Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Computer Interaction Using Vision-Based Hand Gesture Recognition

With the rapid emergence of 3D applications and virtual environments in computer systems; the need for a new type of interaction device arises. This is because the traditional devices such as mouse, keyboard, and joystick become inefficient and cumbersome within these virtual environments. In other words, evolution of user interfaces shapes the change in the Human-Computer Interaction (HCI). Intuitive and naturalness characteristics of “ Hand Gestures” in the HCI have been the driving force and motivation to develop an interaction device which can replace current unwieldy tools. A survey on the methods of analyzing, modeling and recognizing hand gestures in the context of the HCI is provided in this paper. Taxonomy of the different algorithms based on the applications that they have been developed for and the approaches that they have used to represent gestures is presented. In addition, direction of future developments is discussed.
Computing with Neural Synchrony

Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties.
Parametric bootstrap approximation to the distribution of EBLUP and related prediction intervals in linear mixed models

Empirical best linear unbiased prediction (EBLUP) method uses a linear mixed model in combining information from different sources of information. This method is particularly useful in small area problems. The variability of an EBLUP is traditionally measured by the mean squared prediction error (MSPE), and interval estimates are generally constructed using estimates of the MSPE. Such methods have shortcomings like under-coverage or over-coverage, excessive length and lack of interpretability. We propose a parametric bootstrap approach to estimate the entire distribution of a suitably centered and scaled EBLUP. The bootstrap histogram is highly accurate, and differs from the true EBLUP distribution by only O(d 3 n -3/2 ), where d is the number of parameters and n the number of observations. This result is used to obtain highly accurate prediction intervals. Simulation results demonstrate the superiority of this method over existing techniques of constructing prediction intervals in linear mixed models.
Emotion Discrimination Using Spatially Compact Regions of Interest Extracted from Imaging EEG Activity

Lately, research on computational models of emotion had been getting much attention due to their potential for understanding the mechanisms of emotions and their promising broad range of applications that potentially bridge the gap between human and machine interactions. We propose a new method for emotion classification that relies on features extracted from those active brain areas that are most likely related to emotions. To this end, we carry out the selection of spatially compact regions of interest that are computed using the brain neural activity reconstructed from Electroencephalography data. Throughout this study, we consider three representative feature extraction methods widely applied to emotion detection tasks, including Power spectral density, Wavelet, and Hjorth parameters. Further feature selection is carried out using principal component analysis. For validation purpose, these features are used to feed a support vector machine classifier that is trained under the leave-one-out cross-validation strategy. Obtained results on real affective data show that incorporation of the proposed training method in combination with the enhanced spatial resolution provided by the source estimation allows improving the performed accuracy of discrimination in most of the considered emotions, namely: dominance, valence, and liking.
CATERADS AND MOTIVIC COHOMOLOGY

We define "weighted multiplicative presheaves" and observe that there are several weighted multiplicative presheaves that give rise to motivic cohomology. By neglect of structure, weighted multiplicative presheaves give symmetric monoids of presheaves. We conjecture that a suitable stabilization of one of the symmetric monoids of motivic cochain presheaves has an action of a caterad of presheaves of acyclic cochain complexes, and we give some fragmentary evidence. This is a snapshot of work in progress.
Model Checking and Expert System approaches to Attack Graphs

Attempts to compromise networks and computers connected to the Internet are numerous and widespread. And so have been the attempts to thwart them. Several methodologies have been and are being tried out to secure computers from such attacks that are more often than not malicious. One such approach is the deployment of firewalls to restrict the kind of connections that are accepted by computers. It has proved to be a moderate success in fending off the not-so-motivated attacker. But if the attacker is either skilled and/or motivated or is someone trusted, firewalls are not an effective defense. Nevertheless, we need some way of assessing and representing the universe of exploits that an attacker can achieve once the system defense has been breached. Attack graphs are one such representation. Traditionally, attack graphs drawn by hand were used to chart out the ramifications of a vulnerability being exploited in a network. Recently, model checking techniques have been used to generate attack graphs, albeit for very small sized networks. All research efforts conclude that model checking doesn’t scale but they give no explanations for it. One goal of this effort is to determine the limits of model checking approach for modeling and verifying networks for security. We demonstrate that model checking techniques fare very poorly for this task. We also try to explore the reasons for it. The second goal of this effort is to demonstrate a novel way of generating attack graphs using the Java Expert System Shell(JESS)[11] expert system. We also show that this technique scales better than the model checking technique and try to explain why this would be more suitable for this purpose. The paper explores the related work in the next section and gives the basic model we used to derive attack graphs in Section 3 Sections 4 and 5 discuss at length the model checking and expert system efforts respectively. Sections 6 and 7 draw conclusions and explore the future directions respectively.
Reducing Correlated Failures Impact in Peer-to-Peer Storage Systems Using Mobile Agents Flocks

