Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of relative versus absolute pointing devices

In this study, a relative pointing device was compared with two different absolute pointing devices. Participants used a Wii RemoteTM controller with the Wii MotionPlusTM attachment in three different configurations of motion sensing: Relative (6-axis: 3-axis accelerometer and 3-axis gyroscope), Camera Absolute (camera only), and Stabilized Absolute (camera + 6-axis). Twenty-four participants were given a series of movement tasks based on Fitts’ test to complete at three different distances. In terms of information throughput, pointing accuracy, and user preference, relative pointing was clearly superior to absolute pointing, even when absolute pointing included stabilization.
Plasma-induced polarity dependent hot-carrier response of CMOS devices across a wafer

In this study, plasma-processed devices are subjected to hot-carrier stressing experiments to evaluate the reliability across the wafer. Devices with N/sup +/-P, P/sup +/-N, both N/sup +/-P and P/sup +/-N diodes, and no protection diode, are used to establish the nature of the injection (gate and substrate) conditions across the wafer. Results show that P-channel devices subjected to gate injection during plasma processing show higher degradation than those subjected to substrate injection. N-MOSFETs subjected to gate injection during plasma processing show a higher antenna ratio dependence than those subjected to substrate injection. Also, a linear relationship is observed between the pre-stress trapped positive charge in the oxide and threshold voltage shift after hot-carrier stress. Gate injection during plasma processes creates higher trapped positive charge and hence the hot-carrier lifetime of devices subjected to gate injection can be significantly lower than that of devices subjected to substrate injection.
The authoring metaphor to machine understanding of multimedia

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Improving joint stereo audio coding by adaptive inter-channel prediction

A method for exploiting inter-channel redundancies of stereophonic or multichannel audio signals is presented. In contrast to known stereo redundancy reduction techniques used in joint stereo audio coding. Where only the statistical dependencies between two concurrent samples of the left and right channel signals are considered, the adaptive inter-channel prediction also takes into account possible phase or time delay between the channels and exploits more than only one value of the cross-correlation function. The analysis of subjective listening test results has shown that this technique is especially effective for a class of test sequences which has proven to be most critical for the ISO MPEG Layer II and Layer III codecs at bit rates of 2/spl times/64 kbit/s. For these signals the gain due to the stereo redundancy reduction technique used in Layer III joint stereo coding is less than 5-10 dB, while in Layer II joint stereo coding no specific stereo redundancy reduction technique is used. In a first step, the adaptive inter-channel prediction has been applied to an ISO MPEG Layer II codec. The simulation results show that a prediction gain up to 30-40 dB can be achieved for large parts of the above mentioned signals. <<ETX>>
Production Matching for Large Learning Systems

One of the central results of AI research in the 1970''s was that to achieve good performance, AI systems must have large amounts of knowledge. Machine learning techniques have been developed to automatically acquire knowledge, often in the form of if-then rules (productions). Unfortunately, this often leads to a utility problem --- the "learning" ends up causing an overall slowdown in the system. This is because the more rules a system has, the longer it takes to match them against the current situation in order to determine which ones are applicable. To address this problem, this thesis is aimed at enabling the scaling up of the number of rules in production systems. We examine a diverse set of testbed systems, each of which learns at least 100,000 rules. We show that with the best existing match algorithms, the match cost increases linearly in the number of rules in these systems. This is inadequate for large learning systems, because it leads to a utility problem. We then examine the causes of this linear increase, and develop techniques which eliminate the major causes. The end result is an improved match algorithm, Rete/UL, which is a general extension of the existing state-of-the-art Rete match algorithm. Rete/UL''s performance scales well on a significantly broader class of systems than existing match algorithms. The use of Rete/UL rather than Rete significantly reduces or eliminates the utility problem in all the testbed systems.
Bearing estimation for a distributed source via the conventional beamformer

This paper considers the performance of the conventional beamformer (BF) for estimating the bearing of a single, far-field, narrowband, spatially distributed source with an array of passive sensors. The BF offers significant computational advantage compared to the (asymptotically optimum) maximum likelihood estimators (MLEs) which require searches over some multi-dimensional parameter space. However, the price to be paid for such a reduction in computational complexity is a degradation in performance compared to that of the MLEs. This paper studies the nature of this degradation for "coherently" and "incoherently" distributed sources as a function of key scenario parameters such as signal-to-noise-ratio (SNR), mean angle, spatial spreading of the source, and number of sensors, both mathematically and by simulations.
About the use of fuzzy clustering for texture classification

