Miracle-dz/UniFAR-FTUs huggingface dataset:
A constraint-based framework for configuration

The research presented here aims at providing a comprehensive framework for solving configuration problems, based on the Constraint Satisfaction paradigm. This thesis is addressing the two main issues raised by a configuration task: modeling the problem and solving it efficiently. Our approach subsumes previous approaches, incorporating both Simplification and further extension, offering increased representational power and efficiency. Modeling. We advance the idea of local, context independent models for the types of objects in the application domain, and show how the model of an artifact can be built as a composition of local models of the constituent parts. Our modeling technique integrates two mechanisms for dealing with complexity, namely composition and abstraction. Using concepts such as locality, aggregation and inheritance, it offers support and guidance as to the appropriate content and organization of the domain knowledge, thus making knowledge specification and representation less error prone, and knowledge maintenance much easier. There are two specific aspects which make modeling configuration problems challenging: the complexity and heterogeneity of relations that must be expressed, manipulated and maintained, and the dynamic nature of the configuration process. We address these issues by introducing Composite Constraint Satisfaction Problems, a new, nonstandard class of problems which extends the classic Constraint Satisfaction paradigm. Efficiency. For the purpose of the work presented here, we are only interested in providing a guaranteed optimal solution to a configuration problem. To achieve this goal, our research focused on two complementary directions. The first one led to a powerful search algorithm called Maintaining Arc Consistency Extended (MACE). By maintaining arc consistency and taking advantage of the problem structure, MACE turned out to be one of the best general purpose CSP search algorithms to date. The second research direction aimed at reducing the search effort involved in proving the optimality of the proposed solution by making use of information which is specific to individual configuration problems. By adding redundant specialized constraints, the algorithm improves dramatically the lower bound computation. Using abstraction through focusing only on relevant features allows the algorithm to take advantage of context-dependent interchangeability between component instances and discard equivalent solutions, involving the same cost as solutions that have already been explored.
A deformable model of the human iris driven by non-linear least-squares minimisation

This paper describes a deformable model of the human iris which forms part of a system for accurate off-line measurement of binocular eye movements, particularly cyclotorsion (torsion), from video image sequences. At least two existing systems measure torsion from infrared video images by pupil tracking followed by cross-correlation of band-pass filtered iris sectors. Unfortunately, pupil expansion and contraction reduces the accuracy of this method. In addition, infrared iris images typically contain very little texture, so correlation can be unreliable. A five-parameter deformable model of the iris was therefore developed for analysing images taken in visible light. This model can translate (horizontal and vertical eye motion), rotate (torsion) and scale both uniformly and radially (pupil changes). Torsion measurements obtained with the model are repeatable and accurate to within 0.1 0 ; this performance is illustrated by analysing binolcular torsion during constant fixation on a stationary target.
Infra‐red analysis by the derivative method

Derivative infra-red spectra have been obtained by means of an analogue computer and utilized in qualitative and quantitative analysis. The second derivative with respect to time of the light intensity, obtained when the spectrometer is scanning at a fixed rate, may be used to detect and fix the position of minor changes of absorption, while the second derivative of the logarithm of the light intensity approximates very closely to the second derivative of optical density and is a quantitative function of the absorbing material. The value of the derivative function is zero or very small over considerable intervals of the wavelength scale and analyses for a particular component in complex mixtures may frequently be made by a single measurement of the magnitude of the quantitative derivative function at an appropriate wavelength without interference from other components. m-Cresol and o-cresol have been directly estimated in commercial m-cresol, and m- and o-cresol and phenol have been assayed in crude tar phenols without prior fractionation and by a single independent measurement for each. The success of analyses using wide slits is attributed to the triangular form of the spectrometer slit function.
A GHz MOS adaptive pipeline technique using MOS current-mode logic

This paper describes an adaptive pipeline (APL) technique, which is a new pipeline scheme capable of compensating for device-parameter deviations and for operating-environment variations. This technique can also compensate for clock skew and eliminate excessive power dissipation in current-mode logic (CML) circuits. The APL technique is here applied to a 0.4-/spl mu/m MOS 1.6-V 1-GHz 64-bit double-stage pipeline adder, and this paper shows that the adder can operate accurately on condition that the clock has 20% skew. The APL technique uses MOS current-mode logic (MCML) circuits, whose propagation delay time can be varied by the control ports. MCML circuits can operate with lower signal voltage swing and higher operating frequency at lower supply voltage than CMOS circuits can. This paper also shows that MCML circuits are suitable for a low-noise variable delay circuit. Measurement results show that jitter of MCML circuits is about 65% that of CMOS circuits.
EFFECTS OF INTERFACE WINDOWING MODES AND INDIVIDUAL DIFFERENCES ON DISORIENTATION AND COGNITIVE LOAD IN A HYPERMEDIA LEARNING ENVIRONMENT

