Miracle-dz/UniFAR-FTUs huggingface dataset:
Word Sense Disambiguation using Clue Words

This paper presents a new model to disambiguate the correct sense of polysemy word based on the related context words for each different sense of the polysemy word. The related context words for each sense are referred to as clue words for the sense. The WordNet organises nouns, verbs, adjectives and adverbs together into sets of synonyms called synsets each expressing a different concept. In contrast to the structure of WordNet, we developed a model that organizes the different senses of polysemy words based on the clue words. These clue words for each sense of a polysemy word are used to disambiguate the correct meaning of the polysemy word in the given context using any WSD algorithm. The clue word for a sense of a polysemy word may be a noun, verb, adjective or adverb. DOI: http://dx.doi. org/10.3126/jie.v10i1. 10900 Journal of the Institute of Engineering, Vol. 10, No. 1, 2014, pp. 192–198
Improved Self-Adaptive Glowworm Swarm Optimization Algorithm

The sparse sets of linear equations are produced in electrical surveying, how to raise the efficiency of the solution of equations is the key to Object-probed. Glowworm swarm optimization algorithm (GSO) algorithm put forward to solve linear equations.To overcome slow convergence and lower accuracy solution, independent movement and self-adaptive step was proposed to improve the GSO (IGSO). The experimental results prove that, IGSO has a better performance than GSO.
Analysis and compensation of the bitline multiplexer in SRAM current sense amplifiers

Current sensing in SRAMs is very promising to achieve high-speed operation in low-voltage applications. However, so far, a main limitation of the practical use of current sense amplifiers is the finite resistance of the bitline multiplexer (MUX). In this paper, the MUX itself and its influence on two types of current sense amplifiers is analyzed. It is shown that the MUX causes a significant performance degradation. A principle is presented to compensate for the bitline multiplexer by means of a current sense amplifier with improved feedback structure. The proposed solution is implemented in a 512/spl times/24 bit SRAM macro in 0.18-/spl mu/m 1.8-V CMOS. It is shown by theory and measurements that, using the proposed circuit, it is possible to fully compensate for the MUX in terms of speed and signal amplitude with only little layout area penalty. A speed improvement due to the compensation of typically 0.5 ns is measured.
Comparison of Clustering Methods for Segmenting Color Images

Background/Objectives: Image segmentation is the first step for any image processing based applications. The Conventional methods are unable to produce good segmentation results for color images. Methods/Statistical analysis: We present two soft computing approaches namely Fuzzy C-Means (FCM) clustering and Self Organizing Map (SOM) network are used to segment the color images. The segmentation results of FCM and SOM compared to the results of K-Means clustering. Results/Findings: Our experimental results shown that the Fuzzy C-Means and SOM produced the better results than K-means for segmenting complex color images. The time required for the training of SOM is higher. Conclusion/Application: The trained SOM network reduced the execution time for segmenting color images. The performance of FCM and SOM is higher than the K-means for segmenting color images. Applications of color image segmentation are video surveillance, face recognition, fingerprint recognition, object detection, medical image analysis, and Automatic target detection.
Single-sensor active noise cancellation using recurrent neural network predictors

In this paper, we propose a recurrent neural network (RNN) predictor with an application to a single-sensor active noise cancellation (ANC) system. The proposed RNN predictor has one hidden layer whose neurons are classified into two categories, recurrent hidden neurons and non-recurrent hidden neurons. Due to the RNN's ability of modeling time-varying signals such as acoustic noises, the proposed RNN may be more suitable than the LMS-type digital filters and multilayer perceptrons (MLP). Moreover, the number of non-recurrent hidden neurons can be arbitrarily increased according to the complexity of a given problem with a relatively little increase in computation during training. In the simulation on the noise data from a moisture-removing machine, about 22.35 dB attenuation was obtained with the proposed approach while 20.83 dB attenuation with the MLP-based approach, and 14.35 dB with a filtered-x LMS algorithm.
Error activity and error entropy as a measure of psychoacoustic significance in the perceptual domain

Several models have been described in the literature which seek to represent audio stimuli in the perceptual domain to best predict the audibility of errors and distortions. By modelling the principal nonlinear processes of human hearing it is possible to calculate a perceptual domain error surface that represents the audible difference between distorted and original audio signals. A further stage of analysis is required to maximise the usefulness of the auditory model output. The audible error surface must be interpreted to produce an estimate of the overall subjective judgement which would result from the particular distortion. Ideally, the interpretation of the error surface should be broadly analogous to human perceptual mechanisms, and equally, it would be desirable to avoid the complex and cumbersome statistical mapping and clustering techniques proposed by some authors. A technique employed in adaptive transform coding of images, namely cell entropy, offered several desired properties. The paper reports the extension and application of such a technique to the interpretation of perceptual-domain error surfaces produced by an auditory model. Speech data were subjected to an example, algorithmically generated, nonlinear distortion and then processed by the auditory model. The usefulness of the error-activity and error-entropy quantities are illustrated, without optimisation, by comparison of model predictions and experimentally determined opinion scores.
An iterative decorrelator with multipath combiners for CDMA frequency-selective fading channels