This paper describes the use of a complex modular image processing system for texture classification. An introduction into problems that arise when handling textures is given. Furthermore the modules of the proposed system are described, namely the filtering and statistical modules, automatic feature vector optimization module and the classification module using clustering and fuzzy clustering methods. This texture classification system can easily be adapted for other tasks, including tasks in the field of medical imaging, remote sensing and quality control.
The Implementation of One Opportunistic Routing in Wireless Networks

In the paper, it proposes an optimization framework addressing fairness issues for opportunity routing in wireless mesh networks, where we use network coding to ease the routing problem. We propose a distributed heuristic algorithm in the case when scheduling is determined by MAC, and discuss the suitability of our algorithm through simulations. It is found that in most situations our algorithm has better performances than the single-path algorithm and the classical network coding which is based opportunity algorithm MORE.
Signal sonar processing

This paper describes the major trends in sonar signal processing and gives some example of advanced algorithms to illustrate the need in computation power: adaptive beamforming for passive sonars, wideband Doppler code for active sonar in coastal/shallow water environment (reverberation limiting conditions) and synthetic aperture processing for minehunting sonars. The performances of these algorithms compared to conventional ones are shown on real data obtained at sea.
Einfluss einer Online Bahnkorrektur auf die Materialeigenschaften von Prepreg Tows im Fiber Placement Prozess

Seitliche Korrekturen von Prepreg Tows wahrend eines Automated Fiber Placement Prozesses konnen zur Einhaltung beziehungsweise Erhohung der geforderten Bauteilqualitat dienen. Die dabei auftretenden Scherkrafte zwischen Werkzeugoberflache, Material und Kompaktierungsrolle beeinflussen das Materialverhalten wahrend des Korrekturprozesses. Dieses Verhalten in Abhangigkeit verschiedener Ablegeparameter wie Anpresskraft, Korrekturwinkel oder Ablegegeschwindigkeit wurde hier untersucht. Mit Hilfe eines Faserkantendetektors konnte die Qualitat des abgelegten Materials bezuglich Position, Geometrie oder Defekte erfasst werden. Die Versuche haben gezeigt, dass eine Variation der Parameter erhebliche Einflusse auf das abgelegte Material haben kann und dass es aufgrund der seitlichen Auslenkungen zu Abweichungen zwischen der real abgelegten Bahn und der Sollbahn kommt. Erst durch die hier ermittelten Erkenntnisse uber das Materialverhalten kann eine online Bahnkorrektur erfolgreich durchgefuhrt werden und die Qualitat des Ablegeprozesses im Vergleich zur aktuellen Fertigungstechnologien gesteigert werden.
Automated EEG feature selection for brain computer interfaces

A brain computer interface (BCI) utilizes signals derived from electroencephalography (EEG) to establish a connection between a person's state of mind and a computer based signal processing system that interprets the EEG signals. The choice of suitable features of the available EEG signals is crucial for good BCI communication. The optimal set of features is strongly dependent on the subjects and on the used experimental paradigm. Based upon EEG data of an existing BCI system, we present a wrapper method for the automated selection of features. The proposed method combines a genetic algorithm (GA) for the selection of feature with a support vector machine (SVM) for their evaluation. Applying this GA-SVM method to data of several subjects and two different experimental paradigms, we show that our approach leads to enhanced or even optimal classification accuracy.
Analysis of complex surveys

Part 1 Aggregated analysis - standard errors and significance tests: introduction, C.J.Skinner domain means, regression and multivariate analysis, C.J.Skinner chi-squared tests for contigency tables, J.N. K.Rao and D.R. Thomas measures of association for contingency tables, E.A. Molina. Part 2 Aggregated analysis - point estimation and bias: introduction, T.M. F.Smith the effect of selection of regression analysis, G.Nathan and T.M. F.Smith multivariate analysis, T.M. F.Smith and D.J.Holmes selection based on the response variable in logistic regression, A.J.Scott and C.J.Wild. Part 3 Disaggregated analysis - modelling structured populations: introduction, D.Holt multilevel and multivariate models in survey analysis, H.Goldstein and R.Silver regression models for stratified multistage cluster samples, D.Pfeefferman and L.LaVange logistic models for contingency tables, D.Holt and P.D. Ewings.
WWW browser and server with guaranteed QoS support over native ATM API

In this paper, we present WWW browser and server that can utilize guaranteed QoS over ATM network using native ATM API. Native ATM API is the API for native ATM services, i.e., ATM-specific services. It can provide native ATM's benefits directly to its applications, without producing such drawbacks as stack overhead and functional limitations which can be found in IP over ATM, LAN emulation over ATM, and Multiprotocol over ATM mechanisms. We explain these advantages, standardization works and development trend of native ATM API. And then we describe our system architecture and environment for Web browsing with guaranteed QoS support, operation procedure of HTTP over ATM API, and the ways to specify QoS and traffic characteristics for our WWW system.
Extreme programming: a university team design experience

