shown that independent compression of fixed-sized data blocks with a fixed compression ratio can decrease the memory bandwidth for a limited set of compression factors only. To achieve this result, we exploit the statistical properties of the burst-oriented data exchange to memory. It has been found that embedded compression is particularly attractive for bandwidth reduction when a compression ratio 2 or 4 is chosen. This moderate compression factor can be obtained with a low-cost compression scheme such as DPCM with a small acceptable loss of quality.
An Environmental Planning Method for Australian Jurisdictions? Comments on the SIRO-PLAN/LUPLAN Schema

A previous issue of this journal included a paper called “SIRO-PLAN and LUPLAN: an Australian approach to land-use planning”. The approach is described here in more conventional plan-making and plan-evaluation terms and is observed to be inappropriate for the types of problems it is intended to solve, to incorporate a politically unacceptable design and selection procedure, to be oriented to plan-making rather than to decisionmaking, and to be unacceptably aloof from the community client. An approach to planning linking strategic problem solving to tactical zoning controls is advanced as an alternative.
Machine learning for prediction of muscle activations for a rule-based controller

The inductive learning (IL) technique, radial basis function (RBF) type of artificial neural network (ANN), and the combination of IL and RBF were used to predict muscle activation patterns and sensory data based on the preceding sensory data. The input consisted of the hip and knee joint angles, horizontal and vertical ground reaction forces recorded in an able-bodied human. The output data consisted of the patterns of muscle activities. These patterns were obtained from simulation of walking with a functional electrical stimulation (FES) system. The simulation takes into account the individual biomechanical characteristics of the eventual user having spinal cord injury (SCI). The mappings were tested using numerous data from five minutes of walking previously not used for the training. The authors illustrate the technique by presenting the estimation of the activations of the equivalent flexor knee muscle and the knee joint sensor for four strides. The correlation is better and tracking errors are smaller when the combination of IL and RBF is used compared to the usage of IL or RBF. The authors show that the prediction of sensory state is achievable; thus, the delays imposed by the properties of the neuro-muscular system can be minimized.
A Tentative Study of the English Tense from a Metaphorical Perspective

The English tense system has always been one of the main subjects for linguists and grammarians. This paper adopts the metaphorical approach to study the English tense. By analyzing the prototypical uses of the present tense and the past tense, the author gives a convincing and reasonable explanation of these various uses of the English tense. The metaphorical approach used in this paper provides a new perspective for the study of the English tense. The metaphorical mapping processes of the past tense and the present tense reflect the universal cognitive mechanism of human beings, that is, learners acquire knowledge from known to unknown. The last but not least, the new interpretations of the different uses of the English tense offers a practical help for the teaching and learning of tense.
Implementation of an extensible component router

With the rapid development of the network technology, it is increasingly important to dynamically upgrade router's software. In this paper, the authors propose new software architecture applying to component router. The novel feature of the architecture is the ability to dynamically load and configure extensible components at run time. Each component implements one function such as packet classification, packet scheduling and routing protocol etc. We design a simple Component Router Configuration Language (CRCL) to configure and manage the router. The Component Router can be configured in according to per network flow. At present, a prototype system based on highly efficient router operating system (HEROS) has been finished.
Attitude control of a tumbler system with rotational joints using a gyroscope

We develop an unstable structure (a tumbler system with joints) that has circular arc type bottoms, which is a model of a biped walking robot. Its attitude is controlled by using a small gyroscope. This paper describes the design of the feedback control system which controls the attitude by supporting one of the leg and driving the crotch joints. The basic feedback control system is a one-input two-output (SIMO) system. The H/sub /spl infin// control theory is used to design the compensator. The results of our experiment on the designed control system show that we successfully stabilized the control of the tumbler system with rotational joints.
Estimation of left ventricular cavity area with an on-line, semiautomated echocardiographic edge detection system.

