Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding Underlying Structure in Electric Load Data Using Independent Component Analysis

In this paper we analyze electric load data using Independent Component Analysis (ICA) approach. ICA is a method for finding unknown signals from observed ones. Given that observations are linear mixture of independent signal sources, then we can estimate signal sources from just only observations using ICA method. There are some papers studying time-series data with ICA. They apply ICA to economic data, climate data and topic identification. One of the advantages of using ICA is its ability to capture data structures. Among many ICA algorithms, we adopt Complexity Pursuit (CP). CP is based on maximizing nongaussianity and temporal structure of signals. We aim at finding underlying structure of electric load in Kansai Electric Power Co., Inc. As a result, 13 components are extracted from 2004 to 2006 data. Then we explore the meanings of components, and separate weeks based on each component's fluctuation. The groups are related to each season.
A model of free-recall using the ACT-R architecture and the phonological loop

In this paper a model is presented of the free-recall task. It is based on the ACT-R architecture (Anderson, 1993) and a rehearsal theory based on Baddeley’s phonological loop (Baddeley, 1986). Rehearsal has been implemented in ACT-R by Nijdam (1995) in our laboratory. Simulation results show that the model can reproduce experimental results reported by Rundus (1971), Postman and Phillips (1965) and Craik (1970). It can offer explanations for the primacy and recency effect, and the fact that the recency effect disappears and becomes negative if there is a delay between presentation and recall.
Monte Carlo simulation study of regression models used to estimate the credit banking risk in home equity loans

The banking structure of today is quite damaged. This happened because the industry was not able to foresee the different risks that surrounded it. Of the group of risks associated with the business of banking activity, the risk of credit in many occasions accounts for 60%. The risk of credit arises when there exists the possibility of suffering a loss due to the breach of the other party to assume the payment or payments. The default originates a loss for the entity that climbs not onlyto thenonerecoveredamount,butalso to theexpensesincurredin theprocess. The uncertain nature of the risk does mean that this risk is measured through the unexpected loss, which coincides statistically with the standard deviation. This is why statistical methods are needed to enable the prediction of bank credit risk (default and non-payment) in home equity loans through estimates based on statistical models (also called techniques of ‘credit scoring’), to improve the currently available methods.
Researching Travel Behavior and Adaptability: Using a Virtual Reality Role-Playing Game

This article describes a virtual reality role-playing game that was developed as a survey tool to collect travel behavior data and explore and monitor travel behavior adaptation. The Advanced Energy and Material Systems Laboratory has designed, developed a prototype, and tested such a game platform survey tool, called Travel Activity Constraint Adaptation Simulation (TACA SIM). A main objective is investigating adaptability under the simulated situation of rapid fuel price. The computer game survey approach has the potential to capture real behavior data through a well-controlled experiment, because the participant experiences the survey as a role-play exploration. Feedback from participants confirms that TACA SIM collects data efficiently in an acceptable time while the participants enjoyed the experience. The authors propose that this gamed-based survey approach provides the basis for collecting and evaluating travel behavior data and adaptation behavior.
Efficient 3-D Characterization of Surface Defects in Smooth Specular Coatings

Many smooth, highly specular coatings, such as automotive paints and appliance coatings, are subjected to considerable performance demands and manufacturers spend significant sums each year to monitor and repair coating surface quality. Additionally, changing product specifications and environmental regulations will continue to affect the processing parameters that influence surface appearance and quality. Therefore, it is vital to develop robust methods to monitor surface quality on-line and continuously examine the processes that significantly affect surface appearance in real time. As a critical step, this paper presents a cost-effective machine vision system design that utilizes surface reflectance models as a rational basis. Experimental and numerical investigations of diffuse angle images of specular coated surfaces confirm that these images yield a three dimensional characterization of surface defects, efficiently, from a single image. Images can be captured and processed on-board the sensor in milliseconds, facilitating an on-line system which can monitor surface quality in real time.
Modeling communication with Objective VHDL

Objective VHDL was developed to utilize the object-oriented paradigm to the hardware design process. In order to facilitate flexible modeling of communication among (entity) objects appropriate to the specific context, no message passing mechanism has been integrated into the language. Based on earlier ideas related to message passing with Objective VHDL the paper demonstrates the design and implementation of a complete communication mechanism. As an example a non blocking handshake protocol is chosen. Special emphasis has been given to an abstract user-interface and good reusability of the communication mechanism.
A Simple GUI-based Sequencing Format Conversion Tool for the Three NGS Platforms