The paper discusses an experience in applying the extreme programming approach to the 4 year team design project course. Extreme programming is a methodology for software system development that focuses on high customer integration, extensive testing, code-centered development and documentation, refactoring and paired programming. Typically, the project course is managed using the standard waterfall or V-shaped development models with a faculty advisor acting as a customer for the project. In this project extreme programming has been used instead. Extreme programming is based on a sequence of development practices, including pair programming, very accurate configuration management, strong customer interaction based on "system stories", detailed testing. In this project, paired programmers are used for the duration of a release and then the pairs rotate. The distributed programming environment is handled using the JCVS suite of configuration management tools. Every 3-4 weeks, a new fully functional release is delivered and reviewed by the customer. The specifications for each release are captured incrementally using use case scenarios. Only the essential requirements for the current iteration are implemented. The JUnit test suite is also used to test each of the Java classes on an ongoing basis. The test suite verifies all aspects of the software at each build; this is necessary when refactoring components. Requirements capture, design and implementation of the deliverables are performed incrementally and result in quicker development times and reduced defects. Refactoring is applied wherever possible to simplify the code. Documentation is applied using the standard JavaDoc utility and is kept to a minimum. Finally, customer feedback is immediately incorporated into future iterations of the design process.
Hybrid Neuro-fuzzy Legendre-based Adaptive Control Algorithm for Static Synchronous Series Compensator

Abstract This article presents a novel adaptive non-linear control scheme for a static synchronous series compensator to improve power system stability. The proposed control system synergistically integrates the Legendre polynomial functional neural network, a member of the orthogonal polynomials family, with adaptive neuro-fuzzy Takagi–Sugeno control. The control scheme exploits the online, model-free direct control structure, which reduces the computational complexity, latency, and memory requirements, to make the proposed control strategy highly suitable for real-time implementation. The performance of the proposed control system is validated against different contingencies and operating conditions using non-linear time-domain simulations and different performance indices. The performance of the proposed control system is compared with the adaptive neuro-fuzzy Takagi–Sugeno. The results reveal that the proposed control scheme effectively damps the local and inter-area mode of oscillations.
Ablation de matériaux carbonés sous très haut flux : étude multiphysique de l'interaction matériau/écoulement

La necessite de proteger les vehicules de rentree atmospherique a conduit a la selection des materiaux carbones pour les applications les plus extremes [1, 2]. Au vu du cout prohibitif des essais en conditions reelles [1], la simulation permet de predire et comprendre le comportement du materiau lors de la rentree atmospherique. Les modeles de l’ablation du carbone n’ont cesse de se complexifier [1, 3, 4, 5, 6]. Cependant, ils ne donnent pas de descriptions fines de la surface du materiau. C’est pour remedier a cela que plusieurs etudes ont ete lancees au Laboratoire des Composites Thermostructuraux (LCTS) [7, 8]. Le Plasmatron du VKI est le moyen a haut flux de chaleur et a haute vitesse utilise pour cette these [9, 10]. Dans cette etude, des echantillons sont testes sous des flux de chaleur allant jusqu’a 2800 kW/m2. Ces essais sur le composite 3D carbone/carbone (Cf/C) ont mene a des resultats tres interessants sur la morphologie du composite lors de l’ablation. Le four a image d’arc est le moyen a tres haut flux de chaleur et a convection nulle utilise au cours de cette these. Des flux de chaleurs de 10 MW m-2 ont pu etre appliques a des echantillons de 3D Cf/C. Les observations MEB couplees a la reconstruction numerique du four ont permis de noter les differences entre l’oxydation et la sublimation du composite. Un code de diffusion/ablation est developpe depuis plusieurs annees au LCTS [7, 11, 12, 13, 14] : AMA. Il permet de simuler l’ablation d’un materiau en carbone. Ce code a ete valide par J. Lachaud sans prise en compte de l’ecoulement [7]. Un nouveau couplage avec le code Open-Foam [15] a ete developpe et valide. Le code AMA a ete utilise afin de determiner les parametres influencant la rugosite du 3D Cf/C sous un ecoulement laminaire.
Demo: WARP drive - accelerating wireless multi-hop cross-layer experimentation on SDRs

