Miracle-dz/UniFAR-FTUs huggingface dataset:
The Graphical Structure of Respondent-driven Sampling

Respondent-driven sampling (RDS) is a chain-referral method for sampling members of hidden or hard-to-reach populations, such as sex workers, homeless people, or drug users, via their social networks. Most methodological work on RDS has focused on inference of population means under the assumption that subjects’ network degree determines their probability of being sampled. Criticism of existing estimators is usually focused on missing data: the underlying network is only partially observed, so it is difficult to determine correct sampling probabilities. In this article, the author shows that data collected in ordinary RDS studies contain information about the structure of the respondents’ social network. The author constructs a continuous-time model of RDS recruitment that incorporates the time series of recruitment events, the pattern of coupon use, and the network degrees of sampled subjects. Together, the observed data and the recruitment model place a well-defined probability distribution on the recruitment-induced subgraph of respondents. The author shows that this distribution can be interpreted as an exponential random graph model and develops a computationally efficient method for estimating the hidden graph. The author validates the method using simulated data and applies the technique to an RDS study of injection drug users in St. Petersburg, Russia.
Making a case for using electronic performance support systems in academic libraries

Electronic performance support system (EPSS) technology provides a powerful mechanism for helping end-users operate complex systems. This article describes and discusses some research we have undertaken to explore their potential within academic library systems. Based on a needs analysis, an EPSS for supporting library users was designed and implemented. An evaluation of the system showed that an experimental group of EPSS users was more successful than a control group in performing library tasks, showing that aided task performance was better than unaided. Implications of the results and future work are discussed.
Filter generation system with feature reconstruction using genetic algorithm

Real-time tracking of moving objects in natural scenes has taken a great role in computer vision. In order to track the targets, it is necessary to determine the object models, but it is hard to determine them in advance. Moreover, to realize real-time operations, each frame operation should be done in a short time. We propose an automatic filter construction system for tracking objects by filter processing. The filters are designed by the system itself in each environment, and are able to extract their color features which are not contained in other areas. The proposed system generates color filters which can derive feature segments using the clustering process. After that, it reconstructs the filter to obtain better performance by the genetic algorithm. We show how the filters are effective for object detection and tracking a target.
An Overview of the Management System for Heterogeneous Networks (MSHN) The Management System for Heterogeneous Networks

The Management System for Heterogeneous Networks (MSHN) is a resource management system for use in heterogeneous environments. This paper describes the goals of MSHN, its architecture, and both completed and ongoing research experiments. MSHN’s main goal is to determine the best way to support the execution of many different applications, each with its own quality of service (QoS) requirements, in a distributed, heterogeneous environment. MSHN’s architecture consists of seven distributed, potentially replicated components that communicate with one another using CORBA (Common Object Request Broker Architecture). MSHN’s experimental investigations include: (1) the accurate, transparent determination of the end-to-end status of resources; (2) the identification of optimization criteria and how non-determinism and the granularity of models affect the performance of various scheduling heuristics that optimize those criteria; (3) the determination of how security should be incorporated between components as well as how to account for security as a QoS attribute; and (4) the identification of problems inherent in application and system characterization. This research was supported, in part, by the DARPA/ITO Quorum Program.
Analysis of foetal electrocardiogram extraction methods and enhancement using Hilbert-Huang transform

This paper discusses in detail the extraction methods of the foetal Electrocardiogram (fECG) signal from the non-invasive maternal Electrocardiogram (mECG) and enhancement techniques. Foetal ECG compound signals from DaISy database obtained non-invasively by placing electrodes on the abdomen area of the mother were used for the purpose. In this paper two algorithms were used, Extended State Kalman Filter which uses modified nonlinear effective model and priory generated synthetic ECG signals and FastICA which uses the order of Kurtosis. Finally Hilbert-Huang Transform (HHT) was applied to extracted fECG signal to describe the non-linear and non-stationary nature of signals by instantaneous frequency which reveals the intra-wave frequency modulations. Also the efficiencies of these methods were compared based on few important criterions such as output waveforms, PSNR and energy function of the extracted signal. Based on these findings the best method in extracting foetal ECG from noise contaminated source signals was presented.
Freeway Performance Measurement System (PeMS) Version 4