We investigate the performance of a multiuser receiver consisting of the decorrelator, which is implemented using an iterative method, and the multipath combiners for slowly-varying frequency-selective fading channels. The system considered here is an asynchronous direct-sequence code division multiple access (DS-CDMA) system. Using computer simulation, we evaluate and compare the performance of the multiuser receiver in terms of the bit error rate and system capacity. Simulation results show that the multiuser receiver achieves the same performance as that based on the conventional implementation, with much lower computational complexity.
Hand Grasping Choice and Analysis for Tasks

Resulting in an optimal grasping pose of satisfying task requirements is a critical problem for hands manipulation. Based on the problem, taxonomy of grasping poses was created. This paper presents key-based search method that can obtain all hand manipulation poses matching the grasped object. However, these grasping pose must be ranked by combining with task requirements and object geometry. In this way, optimal grasping pose can be achieved. The effectiveness of the method was demonstrated by using grasping pose taxonomy comparisons from motion capture example database.
GPU Accelerated Parallel Cholesky Factorization

One of the fundamental problems in scientific computing is to find solutions for linear equation systems. For finite element problem, Cholesky factorization is often used to solve symmetric positive definite matrices. In this paper, Cholesky factorization is massively parallelized and three different optimization methods - highly parallel factorization, tile strategy and memory scheduling are used to accelerate Cholesky factorization effectively. A novel algorithm using OpenCL is implemented. Testing on GPU shows that performance of the algorithm increases with the dimension of matrix, reaching 785.41GFlops, about 50x times speedup. Cholesky factorization is remarkably improved with OpenCL on GPU.
The impact of repeaters on CDMA system performance

In mobile communication systems, due to practical frequency wave propagation, there are zones in the selected area, where signal coverage is not adequately accomplished by the base-station. These dead spots are valleys, tunnels on highways and railway tracks. Repeaters are typically viewed as a solution to this problem. We examine repeaters from a slightly different perspective, investigating how, when used in a flat terrain environment they not only extend signal coverage, but impact system performance as well.
A multivariable laboratory process with an adjustable zero

A novel multivariable laboratory process that consists of four interconnected water tanks is presented. The linearized dynamics of the system have a multivariable zero that is possible to move along the real axis by changing a valve. The zero can be placed in both the left and the right half-plane. In this way the quadruple-tank process is ideal for illustrating many concepts in multivariable control, particularly performance limitations due to multivariable right half-plane zeros. Accurate models are derived from both physical and experimental data and multi-loop control is illustrated.
Computer network management based on TMN

Computer Network Management is the most important work of the computer network. Two problems in managing of a professional network must be solved, one is to standardize the relationship between the professional network and the management network, and the other is to ensure the security of the network. The first problem will be discussed here. We put forward a new idea here, that is, to build standard computer management network and standard professional network. First, we give a standard model of the relationship between the management network and its subordinate professional network. This model is different with the TMN. It distinguishes the management network and the subordinate professional network clearly in the notion, the place and the property of all the sockets is determined. Subsequently, the corresponding function structure and physical architecture are given together. For each kind of architecture, we define the related rules respectively. These rules are: the relationship between the function module, the standard of the interface, protocol architecture. Then, the procedure of communication signal processing is analyzed. The requirements of all the programming sockets are explained. Finally, we explain some related topics briefly.
Cervical disc arthroplasty

Cervical disc arthroplasty is a motion-preserving procedure that is an alternative to fusion. The goals are to maintain cervical motion, reduce adjacent segment degeneration and eliminate nonunion. Disc replacement was developed to primarily treat neural compressive disorders such as radiculopathy and possibly myelopathy. The number of implants available is growing rapidly. Studies of in vitro wear testing have claimed substantially less wear for cervical implants than that seen with prosthetic hips and knees. Short-term clinical results after decompression and cervical disc replacement for the treatment of cervical radiculopathy or myelopathy are encouraging. Prospective, randomized trials are lacking. Cervical disc replacement is an innovative technology that preserves motion at the instrumented levels and will potentially improve load transfer to the adjacent levels compared with fusion. Clinical reports of success of cervical total disc replacement are encouraging but also quite preliminary. As time progresses, a clearer role for the place of cervical disc replacement should emerge.
A Review of Software Architecture for Collaborative Software’s