Rapid prototyping of cross-layer multi-hop schemes in wireless networks often poses a hard challenge. While SDRs allow to implement virtually any cross-layer technique, the underlying programming models for rapid prototyping are inherently designed for one-hop communication. Moreover, existing solutions are typically non-real-time and fall back to offline processing. While this is well-suited for evaluating techniques at the physical layer, the media access control and network layers demand interactivity. Further, network size becomes a critical parameter in multi-hop settings but the size of SDR testbeds is often limited, requiring costly reimplementations in a network simulator to investigate larger settings. We develop a framework to overcome these limitations and enable rapid prototyping of cross-layer multi-hop mechanisms on SDRs. We build on (1) a modular software design to allow for mechanism exchange, (2) a virtual timeline to abstract from the non-real-time nature of transmissions, and (3) a seamless switch from practical experiments to simulations using the same code. We provide a reference implementation of our framework to the community as a starting point for rapid prototyping of cross-layer multi-hop mechanisms.
Subjective interpretation of emotional behavior through physical interaction between human and robot

Recent advances in robotics have been applied to automation in industrial manufacturing with the primary purpose of optimizing practical systems in terms of such objective measures as accuracy, speed, and cost. This paper introduces research on artificial emotional creatures that seeks to explore a different direction that is not so rigidly dependent on such objective measures. The goal of this research is to explore a new area in robotics, with an emphasis on human-robot interaction. There is a large body of evidence that shows the importance of the interaction between humans and animals such as pets. We have been building pet robots, as artificial emotional creatures, with the subjective appearance of behaviors that are dependent on internal states as well as external stimuli from both the physical environment and human beings. The pet robots have a multi-modal sensory system, actuators, and bodies with artificial skin for physical interaction with human beings. The pet robots will be applied to heal people as "mental commit robots".
Computing Information by Equation Solving

way or computing meaning representations or information structures conveyed by the use of natural language. In a formal semantics like Montague's(1974), a type-theoretic A -calculus with /3-reduction is often used to handle with substitutions. But I argue in this paper that the substitution for equation solving is less constrained that the substitution by 13-reduction and that the former can treat the phenomena of free word-order and partial information in natural language more conveniently that the latter. To support my argument, I will analyze some fagments of Korean and English, particulary those involving scrambling in Korea, and quantification and NP-conjunction in English.
Optimization of induction motor design by using the finite element method

Optimization of the induction motor design can be considered from different view points. However, the nonlinear nature of this kind of motor does not allow the implementation of the classic analytical methods unless several simplified approximations on the magnetic characteristics and also the geometry of the motor are applied. In this work, a combination of finite element method and an iteration method, based on conjugate directions is used and an algorithm for the optimization of the IM design is proposed. The method is applied on a previously designed 3 kW induction motor and the results are compared against the manufacturer's data.
Load Balancing Congestion Control Scheme to Improve the Capability of AOMDV Protocol in MANET

In Mobile Ad hoc Network (MANET) every node is mobile and autonomous. Since there is no infrastructure in such a network, a highly adaptive routing scheme to deal with the frequent topology changes is required. Include large numbers of nodes by that routing packets required a large percentage of the limited wireless bandwidth and this is overstated and exacerbate by the mobility feature often resulting in a lot of data failure regarding wireless links. Due to the limited bandwidth, congestion is the major problem in MANET. The AOMDV maintains the alternate routings possibilities so that these paths can be utilize when the primary path fails. AOMDV protocol can decrease the overall performance when the predefined alternative path no longer satisfies the routing requirement due to the frequent topology changing. In this paper we propose a congestion control load balancing scheme with multipath AOMDV protocol to reduce the problem of congestion. In this scheme the rate of sender is controlled through Acknowledgement (ACK) scheme but some time the sender is taken to control then in that case the packets are stored in the memory(queue) of nodes and also that memory management scheme is assigned. This scheme is used to handle the packets beyond the capacity, so that the packet dropping is minimized. The original AOMDV is not capable only to balance the load in network efficiently. The simulation results of proposed scheme significantly increase the packet delivery ratio and decrease the average delay, the performance is better than other protocols.
A study of data compression using neural networks and principal component analysis (of pulmonary scintigrams)

PCA analysis is similar to neural networks in data compression of segments that have been 'seen', but is superior in compressing 'unseen' images. The difference between 'seen' and 'unseen' images with respect to tsse (total sum square error) is more pronounced in 32 by 16 pixel segments than 8 by 8 segments in PCA compression. This suggests that the dimensional reduction is more consistent in the smaller segments. However the tsse is lower for 'seen' segments in the larger segment PCs. Artificial neural networks also seem to generalise less readily on larger segments. Since the time taken for neural network compression is about an order of magnitude higher than PCA, and PCA is more repeatable in terms of the error magnitude, and produces lower error for 'unseen' segments, it would seem preferable to use PCA analysis than neural network methods to produce the reduced dimensional input to a diagnostic network.