Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on Simple Prediction Method of Heat Load: A Use of Linear Approximation Indicial Response in Basements

This study was conducted to establish a predictable method for a heat load of an underground structure with sufficient accuracy. As the first step, our previous paper reported the measurement results of field experiments on an underground experimental basement under internal heat generation conditions. Also, it presented the results of numerical analyses on the heat and moisture behavior and the influence of internal heat generation of the experimental basement and ground. However, it is practically impossible to utilize the model of simultaneous heat and moisture transfer at the design phase because the prediction by the model of simultaneous heat and moisture transfer requires a long calculation time. In this paper, the authors present the simple load calculation technique, using a linearized approximation indicial response of the inner surface heat flux in a basement to outdoor air temperature change. In addition, the approximation indicial responses for each part of the single-walled concrete drawn using this technique are arranged. The heat load calculation example of application to the basement of the optional size by this technique is shown.
The Volume Grid Manipulator (VGM): A Grid Reusability Tool

This document is a manual describing how to use the Volume Grid Manipulation (VGM) software. The code is specifically designed to alter or manipulate existing surface and volume structured grids to improve grid quality through the reduction of grid line skewness, removal of negative volumes, and adaption of surface and volume grids to flow field gradients. The software uses a command language to perform all manipulations thereby offering the capability of executing multiple manipulations on a single grid during an execution of the code. The command language can be input to the VGM code by a UNIX style redirected file, or interactively while it is most applicable and where the strengths of such software can be utilized. The next two sections describe the memory management and the manipulation command language. The following 8 sections describe simple and complex manipulations that can be used in conjunction with one another to smooth, adapt, and reuse existing grids for various computations. These are accompanied by a tutorial section that describes how to use the commands and manipulations to solve actual grid generation problems. The last two sections are a command reference guide and trouble shooting sections to aid in the use of the code as well as describe problems associated with generated scripts for manipulation control.
Designing intelligent database systems through argumentation

Information systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS). Nowadays intelligent applications require better reasoning capabilities than those present in older data processing systems[7]. Argumentation frameworks appear to be an excellent starting-point for building such systems. Research in argumentation has provided important results while striving to obtain tools for common sense reasoning. As a result, argumentation systems have substantially evolved in the past few years, and this resulted in a new set of argument-based applications in diverse areas where knowledge representation issues play a major role. Clustering algorithms [6], intelligent web search [3], recommender systems [4, 3], and natural language assessment [2] are the outcome of this evolution. We claim that massive data processing systems can be combined with argumentation to obtain systems that administer and reason with large databases. These would result in a system that can extract and process information from massive databases and exhibit intelligent behavior and common sense reasoning as a by-product of the argumentation system used for the reasoning process. In this work, we present a specialization of the DeLP [5] system, called Database Defeasible Logic Programming (DB DeLP). This framework could be easily integrated with a relational database component to achieve a system capable of massive data processing and intelligent behavior. Next, we formally define this system.
X-PLOR Version 3.1: A System for X-ray Crystallography and NMR

X-PLOR is a sophisticated computer programme that provides an interface betweeen theoretical foundations and experimental results in structural biology, with specific emphasis on X-ray crystallography and nuclear magnetic resonance of large biological molecules. This manual to X-PLOR Version 3.1 presents the theoretical background, syntax and function of the programme and also provides a comprehensive list of references and sample input files with comments. It is intended primarily for researchers and students in the fields of protein chemistry, structural biology and computational moecular biology.
GSM-MR compression algorithm with two step sorting based on similarity analysis

Collecting reliable and accurate MR data on time plays a vital role in the mobile communication network optimization. However, with the increment of the number of mobile users, network bandwidth cannot meet with mass transfer of MR. A high performance and high compression ratio GSM-MR compression algorithm is proposed to gain better transfer time. This algorithm utilizes two step sorting in order to reduce the distance between similar content, based on the analytic result about similarities of GSM-MR data sorting by different fields. Experimental results reveal that the algorithm does not only decrease compression consuming time, but also ascends compression ratio with the increment of the size of compression data.
A Comparative Study of two Approaches for Data-Driven Design of Evolving Fuzzy Systems: eTS and FLEXFIS