Software architecture has emerged as an important sub-discipline of software engineering; particularly in the realm of large system development. Collaboration software applications are inherently cooperative, requiring many software applications to coordinate their efforts to produce a software system application. Integral to this effort is developing shared understanding surrounding multiple artifacts, each artifact embodying its own model, over the entire development process. This focus on model collaboration embedded within a larger process is what distinguishes collaboration research in software engineering from broader collaboration research. This article first review a list of goals for software architecture, then collaboration software application, several possible future directions for collaboration in software engineering is presented. The article concludes by noting a problem in performing research on collaborative systems.
Formant coding of speech using dynamic programming

An algorithm is proposed which will obtain, from an input speech signal, formant parameter data to control a parallel formant speech synthesiser. By allowing some delay and employing variable-frame-rate techniques, the parameter data can be obtained at a low frame rate (typically 20 frames per second) suitable for transmission or storage.
Phase II evaluation of paclitaxel, α‐interferon, and cis‐retinoic acid in advanced renal cell carcinoma

Interferon and 13‐cis‐retinoic acid (13‐CRA) therapy showed clinical response rates of 30% in advanced renal cell carcinoma (RCC). This combination also enhanced sensitivity to paclitaxel in a bcl‐2 and mutant p53 expressing renal carcinoma cell line. Based on this, the authors conducted a Phase II clinical trial of the combination of interferon, 13‐CRA, and weekly paclitaxel, in advanced RCC.
ORCHID: Building linguistic resources in Thai

ORCHID (Open linguistic Resources CHanelled toward InterDisciplinary research) is a project aimed at building linguistic resources to support research in, but not limited to, natural language processing. Based on the concept of an open architecture design, the resources must be fully compatible with those which already exist, and software tools must also be made available. This paper describes the construction of a Thai part-of-speech (POS) tagged corpus, a preliminary stage in the construction of a Thai speech corpus. The paper also details the development of a POS tagger to be used in the construction of the POS-tagged corpus. Additionally, we describe a proposal for a new tagset, based on the results of a prior multilingual machine translation project. The corpus is annotated on three levels: paragraph, sentence, and word. Text information is maintained in the form of the text information lines and the number lines, which are both utilized in data retrieval. Finally, we describe a POS neuro tagger, which consists of a three-layer perceptron with elastic input. Computer experiments show that the neuro tagger has an accuracy of 94.4 per cent for tagging ambiguous words when tested on a small Thai training corpus containing 22,311 ambiguous words. A series of comparative experiments further show that the neuro tagger is superior to the statistical models including the frequency model (a baseline model), local n-gram model, and HMM (Hidden Markov Model).
Modeling and Control of a Single-Phase, 10 kW Fuel Cell Inverter

As the world’s energy use continues to grow, the development of clean distributed generation becomes increasingly important. Fuel cells are an environmentally friendly renewable energy source that can be used in a wide range of applications and are ideal for distributed power applications. In this study, the power conversion element of a dual single-phase, 10 kW stand-alone fuel cell system is analyzed. The modular converter consists of a DC-DC front-end cascaded with a half-bridge inverter. The entire system is accurately modeled, to help determine any interactions that may arise. Control strategies based on simplicity, performance, and cost are evaluated. A simple voltage loop, with careful consideration to avoid transformer saturation, is employed for the phase-shifted DC-DC converter. Several experimental transfer functions were measured to confirm the modeling assumptions and verify the control design of the DC-DC converter. Two control options for the inverter are explored in detail, and experimental results confirm that the modulation index must be controlled to regulate the output voltage during various load conditions. The final system is implemented without the use of current sensors, thus keeping the inverter cost down. Experimental results using a power supply are given for resistive, inductive, and nonlinear loads and the performance is acceptable. Fuel cell test results, including transient response, are also displayed and analyzed.
Phonetically adaptive cepstrum mean normalization for acoustic mismatch compensation

We propose a new technique that compensates for an acoustic mismatch. This technique is simple and can estimate the acoustic mismatch more accurately than conventional cepstrum mean normalization (CMN), because it takes into consideration the kind of phonemes and their frequency, and can calculate the acoustic mismatch in detail. In this procedure the acoustic mismatch can be estimated as the difference between the centroid vector of distorted speech and that of acoustic models. The cepstral mean of distorted speech is the centroid vector including the distortion. The centroid vector calculated from parameters of acoustic models is regarded as the centroid vector when the distorted speech is assumed to be clean speech. The acoustic models used for calculation are for phonemes that appear in the transcription of the speech. This technique achieves a high word error reduction rate of 73% for ordinary analog telephone speech and 70% for wireless telephone handset speech.
Semantic Oriented Knowledge Processing Model