PeMS 4 is the latest of four task orders devoted to research, development, and maintenance of the PeMS system. PeMS collects, processes, stores, and makes available online data from the six Caltrans districts (D3, 4, 7, 8, 11, 12), which include the major urban areas in California. The data are obtained from 23,237 loops, grouped into 7,359 vehicle detector stations (VDS). These loops cover 2,812 out of 30,726 miles of interstate and state highways in California. PeMS began as a research project. As the research system evolved, Caltrans determined that the information it provided was very valuable, and significant resources were then directed towards the development of PeMS. This entailed production-level code development and system maintenance. Faculty, post-doctoral fellows, and graduate student researchers at U.C. Berkeley (UCB) conduct the 'research' element of the project. Berkeley Transportation Systems (BTS) is responsible for PeMS 'development' and 'maintenance' activities. The UCB and BTS groups meet weekly. There are periodic conferences with members of Caltrans Division of Traffic Operations. The project is comanaged by the PeMS PI and the Division of Traffic Operations. The product of the research activity is reported in professional meetings and journals and in algorithms, and summarized in this report. The algorithms are incorporated into PeMS applications code as part of the development activity. The maintenance activity is concerned with database management, network troubleshooting, and providing PeMS access to users. PeMS is accessed over a standard web browser via the Internet. The current PeMS user community comprises 956 individuals and 63 'value added resellers' or VARs. During October 2003, PeMS received an average of 4,000 'hits', generating 42 MB of data download, each day. Caltrans users account for 26 percent of hits, and UCB accounts for 12 percent. The remaining usage is by VARs, academic researchers around the country, and transportation professionals. Under PeMS 4, the system changed significantly in three ways. First, the 'look and feel' that users experience has improved. Website navigation is more intuitive. Second, PeMS functionality increased with the incorporation of congestion reports, travel time reliability, loop detector diagnosis, and data correction. Third, the database structure has been changed from a district-by-district orientation to a statewide orientation. As a result, statistics like travel times can be collected for routes that cross district boundaries.
Automatic text location in complex color images using local color quantization

An efficient text location method in complex color images is proposed. To deal with characters on complex background colors, local color quantization is done separately for each color instead of all colors. A candidate text line is extracted merging connected components and confirmed using heuristics based on color profile. I tested the proposed method on complex book cover images and it is shown to be successful in extracting texts in complex color images.
Whatever Became of Educational Technology? The Implications for Teacher Education

The paper explores the reasons for educational technology principles and practices not being more widely accepted and successfully applied in everyday teaching and learning. It argues that these are: an over-emphasis on new technology; a failure to learn from the lessons of the past; and a lack of meta-analysis and collaborative research to evidence the benefits. The paper also brings out the point that the literature fails to acknowledge the important role of educational technology in informal learning and non-formal education. It concludes with recommendations for future research into the broader aspects of educational technology and the employment of more longitudinal and collaborative action research and the nature of pre-service, in-service and postgraduate teacher education in educational technology. Keywords: Education technology, teacher education, teacher training;
Tunnel-Data server: Data Format, Archive Maintencance and Access Protocol

The Tunnel-Data server provides access to the archive of transient data that has been collected by the Hypersonics Group over the past 20 years. These data are associated with the thousands of individual shots of the shock tunnel and expansion tube facilities run by the group and are made available via a web server using simple text-based protocol. This report describes the layout of the data archive, the format of the individual files and the details of the protocol used to access the data. It also describes the scripts used to maintain the archive files, serve data from the archive via CGI, and provide the client-side access for data-analysis envrironments such as MATLAB and Octave. Much of the detailed documentation is embedded in these scripts.
Protocols to capture the functional plasticity of protein domain superfamilies

Most proteins comprise several domains, segments that are clearly discernable in protein structure and sequence. Over the last two decades, it has become increasingly clear that domains are often also functional modules that can be duplicated and recombined in the course of evolution. This gives rise to novel protein functions. Traditionally, protein domains are grouped into homologous domain superfamilies in resources such as SCOP and CATH. This is done primarily on the basis of similarities in their three-dimensional structures. A biologically sound subdivision of the domain superfamilies into families of sequences with conserved function has so far been missing. Such families form the ideal framework to study the evolutionary and functional plasticity of individual superfamilies. In the few existing resources that aim to classify domain families, a considerable amount of manual curation is involved. Whilst immensely valuable, the latter is inherently slow and expensive. It can thus impede large-scale application. This work describes the development and application of a fully-automatic pipeline for identifying functional families within superfamilies of protein domains. This pipeline is built around a method for clustering large-scale sequence datasets in distributed computing environments. In addition, it implements two different protocols for identifying families on the basis of the clustering results: a supervised and an unsupervised protocol. These are used depending on whether or not high-quality protein function annotation data are associated with a given superfamily. The results attained for more than 1,500 domain superfamilies are discussed in both a qualitative and quantitative manner. The use of domain sequence data in conjunction with Gene Ontology protein function annotations and a set of rules and concepts to derive families is a novel approach to large-scale domain sequence classification. Importantly, the focus lies on domain, not whole-protein function.
Mathematical Thinking and Learning