BACKGROUNDAutomated edge detection of endocardial borders in echocardiograms provides objective, reproducible estimation of cavity area; however, most methods have required off-line analysis. A recently developed prototype echocardiographic imaging system permits real-time automated edge detection during imaging and thus, the potential for measurement of cyclic changes in cavity area and the assessment of left ventricular function on-line. Our purpose was to compare measurements of endocardial area manually traced from conventional echocardiograms with those obtained with the real-time automated edge detection system in normal subjects.METHODS AND RESULTSTwo training sets of images were used to establish optimal methods of gain setting; the settings were then evaluated in a test set of images. In the high-gain training group (n = 8 subjects, 119 images), gain settings were adjusted sufficiently high to display at least 90% of the endocardial border. Manually drawn and real-time area measurements correlate.
Path Planning for CNC Contouring around a Corner

Corner motion is a common and important case in contouring applications. If the corner error is well-controlled, a machine can own maximal throughput while maintaining the machining accuracy. In this paper, we investigated corner error yielded by different Acc/Dec processing in the command generation phase. At first, we derive some analytical forms of corner error induced by Acc/Dec processing; both linear and FIR Acc/Dec types are studied. Then a simple method of controlling the corner error without changing the Acc/Dec structure is presented. The method is simply to add some delay time to retard the execution of the second linear command. Although some results here do not explicitly present their final exact analytic expressions, their numerical solutions can be easily solved.
Automated Design Rationale Capture within the CAx Environment

AbstractThe reuse of the design rationale behind company products has become an increasingly important practice for improving designs. This paper proposes a methodology for the automated capture of design rationale. Current industry design rationale capture methods focus on file storage and management through version control while the proposed method provides the additional ability to capture the entire design process rather than only versions of files. The method requires three primary elements: a CAx tool, a communication package, and a storage medium. An implementation that utilizes Siemens NX 6 CAD software, Skype communications software, and Microsoft SQL server is also presented. The additional functionality provided by this implementation is discussed, and methodology for testing and comparing this implementation to other design rationale capture systems is also presented.
Graphical Password Security Evaluation Criteria by Fuzzy Analytical Hierarchical Process (FAHP)

In today's day and age, one of the important topics in information security is authentication and Graphical Password or Graphical User Authentication (GUA) is one of the most secure techniques. This paper will touch on the security aspect of those algorithms and what most researchers have been working on trying to define these security features and attributes. The goal of this study is to develop a complete decision model that allows automatic selection of available GUA algorithms by taking into considerations the subjective judgments of the decision makers based on the Fuzzy Analytic Hierarchy Process (FAHP).
Parameter Calibration Method Based on Screw Theory for Articulated Coordinate Measuring Arm

To improve the measurement accuracy of the articulated coordinate measuring arm (ACMA), the measurement system’s parameters must be calibrated. The mathematical model and the disturbance of the kinematic parameters’ error are critical to the calibration precision. In this paper, product-of-exponential(POE) model is adopted to establish the kinematic model of the ACMA, and an error correction model which utilizes single-point versus multi-pose and the distance between every two points is used to take accuracy and repeatability into account. Then, genetic algorithm is utilized to optimize the error correction model in order to identify kinematic parameters. Experimental results reveal that the proposed calibration method is feasible.
The Effects of Using Storytelling with a Charlie Chaplin Silent Movie Clip on Oral Proficiency Development

This eleven-week study investigated the effects of storytelling using silent movie clips compared to a series of images to improve the oral proficiency of Korean university students who have a low-intermediate level of English proficiency. The subjects of this study were 36 non-English major Korean undergraduate students whose first language is Korean. Participants were divided into two groups: the experimental group used silent movie clips and the control group used a series of images to compare improvements in their oral performance based on two different visual effects. In order to explore whether storytelling with silent movie clips can produce a positive learning effect, this research employed both qualitative and quantitative approaches. The spoken data were analyzed both holistically and analytically, and results revealed that using the storytelling task can develop both groups` oral proficiency. In particular, the experimental group showed significant improvement in discourse, vocabulary, grammar, and sentence complexity. The participants` attitudes toward using movie clips were slightly positive for discourse, vocabulary, and grammar. Moreover, this study discusses how digital storytelling about a silent movie clip can be used as a plausible speaking assessment task for Korean university students learning English.
Query Expansion Associated with Clustering

The aim of the system is to achieve query expansion. The method works combining clustering of hierarchical methods. Through the information proffered by a background document, doc_ID, concerning the initial query, a cluster containing doc_ID can be produced by hierarchical clustering. And the word co-occurrence information can be extracted from the candidate documents in this cluster. Compared with the content in doc_ID, the result of the experiment using the system shows an expected performance to develop expanded terms which are qualified to add to original query.
A Research of HTN-Based Anytime Planning Algorithm on FPS Games

With the development of game industry, the requirements of game AI are also increasing. Recently a planning formalism called HTN (Hierarchical Task Network) was used to design AI behaviors. In this paper we describe how to implement an anytime planner based on HTN to handle a dynamic environment, which is the key feature of computer game worlds. This planner allows agent to interrupt its sequence of actions at anytime based on the changes of environment meanwhile return a valid replacement plan. We use Unreal Tournament 2004 which is a famous first-person shooter game as the platform and test our anytime planner.
Influence of channel estimation on the performance of a coherent DS-CDMA system

