Miracle-dz/UniFAR-FTUs huggingface dataset:
Space and iconicity in German sign language (DGS)

This dissertation investigates the expression of spatial relationships in German Sign Language (Deutsche Gebardensprache, DGS). The analysis focuses on linguistic expression in the spatial domain in two types of discourse: static scene description (location) and event narratives (location and motion). Its primary theoretical objectives are to characterize the structure of locative descriptions in DGS; to explain the use of frames of reference and perspective in the expression of location and motion; to clarify the interrelationship between the systems of frames of reference, signing perspective, and classifier predicates; and to characterize the interplay between iconicity principles, on the one hand, and grammatical and discourse constraints, on the other hand, in the use of these spatial devices. In more general terms, the dissertation provides a usage-based account of iconic mapping in the visual-spatial modality. The use of space in sign language expression is widely assumed to be guided by iconic principles, which are furthermore assumed to hold in the same way across sign languages. Thus, there has been little expectation of variation between sign languages in the spatial domain in the use of spatial devices. Consequently, perhaps, there has been little systematic investigation of linguistic expression in the spatial domain in individual sign languages, and less investigation of spatial language in extended signed discourse. This dissertation provides an investigation of spatial expressions in DGS by investigating the impact of different constraints on iconicity in sign language structure. The analyses have important implications for our understanding of the role of iconicity in the visual-spatial modality, the possible language-specific variation within the spatial domain in the visual-spatial modality, the structure of spatial language in both natural language modalities, and the relationship between spatial language and cognition
Effects of Writing for Digital Storytelling on Writing Self-Efficacy and Flow in Virtual Worlds

A significant amount of research examines using video editing software such as Windows Movie Maker to create video clips. However, in this study, the researcher suggests performing digital storytelling in virtual worlds, and places more stress on the writing process. The purpose of this study is to examine the effects of writing for digital storytelling on writing self-efficacy and on flow in the virtual world of Second Life. The researcher organized an activity for undergraduate students creating digital stories. Participants were divided into two groups. One group created their digital stories in Second Life. The other group created their digital stories off-line. The two groups’ independent samples t-tests were employed to compare writing self-efficacy and flow. The results of the experiment demonstrate that digital storytelling in virtual worlds is more effective than digital storytelling off-line. The findings of this study suggest that the technique of digital storytelling can be used effectively in classroom settings as a way of teaching writing.
A DESCRIPTIVE ANALYSIS OF USING THE SOFTWARE Tell Me More IN THE TEACHING OF ENGLISH AT SMP NEGERI 1 DEPOK IN THE ACADEMIC YEAR OF 2009/2010

This research is aimed at describing the software and describing the use of the software Tell Me More in the teaching of English for Junior High School students in the academic year of 2009/2010. This research is descriptive qualitative research. The respondents of this research were the teachers and the students. The steps used in conducting this study were contents analysis, conducting an observation, distributing a questionnaire, doing an in-depth interview and taking some pictures to collect the data. The research instruments in this research were an observation sheet, an interview guide, and a questionnaire sheet. The data collected were forms of field notes, interview transcripts, score and documents. The qualitative data were analyzed qualitatively, while quantitative data were analyzed quantitatively. To ensure the validity of the data, the triangulation technique was used. Based on the data analysis, the software Tell Me More is software that covers the material of listening, speaking, reading, and writing. The materials are appropriate with SK and KD of SMP in the second semester. The research findings show the following characteristics of the software Tell Me More: (1) The materials of the software are appropriate with the SK and KD and has different levels (2) The materials of software consist of the four skills material (listening, writing, speaking, and reading) (3) The benefits of using the software are students are able to improve their understanding, ideas, feeling, attitude, sell-confidence, and they can improve their speaking ability by using the software (4) The discussion technique is the most dominant technique in supporting the use of software Tell Me More. In conclusion, this software can be used by the students as supplementary materials which are appropriate with the SK and KD.
PENGEMBANGAN MODUL IPA TERPADU BERMUATAN MIND MAPPING PADA TEMA CAHAYA DAN PENGLIHATAN UNTUK KELAS VIII SMP/MTs