This chapter presents a selective review of the recent research on the development, learning, and teaching of mathematical knowledge and thinking. While school mathematics involves not only arithmetic but also algebra, measurement and geometry, and data handling and probability, the present chapter focuses on arithmetic only, a focus that reflects the preponderance of current psychological and educational research on mathematics education. And within arithmetic the emphasis is on number sense, whole number arithmetic, and word-problem solving—topics that have been stressed in recent reform documents because of their importance for the acquisition in children of basic competence in mathematics. The review is also selective with regard to age range, focusing on primary school children. As a framework for reviewing the literature, and for the presentation and discussion of research-based instructional interventions, we use a model for the design of powerful environments for learning and teaching mathematics that is structured according to four interrelated components, namely, competence (aspects of mathematical proficiency), learning (characteristics of productive mathematics learning processes), intervention (principles for the design of environments for mathematics learning and instruction), and assessment (forms of assessment for monitoring and improving mathematics learning and teaching). Keywords: classroom assessment; large-scale assessment; mathematical competence; mathematical learning; mathematical thinking; mathematics education; mathematics learning environments; mathemetics-related beliefs; multidigit arithmetic; number sense; single-digit computation; word problem solving
Syntactic part of speech tagging guidelines for Bangla text

Recently, several techniques have been tested to automatically assign part-of-speeches to Bangla texts using different tag sets. But there is always a need for a standard tagset for Bangla that has been formally published for syntactical bracketing, along with a details POS tagging guideline for the annotators which shows how a word should be tagged in a particular context. This document presents a guideline for annotating Bangla text by part-of-speech to assist the syntactical bracketing task. This tagset consists of total 55 tags tried to precisely distribute all of the required syntactic categories and encode necessary syntactic information to facilitate advanced linguistic analysis of a morphologically rich and flexible word ordered language. After trained a simple Brill tagger on a manually tagged corpus consists of around 25,000 words, overall accuracy has been achieved 70.6% which is comparable to minimal standard set by different experimental results using any simple supervised learning method on Bangla text.
Minimal cut-set methodology for artificial intelligence applications

This paper suggests that given the considerable (and growing) literature of expert systems for diagnostics and maintenance, consideration of the theory of minimal cut sets should be most beneficial. The minimal cut-set approach uses disjunctive normal form in Boolean algebra and various Boolean operators to simplify very complicated tree structures composed of AND/OR gates. The simplification reduces the tree to an equivalent diagram displaying the smallest combinations of independent component failures which could result in the fault symbolized by the root of the tree and called the top event. This paper reviews minimal cut-set theory and illustrates its application with an example. Using this approach, expert diagnostic systems would have a tool in which, with minimum search, the description of fault causes is made clear and explicit, contributor sequences to a top event fault are easily quantified and ranked, and the probability of the top event is easily computed. Finally, the application of minimal cut sets to planning and problem solving is developed.
Information fusion and tracking of maneuvering targets with artificial neural network

A novel algorithm for tracking manoeuvring targets is presented in this paper. This algorithm is implemented with a pair of parallel adaptive filters by the information fusion technique together with the current statistical model (CSM) and backpropagation (BP) neural network. In order to adapt to different cases of movement, BP network fuses all state information of both filters and adjusts the system variance for one of the filters according to the trained sample set. Computer simulation results show that this algorithm can successfully tracks manoeuvring targets over a wide range of conditions, and has a higher tracking precision. <<ETX>>
Adaptive Transmission for OFDM

To respond to dynamic channel conditions caused by fading, shadowing, and other time-varying disturbances, orthogonal frequency division multiplexing (OFDM) packet radio systems should adapt transmission parameters on a packet-by-packet basis to maintain or improve performance over the channel. For this to be possible, there are three key ideas that must be addressed: first, how to determine the subchannel conditions; second, which transmission parameters should be adapted; and third, how to adapt those parameters intelligently. In this thesis, we propose a procedure for determining relative subchannel quality without using any traditional channel measurements. Instead, statistics derived solely from subcarrier error counts allow subchannels to be ranked by order of estimated quality; this order can be exploited for adapting transmission parameters. We investigate adaptive subcarrier power allocation, adaptive subcarrier modulation that allows different subcarriers in the same packet to use different modulation formats, and adaptive coding techniques for OFDM in fading channels. Analysis and systems simulation assess the accuracy of the subcarrier ordering as well as the throughput achieved by the proposed adaptive transmission protocol, showing good performance across a wide range of channel conditions.
Lightweight support for fine-grained persistence of stock hardware