This paper introduces MinCor (Minimum of Correlations), a decentralized simulated annealing algorithm designed for the data placement in peer-to-peer networks. Its goal is to reduce the correlated failures impact in such data storage systems. This data placement is realized using a multi-agent system which turns the documents into mobile agents flocks. After a network clustering step where highly correlated peers are regrouped together, the flocks executing MinCor are able to find a placement minimizing the number of agents on the same clusters. This placement is obtained in a decentralized way thanks to the environment exploration capabilities of the flocks. A set of experiments are performed on this system in presence of correlated failures. They show that, in practice, the expected placement is well obtained. They also show that, flocks using the MinCor algorithm suffer less simultaneous losses in presence of correlated failures than a mere random placement.
Reserve Price Reporting Mechanisms for Negotiation Support Systems

Information and Communication Technologies (ICT) changed our everyday business drastically. Business routines have been transformed to online activities. New theories and models were developed for the brand new online environment. For online negotiations, however, the research on new mechanisms is not enough, especially for bilateral distributive negotiations. A reserve price reporting mechanism (RPR) together with its extended version (ERPR) is proposed in this paper. The key improvement of reserve price reporting mechanisms is to let the negotiators report their reserve price to a third-party system before they actually start the negotiation. Analytical models of these mechanisms are built to prove truth revelation condition and the reduction of total social welfare comparing with traditional direct bargaining (TDB). A prototype of this RPR system is developed and a lab experiment is conducted to test the performance of the three mechanisms. The results of the experiment support that the reserve price report mechanisms proposed are more efficient than the traditional one in several dimensions.
\Turbo DPSK" Using Sphere Decoding without Channel State Information

Coded interleaved dieren tial M-ary phase-shift keying (MDPSK) with iterative decoding is known as power-ecien t transmission format, which is particularly suited to detection without channel state information (CSI). However, the soft-input soft-output (SISO) component decoder for DPSK is the computational bottleneck if performance close to the ideal case of perfect CSI is desired. In this paper, we take a fresh look at SISO decoding without CSI and apply sphere decoding (SD) to reduce complexity. In particular, we devise a maximum a posteriori (MAP) multiple-symbol dierential sphere decoder (MSDSD) which ecien tly solves the high-dimensional search problem inherent to detection without CSI. Together with a soft-output generation device the MAP-MSDSD algorithm forms a new SISO-MSDSD module for iterative decoding. From the extrinsic information transfer (EXIT) characteristic of the novel module, we are able to design powerful encoder and decoder structures. For the continuously time-varying Rayleigh fading channel without CSI these designs operate within 2.3-2.5 dB of channel capacity assuming perfect CSI. These gures compare favorably with results available in the literature, especially for reasonably high data rates of 1-2 bit/(channel use) considered in this paper.
Securing Deployed RFIDs by Randomizing the Modulation and the Channel

RFID cards are widely used today in sensitive applications such as access control, payment systems, and asset tracking. Past work shows that an eavesdropper snooping on the communication between a card and its legitimate reader can break their cryptographic protocol and obtain their secret keys. One solution for this problem is to install stronger cryptographic protocols on the cards. However, RFIDs’ size, power, and cost limitations do not allow for conventional cryptographic protocols. Further, installing new protocols requires revoking billions of cards in consumers’ hands and facilities worldwide, which is costly and impractical. In this paper, we ask whether one can secure RFIDs from such attacks without revoking or changing the insecure cards. We propose LocRF, a solution that changes the signal used to read the RFID cards but does not require any changes to the cards themselves. LocRF introduces a new approach that randomizes the modulation of the RFID signal as well as the wireless channel. This design protects RFIDs from eavesdroppers even if they use multi-antenna MIMO receivers. We built a prototype of LocRF on software-defined radios and used it to secure the communication of offthe-shelf cards. Both our analysis and empirical evaluation demonstrate the effectiveness of LocRF.
Estimating parameters in scientific computation - A survey of experience from oil and groundwater modeling