Munculnya Permendiknas No. 22 tahun 2006 yang menyatakan bahwa substansi mata pelajaran IPA pada SMP/MTs merupakan IPA Terpadu perlu dukungan dengan adanya bahan ajar terpadu. Telah dilakukan pengembangan modul IPA Terpadu bermuatan mind mapping pada tema cahaya dan penglihatan. Tujuan penelitian ini adalah untuk mengembangkan modul IPA Terpadu dan mengetahui kelayakannya sebagai bahan ajar.Penelitian ini menggunakan metode Research and Development dengan 2 tahap uji coba, yaitu uji keterbacaan modul dan uji coba pemakaian modul. Uji keterbacaan modul dilakukan oleh 8 siswa kelas IX dan 3 orang guru IPA, sedangkan uji coba pemakaian modul dilakukan di kelas VIII F. Hasil kelayakan modul diperoleh dari validasi ahli mencapai >80%, hasil tanggapan guru sebesar 93,34%, hasil uji keterbacaan modul mencapai skor 92,5%, hasil tanggapan siswa sebesar 93,6% pada uji coba pemakaian modul, serta hasil belajar siswa dengan ketuntasan klasikal sebesar 94,4%. Berdasarkan hasil penelitian di atas, dapat disimpulkan bahwa modul IPA Terpadu bermuatan mind mapping pada tema cahaya dan penglihatan telah memenuhi syarat kelayakan bahan ajar. Disarankan untuk mengembangkan modul mind mapping pada materi yang berbeda dengankegiatan belajar yang lebih menyenangkan. Permendiknas No . 22of 2006 states that thesubstance ofteaching integrated science for Junior High School needs asupportof providing an integrated teaching materials . Based on that background the development of integrated science modul with mind mapping approach has been done. The research objective is to develop an Integrated Science modul and determineits feasibilityas a teaching material . This research used the Research and Development design with 2 phases . They are readability test and application test . Readability test was carried outfor 8 students of IX grade and 3 science teachers, while theapplication wascarried outfor students of VIIIF.Feasibility result sobtained from expert validation modul reached >80%, the results ofthe teachers responsewas93.34%, the results of student responses were 92.5% while in readability testand93.6% in application test. The students also achieved classical completeness of 94.4 %. Based on the results aboveit can be concludedthat the Integrated Science modul withmind mapping approach “lightandvision”, theme is eligible to be used as teaching material. It can be recommended to develop a mind mapping modul in a different material with more interesting activity .
An Initial Registration Method of Point Clouds Based on Random Sampling

As the first step in 3D point cloud process, registration plays an critical role in determining the quality of subsequent results. In this paper, an initial registration algorithm of point clouds based on random sampling is proposed. In the proposed algorithm, the base points set is first extracted randomly in the target point cloud, next an optimal corresponding points set is got from the source point cloud, then a transform matrix is estimated based on the two sets with least square methods, finally the matrix is applied on the source point cloud. Experimental results show that this algorithm has ideal precision as well as good robustness.
Software Reuse and Reusability Metrics and Models

As organizations implement systematic software reuse programs to improve productivity and quality, they must be able to measure their progress and identify the most effective reuse strategies. This is done with reuse metrics and models. In this paper, we survey metrics and models of software reuse and reusability, and provide a classification structure that will help users select them. Six types of metrics and models are reviewed: cost-benefit models, maturity assessment models, amount of reuse metrics, failure modes models, reusability assessment models, and reuse library metrics.
An Introduction to Models

We survey the origins, development, and applications of models and modeling and discuss their dramatic usefulness and possible dangers. We go on to present a nontechnical introduction to some basic abstract models used in mathematics, statistics, and systems engineering. We strongly emphasize the difference between models and things modeled and touch on the role of modeling in play, art, operations analysis, and modern physics.
Digital Pictures: Representation, Compression and Standards

From the Publisher: Since the first edition of Digital Pictures in 1988, several international standards have been established for digitization of bilevel images, color pictures, videoconferencing, and television. In Digital Pictures, Second Edition, Arun N. Netravali and Barry G. Haskell address these modern innovations and review recently established international standards for digital imagery. They discuss the current state of the art, including JBIG, JPEG, H.261, CCIR601, CCIR723, MPEG1, MPEG2, and HDTV technology. Their book also thoroughly covers the fundamentals and practical algorithms of image digitization and compression. The text's new chapters feature examples and questions designed to stimulate greater understanding of the topics which describe: basic aspects of the JBIG algorithm and different JPEG operating modes; some methodologies used for video codecs operating at subprimary bit-rates; a generic coding standard that can be used in many digital video implementations; and the main characteristics of HDTV; its current state in Europe, Japan, and the United States; and expected future developments. Digital Pictures, Second Edition, concludes with a review of source encoding limitations and brief descriptions of two approaches to model-based coding of video. Its comprehensive coverage of progress in the field will be valuable for communication systems engineers and researchers working in the areas of image compression, communication, and processing. Advanced undergraduate and graduate students will find it an essential text on image digitization, processing, coding, and compression.
Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy Controller

