Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hidden Markov Model based transitional description of camera networks

Abstract We consider the problem of building a transitional model of an initially uncalibrated camera network. More specifically, we discuss a Hidden Markov Model (HMM) based strategy in which the model's state-space is defined in terms of a partition of the physical network coverage. Transitions between any two such states are described by the distribution of the underlying Markov Process. Extending previous work in (Cenedese et al., 2010), we show how it is possible to infer the model structure and parameters from coordinate free observations and we introduce a novel performance index for model validation. We moreover show the predictive power of this HMM approach in simulated and real settings that comprise Pan-Tilt-Zoom (PTZ) cameras.
An enhanced detection of the evoked potential signal using a hybrid QMF algorithm

The authors introduce an efficient technique to detect the evoked potential, EP, transients. A hybrid algorithm using Daubechies (1990, 1994) as the father and Coiflet as the mother wavelet is employed on both a single and four-averaged EP sweeps. A 60% reduction in the number of sweeps with a high quality performance has been achieved when compared to traditional techniques.
Geometric Aspects of Interconnection and Damping Assignment - Passivity-Based Control

This dissertation deals with smooth feedback stabilization of control-affine systems via Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC). The IDA-PBC methodology is a feedback control design technique that aims to establish or manipulate a port-Hamiltonian structure of the closed-loop system. For a mechanical control system, a port-Hamiltonian system is a natural description of the dynamics, and several effective controller designs have been presented for this class of systems. In other fields of engineering, the development of such controller design is an active area of research. In particular, applications of IDA-PBC techniques prove to be difficult in practice for process control applications where the concept of energy is usually ill-defined. This thesis seeks to extend the application of the IDA-PBC methodology beyond mechanical control systems. This is achieved by following three directions of research. First, we establish conditions under which a port-Hamiltonian system can be written as a feedback interconnection of two port-Hamiltonian system. We identify such an interconnection structure for linear control systems based on their intrinsic properties. Second, as observed in application of IDA-PBC to nonmechanical systems, several additional assumptions on the structure of the desired port-Hamiltonian system can effectively reduce the complexity of the matching problem. We establish a unified approach that considers these additional assumptions. ii Third, we connect the matching problem to the classical feedback equivalence approach. We show that feedback equivalence between control-affine systems can be employed to construct some feasible interconnection and damping structures.
Image Coding Using Pseudorandom Shift Register Sequences

The coding of digital images using linear feedback shift register (LFSR) sequences is considered analytically and in computer simulations. It is shown that LFSR sequences can provide efficient representations of binary and multilevel images in terms of a relatively small set of integers related (in limiting cases) to image complexity and randomness.
Network design for time‐constrained delivery

To meet customer demand, delivery companies are offering an increasing number of time‐definite services. In this article, we examine the strategic design of delivery networks which can efficiently provide these services. Because of the high cost of direct connections, we focus on tree‐structured networks. As it may not be possible to identify a tree‐structured network that satisfies all of the delivery guarantees, we allow these guarantees to be violated but seek to minimize the sum of the violations. We establish the complexity of the problem and exploit an empirically identified solution structure to create new neighborhoods which improve solution values over more general neighborhood structures. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008
TRAINING ALGORITHM OF UNIFORM PARZEN WINDOW NEURAL NETWORKS

In this article, we propose a uniform Parzen window neural network, and introduce the configuration of the neural network, methods for decision boundary determination, and forward training algorithms. For the neural network, we adopt the uniform distributed Parzen window density function to construct the nodes of the hidden layer, and the union function for the output nodes. We also design a pattern generator algorithm to create artificial pattern data, which can be used for simulation, performance evaluation, and neural network optimization.
An Evaluation of Consumer Privacy Protection in E-Commerce Websites: A Comparative Study of Six E-Stores: Part II

Abstract. E-visitors visiting E-Stores are generally at the mercy of E-merchants when it comes to the private data they have to make available. Web vendors are capable of have secondary uses for their information, viz. data mining or spam lists. The consumer's relative privacy protection of six major Web stores based in Europe and North America is reviewed and reviewed by means of the framework proposed. A descriptive type of research design was used. A categorization of consumer privacy protection mechanisms was discussed about four areas: fair information practices, buyer flexibility, technology, and external regulation. An online questionnaire for the evaluation of consumer privacy in E-Commerce was hosted on http://www.surveymonkey. com The highest score in our E-Store appraisal, 73.16%, corresponded to ebookers, a Swiss Web store, while the least one, 60.53%, belonged to Amazon, an American E-retailer. Amazon could barely contest 88.46% of the points attained by its next contender, Chapters, a Canadian retail company. The left over four E-vendors were reasonably close to each other, with an average of 70.66% amid them. As limitations of the sample privacy evaluation, the consequent concerns were acknowledged: Some features could not be appropriately established. Most of the information employed for the investigation initiated from what the E-merchants said about themselves on their E-Stores. Web sites were predominantly appraised with a black box approach. In this article, some factors that proficiently provide privacy protection were examined and a relative analysis of six major E-Stores was carried out vis-à-vis e-consumer privacy protection in E-Commerce websites. This paper provides a positive overview of a scenario of consumer privacy protection in case of E-Commerce websites by carrying out relative assessment of six major E-Stores and transforming “digital challenges” like risk in E-Commerce into “digital opportunities. ”
Network error correction