To allow for a quick conversion of the proprietary sequence data from various sequencing platforms, sequence format conversion toolkits are required that can be easily integrated into workflow systems. In this respect, a format conversion tool, as well as quality conversion tool would be the minimum requirements to integrate reads from different platforms. We have developed the Pyrus NGS Sequencing Format Converter, a simple software toolkit which allows to convert three kinds of Next Generation Sequencing reads, into commonly used fasta or fastq formats. The converter modules are all implemented, uniformly, in Java GUI modules that can be integrated in software applications for displaying the data content in the same format. Availability: You may download the conversion module from Sourceforge.net (https://sourceforge.net/projects/ ngssequencealig/files/PyrusNGSSequencingFormatConverter. zip/download).
Design of a bipolar 10-MHz programmable continuous-time 0.05 degrees equiripple linear phase filter

A bipolar seventh-order 0.05 degrees equiripple linear phase (constant group delay) transconductance-capacitor (g/sub m/-C) low-pass filter with a cutoff frequency (f/sub c/) tunable between 2 and 10 MHz is presented. Programmable equalization up to 9 dB at f/sub c/ is also provided. Total harmonic distortion at 2 V/sub p-p/ is less than 1%, with a dynamic range equal to 49 dB. Nominal power consumption from a single 5-V supply is 135 mW. The circuit also has a low-power mode ( >
Combining reactive behaviors using a hierarchy of fuzzy controllers

Realizing complex robotic tasks by combining elementary behaviors is simple, robust and effective. Learning controllers from examples avoids manual identification of system states and actions and direct definition of their relationships. Fuzzy controllers represent direct associations between input and output variables, typical of reactive behaviors, in a form understandable by both automatic tools and humans. The paper describes the application of a set of tools developed for supporting the automatic design of fuzzy controllers (recording of associations between control commands and system states, identification of the required controller's components). Safe navigation of a real vehicle in an unknown indoor environment is addressed by combining two behaviors, wall-following and door-crossing, using a third module for judging their competence in each situation. Its performance, driving a Scout in our offices, is shown and related to the limitations of the two basic controllers.
Verification and validation of neural networks for safety-critical applications

Onboard nonlinear models are a key enabling technology for virtual sensors, model-based control, reconfigurable control and model-based diagnostic algorithms. Before such models can be used in safety-critical applications, such as civilian aircraft, they must undergo extensive testing to verify that there is no combination of inputs that will generate an undesirable output. This paper presents analysis techniques that can be used as part of a verification procedure for polynomial neural networks (PNNs) that are trained to replace lookup tables in a variety of safety-critical control applications. The technique builds on previous research that uses Lipschitz constants to provide guaranteed bounds on network output and error for all possible inputs without having to test the network at all possible input combinations. The focus of the work presented here is on static, feedforward, multilayer networks, with polynomial basis functions. The methods described form the basis of a software tool, which is in the process of being qualified by the FAA for use in verifying neural networks for safety-critical flight control applications.
Downlink performance of a CDMA system with distributed base station

High-speed and high-capacity communication is required in 4G mobile communication. However the currently used frequency band (2 GHz) will be insufficient to meet such a demand, thus more bandwidth, that seems to be allocated at higher frequencies (3 GHz or 5 GHz), is required. As the frequency band becomes higher, the propagation loss increases; thus mobile terminals (MT) need to strengthen transmission power. However, since there is a limitation on power consumption in an MT, the higher frequency band leads to reduction of cell size. Thus more base stations (BS) are needed to maintain the same area as a conventional system, boosting the infrastructure cost. To solve this problem, a system is proposed that uses some simple relay sub-base stations (SBS) for uplink and downlink and maintains the same coverage area as a conventional system. Due to the imbalance of uplink and downlink traffic, it is expected that capacity requirements are much higher in the downlink. We describe a CDMA (code division multiple access) based distributed base station (BS+SBS) system that fulfills coverage requirements. We evaluate the downlink performance of the proposed system through computer simulation and demonstrate an overall increased system capacity.
TASK-BASED DESIGN FOR LECTURER-STUDENT COMMUNICATION IN TEACHING XHOSA AS A SECOND LANGUAGE

This mini-thesis examines the features of a range of communication tasks in Xhosa that characterize lecturer-student conversations in tertiary context as regards problems of some individual students assuming the Task-based Theory of second language learning and teaching. The study is motivated by the need that exists for the development of specific purposes language courses for African languages like Xhosa in South Africa in the light of the constitutional provision for multilingualism and the advancement of the African languages. The introduction of multilingualism and the advancement of the status and use of the African languages are also specified in the National language policy for Higher Education. In order to commence on the kind of research on syllabus design required for quality second language courses for Xhosa within tertiary context the nature of lecturer-student communication relating to the problems of individual students is investigated in this study. The study focuses in particular on the issue of task design, i.e. the features posited by Pica et al (1993) relating to the interactant relationship between the participants, the interactant requirement (one-way or two-way), the communication goal orientation (i.e. convergent or divergent), and the goal outcome option (i.e. one or several outcome options). The analysis of the Xhosa communication tasks is of crucial significance for syllabus design, course design and pedagogic task design for task-based language teaching.
A polyimide-on-silicon electrostatic fingertip tactile display