Direct-sequence code division multiple access (DS-CDMA) has become one of the favourite candidates for future mobile radio communication systems. The uplink of a coherent DS-CDMA system is investigated. The channel estimation is carried out via a control channel, which is transmitted simultaneously to the data channel. This concept is very closely related to the CODIT-CDMA concept. In the channel estimation, an averaging process is involved, which for long averaging periods, suppresses the noise influence efficiently. On the other hand, long averaging intervals lead to systematic errors in the estimated channel coefficients due to the time-variant behavior of the channel. Taking into account these effects, a closed-form analysis of the data-channel symbol-error rate (SER) is presented. This analysis allows the prediction of the system's performance and helps to optimize the parameter settings for channel estimation.
Mean‐Shift Object Tracking with Discrete and Real AdaBoost Techniques

An online mean‐shift object tracking algorithm, which consists of a learning stage and an estimation stage, is proposed in this work. The learning stage selects the features for tracking, and the estimation stage composes a likelihood image and applies the mean shift algorithm to it to track an object. The tracking performance depends on the quality of the likelihood image. We propose two schemes to generate and integrate likelihood images: one based on the discrete AdaBoost (DAB) and the other based on the real AdaBoost (RAB). The DAB scheme uses tuned feature values, whereas RAB estimates class probabilities, to select the features and generate the likelihood images. Experiment results show that the proposed algorithm provides more accurate and reliable tracking results than the conventional mean shift tracking algorithms.
Researching on Parsing

Syntactic analysis is the core technology of natural language processing and it is the cornerstone for further linguistic analysis. This paper, first introduces the basic grammatical system and summary the technology of current parsing. Then analysis the characteristics of probabilistic context-free grammars deep and introduce the method of improving for probabilistic context-free. The last we point the difficulty of Chinese parsing.
Pervasive Computing for Hospital, Chronic, and Preventive Care

An emerging area of great impact and significance is the application of pervasive computing technologies in healthcare. Pervasive healthcare refers to the set of technologies designed to seamlessly integrate health education, interventions, and monitoring technology into our everyday lives, regardless of space and time. This approach can increase both the coverage and quality of care. Over the last decade, pervasive computing solutions for healthcare have become increasingly prevalent in both research and commercial efforts. This survey analyzes a variety of research projects and commercial solutions devoted to understanding, designing, and implementing pervasive healthcare applications in support of preventive care, hospital care, and chronic care. Taking into account the working conditions of clinicians and the needs of patients, pervasive computing offers a variety of attractive solutions for many of the challenges to care delivery in these domains. The work of clinicians is intrinsically tied to the physical domain of the patient, not to digital material available in computer systems; clinicians as well as other non-clinical caregivers continually switch between different caregiving contexts. Furthermore, their work is characterized by high mobility, ad hoc collaboration, and interruptions. At the same time, patients and family members frequently demonstrate poor adherence to both behavioral and pharmaceutical interventions and experience inadequate communication with those providing care. The use of health education to promote motivation, reinforcement, advice, and tools for capturing and tracking health information supporting self-monitoring can help patients to overcome these challenges. Pervasive computing offers solutions for clinicians, patients, and a variety of other caregivers to assist them with these problems including applications and mechanisms to: • ease the recording, tracking, and monitoring of health information; • allow communication, collaboration, and coordination among the varied stakeholders; • encourage clinical adherence and disease prevention; • support the nomadic work of clinicians and seamless integration of the physical and digital worlds; and • enable the development of novel medical devices. In this survey, we present an overview of the history of pervasive healthcare research as a human-centered vision driven by a healthcare model that includes preventive, hospital, and chronic care. We then summarize the research in this space, outlining research challenges, current approaches, results, and trends. Finally, we discuss future research directions as a springboard for new focus in pervasive healthcare. This survey is based on analysis of the literature as well as our own research experiences and those of many of our colleagues.
Multicomponent image segmentation: a comparative analysis between a hybrid genetic algorithm and self‐organizing maps