In this paper, two approaches for the incremental data-driven learning of one of the most effective fuzzy model, namely of so-called Takagi-Sugeno type, are compared. The algorithms that realize these approaches include not only adaptation of linear parameters in fuzzy systems appearing in the rule consequents, but also incremental learning and evolution of premise parameters appearing in the membership functions (i.e. fuzzy sets) in sample mode together with a rule learning strategy. In this sense the proposed methods are applicable for fast model training tasks in various industrial processes, whenever there is a demand of online system identification in order to apply models representing nonlinear system behaviors to system monitoring, online fault detection or open-loop control. An evaluation of the incremental learning algorithms are included at the end of the paper, where a comparison between conventional batch modelling methods for fuzzy systems and the incremental learning methods demonstrated in this paper is made with respect to model qualities and computation time. This evaluation is based on high dimensional data coming from an industrial measuring process as well as from a known source on the Internet, which underlines the usage of the new method for fast online identification tasks. (c) Taylor and Fransis Group (to appear in International Journal on General Systems)
Frontal ablation and temporal variations in surface velocity of Livingston Island ice cap, Antarctica

The manuscript reports on the estimation of mass balance for an extensively ice covered island in the Antarctic Peninsula region, based mainly on information derived from observations by various Earth observation satellites, complemented by in situ measurements for limited areas. Considering the poor knowledge on mass balance of glaciers in the Antarctic periphery, it is certainly a valid goal trying to reduce this uncertainty. Unfortunately the available data base is rather inadequate for deriving accurate mass balance numbers for the ice body of Livingston Island, so that the impact of the work regarding uncertainties in mass balance of the Antarctic Peninsula region is rather limited.
Evaluation of a novel myoelectric training device

EVALUATION OF A NOVEL MYOELECTRIC TRAINING DEVICE By Ryan Clingman, B.S. Biomedical Engineering A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Biomedical Engineering at Virginia Commonwealth University. Virginia Commonwealth University, 2012 Major Director: Gerald E. Miller Ph.D Chair, Department of Biomedical Engineering While research shows that a patient’s success in using a myoelectric prosthetic arm is dependent on receiving effective training, current methods of training are not designed to effectively hold attention long enough for optimal training. This study focused on evaluating a novel myoelectric training device, consisting of a toy car controlled by EMG signals from the arm. Subjects’ performance with the trainer was evaluated to determine its ability to provide experience with EMG controls. Eight healthy adult subjects were taken through typical initial stages of myoelectric training, then asked to drive the car through a slalom course while the time, number of errors, and reversals required to complete the course were recorded, as well as the degree of difficulty subjects reported. The learning induced by using the trainer was found to be statistically significant (p < 0.002), with subjects demonstrating dramatic improvements (> 49%) in performance.
Modeling and Analysis of Semi-automated Fusion in the Intelligence Process

Abstract : Technology today provides more data than humans can possibly analyze manually. Semi-automation fusion (SAF), where a system filters and fuses information in preparation for human analysis, is one way to process and organize vast amounts of data for more efficient human handling. The question that arises is how SAF will affect the human's workload. This analysis quantified the impact that SAF might have on mission times and the cognitive workload for four Infantry Battalion S2-level intelligence analysts. The objectives were to determine and compare workloads for the analysts when using a manual information analysis process and when using a SAF-assisted process. Of particular interest was the analysis time to discovery time ratio. For this model, the ratio was higher with the SAF process, indicating that analysts were able to better employ their time and skills on analysis rather than information gathering. However, improvement is still needed in order for the analysts to fully exploit the available information while maintaining a reasonable cognitive workload level.
The Challenge of Usability Evaluation of Online Social Networks with a Focus on Facebook