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy EFFECTS OF INTERFACE WINDOWING MODES AND INDIVIDUAL DIFFERENCES ON DISORIENTATION AND COGNITIVE LOAD IN A HYPERMEDIA LEARNING ENVIRONMENT By Muhammet Demirbilek August 2004 Chair: Mary Grace Kantowski Major Department: Curriculum and Instruction The purpose of our study was to investigate the effects of different interface windowing modes (tiled and overlapping windows) and individual differences (computer experience) on users’ disorientation and cognitive overload in a hypermedia learning environment. The second aim of our study was to make suggestions for designing more effective interface and hypermedia systems that minimize user disorientation, and cognitive overload. Literature on hypermedia systems, disorientation, cognitive overload, web-based navigation, interface design, and individual differences helped to frame the study and clarify research questions. A quantitative study was conducted to reveal the answers to research question. The study involves three dependent variables, and one independent variable with two levels. Dependent variables were user disorientation, cognitive overload, and computer understanding and experience. Data were collected from surveys, Active Script Pages and Java Script coded web pages and the Internet Explorer History file. Participants were
Compression de maillages 3D de grande résolution par transformée en ondelettes au « fil de l'eau »

In this paper we introduce a method allowing to perform a Scan-based Wavelet Compression of 3D semi-regular multiresolution meshes. This method consists in processing the data progressively during the acquisition while reducing considerably memory usage. The experiments show that the method is very effective in terms of memory usage and access. Moreover the proposed algorithm allows reducing the complexity of processing from O(N2) to O(N).
Fluorous Reverse Phase Silia Gel. A New Tool for Preparative Separations in Synthetic Organic and Organofluorine Chemistry

Fluorous reverse phase silica gel, or silica gel with a fluorocarbon bonded phase, can be readily prepared by standard techniques, but shows unusual separation features. This silica gel separates primarily by fluorine content. Uses of fluorous reverse phase silica gel in both synthetic organic chemistry and organofluorine chemistry are introduced. Solid phase extraction can be used to separate fluorous or fluorous-tagged compounds from organic compounds. Fluorous chromatography can be used to purify mixtures of compounds with differing fluorine content as well as for "demixing" in the new technique of fluorous mixture synthesis.
Analysis and Application of Web-Based L2 Tasks

Kim, Heyoung (2004). Analysis and application of web-based L2 tasks. Multimedia-Assisted Language Learning, 7(2), 81-101. Although task-based language teaching (TBLT) has been recognized as an effective way of teaching English, it seems far less applicable to the Korean EFL context for many reasons. This study attends to the barriers to task-based language instruction in FL learning environments and suggests ways to incorporate online tasks into the EFL curricula. First of all, this study introduces and analyzes four online activities: Treasure hunts, Ask-an- expert, Webquests, and Virtual field trip, from a second language task frame (Chapelle, 1999) to examine whether they are qualified as authentic L2 tasks from a TBLT perspective. Second, this study looks into how these online tasks are integrated into the existing curriculum with only minor modifications. The new software, Tasks Online in English Teacher's DeskTM, designed in this project is suggested as a solution that can reduce teachers' effort and time in creating online tasks. Some suggestions to working with current textbooks and curricula are also explained with some sample activities.
Analysis of Long-term Market Trend by Text-Mining of News Articles

In this study, we developed a new method of the long-term market analysis by using text-mining of news articles. Using our method, we conducted extrapolation tests to predict stock price averages by 19 industry and two market averages, TOPIX and Nikkei225 for about 10 years. As a result, 8 sectors in 21 sectors (about 40%) showed over about 60% accuracy, and 15 sectors in 21 sectors (over 70%) showed over about 55% accuracy. We also developed a web system of financial text-mining based on our method for financial professionals.
A Method for Extracting Topics in News Twitter

Twitter that represents the social network makes it available to retweet the tweet that other users have written without restriction. Therefore, information can be conveniently delivered on a real-time basis. Thanks to such an advantage, studies that utilize twitter are recently being developed. This paper is intended to establish data base based on BBC News Twitter on a daily basis making a daily tweet as a token according to gap and moving to a phase of reprocessing that removes the stopwords. Each word that is created and retweeted after a phase of reprocessing is applied to calculate the total added retweet value, dividing them by the number of daily average retweet to derive topic weight value. This procedure is called ‘Topic Weight Measurement. ’ This way, the topics are extracted. After analyzing the pattern according to the date, topics that are extracted using proposed procedures are compared with frequency pattern that are provided by Google Trends. As a result, it was confirmed that topics provided by BBC News Twitter is similar with word searching pattern graph of Google Trends
Continuous n-tuple classifier and its application to face recognition

