Miracle-dz/UniFAR-FTUs huggingface dataset:
A graph matching technique for an appearance-based, visual SLAM-approach using Rao-Blackwellized Particle Filters

In continuation of our previous work on visual, appearance-based localization in manually built maps in this paper we present a novel appearance-based, visual SLAM approach. The essential contribution of this work is, an adaptive sensor model which is estimated online and a graph matching scheme to evaluate the likelihood of a given topological map. Both methods enable the combination of an appearance-based, visual localization concept with a Rao-Blackwellized Particle Filter (RBPF) as state estimator to a real-world suitable, online SLAM approach. In our system, each RBPF particle incrementally constructs its own graph-based environment model which is labeled with visual appearance features (extracted from panoramic 360deg snapshots of the environment) and the estimated poses of the places where the snapshots were captured. The essential advantages of this appearance-based SLAM approach are its low memory and computing-time requirements. Therefore, the algorithm is able to perform in real-time. Finally, we present the results of SLAM experiments in two challenging environments that investigate the stability and localization accuracy of this SLAM technique.
Group randomly addressed polling for multicell wireless data networks

An effective multiple access protocol for wireless (mobile) networks such as wireless LANs is under active investigation. Randomly addressed polling (RAP) designed to operate in multicell wireless (data) networks was proposed to satisfy channel utilization, no handoff roaming, transparency to different physical layer transmissions, and other desirable features. Taking system stability and system capacity into consideration, the authors further modify RAP to GRAP (group randomly addressed polling) for wireless LANs and possible other personal/mobile communication networks with multicell coverage. The performance of GRAP has been theoretically analyzed and the numerical results are also presented. GRAP with better performance and stability than RAP while keeping all the desirable features of RAP is clearly one of the best candidates for multicell wireless networks. <<ETX>>
Real-time 3D ultrasound fetal image enhancment techniques using motion-compensated frame rate up-conversion

In this paper, we present a motion compensated frame rate up-conversion method for real-time three-dimensional (3-D) ultrasound fetal image enhancement. The conventional mechanical scan method with one-dimensional (1-D) array converters used for 3-D volume data acquisition has a slow frame rate of multi-planar images. This drawback is not an issue for stationary objects, however in ultrasound images showing a fetus of more than about 25 weeks, we perceive abrupt changes due to fast motions. To compensate for this defect, we propose the frame rate up-conversion method by which new interpolated frames are inserted between two input frames, giving smooth renditions to human eyes. More natural motions can be obtained by frame rate up-conversion. In the proposed algorithm, we employ forward motion estimation (ME), in which motion vectors (MVs) ar estimated using a block matching algorithm (BMA). To smooth MVs over neighboring blocks, vector median filtering is performed. Using these smoothed MVs, interpolated frames are reconstructed by motion compensation (MC). The undesirable blocking artifacts due to blockwise processing are reduced by block boundary filtering using a Gaussian low pass filter (LPF). The proposed method can be used in computer aided diagnosis (CAD), where more natural 3-D ultrasound images are displayed in real-time. Simulation results with several real test sequences show the effectiveness of the proposed algorithm.
Meaningful Use of Animation and Simulation in the Science Classroom

Meaningful Use of Animation and Simulation in the Science Classroom. by Kevin T. Swain Science classes should place a strong emphasis on incorporating educational technologies, such as animations, interactive computer programs and various other technologies into the classroom. The use of animations and computer based simulations throughout instruction increases student understanding and achievement (Rosen, 2009). The use of educational technology in the science classroom, not only helps with student understanding of content, but also positively impacts students’ engagement in lessons and their attitudes towards learning (Shu-Nu, Yau-Yuen & May, 2009). Studies have shown that instruction in a science classroom should incorporate students being actively engaged in the material in order for maximum achievement to occur. Students need to be able to take concepts from the science classroom and apply them to their everyday lives. Through the use of animations and simulations this connection can be bridged more effectively than through traditional instruction. The incorporation of computer animations and models provide enhancement and relevance to science learning. Incorporating more educational technology such as animations and computerbased simulations is of ever increasing importance because federal legislation mandates an emphasis on technology integration in all areas of K-12 education (U.S. Department of Education, 2002). Under this mandate, education leaders at the state and local levels are expected to develop plans to effectively utilize educational technologies, such as simulations in the classroom. Meaningful Use of Animation and Simulation in the Science Classroom 5
Active Participation in Fieldwork Level I: Fieldwork Educator and Student Perceptions