In today’s era online social networks are getting extensive popularity among internet users. People are using online social networks for different purposes like sharing information, chatting with friends, family and planning to hang out. It is then no surprise that online social network should be easy to use and easily understandable. Previously many researchers have evaluated different online social networks but there is no such study which addresses usability concerns about online social network with a focus on Facebook on an academic level (using students as subjects). The main rationale behind this study is to find out efficiency of different usability testing techniques from social network’s point of view, with a focus on Facebook, and issues related to usability. To conduct this research, we have adopted the combination of both qualitative and quantitative approach. Graduate students from BTH have participated in usability tests. Our findings are that although think aloud is more efficient then remote testing, but this difference is not very significant. We found from survey that different usability issues are in Facebook profile, media, Picture Tagging, Chatting etc.
Programming model for distributed intelligent systems

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.
Hand Calculators: A 1969 Report on their use in Schools

“It is clear that desk machines will increasingly be used in schools at all levels” Some Lessons in Mathematics, 1964 “Machines can illuminate the idea of place value” Nuffield Project Desk Calculators, 1967 “A realisation that the use of machines has arrived in order to ease any necessary burdens of computation” Examinations Bulletin No. 1 1963
Semantic Web Services with Web Ontology Language (OWL-S) - Specification of Agent-Services for DARPA Agent Markup Language (DAML)

Abstract : CMU did research and development on semantic web services using OWL-S, the semantic web service language under the Defense Advanced Research Projects Agency- DARPA Agent Markup Language (DARPA-DAML) program. The objective was to develop a markup language to allow intelligent agents to communicate. The DAML program resulted in the Web Ontology Language (OWL) Markup as a W3 recommendation. OWL-S is a markup language based on OWL to create computer discoverable web services. The report includes documentation of research on the OWL-S profile, process model and grounding. The research also includes intelligent web service composition, brokering and an OWL-S virtual machine.
Gene Technology and Social Acceptance

chapter 1 Introduction chapter 2 Factors that Determine Social Acceptance of a New Technology chapter 3 Applications of Gene Technology chapter 4 Patents and Gene Technology chapter 5 Understanding the Living World chapter 6 Technology in the Context of Society chapter 7 Coming to Societal Decisions in a Fast-Changing Environment chapter 8 Summation and Outlook
Integrated Cognitive Architectures For Robust Decision Making

Abstract : Introduction The project s goal was to reproduce robust and intelligent decision making capabilities in artificial agents by integrating two successful cognitive architectures, ACT-R (Anderson, 2007) and Leabra (O Reiily & Munakata, 2000). The rationale was that such an integration effort would yield insights on the general mechanisms that allow rapid decision-making in real-time. Taken separately, ACTR and Leabra incorporate different views of how decision-making and robust behavior occur. The two architectures have different and complementary strengths and weaknesses and work at different levels of abstractions. Thus, an integration of the two would possibly yield a uniform framework for understanding the computational basis of robust intelligence and decision-making in humans.
A Semantic Field Approach to Passive Vocabulary Acquisition for Advanced Second Language Learners

Current ESL instructors and theorists agree that university students of ESL have a need for a large passive vocabulary. This research was undertaken to determine the effectiveness of a semantic field approach to passive vocabulary acquisition in comparison to a traditional approach. A quantitative analysis of the short-term and long-range results of each approach is presented. Future research and teaching implications are discussed. The outcome of the experimentation lends tentative support to a semantic field approach.
Robust self-localization of mobile robots in dynamic environments using scan matching algorithms

