Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of several wavelet coefficient confusion methods applied in multimedia encryption

Wavelet transform is widely used in image and video encoding. And some multimedia encryption methods have been proposed during the past decade. The methods based on wavelet coefficient confusion are often used in wavelet encoding. This paper proposes a coefficient confusion method based on quad-tree structure. The method, together with the other two confusion methods, is analyzed by comparing their key space, effect on compression ratio and bit rate control. And some means are proposed to strengthen the security of the encryption system. The analysis and experiment results show that the confusion method based on quad-tree confusion is of low-cost and is easy to realize bit rate control, so it is suitable for image or video encryption in network transform with real-time requirement, especially in mobile multimedia network.
A dog and fox oscillator simulation for the coupling between heart and lungs

An electric analog model of the possible interactions between cardiac and respiratory oscillations is presented. Two oscillators (called dog and fox) are connected to the inputs of a numerical exnor to give a qualitative simulation of the behavior of the correspondent physiological systems under normal conditions. An effective decoupling of the two oscillators with the shift of the characteristic frequencies is shown. <<ETX>>
A Multiple Ring Fast Computing Method Based on MapReduce in Digraph

Graph algorithm has been widely used in modern computer network technology, and with the increase of data, graph algorithm is faced with the challenge of big data. Using MapReduce programming framework, this paper puts forward a multiple ring fast computing method in diagraph. Compared with the previous methods, this method is more efficient. And through the experiment the method are compared with the previous method.
Obtaining 3D shape of potted plants and modeling

An approach obtaining three dimensional object shapes from a series of silhouette images is presented. A two dimensional image sequence of an object put on a turning table is taken by a video camera at regular time intervals to obtain silhouette images from multiple viewpoints. A pillar is obtained by sweeping the silhouette along a line parallel to the viewing direction. An intersection of the pillars from all the viewpoints surrounding the object is sampled to give a set of volume data. The segmentation and the modeling of potted plants are also studied as an application of computer graphics. The set of volume data is segmented into three parts of a potted plant, i.e., a pot, stems and leaves. Then, the pot and the stems are modeled by frustums and each of the leaves is approximated by two Bezier surface patches.
Closed-Loop Behavior of an Autonomous Helicopter Equipped with a Robotic Arm for Aerial Manipulation Tasks

This paper is devoted to the control of aerial robots interacting physically with objects in the environment and with other aerial robots. The paper presents a controller for the particular case of a small-scaled autonomous helicopter equipped with a robotic arm for aerial manipulation. Two types of influences are imposed on the helicopter from a manipulator: coherent and non-coherent influence. In the former case, the forces and torques imposed on the helicopter by the manipulator change with frequencies close to those of the helicopter movement. The paper shows that even small interaction forces imposed on the fuselage periodically in proper phase could yield to low frequency instabilities and oscillations, so-called phase circles.
Load sharing among muscles and dynamic relationship between multi-muscle EMGs and isometric joint moment

An in vivo and noninvasive technique was developed to determine the human elbow extension moment distribution among the 3 heads of the triceps and the anconeus muscles, and to model the relationship between the multi-muscle EMGs and the joint extension moment dynamically. The static M-wave and joint moment relationships for each head of the muscles was used to calibrate the EMG signals and determine load sharing during voluntary tasks. Results showed that the medial head triceps was the prime elbow extensor and the anconeus contributed significantly at low levels of the extension moment. Both load sharing and the model parameters varied with the joint extension moment. Contributions of the medial head triceps and anconeus decreased with the mean joint moment, while those of the lateral and long heads of triceps increased with it.
On multi-robot task allocation

Despite more than a decade of experimental work in multi-robot systems, important theoretical aspects of multi-robot coordination mechanisms have, to date, been largely ignored. To address part of this negligence, this dissertation focuses on the problem of multi-robot task allocation (MRTA). Most work on MRTA has been ad hoc and empirical, with many coordination architectures having been proposed and validated in a proof-of-concept fashion, but infrequently analyzed. With the goal of bringing some objective grounding to this important area of research, this dissertation presents a formal study of MRTA problems. A domain-independent taxonomy of MRTA problems is given, and it is shown how many such problems can be viewed as instances of other, well-studied, optimization problems. By casting MRTA problems in the well-understood framework of optimization, a half-century of work in operations research, game theory, economics, and network flows can be adapted for use in robotic domains. This dissertation demonstrates how such theory can be used for analysis and greater understanding of existing approaches to task allocation, and suggests how the same theory can be used in the synthesis of new approaches. Although vital for the advancement of the field, analysis is only one component of a comprehensive research agenda. Sensor-actuator systems such as robots present a rich, complex problem domain that can exhibit significant levels of noise and uncertainty. One must implement and empirically validate proposed MRTA algorithms. Thus this dissertation also presents experimental work with an auction-based task allocation system, implemented on physical robots. Optimization theory is used to explain how and why this approach is successful. This kind of empirical work is a natural complement to formal analysis, and can serve the crucial role of suggesting modifications to the formal model that is analyzed. Such experiments require substantial supporting software infrastructure. This dissertation describes the underlying software facilities that were developed for experimental use in the study of MRTA, as well as for more general use. Specifically discussed is the Player/Stage project, which produces high-quality Open Source software to support robotics research, with the goal of providing a standard platform for mobile robot experimentation and simulation.
Recognition of mixed facial expressions by neural network