and engineering depends upon the accuracy of numerical models. On what does the accuracy of the models depend? Several things: the correctness of the underlying mathematical formulation, the numerical discretization used, the solution algorithms employed, and the accuracy of values for the physical parameters that appear in the model. It is this last factor that we want to examine in some depth. First, what do we mean by a parameter? In physics, a parameter typically describes a property of a material (such as mass, viscosity, or density) that can vary without changing the underlylng natural laws. For example, consider a group of particles moving about in a closed container. The number of particles, their masses, and their charge are parameters. Other parts of a physical model are not parameters. The fact that the equations of motion are given by a sytem of second-order differential equations, for instance, is not describable by a parameter-it is a fundamental characteristic of the model.
EXTENSIN18 is required for full male fertility as well as normal vegetative growth in Arabidopsis

EXTENSINS (EXTs) are a 65-member subfamily of hydroxyproline-rich glycoproteins (HRGPs) of which 20 putatively form crosslinking networks in the cell wall. These 20 classical EXTs are involved at the start of new wall assembly as evidenced by a requirement for EXT3 during cytokinesis, and the ability of some EXTs to polymerize in vitro into dendritic patterns. EXT3 was previously shown to form pulcherosine (three Tyrosines) cross-links. Little direct data exists on the other 19 classical EXTs. Here, we describe the phenotypes of ext18 mutants and rescued progeny as well as associated expression profiles of all 20 classical EXT genes. We found that EXT18 is required for full male fertility, as well as for normal vegetative growth. EXT18 has potential to form crosslinking networks via di-iso-di-tyrosine (four Tyrosines) covalent bonds, and not via pulcherosine due to deficit of lone Tyrosines. This together with ext18 defective pollen grains and pollen tubes, and reduced plant size, suggests that EXT18-type EXTs are important contributors to wall integrity, in pollen and other rapidly extending walls. The data also show that a knockout of EXT18 had a pleiotropic affect on the expression of several EXTs, as did the reintroduction of the native EXT18 gene, thus supporting the thesis that transcription of groups of EXTs are co-regulated and work in different combinations to make distinctive inputs into wall assembly of different cell types. These insights contribute to basic knowledge of cell wall self-assembly in different cell types, and potentially enable biotechnological advances in biomass increase and plant fertility control.
Parallel simulation techniques for large-scale networks

Simulation has always been an indispensable tool in the design and analysis of telecommunication networks. Due to performance limitations of the majority of simulators, usually network simulations have been done for rather small network models and for short timescales. In contrast, many difficult design problems facing today's network engineers concern the behavior of very large hierarchical multihop networks carrying millions of multiprotocol flows over long timescales. Examples include scalability and stability of routing protocols, packet losses in core routers, of long-lasting transient behavior due to observed self-similarity of traffic patterns. Simulation of such systems would greatly benefit from application of parallel computing technologies, especially now that multiprocessor workstations and servers have become commonly available. However, parallel simulation has not yet been widely embraced by the telecommunications community due to a number of difficulties. Based on our accumulated experience in parallel network simulation projects, we believe that parallel simulation technology has matured to the point that it is ready to be used in industrial practice of network simulation. This article highlights work in parallel simulations of networks and their promise.
Supervenient Hierarchies of Behaviors: Lessons learned from a Vacuuming Robot *

In this paper we describe the use of behavior hierarchies based on "merging" two models of multi-layer architecture -- the supervenience model of (Spector, 1992) and the subsumption model of (Brooks, 1990). The behavior hierarchy approach allows us to use the robustness of reactivity in behavior design. It also encourages the design of modular behaviors that can be reused or more importantly recalibrated in different situations. We argue that behavior hierarchies extend our ability to design and program effective solutions that do not require any explicit planning. We also describe ongoing work in using this model for integrating planning and reacting This work is being used in support of an implemented system in which an autonomous mobile robot performs a vacuuming task.
SOME REMARKS ON THE VISCOUS APPROXIMATION OF CRACK GROWTH

We describe an existence result for quasistatic evolutions of cracks in antiplane elasticity obtained in [16] by a vanishing viscosity approach, with free (but regular enough) crack path. We underline in particular the motivations for the choice of the class of admissible cracks and of the dissipation potential. Moreover, we extend the result to a model with applied forces depending on time.
Pattern Mining from Trajectory GPS Data