Abstract: The most fundamental task for any mobile robot is to perform self-localization in the world in which it is currently active, i.e. determine its position relative its world. Encoders that count wheel rotations are often used, which can be turned into relative position estimates by means of integration. This process is commonly referred to as dead reckoning. Unfortunately, the errors in such position estimates grow over time due to the underlying measurements errors, which means that the errors in the dead reckoning estimates must be regularly corrected by absolute position estimates provided by other sensors. The goal of this thesis is to evaluate the possibilities of using so called scan matching algorithms for robust position estimation of a mobile robot, especially in environments that change over time. A scan is a set of range measurements of the environment provided by e.g. a laser scanner. By comparing a scan taken at the actual position of the robot with a scan previously taken and stored in a map of the environment, an estimate of the absolute position of the robot can be obtained. It is important that scan matching algorithms are robust against changes in the environments, are robust against different types of environments and can judge their own results. The main contributions of the thesis are threefold. First, two new sector-based scan matching algorithms are presented that are based on two existing scan-matching algorithms known as the Cox´s and IDC algorithm. The sector-based variants, Cox-S and IDC-S, increase the performance of the existing algorithms, especially in environments containing severe changes. Second, two new methods are presented for estimating the uncertainty of the IDC algorithm. These methods improve the self-judgment of the IDC and IDC-S significantly, as the existing method for estimating the uncertainty was not reliable. Third, the new sector-based scan matching algorithms are evaluated and compared to the existing algorithms on the basis of simulations and real world experiments made with two different mobile robots. The experiments focus on the performance of the algorithms in changing environments and on their performance as part of a complete localization system, i.e. fusing the outcome with dead reckoning. The experiments show a clear advantage of using sector-based scan matching algorithms in terms of increased robustness against changed environments. The experiments show that use especially of a combination of the two sector-based algorithms Cox-S and IDC-S, while also using the new method for estimating the uncertainty of the IDC-S, achieves significantly better performance in changing environments compared to the existing algorithms. Keywords: Mobile robot, self-localization, scan matching algorithm, changed environments, dynamic environments, co-variance matrix, Kalman filter
Dynamic neural network-based feedback linearization of electrohydraulic suspension systems

Resolving the trade-offs between suspension travel, ride comfort, road holding, vehicle handling and power consumptions is the primary challenge in designing Active-Vehicle-Suspension-Systems (AVSS). Controller tuning with global optimization techniques is proposed to realise the best compromise between these conflicting criteria. Optimization methods adapted include Controlled-Random-Search (CRS), Differential-Evolution (DE), Genetic-Algorithm (GA), Particle-Swarm-Optimization (PSO) and Pattern-Search (PS). Quarter-car and full-car nonlinear AVSS models that incorporate electrohydraulic actuator dynamics are designed. Two control schemes are proposed for this investigation. The first is the conventional Proportional-Integral-Derivative (PID) control, which is applied in a multi-loop architecture to stabilise the actuator and manipulate the primary control variables. Global optimization-based tuning achieved enhanced responses in each aspect of PID-based AVSS performance and a better resolve in conflicting criteria, with DE performing the best. The full-car PID-based AVSS was analysed for DE as well as modified variants of the PSO and CRS. These modified methods surpassed its predecessors with a better performance index and this was anticipated as they were augmented to permit for efficient exploration of the search space with enhanced flexibility in the algorithms. However, DE still maintained the best outcome in this aspect. The second method is indirect adaptive dynamic-neural-network-based-feedback-linearization (DNNFBL), where neural networks were trained with optimization algorithms and later feedback linearization control was applied to it. PSO generated the most desirable results, followed by DE. The remaining approaches exhibited significantly weaker results for this control method. Such outcomes were accredited to the nature of the DE and PSO algorithms and their superior search characteristics as well as the nature of the problem, which now had more variables. The adaptive nature and ability to cancel system nonlinearities saw the full-car PSO-based DNNFBL controller outperform its PID counterpart. It achieved a better resolve between performance criteria, minimal chatter, superior parameter sensitivity, and improved suspension travel, roll acceleration and control force response.
Power control techniques in a multihop CDMA packet radio network

In this paper, we have investigated power control techniques for two different routing schemes in a multihop code division multiple access (CDMA) packet radio network. These techniques control the signal power based not only on the transmission distance, but also on the transmission direction. These techniques reduce the amount of interference from the other terminals, and improve the probability of packet success and the expected forward progress per hop.
Extraction of word senses from bilingual resources using graph-based semantic mirroring

In this thesis we retrieve semantic information that exists implicitly in bilingual data. We gather input data by repeatedly applying the semantic mirroring procedure. The data is then represented by vectors in a large vector space. A resource of synonym clusters is then constructed by performing K-means centroid-based clustering on the vectors. We evaluate the result manually, using dictionaries, and against WordNet, and discuss prospects and applications of this method.
Algebraic Identification and Estimation Methods in Feedback Control Systems

Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws.This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology.Key features:Presents a radically new approach to online parameter and state estimation.Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory.Includes examples in a variety of physical applications with experimental results.Covers the latest developments and applications.Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.