Deals with a neural network method for the machine recognition of mixed facial expressions by decomposing mixed facial expression into 2 or 3 components of 6 basic ones. The authors obtain the facial images, which show mixed facial expressions, from video tape recorded facial images and from the information of facial expressions in terms of the (x,y) coordinates of facial characteristic points. Then the position information of facial image is generated for 19 clients, and is used for the neural network training and recognition test. The recognition test is done by inputting the facial information, not being used in training the neural network, to the trained neural network. The recognition results obtained by the neural network are compared with those by humans. The neural network method is found to give a rather high agreement rate of about 70% compared with those obtained by humans. <<ETX>>
Integration system of a nonlinear transient network-analysis program

Users of nonlinear transient network-analysis programs, which use explicit integration procedures, have reported that excessive computer time is required to compute the transient response of networks containing widely separated time constants. Several recent papers have shown that for these problems significant computation-time reductions can be obtained by using implicit integration formulas. This paper is concerned with the selection and implementation of an implicit integration formula used in the CIRPAC nonlinear transient network-analysis program. Time-comparison data presented here indicate that the integration system that is described in this paper is significantly faster than the integration system of a network-analysis program that uses an explicit integration algorithm.
DEAS 2005: workshop on the design and evolution of autonomic application software

Understanding software engineering issues for autonomic computing systems is critical for the software and information technology sectors, which are continually challenged to reduce the complexity of their systems. To be autonomic, a system must know itself as well as its boundaries and its environment, configure and reconfigure itself, continually optimize itself, recover or heal from malfunction, protect itself, and function in a heterogeneous world-while keeping its complexity hidden from the user. The goal of this workshop is to bring together researchers and practitioners, who investigate concepts, methodologies, techniques, technologies, and tools to design and evolve autonomic software.
Dynamics of TCP flow control over high-speed ATM networks

TCP performance over high-speed ATM networks is evaluated. In TCP over UBR (unspecified bit rate), packet losses caused by congestion deteriorates throughput and fairness. Even if early packet discard (EPD) is added, fairness still remains as a problem as long as cell loss occurs. TCP over ABR(ER) (available bit rate-explicit rate) can provide high performance by suppressing cell loss, as long as ABR rate control does not interact with TCP flow control. Coarse timer granularity and large window size can avoid the interaction. When end-to end ABR is not available, further enhancement of TCP control using implicit or explicit congestion notification is needed for performance improvement.
Using combination of color, texture, and shape features for image retrieval in melanomas databases

This paper deals with Computer Aided Diagnosis for skin cancers (melanomas). The diagnosis is based on some rules called the ABCD mnemonics. They take into account color distribution, lesion's diameter, etc. The goal isn't to classify the lesion but to find those, which are the most similar, in order to help the expert to confirm his diagnosis and to avoid any useless excision. This is done thanks to an indexation system, which compare the signatures of previously diagnosed lesions contained in a database and patient's lesion signature. This last is constructed by translating the rules into image processing attributes. We have divided then into three families: Color attributes (color and fuzzy histograms), Texture attributes (co-occurrence matrix and Haralick indices) and Shape attributes (lesion surface and maximum included circle). Image quantization permits us to keep only the most significant colors, thus giving a light structure. Finally, we define a distance for each attribute and use weighted combination for the similarity measure.
Sar And Passive Microwave Observations Of The Odden During Mizex '87