This paper discusses the error correction in all existing communication networks which is done on a link-by-link approach. We define a network coding and a distributed error correction in a network is considered when a source message is transmitted to a set of receiving nodes on a network. Network generalizations of the Hamming bound and Gilbert-Varshamov bound are obtained.
Passive microwave remote sensing for estimation of rice water content in Vietnam

Rice is one of the world's major staple foods that accounts for 15% of the world's total cultivated area. In Asia where 94% of the world's rice is produced, rice is the main source of food and a significant source of income. In Vietnam, rice cultivated area occupies 47% of agricultural land of the country. Rice growing conditions are essential for crop monitoring and yield prediction while rice water content decides the evolutional process and yield per year of the crop. A model for passive microwave emission from water-rice fields, i.e. rice planted on a water layer, is presented in the paper. Field experiments carried out by scientists of Space Technology Application Centre (STAC), Institute of Physics, National Centre for Natural Science and Technology of Vietnam (NCST) using L- and C-band radiometers on water-rice fields are described. An estimation of the rice water content was made that well agreed to ones received by direct measurements. The results are interesting and useful for crop monitoring of agricultural services.
Sound and Music Computing: Research Trends and Some Key Issues

Abstract This contribution attempts to give an overview of current research trends and open research problems in the rich field of Sound and Music Computing (SMC). To that end, the field is roughly divided into three large areas related to Sound, Music, and Interaction, respectively, and within each of these, major research trends are briefly described. In addition, for each sub-field a small number of open research (or research strategy) issues are identified that should be addressed in order to further advance the SMC field.
One Joule per GFlop for BLAS2 Now

Energy consumption is today one of the major topics that the HPC community tries to tackle. In this paper, the authors present a thought experiment aiming at building a node of a supercomputer based on a GPU (Nvidia GTX280). The paper concentrate on BLAS2 operations that dominate many scientific applications. They show that it is already possible today to build a node that is able to perform one GFlop while consuming only one Joule. This corresponds to an energy reduction by one to two orders of magnitude. Technical limitations imposed by computer manufacturers hinder the realisation of such ecological resources. In a second part of the paper a new FLOPS‐driven governor is presented aiming at boosting the CPU performance for applications that are not main memory access bound, and showing results on an Intel mobile processor.
Design And Descriptive Tools For Systolic Architectures

Automated design and descriptive tools are essential for the practical application of highly parallel special-purpose hardware such as systolic arrays. The use of special-purpose hardware can greatly increase the capabilities of signal processing systems. However, the more limited applications base makes design costs a critical factor in determining technical and economic viability. Systolic systems can be described at several levels of abstraction, each of which has unique descriptive requirements. This paper focuses on the descriptive issues involved at the system architectural level. Tools at this level must cridge the gap between logic- and circuit-oriented computer-aided design tools and algorithmic descriptions of systolic architectures. Traditionally, hardware description languages (HDLs) have been used at this level to describe conventional computer architectures. Systolic architectures, however, have different requirements. This paper examines these requirements and develops a set of criteria for evaluating HDLs. Four popular HDLs are evaluated and their strengths and weaknesses noted. The final section of the paper summarizes ongoing efforts at Los Alamos to develop a systolic array HDL based on the CONLAN family of languages.
Green Process in Glycotechnology

Oligo- and poly-saccharides are important macromolecules in living systems. They show their multifunctional characteristics in the construction of cell walls, energy storage, and various biological phenomena like cell recognition. The development of a new glycosylation reaction is demanded in order to supply a sufficient amount of oligo- and poly-saccharides for basic research. Enzymes have several remarkable catalytic properties compared with other types of catalyst in terms of their selectivity, high catalytic activity, lack of undesirable side-reactions, and ability to operate under mild conditions. This account presents an overview of recent advances in the glycosylation reactions for synthesis of oligo- and poly-saccharides catalyzed by glycosyl hydrolases. A new carbon cyclic system of “Glyco-Chemistry Cycles” has been proposed based on the renewable polysaccharide biomass.
Assisted Research of the Dynamic Neural Networks with Time-Delays and Recurrent Links