The author describes the continuous n-tuple classifier: a new type of n-tuple classifier that is ideally suited to problems where the input is continuous or multi-level rather than binary. Results on a widely used face database show the continuous n-tuple classifier to be as accurate as any method reported in literature, while having the advantages of speed and simplicity over other methods.
A multilanguage platform for Open Source Intelligence

Abstract Open Source Intelligence (OSINT) is an intelligence gathering discipline that involves collecting information from open sources and analyzing it to produce usable intelligence. The revolution in information technology is making open sources more accessible, ubiquitous, and valuable, making open intelligence at less cost than ever before. The explosion in OSINT is transforming the intelligence world with the emergence of open versions of the specialistic arts of human intelligence (HUMINT), overhead imagery intelligence (IMINT), and signals intelligence (SIGINT). The international Intelligence Communities have seen open sources grow increasingly easier and cheaper to acquire in recent years. But up to 80% of electronic data is textual and most valuable information is often hidden and encoded in pages which are neither structured, nor classified. The process of accessing all these raw data, heterogeneous in terms of source and language, and transforming them into information is therefore strongly linked to automatic textual analysis and synthesis, which are greatly related to the ability to master the problems of multilinguality. This paper describes a multilingual indexing, searching and clustering system, designed to manage huge sets of data collected from different and geographically distributed information sources, which provides language independent search and dynamic classification features. The Joint Intelligence and EW Training Centre (CIFIGE) is a military institute, which has adopted this system in order to train the military and civilian personnel of Defence in the OSINT discipline . Keywords:
Comparative Aspects of Neural Network Algorithms for On-Line Modelling of Dynamic Processes

This paper reviews the model structures and learning rules of four commonly used artificial neural networks: the cerebellar model articulation controller (CMAC), B-splines, radial basis functions (RBF) and multi-layered perceptron (MLP) networks. Their dynamic modelling abilities are compared using a two-dimensional non-linear noisy time series. The network performances are evaluated based on their network surface plots, phase/time history plots, learning curves, prediction error autocorrelation functions and finally their short-range prediction error variances. The modelling results suggest that all four networks were able to capture the underlying dynamics of the time series. Also, specific prior knowledge about the time series was incorporated into the B-splines model, and is used to highlight an important trade-off between the model flexibility and high-dimensional modelling ability in the B-splines and CM AC networks. In general, when the network model is well conditioned and linear with respect to its adaptable parameters, simpler on-line learning rules often provide adequate convergence properties. Alternatively, when the model is highly non-linear, complicated learning rules which utilize high-order gradient information are generally required at the expense of increased computational complexity.
A New Tool for Supporting Retailers in Advanced Technologies Risk Management

Due to the increasing importance of innovation for maintaining competitive advantages, firms are forced to innovate in each organizational sector. Thus, also retail sector, with emphasis on the points of sale, needs to adopt new strategies for maintaining existing consumers and attracting new ones. Despite this need, there is still a lack of tools for supporting retailers’ decision concerning the introduction of innovations in the store. The aim of our work is to provide a new tool, the Risk/Span of use matrix, which integrates elements from the obsolescence risk analysis concerning a new technology and from Technology Acceptance analysis for supporting retailers in the decision-making process.
THEORETICAL ASPECTS OF MEASUREMENT AND MANAGEMENT OF COMPANY'S PERFORMANCE

The concept of performance is one of the most important categories of economic analysis, it has been extensively used and it has a broad interpretation. To describe the concept of performance, the related words are used, linked by the noun “performance”: performance management, performance measurement, and performance assessment. In Latvia, these concepts have not been analysed and assessed; therefore, there is a necessity to carry out a theoretical investigation into the concept of performance as well as the concept of performance measurement and management. The research is based on the analysis of foreign scientific publications and special literature devoted to the concept of performance and issues of performance measurement and management. The aim of the research is to carry out a theoretical investigation into company’s performance and performance measurement and management General research methods are employed in this research: the monographic or descriptive research method, the comparative research method, carrying out exploration of the concepts “performance” and “performance measurement and management framework”, based on the extensive study of literature. As a result of the research, the investigation into the concept of performance has been carried out, systematization of the performance measurement and management frameworks and systematization of the small and medium-sized companies’ performance measurement and management frameworks have been performed.
Exploiting wordnet for semantic routing in unstrutured peer to peer information retrieval

Unstructured peer-to-peer networks offer attractive benefits in large-scale information retrieval and search systems because of its fault-tolerance, scalability and decentralization. However, its architecture makes it hard to share useful semantic knowledge among peers. In this paper we propose a semantic based method for unstructured peer-to-peer query routing. Here we exploit the semantic correlation among peers based on the query terms. The term expansion mechanism is the key part of this approach where the term is expanded based on the use of WordNet. Simulation results show that, our approach improves the retrieval and use small number of messages in query routing and retrieval.
A Novel Intelligent Condition Evaluation Method of Mechatronic Equipment based on SVM and GA