The Odden, a protuberance of sea ice in the Greenland Sea Basin, was studied using the NIMBUS-7 scanning multichannel microwave radiometer (SMMR) satellite and an X-band (3 cm) synthetic aperture radar (SAR) aircraft. The sea ice, meteorological, and oceanographic conditions within the northern portion of the Odden were also studied in March and April 1987. The SMMR data, which were first validated with in situ ship measurements and the SAR data, showed rapid 2-4 day oscillations of the Odden ice edge. The oscillations at 74-75 deg N were several hundred kilometers in extent. The rapid oscillation of the Odden does not appear to be a result of wind-induced ice drift, but rather results from the rapid formation of thin ice off the main ice edge.
INDIVIDUAL WEBSITES: INNOVATION FOR RAISING LANGUAGE AWARENESS IN ADULT LEARNERS

The paper aims to demonstrate how weblogging can raise learners’ language awareness and prepare them for communication in the networked world. The research included the application of the innovative technique for written and oral communication in English classes. The exploratory study of using a variety of Information Communication Technology activities at tertiary level was conducted. Class experiences of creating weblogs for learning purposes and using them for online activities with the students who learn English for Specific Purposes are described. The methods employed for data gathering consisted of administering specially designed questionnaires, analyzing students’ responses, carrying out weblogging activities, providing feedback to learners, evaluating students’ performance in various online activities, and finally assessing the utility of weblogging. Our results show that the experience of public writing provides an important opportunity for learning English. Despite a limitation of research - the data are received from a comparatively small sample of participants - some practical implications are indicated. Article in English
Plasticity following skilled learning and the implications for BCI performance

Brain Computer Interfaces (BCIs) rely on robust detection and classification algorithms for stable and accurate device control. Here we investigate the effects of skilled motor learning on the stability of movement related cortical potentials (MRCP). Eight subjects were trained for 32 min on a task known to induce plasticity. Significant increases in performance were accompanied by significant increases in the variability of the EEG signal from two to one second prior to movement onset. The implications of these results for the use of the MRCP for online device control are discussed.
Geotracking of webpage sources: a defence against drive-by-download attacks

Currently, numerous freeware URL screening tools are available online. While these tools exhibit various levels of sophistication in dealing with traditional web-based exploits, most of them are quite ineffective in detecting some more subtle forms of infection. In particular, most of these tools omit to detect and/or alert against drive-by-download injections that do not result in the download and/or execution of a malware, but instead only aim to tarnish the credibility of the compromised website or intrude on the privacy of its users. In this paper, we present our new visual location-based URL screening tool, named VLUS. We demonstrate that with this tool, various forms of drive-by-download injection leading to redirection can be easily spotted, irrespective of the nature of the injected content. The tool is also useful for the purposes of general webpage content analysis. We close the paper by outlining an alternative implementation of VLUS in the form of a browser Chrome extension. By a simple monitoring of the application-level traffic calls performed by the browser, this implementation offers several unique advantages over the standard VLUS implementation.
Robust Hand Gesture Detection Based on Feature Classifier

In this article, a novel automatic hand gesture detection approach based on the boosted classifiers is proposed, which analyze the hand gesture features. At first, hand gesture images are processed with local binary pattern (LBP) operator which has the powerful capability of texture feature description. And then these features are presented with LBP descriptor of hand gesture image which is divided into several blocks, because of too much dimension of feature vector, using Principal Component Analysis (PCA) to reduce dimension and compression. Finally, Kalman predictor is adopted to detect hand gesture, which is able to make the detection result more stable and accurate. Experiments have been carried out and the target regions have been detected and took it as the gesture truth to compare with the detection results. The proposed algorithm provides better detection result in comparison with various hand gesture detection algorithms. The proposed approach is robust to background, and it can detect the hand gesture quickly and effectively.
A robust 2400 bit/s MBE-LPC speech coder incorporating joint source and channel coding

A robust speech coder based on the multiband excitation (MBE) model is presented. Unlike many MBE coders, the spectral envelope information is represented using linear predictive coefficients (LPCs), which are quantized and encoded using a joint source and channel trellis coding scheme to obtain remarkable robustness to random channel errors without increase in bit rate (i.e., no redundant forward error correction (FEC) required). The coder produces communications quality speech at 2400 b/s and can maintain acceptable speech quality at bit error rates (BERs) up to 5%. The complexity is low enough for implementation on commercial DSP devices. <<ETX>>
Some Recent Developments on Nonparametric Econometrics

In this paper we survey some recent developments of nonparametric econometrics in the following areas: (i) Nonparametric estimation of regression models with mixed discrete and continuous data; (ii) Nonparametric models with nonstationary data; (iii) Nonparametric models with instrumental variables; (iv) Nonparametric estimation of conditional quantile functions. In each of the above areas we also point out some open research problems.
Improved power estimation for behavioral and gate level designs