A polyimide-on-silicon electrostatic fingertip tactile display has been fabricated and tested. The display consists of 49 electrodes arranged in a square array. Preliminary experiments using 200-600 V pulse excitation resulted in a moderate strength perception. The fingertip sensation is described as "sticky" or "buzzing".
PTList: Mining XML Data Stream Using Paging Schema

Aiming at unlimited growing XML data stream and large XML document, we present PTList, mining frequent subtrees in XML using paging schema. PTList pages XML data stream, manages cross-page nodes and frequent candidate subtrees growing across page, mines frequent subtrees page-by-page, selects frequent subtree according to the page minimum support, and prunes branches based on the decaying factor. PTList mines XML data stream in the limit of the error of support, improves the memory utilization, and speeds up the mining process.
QBARM: A Queue Theory-Based Adaptive Resource Usage Model

Workflow is becoming a more and more important tool for business operations, scientific research and engineering. Cloud computing provides an elastic, on-demand and high cost-efficient resource allocation model for workflow executions. During workflow execution, the load will change from time to time and therefore, it becomes an interesting topic to optimize resource utilization of workflows in the cloud computing environment. In this paper, a workflow framework is proposed that can adaptively use cloud resources. In detail, after users specify the desired goal to achieve, the proposed workflow framework then monitors the workflow execution, and utilizes different pricing models to acquire cloud resources according to the change of workflow load. In this way, the cost of workflow execution is reduced.
Large margin algorithms for discriminative continuous speech recognition (זיהוי דיבור רציף באמצעות אלגוריתמי שוליים רחבים.)

Automatic speech recognition has long been a considered dream. While ASR does work today, and it is commercially available, it is extremely sensitive to noise, talker variations, and environments. The current state-of-the-art automatic speech recognizers are based on generative models that capture some temporal dependencies such as hidden Markov models (HMMs). While HMMs have been immensely important in the development of large-scale speech processing applications and in particular speech recognition, their performance is far from the performance of a human listener. HMMs have several drawbacks, both in modeling the speech signal and as learning algorithms. The present dissertation develops fundamental algorithms for continuous speech recognition, which are not based on the HMMs. These algorithms are based on latest advances in large margin and kernel methods, and they aim at minimizing the error induced by the speech recognition problem. Chapter 1 consists of a basic introduction of the current state of automatic speech recognition with the HMM and its limitations. We also present the advantages of the large margin and kernel methods and give a short outline of the thesis. In Chapter 2 we present large-margin algorithms for the task of hierarchical phoneme classification. Phonetic theory of spoken speech embeds the set of phonemes of western languages in a phonetic hierarchy where the phonemes constitute the leaves of the tree, while broad phonetic groups — such as vowels and consonants — correspond to internal vertices. Motivated by this phonetic structure, we propose a hierarchical model that incorporates the notion of the similarity between the phonemes and between phonetic groups. As in large margin methods, we associate a vector in a high dimensional space with each phoneme or
Hybrid Methods of Desktop Journal Article Delivery

Summary This presentation demonstrated a method of delivering journal tables of contents and journal articles to a geographically dispersed user population. Users of the Ruth H. Hooker Research Library of the Naval Research Laboratory are able to have selected tables of contents e-mailed to them. URLs are given in the e-mail header if the journal is available electronically. If not, users can request photocopies of articles by replying to the e-mail. The system is set up to require minimum maintenance from library staff.
Research on Various Methods for Visual Concept Detection

Visual concept detection is a functional way to detect, manage and classify visual information. No matter it is image retrieval or video retrieval, the system can distinguish object and scene concepts by learning image descriptions itself. However, when the viewing conditions is different or the viewing points is changed, all these will lead to a various result of the image description which collect by the system. So an effective visual concept classification methods should be invariant to different and accidental recording circumstances or conditions. This paper has analysis and summarize the current research status and detection methods of Visual concept detection technologies. Including such methods: salient point detection; social tagged images as a training resource for automated concept detection; extracting distinctive invariant features from images; cross-domain kernel learning method for visual concept detection, etc. And in the end, this paper seeks to unravel the effective when using MIR Flickr in visual concept detection. After comparasion, we want to find the advantages and disadvantages of these typical methods, and hope to give a valuable reference to the following researchers who is interested in visual concept detection and classifications.
Effects of Speech Intelligibility, Morphological Confusions, and Redundancy on Task Performance