Condition evaluation of mechatronic equipment is always a hot research point in fault diagnosis fields, and it can provide a decision-making for condition based maintenance. In this paper, a novel intelligent condition evaluation method based on SVM and GA is proposed, and it combines the feature selection method and condition classification method to evaluate the operational condition of mechatronic equipment. In order to validate the intelligent condition evaluation method proposed in this paper, the rolling element bearing fault dataset is introduced. Experiment results show that the optimal feature subset can be selected with very good classification accuracy rate and the dimension of the optimal feature subset significantly decreases.
Measuring Task Complexity in Human Computation Systems

Human computation platforms offer requesters the possibility to outsource human intelligence tasks or HITs to large amounts of workers around the world. Researching the various aspects of HIT design has the potential to improve the human computation experience for both requesters and workers. This thesis researches the relationship between quantitative aspects of HITs and their perceived complexity. Specifically, we consider three categories of task attributes: Metadata, Content and Visual. In order to measure these attributes, we constructed a real-time human computation market crawler that we used to gather HIT data and reinstantiate HITs from the largest human computation market, Amazon Mechanical Turk, and a task attribute analysis pipeline to obtain task attribute measurements from the market data. We present an analysis of the various task attributes, and perform an experiment predicting HIT throughput based on task attribute and market data. Our analysis shows that market statistics, task batch size and semantic content features can be used to predict throughput. We also conduct an initial exploration into measuring subjective HIT complexity as perceived by workers. Based on our analysis and experimental results, we identify three key points of advice for human computation task designers.
Chemical Structural and Chain Conformational Characterization of Some Bioactive Polysaccharides Isolated from Natural Sources

Abstract Some polysaccharides isolated from natural sources show various important biological activities, such as antitumor, immunomodulatory, and anti-inflammatory effects, which are strongly affected by their chemical structures and chain conformations. This article attempts to review the current development on structural and conformational characterization of some importantly bioactive polysaccharides isolated from natural sources. The chemical structures were analyzed by FTIR, liquid-state NMR (one and two dimensions), solid-sate NMR, Raman spectroscopy, gas chromatography (GC), GC–Mass (GC–MS), and high-performance liquid chromatography (HPLC). The chain conformations of polysaccharides in solutions were investigated using static and dynamic light scattering, viscosity analysis based on the theory of dilute polymer solution, circular dichroism analysis, atomic force microscopy (AFM) including single molecular AFM and AFM-based single-molecule force spectroscopy, fluorescence correlation spectroscopy and NMR spectroscopy.
Application of a Serum‐Free Medium for the Growth of Vero Cells and the Production of Reovirus

Two strains of reovirus (serotype 1 Lang/TIL and serotype 3 Dearing/T3D) were propagated in Vero cells grown in stationary or agitated cultures in a serum‐free medium, M‐VSFM. Solid microcarriers (Cytodex‐1) were used to support cell growth in agitated cultures with a normal doubling time of 25 h. Cell yields of 1 × 106 cells/mL were obtained from an inoculum of 2 × 105 cells/mL in 4 days in microcarrier cultures. The growth profile and cell yield was not significantly different from serum‐supplemented cultures. The virus titer increased by 3−4 orders of magnitude over a culture period of 150 h. The maximum virus titer in stationary cultures reached >1 × 109 pfu/mL for both strains of reovirus in M‐VSFM. M‐VSFM also supported high viral yields in microcarrier cultures. Both the specific productivity and final viral yield was higher in M‐VSFM than serum‐supplemented cultures. The high viral productivity suggests that this is a suitable system for the production of reovirus as an oncolytic agent for human therapeutic use.
Cybersickness and desktop simulations: field of view effects and user experience

We used a desktop computer game environment to study the effect Field-of-View (FOV) on cybersickness. In particular, we examined the effect of differences between the internal FOV (iFOV, the FOV which the graphics generator is using to render its images) and the external FOV (eFOV, the FOV of the presented images as seen from the physical viewpoint of the observer). Somewhat counter-intuitively, we find that congruent iFOVs and eFOVs lead to a higher incidence of cybersickness. A possible explanation is that the incongruent conditions were too extreme, thereby reducing the experience of vection. We also studied the user experience (appraisal) of this virtual environment as a function of the degree of cybersickness. We find that cybersick participants experience the simulated environment as less pleasant and more arousing, and possibly also as more distressing. Our present findings have serious implications for desktop simulations used both in military and in civilian training, instruction and planning applications.