A technique is presented for accurately computing the power of digital circuits described by behavioral- and gate-level designs. Accurate power estimation for high-level designs provides early warning of potential power problems, supporting design flexibility and a reduction of time and cost. The technique uses a behavioral VHDL specification or gate-level netlist as input. For a variety of combinational benchmark circuits, assuming the zero-delay model and uncorrelated primary inputs, the approach has been tested and compared with the Berkeley SIS power estimator. The proposed technique has been implemented in a program called the Behavioral Level Activity and Power Estimator (BLAPE). Experimental results demonstrate a savings in time with an average error less than 1.00%.
Securing large-scale military networks: homogenous protection for disparate environments

This article provides an overview of the US Defense Department's organizations and command structure for defending unclassified networks. After briefly describing the relationships between the major organizations that conduct defensive operations, the article discusses some of the issues and problems the Defense Department faces in defending its networks and how it tries to solve them. These issues include fielding security patches, dealing with computer or network security incidents, and accurately reporting computer and network security breaches. The article ends by describing long standing shortfalls in the computer and network security areas that are of immediate concern to the Defense Department.
Text extraction in real scene images on planar planes

This paper proposes a hybrid approach of a texture-based method and a connected component-based one for extracting texts in real scene images. For detecting texts having a lot of variations in size, shape, etc, we use a multiple-continuously adaptive mean shift algorithm on the text probability image produced by a multi-layer perceptron. It is assumed that the scene text lies on planar rectangular surfaces with homogeneous background colors. We correct perspective distortion using warping parameters calculated after segmentation of an input image. We can detect and reconstruct text images accurately and efficiently.
A generic channel simulator for wireless channels

This paper reviews the wireless channels simulated by the generic channel simulator (GCS) a software package developed for the DoD. The wireless channels considered are: cellular/PCS, VHF/UHF mobile-mobile and mobile-base station, VHF/UHF air-air and air-ground, land mobile satellite, indoor channels, and HF ionospheric. Simulations include distortion (multipath) and additive disturbances. Input parameters and environments for default scenarios are discussed. The background and current status of the GCS are reviewed.
3D Face Reconstruction With Local Feature Refinement

In this paper, we propose 3D face reconstruction from two or three images. The reconstruction process begins with a face localization and facial feature extraction. Global transformation process is done for facial features which have been obtained. Local feature refinement is used to refine the result of global transformation. Last, texture mapping process is done to provide texture of 3D model. The method used for face reconstruction can generate accurate and fast result for various poses and facial expressions, and by using local feature refinement can improve the quality of reconstruction output more similar to the original face image.
Design and analysis of swarm-based sensor systems

Miniaturization of electronics and mechanical elements has resulted in an explosion of small, computationally powerful sensor devices. These devices mounted on multiple mobile platforms - provide information gathering methods in a wide range of environments. Current sensor networks that produce large amounts of information lack an efficient method for returning data to the user. The purpose of this research is to develop and evaluate through simulation a cooperative communications and processing system.
The Research of Heuristic Algorithm for Flow Shop Scheduling Problem

For the flow shop scheduling problem which aims to minimize makespan, this paper gives a new derivation about its mathematical definition, and mining characteristics of the problem itself further. By which analysis, the new heuristic method proposed in the paper shorten the waiting time of each job as much as possible on the basis of reduce the processing time of the first machine and last job. The result of simulation experiments shows that, our new heuristic algorithm has good performance, and the average quality and stability of scheduling sequences generated by new method is significantly better than other heuristic algorithm which has the same complexity.
Bayesian Nonparametric Approach to Credibility Modelling

ABSTRACT Current methods in credibility theory often rely on parametric models, e.g., a linear function of past experience. During the last decade, the existence of high speed computers and statistical software packages allowed the introduction of more sophisticated and flexible modelling strategies. In recent years, some of these techniques, which made use of the Markov Chain Monte Carlo (MCMC) approach to modelling, have been incorporated in credibility theory. However, very few of these methods made use of additional covariate information related to risk, or collection of risks; and at the same time account for the correlated structure in the data. In this paper, we consider a Bayesian nonparametric approach to the problem of risk modelling. The model incorporates past and present observations related to risk, as well as relevant covariate information. This Bayesian modelling is carried out by sampling from a multivariate Gaussian prior, where the covariance structure is based on a thin-plate spline. The model uses the MCMC technique to compute the predictive distribution of future claims based on available data.