This paper directed the speed-sensorless vector control of induction motor drive with PI and fuzzy controllers. Natural observer with fourth order state space model is employed to estimate the speed and rotor fluxes of the induction motor. The formation of the natural observer is similar to and as well as its attribute is identical to the induction motor. Load torque adaptation is provided to estimate the torque and rotor speed is estimated from the load torque, rotor fluxes and stator currents. There is no direct feedback in natural observer and also observer gain matrix is absent. Both the induction motor and the observer are characterized by state space model. Simple fuzzy logic controller and conventional PI controllers are used to control the speed of the induction motor in closed loop. MATLAB simulations are made with PI and fuzzy controllers and the performance of fuzzy controller is better than PI controller in view of torque ripples. The simulation results are obtained for various running conditions to exhibit the suitability of this method for sensorless vector control. Experimental results are provided for natual observer based sensorless vector control with conventional PI controller.
Mining and Integrating Reliable Decision Rules for Imbalanced Cancer Gene Expression Data Sets

There have been many skewed cancer gene expression datasets in the post-genomic era. Extraction of differential expression genes or construction of decision rules using these skewed datasets by traditional algorithms will seriously underestimate the performance of the minority class, leading to inaccurate diagnosis in clinical trails. This paper presents a skewed gene selection algorithm that introduces a weighted metric into the gene selection procedure. The extracted genes are paired as decision rules to distinguish both classes, with these decision rules then integrated into an ensemble learning framework by majority voting to recognize test examples; thus avoiding tedious data normalization and classifier construction. The mining and integrating of a few reliable decision rules gave higher or at least comparable classification performance than many traditional class imbalance learning algorithms on four benchmark imbalanced cancer gene expression datasets.
Outerjoins in Uncertain Databases.

We consider the problem of incorporating outerjoins into uncertain databases. We motivate why outerjoins are useful, but tricky, in uncertain databases, arguing that standard possible-worlds semantics may be inappropriate for outerjoins. We explore a variety of alternative semantics through a running example, and we briefly discuss implementation considerations.
Design and Control of the Mobile Micro Robot Alice

This paper describes the design methodology to build an autonomous mobile robot of just few cubic centimeters (2 x 2 x 2 cm). Starting from the expected features, the design path will be shown, going through solution proposition, component search, subsystems interconnections, several versions and ending to the final product. The second part of the paper will be dedicated to the control of such a robot which has implications in the control and software architecture. The overall design cycle results in the last version “Alice 2002” which has up to 10 hours autonomy with rechargeable battery, proximity sensors and remote control possibility. Furthermore many additional hardware modules like a radio or a linear camera can extend the basic capabilities. At the moment about 300 Alices exist and are used in various exhibitions and research programs.
A Systems Model of the City and Experiments in Using it for a Functional and Spatial Analysis of Moscow

This paper examines general principles of the approach to mathematical modelling of the urban system adopted in the authors' work on Moscow. It describes the formal model that has been constructed of spatial interactions between the city's functional subsystems, and indicates the general structure of its data base. It introduces certain quantitative indices of the urban territory that have been formulated for use in solving various town planning problems and describes some of the useful general observations that have already emerged from their application to problems of Moscow and its immediate region.
Machine Learning-Based Parameter Validation

As power system grids continue to grow in order to support an increasing energy demand, the system’s behavior accordingly evolves, continuing to challenge designs for maintaining security. It has become apparent in the past few years that, as much as discovering vulnerabilities in the power network, accurate simulations are very critical. This study explores a classification method for validating simulation models, using disturbance measurements from phasor measurement units (PMU). The technique used employs the Random Forest learning algorithm to find a correlation between specific model parameter changes, and the variations in the dynamic response. Also, the measurements used for building and evaluating the classifiers were characterized using Prony decomposition. The generator model, consisting of an exciter, governor, and its standard parameters have been validated using short circuit faults. Single-error classifiers were first tested, where the accuracies of the classifiers built using positive, negative, and zero sequence measurements were compared. The negative sequence measurements have consistently produced the best classifiers, with majority of the parameter classes attaining F-measure accuracies greater than 90%. A multiple-parameter error technique for validation has also been developed and tested on standard generator parameters. Only a few target parameter classes had good accuracies in the presence of multiple parameter errors, but the results were enough to permit a sequential process of validation, where elimination of a highly detectable error can improve the accuracy of suspect errors dependent on the former’s removal, and continuing the procedure until all corrections are covered.
Approximation algorithms for facility location problems