Image segmentation is an essential process in image analysis. Several methods have been developed to segment multicomponent images and the success of these methods depends on the characteristics of the acquired image and the percentage of imperfections in the process of its acquisition. Many of the segmentation methods are parametric, which means that many parameters need to be computed or provided before the segmentation process, and any method that works on one type of multicomponent image cannot necessarily work on another. In addition, many segmentation methods are supervised, where a priori knowledge is needed, such as the number of classes. To overcome these obstacles, a self‐organizing map (SOM), which is an unsupervised nonparametric method, was used to segment four different types of multicomponent images (Landsat, SPOT, IKONOS and CASI), and the results compared to those of a new nonparametric unsupervised genetic algorithm (GA) for image segmentation. To improve the performance of the GA, a hill‐climbing process and another random heuristic module were added to escape the local‐minima trap and to improve the speed of the GA; the new algorithm is called the hybrid genetic algorithm (HGA). Verification of the results was performed using two different techniques: field verification and the functional model. These verification techniques show that the HGA is more accurate in multicomponent image segmentation than the SOM.
A design method of circularly polarized rectangular microstrip antenna by one‐point feed

This paper describes a method for designing backfeed-type one-point fed circularly polarized antennas. These antennas are fed at one point from the back side of the substrate and have degeneracy-resolving segments. Characteristics of the rectangular microstrip antennas with degeneracy-resolving segments are obtained by means of a variational method. The equivalent circuit at and near the resonance with perturbations is obtained and the condition for circularly polarized antennas is found from both theoretical and experimental viewpoints. Configurations and radiation characteristics of these antennas are discussed and it is shown that these antennas can be used as array elements.
A New Automatic Exposure Algorithm for Astronomical Image and its FPGA Implementation

Automatic exposure control is the process of controlling the exposure time of the digital imaging system to obtain the desired image which can fit the human vision during the imaging process. A new automatic exposure algorithm for astronomical image is proposed. The pixel value weight is determined by exploring the maximum range of the image histogram. Additionally, the structure of the implementation based on FPGA and experiment results for real data are given. The experiment results show that the proposed algorithm can effectively achieve the real-time automatic exposure control.
An architecture-independent workload characterization model for parallel computer architectures

A model is presented for representing and comparing workloads, based on the way they would exercise parallel machines. This workload characterization is derived from parallel instruction centroid and parallel workload similarity. The centroid is a simple measure that aggregates average parallelism instruction mix, and critical path length. When captured with abstracted information about communication requirements, the result is a powerful tool in understanding the requirements of workloads and their potential performance on target machines. The workload similarity is based on measuring the normalized Euclidean distance (ned) between workload centroids. It is shown that this workload representation method outperforms comparable ones in accuracy, as well as in time and space requirements. Analysis of the NAS Parallel Benchmarks and their performance is presented to demonstrate some of the applications, such as performance prediction with good accuracy, and insight provided by this model.
Statistical Model‐Based Noise Reduction Approach for Car Interior Applications to Speech Recognition

This paper presents a statistical model‐based noise suppression approach for voice recognition in a car environment. In order to alleviate the spectral whitening and signal distortion problem in the traditional decision‐directed Wiener filter, we combine a decision‐directed method with an original spectrum reconstruction method and develop a new two‐stage noise reduction filter estimation scheme. When a tradeoff between the performance and computational efficiency under resource‐constrained automotive devices is considered, ETSI standard advance distributed speech recognition font‐end (ETSI‐AFE) can be an effective solution, and ETSI‐AFE is also based on the decision‐directed Wiener filter. Thus, a series of voice recognition and computational complexity tests are conducted by comparing the proposed approach with ETSI‐AFE. The experimental results show that the proposed approach is superior to the conventional method in terms of speech recognition accuracy, while the computational cost and frame latency are significantly reduced.
Analysis for mean effective gain of mobile antennas in land mobile radio environments

A method is described for analyzing the mean effective gain (MEG) of antennas moving in a mobile communication environment. The MEG characteristics of a mobile antenna are determined by the mutual relation between the antenna patterns and the statistical distribution of incident waves in an environment. To analyze this relation theoretically, a general expression for the MEG using a statistical model of incident waves is derived, and a novel statistical model, whose distribution is uniform in azimuth and Gaussian in elevation, is proposed. The validity of the statistical model is confirmed through 900-MHz-band measurements carried out in a Tokyo urban area, and the empirical parameters for the statistical distribution are described. The MEG characteristics of a half-wavelength dipole antenna are investigated using the proposed method, and it is shown that the theoretical curves calculated using the empirical parameters are in excellent agreement with experimental results. This analysis is extremely applicable for evaluating the MEG characteristics of arbitrary mobile antennas in various mobile communication environments. >