ABSTRACTFieldwork experiences bridge the gap between a student's education and entry-level practice. Academic programs, faculty members, and fieldwork educators are challenged to prepare occupational therapy students for entry-level practice. The Accreditation Council for Occupational Therapy Education (ACOTE) standards advocate for both active participation and guided observation in Level I fieldwork experience (. Students report their most meaningful learning experiences, which include performance of clinical skills and participation in clinical reasoning. However, many students enrolled in the author's entry-level master's program and the other schools within a regional consortium report their Level I fieldwork experience is primarily observation. This article describes the results of a survey administered to fieldwork educators and occupational therapy students eliciting their perceptions of active participation in Level I fieldwork. Results indicate that perceptions of the groups are dissimilar. Reco.
Nearest Neighbor-Based Indonesian G2P Conversion

Grapheme-to-phoneme conversion (G2P), also known as letter-to-sound conversion, is an important module in both speech synthesis and speech recognition. The methods of G2P give varying accuracies for different languages although they are designed to be language independent. This paper discusses a new model based on pseudo nearest neighbor rule (PNNR) for Indonesian G2P. In this model, partial orthogonal binary code for graphemes, contextual weighting, and neighborhood weighting are introduced. Testing to 9,604 unseen words shows that the model parameters are easy to be tuned to reach high accuracy. Testing to 123 sentences containing homographs shows that the model could disambiguate homographs if it uses long graphemic context. Compare to information gain tree, PNNR gives slightly higher phoneme error rate, but it could disambiguate homographs.
Application of functional abstractions to verification of flexible manufacturing systems modelled using Petri nets

A number of Petri net models (generic modules) of typical components of AGV-based FMSs were previously proposed by the authors (1989). In this paper they discuss some aspects of modeling and implementation of the generic modules and their functional abstractions. It is pointed out that the availability of generic modules and their functional abstractions allows for models of complex FMSs to be assembled quickly and then analyzed. The complexity of the verification models is reduced by using functional abstractions of the constituent modules. The modeling effort can primarily concentrate on the model structure and not on its components. Since the generic modules represent only invariant functional properties of the proposed components of AGV-based FMSs, the details of these modules have to be defined by the user. This can be done either by using the stepwise refinement techniques or by suitable generic modules. <<ETX>>
Neuro-fuzzy network control for a mobile robot

A control structure that makes possible the integration of a kinematic controller and a neuro-fuzzy network (NFN) dynamic controller for mobile robots is presented. A combined kinematic/dynamic control law is developed using backstepping and stability is guaranteed by Lyapunov theory. The NFN controller proposed in this work can deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamic in the mobile robot. On-line NFN parameter tuning algorithms do no require off-line learning yet guarantee small tracking errors and bounded control signals are utilized.
An adaptive CMOS matrix-vector multiplier for large scale analog hardware neural network applications

The authors present an analog four-quadrant matrix-vector multiplier of low circuit complexity in floating gate CMOS technology, capable of on-chip weight adaptation following an arbitrary incremental outer-product local learning scheme, and with permanent storage of the weights after learning is performed. The complete adaptive circuit employs, on average, as few as two transistors per matrix element (C.F. Neugenbauer et al., 1990), allowing a very compact VLSI circuit layout (less than 30 mu m*30 mu m per synapse in standard 2 mu m CMOS technology) suitable for the use in fully interconnected neural network hardware of densities above 256 neurons per cm/sup 2/. With proper biasing techniques, an input linearity region for the multiplier ranging 800 mV at modest current levels are demonstrated. Four-quadrant outer-product weight adaptation, performed locally on-chip by floating gate voltage increments under ultraviolet illumination, has been achieved with floating gate adaptation up to 10 mV/s. <<ETX>>
Probabilistic character disambiguation for reduced keyboards using small text samples

Reduced keyboards are text typing keyboards which contain fewer than 26 alphabetic keys, and which may therefore be accessed and used by certain physically disabled persons more easily than a conventional “QWERTY” typing keyboard. Automatic character disambiguation systems enable text to be typed upon a reduced keyboard with a keying efficiency approaching one key/character, despite the fact that each key represents more than one alphabetic character. Existing disambiguation systems typically use probabilistic models of character sequences (n-grams) from representative text samples to predict the next character, and hence disambiguate among the different characters on each key. N-grams for such disambiguation models have been extracted previously from large (1 million word) text corpora. The research reported here shows that a much smaller corpus of limited domain can be used with similar results, thus facilitating development of disambiguation systems by eliminating the need for a large corpus. Four redu.
S-SoDiA: a semantic enabled social diagnosis advisor