In this paper, we consider data mining from large discrete trajectory data. We study closed pattern mining for the class of trajectory envelope patterns. First, we introduce the basic definition of trajectory data. Then, we present a depth-first search algorithm that finds all trajectory envelope patterns in a given database that satisfies constrants on maximum width, minimum length, and minimum frequency. Finally, we ran experiments on a real trajectory dataset to evaluate our algorithm.
Value of systolic pulmonary arterial pressure as a prognostic factor of death in the systemic sclerosis EUSTAR population

Objective. The aim of this study was to assess the prognostic value of systolic pulmonary artery pressure (sPAP) estimated by echocardiography in the multinational European League Against Rheumatism Scleroderma Trial and Research (EUSTAR) cohort. Methods. Data for patients with echocardiography documented between 1 January 2005 and 31 December 2011 were extracted from the EUSTAR database. Stepwise forward multivariable statistical Cox pulmonary hypertension analysis was used to examine the independent effect on survival of selected variables. Results. Based on our selection criteria, 1476 patients were included in the analysis; 87% of patients were female, with a mean age of 56.3 years (s.d. 13.5) and 31% had diffuse SSc. The mean duration of follow-up was 2.0 years (s.d. 1.2, median 1.9). Taking index sPAP of <30 mmHg as reference, the hazard ratio (HR) for death was 1.67 (95% CI 0.92, 2.96) if the index sPAP was between 30 and 36 mmHg, 2.37 (95% CI 1.14, 4.93) for sPAP between 36 and 40 mmHg, 3.72 (95% CI 1.61, 8.60) for sPAP between 40 and 50 mmHg and 9.75 (95% CI 4.98, 19.09) if sPAP was >50 mmHg. In a multivariable Cox model, sPAP and the diffusing capacity for carbon monoxide (DLCO) were independently associated with the risk of death [HR 1.833 (95% CI 1.035, 3.247) and HR 0.973 (95% CI 0.955, 0.991), respectively]. sPAP was an independent risk factor for death with a HR of 3.02 (95% CI 1.91, 4.78) for sPAP ≥36 mmHg. Conclusion. An estimated sPAP >36 mmHg at baseline echocardiography was significantly and independently associated with reduced survival, regardless of the presence of pulmonary hypertension based on right heart catheterization.
AUTOMATIC PROCEDURE FOR THE REGISTRATION OF THERMOGRAPHIC IMAGES WITH POINT CLOUDS

This paper presents a procedure for the automatic registration of thermographies with laser scanning point clouds. Given the heterogeneous nature of the two modalities, we propose a feature-based approach, satisfying the requisite that extracted features have to be invariant not only to rotation, translation and scale but also to changes in illumination and dimensionality. As speed and minimum operator interaction are prerequisites for the viability of the process in the building industry, our automatic registration procedure includes automatic feature extraction with no human intervention. With this aim, a line segment detector is used to extract 2D lines from thermographies, and 3D lines are extracted through segmentation of the point cloud. Feature-matching and the relative pose between thermographies and point cloud are obtained from an iterative procedure applied to detect and reject outliers; this includes rotation matrix and translation vector calculation and the application of the RANSAC algorithm to find a consistent set of matches. An automatically textured thermographic 3D model is the expected result of these procedures once the point cloud is filtered and triangulated.
Managing complex IT outsourcing-partnerships

This article discusses the management of complex IT outsourcing partnerships from the perspective of both outsourcing companies and IT suppliers. The research project included 24 interviews with business and IT executives of outsourcing companies, executives of IT suppliers and experts. This article aims to provide a better understanding of managing complex IT outsourcing partnerships by proposing a descriptive framework containing relevant governance factors. The investigated cases and expert interviews and IT outsourcing literature are used to evaluate the framework. The results of the analysis and the framework itself illustrate the various complex issues arising in managing complex IT outsourcing partnerships.
Visual Analysis of the Air Pollution Problem in Hong Kong

We present a comprehensive system for weather data visualization. Weather data are multivariate and contain vector fields formed by wind speed and direction. Several well-established visualization techniques such as parallel coordinates and polar systems are integrated into our system. We also develop various novel methods, including circular pixel bar charts embedded into polar systems, enhanced parallel coordinates with S-shape axis, and weighted complete graphs. Our system was used to analyze the air pollution problem in Hong Kong and some interesting patterns have been found.