The facility location problem is one of the most well-studied problems in optimization literature over the last four decades. Given a set of client locations, the problem seeks to find an optimal set of locations to build facilities (warehouses) minimizing the sum of the cost of building the facilities along with the cost of assigning clients (stores) to facilities. The assignment cost is often modeled by a weight times the metric distance. The facility location problem and its variant the k-median problem, which minimizes the assignment cost allowing at most k facilities, have been used in a variety of applications, for example network design, web-caching, and clustering. These problems are NP-hard, and have been studied from perspectives of empirical investigation of different heuristics, average-case analysis, polyhedral characterization and approximate heuristics with worst-case performance guarantees, among others. These problems showcase some of the most interesting techniques in approximation algorithms, including local search, linear programming rounding, and primal-dual algorithms. We study these approaches and propose the first constant factor approximation for the k-median problem. We provide the best known approximation algorithms and the best known lower bounds for these two problems. We extend the techniques to solve different variants, incorporating capacities, fault-tolerance, hierarchical placement, and lower bounds on demand assigned to facilities. We use these variants to provide the first constant factor approximation algorithm for single-sink edge-installation problem. This problem models a distribution network of utility companies and service providers. The problem minimizes the cost of designing a network which routes all the demand to a special sink node, where the cost per unit length of any edge obeys economies of scale and is a concave function of traffic through the edge. Clustering large datasets, such as click streams, web pages, multimedia data, retail transactions, and telecommunication records, necessitate scalable algorithms that revisit data sparingly, and consume small space. We extend the k-median algorithms to the data-stream model, which only allows a single pass over the data with limited space. We use some of these approximation techniques to develop a robust hierarchical agglomerative clustering algorithm.
Alternatives for Projecting MDG Indicators

Although the Millennium Development Goals are global, in the sense that they are to be reached by the whole world, not necessarily by countries individually, in many countries the true commitment to them has led many to ask the question: will my country reach all or some of the MDGs by 2015? Are we on or off track? If off track, how far are we? To answer this question it is mandatory to perform some kind of projecting exercise. We talk of projections, not of forecasts, for there are many variables that can intervene to determine the performance of a country in its pursuit of the goals. Furthermore we have to deal with the fact that we cannot really predict what is going to happen up to 2015, but just make assumptions. However, projections can indeed be so accurate as to resemble forecasts. This is the case when there is plenty of data available, as well as technical expertise in projecting, and time. Unfortunately, this is seldom the case, particularly in developing countries. The common situation faced by those who ask the question on whether the MDGs will be reached by a certain country by 2015 is that of scarcity of data and/or of technical skills. (.)
A smart antenna array for CDMA systems with noncoherent M-ary orthogonal modulation

DS/CDMA cellular systems are plagued with the near-far problem which can result in considerable reduction in capacity. Adaptive antenna arrays are used to increase link capacity, improve coverage and permit less stringent power control. Adaptive beamforming algorithms are crucial to the success of the smart antennas. The existing beamforming methods are found to be far from satisfactory for DS/CDMA in the urban multipath environment where user signals are very dissimilar in strength and perfect power control is hardly possible. This paper proposes a new decision-directed beamforming algorithm for CDMA with noncoherent M-ary orthogonal modulation which performs very well in typical CDMA environments. We introduce a quality measure of a symbol decision and a criterion for picking good weights and rejecting bad weights during the process of adaptation. With incorporating the measure into the least-squares algorithm, we can select weights in a positive manner such that the beamformer is forced to keep track of its optimum weights. The advantages of the proposed algorithm include: (1) an amount of immunity to the near-far effect; (2) the ability of tracking the optimum weight vector in the context of time-variant channels; (3) insensitivity to decision errors; (4) good convergence property; (5) the ability of working in low SNR scenarios; (6) tolerance to timing errors between the antennas; (7) mild synchronization requirement, and (8) computational simplicity. The simulation results are given in this paper to demonstrate the effectiveness of the proposed algorithm.