Medical information systems have recently gained momentum as a proof-of-concept of the efficiency of new support-oriented technologies, in particular, semantic technologies. In principle, diagnosis or medicine advisory and recommendation can change the current biomedical IT landscape, providing intelligent reasoning and inference support. This paper presents S-SoDiA, a social diagnosis advisor based on semantics, which aims at bridging the gap between state of the art ad-hoc e-health applications and intelligent diagnosis decision support systems.
Towards Adapting NAS Mechanism over Solid State Disks

Flash memory storage such as SSDs (Solid State disks) have been gaining popularity due to its low energy consumption and durability in embedded systems and laptops. With the fast technical improvement, Solid State Disks (SSDs) are becoming an important part of the computer storage hierarchy to significantly improve performance and energy efficiency. However, due to its relatively high price and low capacity, a major system research issue to address is on how to make SSDs play their most effective roles as a high-performance storage system in cost- and performance-effective ways. In this paper, we describe a NAS prototype that eliminates most software overheads and makes Solid State Disks a high-performance storage system in cost- and performance-effective ways. NAS integrates a network adapter into SSDs, so the SSDs remove the random access time, Reduce administrative overhead while delivering scalable, reliable data storage. NAS can also give support block based I/O rather than traditional NAS system which supports only file I/O protocol such as NFS and CIFS. Our scale-out NAS solutions can boost capacity and performance while enabling flexible provisioning, no disruptive operations, easy scalability, and virtualization. As the storage and processing requirements of the file server continued to increase data security and integrity became difficult to
Scoring recognizability of faces for security applications

In security applications the human face plays a fundamental role, however we have to assume non-collaborative subjects. A face can be partially visible or occluded due to common-use accessories such as sunglasses, hats, scarves and so on. Also the posture of the head influence the face recognizability. Given a video sequence in input, the proposed system is able to establish if a face is depicted in a frame, and to determine its degree of recognizability in terms of clearly visible facial features. The system implements features filtering scheme combined with a skin-based face detection to improve its the robustness to false positives and cartoon-like faces. Moreover the system takes into account the recognizability trend over a customizable sliding time window to allow a high level analysis of the subject behaviour. The recognizability criteria can be tuned for each specific application. We evaluate our system both in qualitative and quantitative terms, using a data set of manually annotated videos. Experimental results confirm the effectiveness of the proposed system.
Detecting specialised neologisms in researchers’ blogs

The present paper explores whether researchers' blogs may be useful as corpora to detect specialised neologisms in economic-administrative domains, such as Finance, Management or Macroeconomics. Three different blogs have been selected as corpora ( Crisis, restructuring and growth, Center for service innovation and Focus , respectively), all representing cross-disciplinary research projects within the economic-administrative domains at the Norwegian School of Economics. In the study I focus on specialised neologisms, i.e., expressions or terms which are used to describe concepts relevant within the cross-disciplinary research projects. This includes expressions originating from English which are now either used as English loan words (anglicisms) in Norwegian (‘self-serving biases'), as calques, such as ‘spill-over-effekter' (‘spill-over effects') or ‘multikanalsetting' (‘multi-channel setting'), or as Norwegian "substitute words" like ‘samskaping' (‘co-creation') (Sandoy 1997). The analysis builds on a study which explores methods for detecting specialised neologisms in the Norwegian Newspaper Corpus (NNC; http://avis.uib.no/), with particular focus on financial jargon (Kristiansen 2012a). A motivation behind the study is to contribute to lexicographical and terminological work with focus on maintaining and developing Norwegian special language of economic-administrative domains. Furthermore, it aims at providing a basis for discussion among researchers about which expressions should be used to denote the various topics and concepts in question. This will in turn be important input to those involved in popularising the research and to lecturers in the relevant domains. The methodology is based on the NNC and in particular its neology extractor which detects and produces lists of word forms of newly harvested texts not previously recorded in the NNC (i.e. some 5 million word forms) (Andersen and Hofland 2012). The corpora have been established by Knut Hofland at the Computational Language Unit at Uni Computing. Keywords: scientific blog, neologism, economic terminology
Towards a cognitive theory of expression: The performance and perception of rubato

Expression is examined from the viewpoint of communication theory and it is argued that a proper understanding of expression involves an integrated description of both performance and perception. A framework is developed in which to couch a general theory of expression. As an example, a number of algorithms, implemented in Lisp are described which model the performance and perception of rubato. The model is based on two factors: 1) the use of “phrase final lengthening” to signal a group boundary and 2) the ability of the listener to track a variable tempo. The study shows that rubato is a rich source of information for the listener and that any realistic music parser must take this into account. On the other hand any performance model must take into account the constraints of perception.
The impact of the language of instruction: How economics students in the Netherlands evaluate an English-taught Undergraduate Programme