The objective of knowledge processing system is to promote knowledge integration, sharing and retrieval in distributed and heterogeneous environment. This paper puts forward a semantic oriented intelligent processing model-SOKPM for knowledge processing, which promises better access to relevant knowledge by producing a global domain ontology that is used for establishing semantic connections among the local autonomous knowledge sources as well as for retrieving those sources. In SOKPM, an up-bottom knowledge integration approach with a semantic transformation adapter framework is proposed to solve both the semantic heterogeneities and the query answering problems.
Estimación de la resistencia del rotor usando una red neuronal artificial en el control vectorial indirecto del motor de inducción

Resumen--Este artículo presenta un estimador de la resistencia del rotor basado en una red neuronal artificial (RNA) usada en el control vectorial indirecto (CVI) del motor de inducción (MI). La mayor atención se enfoca al comportamiento dinámico del estimador neuronal de la resistencia del rotor, el cual tiene mejores prestaciones que el estimador de la resistencia del rotor basado en lógica difusa que aparece en la literatura técnica. La simulación se realizó utilizando primero un motor de inducción de 1,5 hp y posteriormente se utilizó un MI de 20 hp. Se pudo utilizar la misma RNA debido al escalamiento (normalización) de las entradas y salida de la RNA en cada motor. El entrenamiento de la RNA se realizó fuera de línea mediante el algoritmo de Levenberg-Marquardt. La RNA es una red de tres capas; la primera capa tiene catorce neuronas, la capa oculta tiene cinco, y la capa de salida tiene sólo una neurona debido a que la única señal de salida es el valor de la resistencia del rotor. Los resultados de la simulación indican la viabilidad de este estimador como una alternativa a los métodos basados en los valores de los parámetros de MI. Además en el artículo se presentan las consideraciones prácticas para implementar el estimador neuronal de la resistencia del rotor en un sistema de desarrollo de dSPACE.
Modelling Parsing Constraints with High-dimensional Context Space

Deriving representations of meaning has been a long-standing problem in cognitive psychology and psycholinguistics. The lack of a m odel for representing semantic and grammatical knowledge has been a handicap in attempting to model the effects of semantic constraints in hum an syntactic processing. A computational model of high-dim ensional context space, the Hyperspace A nalogue to Language (H AL), is presented with a series of simulations modelling a variety of human empirical results. HAL learns its representations from the unsupervised processing of 300 million words of conversational text. W e propose that HAL's high-dim ensional context space can be used to (1) provide a basic categorisation of semantic and grammatical concepts, (2) model certain aspects of morphological ambiguity in verbs, and (3) provide an account of semantic context effects in syntactic processing. W e propose that the distributed and contextually derived representations that HAL acquires provide a basis for the subconceptual kn.
Sub-Pixel Edge Detection on the Product Line

In this paper, we present a new method to detect sub-pixel edges of shape-known objects. Differ from other sub-pixel edge detection methods based on normal information, we use tangential information. We introduce theories of this method, as well as the influences on the performance of this method caused by size, sampling location and direction of the object. This new method has been practically applied and compared with other methods in real pictures on the product line. Results show that this method provides more accurate sub-pixel edge in practical applications.
Trust Online: Young Adults' Evaluation of Web Content

Little of the work on online credibility assessment has considered how the information-seeking process figures into the final evaluation of content people encounter. Using unique data about how a diverse group of young adults looks for and evaluates Web content, our paper makes contributions to existing literature by highlighting factors beyond site features in how users assess credibility. We find that the process by which users arrive at a site is an important component of how they judge the final destination. In particular, search context, branding and routines, and a reliance on those in one’s networks play important roles in online information-seeking and evaluation. We also discuss that users differ considerably in their skills when it comes to judging online content credibility.
Sub-1-V swing internal bus architecture for future low-power ULSIs

A bus architecture is proposed for reducing the operating power of future ULSIs. It uses new types of bus driver circuits and bus receiver circuits to reduce the bus signal swing while maintaining a low standby current. The bus driver circuit has a source offset configuration, achieved by the use of low-V/sub T/ MOSFETs and an internal supply voltage corresponding to the reduced signal swing. The bus receiver circuit has a symmetric configuration with two-level conversion circuits, each of which consists of a transmission gate and a cross-coupled latch circuit. Fast level conversion is achieved without increasing the standby current. The combination of the new bus driver and receiver enables the bus swing to be reduced to one-third that of the conventional architecture while maintaining high-speed data transmission and a low standby current. A test circuit designed and fabricated using 0.3- mu m processes verifies the operation of the proposed architecture. Further improvements in the speed performance are possible with device optimization. >