The paper showed the assisted research of one new model of digital dynamic neural network by using the LabVIEW proper virtual instrumentation and proper mathematical model. In the research were used some different way to optimize the convergence process, for example: using one time- delay of the first and second output from the neural layers; using the recursive link and time- delay; using the bipolar sigmoid hyperbolic tangent sensitive function replacing the sigmoid simple sensitive function. By on-line simulation of the neural network it is possible to know what will be the influences of all network parameters like the input data, weight, biases matrix, sensitive functions, closed loops and time- delay, to the gradient errors, in a convergence process. By on-line using the proper virtual LabVIEW instrumentation, were established some influences of the network parameters: number of input vector data, number of neurons in each layers, to the number of iterations before canceled the mean square error to the target. In the optimization research we used the minimization of the gradient error function between the output and the target.
AN APPLICATION OF CLUSTER ANALYSIS TO THE PROBLEM OF LOCATING ITEMS WITHIN A WAREHOUSE

Abstract The order picking function in a warehouse involves selection of items from storage areas in order to satisfy customer demand. It has been identified as the most costly warehouse operations activity. Cluster analysis identifies groups of items that are frequently ordered together. Items within a cluster may be located near one another, and efficient picking tours may, thus, be formed. We formulate the clustering problem as a p-median 0-1 integer program which may efficiently be solved to optimality.
Analytic Techniques for the Assessment of Operator Workload

Workload techniques may be divided into two broad classes: 1) Analytic techniques — predictive techniques that may be applied early in system design before “operator-in-the-loop” studies; and 2) Empirical techniques — workload measurements taken with “operator-in-the-loop” during simulator, prototype, or system evaluations. Described here are five categories of the analytic techniques: 1) Comparability Analysis; 2) Mathematical Models; 3) Expert Opinion; 4) Task Analytic Methods; and 5) Simulation Models. A description, with examples, is given for each category. The motivation for focusing on the analytic techniques lies in their application during the earliest stages of system development where the greatest design flexibility is available at the least cost.
Functional electric stimulation for sensory and motor functions: progress and problems

Functional Electrical Stimulation (FES) endeavors to restore the lost functions of the nervous system by means of electrical stimulation. It is a multidisciplinary field on the interface between the neuroscience, engineering, rehabilitation and the clinic. In this review, the principal notions behind FES are outlined together with the relevant moments of its history. The specific research problems encountered in the development of FES applications are extensively covered. From an engineering perspective, special attention is dedicated to the electrodes for selective stimulation. The major clinical applications are overviewed: pacing of the heart, respiratory pacing of the diaphragm, cochlear neuroprostheses for restoration of hearing, the rehabilitation and restoration of locomotion and hand functions, and the restoration of bladder and bowel functions. An analysis of the current FES applications is performed from the perspective of the evidence-based clinical approach. Currently, FES for restoration of the lost locomotor functions is a rapidly developing area that is on the verge of broadening its acceptance in the clinic. Evidence for this is the increasing number of various neuroprosthetic devices, some of them already beyond the prototype stage, that have been developed recently. The present FES treatments combined with conventional occupational and physical therapy still remain the most promising approach in rehabilitation of the spinal cord injury patients and the stroke patients. FES in combination with neuromodulation, which is however still in a rather empirical state of operation, becomes a viable option in the treatment of various urological disorders. The analysis indicates that the pacing of the heart and cochlear neuroprostheses remain the most developed applications of FES. The presented overview of the FES applications shows that a number of fundamental scientific problems have to be solved before a comparable degree of effectiveness and penetration in the common medical practice is achieved for the locomotion neuroprostheses and the urological FES appliances. Finally, a summary is given of the major clinical and fundamental directions of research needed for further improvement of FES. Biomedical Reviews 2003; 14: 23-50.
Autotuned Multilevel Clustering of Gene Expression Data

DNA microarray technology has revolutionized biological and med ical research by enabling bio logists to measure expression levels of thousands of genes in a single experiment. Different computational techniques have been proposed to extract important biological information fro m the massive amount of gene expression data generated by DNA microarray technology. This paper presents a top down hierarchical clustering algorithm that produces a tree of genes called GERC tree (GERC stands for Gene Exp ression Recursive Clustering) along with the generated clusters. GERC tree is an amp le resource of biolog ical information about the genes in an expression dataset. Unlike dendrogram, a GERC tree is not a binary tree. Genes in a leaf node of GERC t ree represent a cluster. The clustering method was used with real-life datasets and the proposed method has been found satisfactory in terms of ho mogeneity, p value and z-score.
Efficient implementation of multiple scattering Monte Carlo estimates in time-of-flight neutron spectrometry exploiting wide-area detectors