In this article student ratings of undergraduate level Economics courses are analysed on the basis of the aggregated results of end-of-term questionnaires. Two groups of students were involved, one of which was taught in Dutch and the other in English. In the analysis the influence was investigated of studentsâ€™ assessments of both their own and their lecturersâ€™ language proficiency, and of the didactic skills of the lecturers. Various differences between the judgements of the two groups were found; moreover, in course of time, some of the judgements evolved. The multivariate analysis shows that as studentsâ€™ judgements of the didactic skills of their lecturers rose, so did the course ratings in general. Surprisingly, the judgements of neither the studentsâ€™ own linguistic proficieny, nor that of the lecturers proved to be significant.
An evolution computation approach to hybrid dynamic system optimal control problems

This paper deals with optimal control problems of hybrid dynamic systems. Since the solution of such complex problems has comprehensive applications in practice, a generic approach based on genetic algorithms is proposed in this paper to effectively handle the continuous-time and discrete-event dynamics with multiple optimization objectives. A multitank blending system control problem is presented as a case study to show the implementation of the proposed method. The results demonstrate that this approach has the theoretical significance, and the promising prospects due to the comprehensive applications in practice.
Celebrating 70: An Interview with Don Berry

Donald (Don) Arthur Berry, born May 26, 1940 in Southbridge, Massachusetts, earned his A.B. degree in mathematics from Dartmouth College and his M.A. and Ph.D. in statistics from Yale University. He served first on the faculty at the University of Minnesota and subsequently held endowed chair positions at Duke University and The University of Texas M.D. Anderson Center. At the time of the interview he served as Head of the Division of Quantitative Sciences, and Chairman and Professor of the Department of Biostatistics at UT M.D. Anderson Center.
Reusable learning objects

Does your institution or medical school have online learning resources? If you are lucky then you may have access to a wealth of online learning modules or objects, but if you're in a poor institution then you probably wont. But no matter how big your institution, it's a fair guess that its online learning resources will have at least some gaps. How should you fill them? One possibility would be for all medical schools everywhere to share their online learning resources. This is the idea of Ron Harden, and he and his …
A Study on the CBR Pattern using Similarity and the Euclidean Calculation Pattern

CBR (Case-Based Reasoning) is a technique to infer the relationships between existing data and case data, and the method to calculate similarity and Euclidean distance is mostly frequently being used. However, since those methods compare all the existing and case data, it also has a demerit that it takes much time for data search and filtering. Therefore, to solve this problem, various researches have been conducted. This paper suggests the method of SE(Speed Euclidean-distance) calculation that utilizes the patterns discovered in the existing process of computing similarity and Euclidean distance. Because SE calculation applies the patterns and weight found during inputting new cases and enables fast data extraction and short operation time, it can enhance computing speed for temporal or spatial restrictions and eliminate unnecessary computing operation. Through this experiment, it has been found that the proposed method improves performance in various computer environments or processing rate more efficiently than the existing method that extracts data using similarity or Euclidean method does.
The Identification of EEG Feature Evoked by Imaginary Movement

Aiming to the ERD/ERS phenomenon of left-right hand imaginary movement, this paper presents a method of wavelet transform combined with statistical analysis to extract EEG features evoked by imaginary movement. And the features were classified using the support vector machine based on RBF kernel and cross-validation accuracy (CVA) method. The results have shown that this method can perform effectively to extract features and reflect ERS and ERD characteristics of EEG signal. The accuracy of classification can reach 90% within the time costing 3.5 seconds. The highest signal to noise ratio is 1.445, and the maximum mutual information is 0.645bit. The results can meet the real-time brain-computer interface system.
The Rough Set Theory applied to a set of the new severity indices

In this paper it is presented a study were the Rough Set Theory is applied to evaluated a set of the new severity index. The developed methodology produces a classification of the system operation in four possible states: normal, alert, emergency (emergency I and emergency II). The states can be classified as secure, that correspond to the normal state and insecure for the remaining ones. Severity indices are used to represent the impact of the reliable contingencies in electric power system Security studies. In this study the severity index are used to classify and ranked the contingencies. This methodology was applied to the 118IEEE busbar test power network, and the results obtained are analyzed. Finally, some conclusions that provide a valuable contribution to the understanding of the power system security analysis are pointed out.
Nonholonomic control systems: from steering to stabilization with sinusoids

The authors present a control law for globally asymptotically stabilizing a class of controllable nonlinear systems without drift. The control law combines earlier work in steering nonholonomic systems using sinusoids at integrally related frequencies, with the ideas in recent results on globally stabilizing linear and nonlinear systems through the use of saturation functions. Simulation results for stabilizing a simple kinematic model of an automobile are included. <<ETX>>