Speech is a vital means of communication for completing many tasks. The speech intelligibility needed for successful communication may be degraded by ambient noise levels, poor communication equipment, or hearing impairments. The present research tested the impact of speech message content on task performance under conditions of degraded speech intelligibility. Sixteen subjects participated in a laboratory experiment using on a board game. Message redundancy, morphological confusions, and speech intelligibility were varied. Task performance and subjective workload were measured. Morphological confusions adversely affected performance (both speed and accuracy) and subjective workload (SWAT) to an increasingly greater extent as speech intelligibility decreased. High redundancy improved the accuracy of performance and subjective workload when speech intelligibility decreased; however, high redundant messages were longer and required more time to process than low redundant messages. These results extend earlier work which measured the impact of morphological confusions and redundancy on speech intelligibility itself to the measurement of their impact on performance. Implications for the development of message content guidelines and their impact on performance are discussed.
1 V power supply, low-power consumption A/D conversion technique with swing-suppression noise shaping

A 1 V power supply and low-power consumption A/D conversion technique using swing-suppression noise shaping is proposed. This technique makes it possible to power the on chip A/D converter in digital LSI's directly by a one-cell battery, without a dc-dc converter. Experimental results indicated good performance for the RF-to-baseband analog interface of a digital cordless phone. The A/D converter, fabricated with a 0.5 /spl mu/m CMOS process, operates on a 1 V power supply, has a 10 bit dynamic-range with a 384 ksps sampling speed and consumes only 1.56 mW. >
Multimodal methods for researching digital technologies

This chapter provides an introduction to the field of multimodality and discusses its potential application for researching digital data and environments. It begins by outlining what multimodality is, its theoretical origins in social semiotics, and its underlying assumptions. A number of concepts central to multimodality are introduced: these include mode, semiotic resource, materiality, modal affordance, multimodal ensemble and meaning functions. The scope and potential of multimodality for researching digital technologies are then discussed. The chapter sets out an illustrative example of multimodal research. It concludes with a discussion of the limitations and challenges of a multimodal approach for researching digital technologies. What is multimodality? Multimodality is an inter-disciplinary approach drawn from social semiotics that understands communication and representation as more than language and attends systematically to the social interpretation of a range of forms of making meaning. It provide concepts, methods and a framework for the collection and analysis of visual, aural, embodied, and spatial aspects of interaction and environments (Jewitt, 2009; Kress, 2010). While other modes of communication, such as gesture, have been recognized and studied extensively (e.g. McNeill, 1992), multimodality investigates the interaction between communicational means and challenges the prior predominance of
Optimizing imaging hardware for estimation tasks

Medical imaging is often performed for the purpose of estimating a clinically relevant parameter. For example, cardiologists are interested in the cardiac ejection fraction, the fraction of blood pumped out of the left ventricle at the end of each heart cycle. Even when the primary task of the imaging system is tumor detection, physicians frequently want to estimate parameters of the tumor, e.g. size and location. For signal-detection tasks, we advocate that the performance of an ideal observer be employed as the figure of merit for optimizing medical imaging hardware. We have examined the use of the minimum variance of the ideal, unbiased estimator as a figure of merit for hardware optimization. The minimum variance of the ideal, unbiased estimator can be calculated using the Fisher information matrix. To account for both image noise and object variability, we used a statistical method known as Markov-chain Monte Carlo. We employed a lumpy object model and simulated imaging systems to compute our figures of merit. We have demonstrated the use of this method in comparing imaging systems for estimation tasks.
METHODS OF IMPROVING WORK-PLACE LAYOUT

SUMMARY Mass production of man-operated machines entails that their dimensions should be so designed as to suit the majority of their users. The first part of the paper is devoted to a critical review of work-spaces which demonstrates the discomfort to which certain average individuals are subjected. These individuals are the result of world-wide anthropometric-statistical measurements carried out over a number of years. Ergonomists have widened the conception of work-spaces by introducing improved trial-and-error methods. They have constructed clearance tables for various body regions, as well as manikins to scale and mock-ups of work-spaces, into which certain average individuals were placed. It thus seems that a new method has come into use which integrates ergonomic data concerning body dimensions and the optimal angles between the various body segments. One can, therefore, no longer consider the dimensional adaptation of work-spaces as consisting in the mere application of a series of separate recomm.