The substantial upgrade in new-generation reactor-based time-of-flight spectrometers lies in their hugely increased detection area ensuring high neutron-collection power and remarkably good count statistics in relatively short times. Dealing with thousands of time channels and several tens of thousands of detection pixels is, however, quite punishing for data handling and correction. Real-geometry multiple scattering evaluation, even in an approximate way, is often the most demanding step in the treatment of inelastic neutron data, and becomes a very hard task in widely-extended detection geometries, as those of spectrometers like BRISP, IN4 or IN5 at the Institut Laue Langevin in Grenoble. We refreshed our approach to multiple scattering calculations, in order to obtain reasonably accurate real-geometry results in nearly real-time conditions. Our new code, originating from a long standing experience in the application of Monte Carlo (MC) integration techniques to multiple scattering calculations, is now made particularly efficient in computing time both by a careful application of the MC importance sampling method, and by the use of programming languages allowing for an efficient use of matrix algebra to avoid the far slower nested-loop logic of more traditional languages. The concepts at the basis of the algorithm and several implementation details are presented, together with the application to a real experimental test case.
A computer input device for medically impaired users of computers

Introduces a novel computer input device capable of receiving input by processing the images of the scene viewed by a camera; i.e. there is no need for any physical contact. The user of this input device can use any part of his body to issue a computer command. The system described is a cursor-positioning input device. In addition to cursor-positioning commands it also provides a simulated keyboard to allow users to input text without using the physical keyboard. The system described has been successfully built; preliminary experience in using the system has been very encouraging. <<ETX>>
Oceanographic applications of spaceborne bistatic SAR

This work presents an analysis of the attainable performance of a bistatic SAR for oceanographic applications, such as the determination of sea state parameters and the reconstruction of the sea wave spectrum. The analysis has been developed with regard to the spaceborne bistatic SAR of the BISSAT mission. It is based on a receiving-only antenna, flying on board a small satellite, that gathers echoes from the area illuminated by an active SAR operating on an independent large platform. It is shown that in the case of bistatic acquisitions the region of the sea wave spectrum that can be retrieved through linear inversion is wider than the one relevant to a monostatic survey. Specifically, the improvement consists of higher sea states (up to 15-20%) and a wider range of azimuth angles of propagation of the sea waves, increasing for larger antenna baselines. Also, the image degradation due to acceleration smearing is reduced. Improvements can achieve 20% for larger azimuth angles of propagation and baselines.
A reconceptualisation of Decision Conferencing: towards a command methodology

Decision Conferencing can be viewed as comprising two major elements: (a) the decision modelling component and (b) the process of group communication and facilitation in which the modelling is embedded. Whilst the former has a theoretical foundation in Decision Theory, the process of group communication and facilitation in which the modelling is embedded is, we argue, seriously under-theorised. It is therefore open to different interpretations, depending upon the assumptions held by individual facilitators about the nature of groups and their facilitation as well as about the process of communication within groups. This paper sets out to augment the current theories underpinning Decision Conferencing. The discussion relates to Decision Conferencing as applied to strategic planning. The proposed theoretical framework draws on Habermas' theory of communicative rationality by developing a command methodology. Implications of this formulation are described and discussed.
An Approach to Automatic Robot Programming Based on Inductive Learning

Automatic programming of manipulator robots attracts in creasing interest within the context of mechanical assembly. In this paper we focus on the problem of mating two parts, which requires sensor-based strategies to deal with geometric uncertainty. We present a system that embodies a two-phase approach to build robot programs implementing such strate gies. First a training phase interacts with the robot actuators and sensors and produces traces of execution of a given part- mating operation. Next a purely computational induction phase transforms these traces into an executable manipula tor-level program for the operation. The system embedding this approach has been completely implemented, and it has been used experimentally on several assembly tasks.
Fractionally-spaced blind equalization with CRIMNO algorithm

The CRIMNO criterion is extended to the case of fractionally spaced blind equalization. Simulation results show that the fractionally spaced CRIMNO algorithm, especially its adaptive version, converges faster than the synchronous CRIMNO algorithm, and faster than the fractionally spaced Goddard (1980) CMA algorithm. Insights into why the fractionally spaced blind equalization algorithm has faster convergence are given. <<ETX>>