Persistent programming languages combine the features of database systems and programming languages to allow the seamless manipulation of both short- and long-term data, thus relieving programmers of the burden of distinguishing between data that is transient (temporarily allocated in main memory) or persistent (residing permanently on disk). Secondary storage concerns, including the representation and management of persistent data, are directly handled by the programming language implementation, rather than the programmer. Moreover, unlike traditional database systems, persistent programming languages extend to persistent data all the data structuring features supported by the language, not just those imposed by the underlying database system. Prototype persistent languages have until now focused more on functionality than performance. In contrast, this dissertation addresses performance issues in the language implementation. It presents an architecture and framework for persistence which allows programming language implementation techniques to be brought to bear on the problem of performance. Building on this framework, a prototype persistent programming language is implemented, and submitted to performance evaluation to obtain direct comparisons of the performance of several implementation alternatives for different aspects of persistence. The results of these performance evaluations, which use established benchmarks, indicate that persistence can be implemented on general-purpose machines without imposing significant overhead above and beyond the fundamental costs of data transfer to and from secondary storage. Moreover, the results show that software-mediated implementation techniques can be a competitive alternative to techniques that rely on low-level support from the operating system and hardware.
The Old English copula weorðan and its replacement in Middle English

With the aid of a specially compiled corpus, this paper accounts for the replacement – mainly by become – of weorðan ‘become’, whose use rapidly decreased in Middle English. Drawing on Goldbergian construction grammar, the paper posits the existence of a lexeme-independent network of copular constructions [Copula + np/ap/…]. Copular uses of weorðan are associated with this network, but also form part of a second network exclusive to weorðan , which, already in Old English, served as a model for the extension of becuman to copular uses. In early Middle English, weorðan reacted to changes in the lexeme-independent copular network. Weorðan was no longer used with adjectival participles when these were constructionally separated from its most frequent collocates, namely human propensity adjectives. Furthermore, reacting to an influx of various adjectives in predicate position, becuman , which had no collocational preferences, extended its use to these adjectives and eventually took over from weorðan completely.
Optimization of low-frequency properties of eight-to-fourteen modulation

A description is given of the eight to fourteen modulation system (EFM) designed for the Compact Disc Digital Audio System with optical read-out. EFM combines high information density and immunity to tolerances in the light path with low power at the low-frequency end of the modulation bit stream spectrum. In this modulation scheme, blocks of eight data input bits are transformed into fourteen channel bits, which follow certain minimum and maximum run-length constraints by using a code book. To prevent violation of the minimum and maximum run-length constraints a certain number of merging bits are needed to concatenate the blocks. There are cases where the merging bits are not uniquely determined by the concatenation rules. This freedom of choice thus created is used for minimizing the power of the modulated bit sequence at low frequencies. The paper presents the results of algorithms that were used to minimize this low frequency content.
The Language of Design: Theory and Computation

The Language of Design: Theory and Computation articulates the theory that there is a language of design. This theory claims that any language of design consists of a set of symbols, a set of relations between the symbols, features that key the expressiveness of symbols, and a set of reality producing information processing behaviors acting on the language. Drawing upon insights from computational language processing, the language of design is modeled computationally through latent semantic analysis (LSA), lexical chain analysis (LCA), and sentiment analysis (SA). The statistical co-occurrence of semantics (LSA), semantic relations (LCA), and semantic modifiers (SA) in design text are used to illustrate how the reality producing effect of language is itself an enactment of design. This insight leads to a new understanding of the connections between creative behaviors such as design and their linguistic properties. The computation of the language of design makes it possible to make direct measurements of creative behaviors which are distributed across social spaces and mediated through language. The book demonstrates how machine understanding of design texts based on computation over the language of design yields practical applications for design management such as modeling teamwork, characterizing the formation of a design concept, and understanding design rationale. The Language of Design: Theory and Computation is a unique text for postgraduates and researchers studying design theory and management, and allied disciplines such as artificial intelligence, organizational behavior, and human factors and ergonomics.