Miracle-dz/UniFAR-FTUs huggingface dataset:
New parameterized foot trajectory shape for multi-gait quadruped locomotion with state machine-based approach for executing gait transitions

This paper presents a method of generating adjustable robot foot trajectories to provide forward open-loop locomotion for different gaits of a planar quadruped robot. The trajectory is described by a small set of tunable parameters that are related to the motion animals perform. This allows faster and easier adjusting of the foot trajectories for different quadruped robots. This method was tested on a simulation model while performing different type of gaits: walk, trot, pace and bound gait. The proposed trajectory shape exhibited great results in simulation. Robot locomotion speed was controlled by scaling the obtained trajectory execution time. This way robot can achieve a wide range of speeds over all of the observed gaits. Additionally, a state-machine based approach for controlling trajectory execution and gait switching is presented. By covering a certain amount of possible events along with ground contact feedback, a quadruped can execute gait transition in a controlled way at overlapping configurations between gaits. The gait transition is performed by defining a set of rules which must be satisfied in order for the gait transition to take place. The simulation results have confirmed that robot maintains stable locomotion after executing gait transition.
An effective model of using negative relevance feedback for information filtering

Over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. This paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. This study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. The former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. The later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. An iterative algorithm is also proposed to implement this approach on RCV1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.
A blueprint for a brain map of syntax1

I review the current state of the evidence regarding the representation of syntax in the brain. Broca’s region turns out to be one of several areas that govern syntactic operations. Citing a wide range of cross-linguistic and cross-task evidence from aphasia and fMRI, I show that syntactic movement (and not much else) is consistently related to Broca’s region, albeit in intriguingly varied ways. I analyze this variation and show that it follows from the Trace-Deletion Hypothesis, if this hypothesis is construed modulo the syntactic variation that the world’s languages exhibit, as well as the different demands made by the various tasks. Next, I review recent fMRI results from healthy speakers of 3 languages, regarding the neural computation of intra-sentential dependencies that are distinct from movement. Operations that govern Dative Shift seem to map onto the right hemisphere (anterior Insula and vPCS), located on the same side of, and just posterior to, operations that are related to reflexive binding (which are on the right Superior Frontal Gyrus). I use the emerging map to explore the possibility that this neurological distribution of syntactic operations is not accidental, and that the brain map for syntax is both neurologically and linguistically meaningful.
A simulation study on the capabilities of rotor wing unmanned aerial vehicle in aerial terrain mapping

Many applications can be solved by using the unmanned aerial vehicle (UAV) technology such as farming, surveillance, monitoring, fire disaster, flood monitoring and aerial terrain mapping. This study was carried out to investigate the use of light weight rotary-wing UAV for mapping simulation model. The accuracy of photogrammetric product will be assessed as one of the objectives of this study. There are two types of UAV units known as rotor wing and fixed-wing. Based on few studies, rotor wing units are more stable and are able to capture images easily. It allows remote control UAV to be practiced in the environment and urban mapping. In the simulation model, ground control points (GCP) and checked point (CP) were established using total station. The GCP is used in the photogrammetric processes to produce photogrammetric output while the CP is used for accuracy assessment. This study also used a low cost digital camera in image acquisition to capture the aerial image of a simulated model. Two methods were implemented in this study. In the first method, the camera was mounted vertically at a fixed height on the simulated model. In the second method, the camera was mounted vertically; it was then attached at the bottom of rotary-wing UAV and the images were captured at an altitude. The productions of digital orthophoto and digital elevation model of the simulated model were obtained after the acquired images were processed using the photogrammetric software. Based on the finding, the root mean square errors (RMSEs) for fixed platform are ±0.002, ±0.001 and ±0.214 for coordinate x, y and z, respectively while the RMSE for UAV platform are ±0.002, ±0.002 and ±0.223 for coordinate x, y and z, respectively. It can be concluded that the differences between the mobile and fixed platforms are small. In conclusion, UAV system can be used for large scale mapping of aerial terrain mapping.
Anonymization : Enhancing Privacy and Security of Sensitive Data of Online Social Networks

Privacy is one of the major concerns when publishing or sharing social network data for social science research and business analysis. This paper is motivated by the recognition of the need for a finer grain and personalized privacy in data publication of social netwoks.Recently , researchers have proposed a privacy protection scheme that not only prevents the disclosure of identity of users but also the disclosure of selected features in user’s profiles. An individual user can select which features of his profiles he wishes to conceal. The social networks are modeled as graphs in which users are nodes and features are labels. Labels are denoted either as sensitive or as non-sensitive. We treat node labels both as background knowledge an adversary may possess, and as sensitive information that has to be protected. Privacy protection algorithms that allow for graph data to be published in a form such that an adversary who possesses information about a nodes neighborhood cannot safely infer its identity and its sensitive labels. To this aim, the algorithms transform the original graph into a graph in which nodes are sufficiently indistinguishable. The algorithms are designed to do so while losing as little information and while preserving as much utility as possible. We evaluate empirically the extent to which algorithms preserve the original graph’s structure and properties. We show that our solution is effective, efficient and scalable while offering stronger privacy guarantees than those in previous research. Privacy models evolved w.r. t kanonymity to prevent node reidentification through structure information.
Particles cross-influence for entity grouping

In this paper we propose a novel approach to detect and track moving entities in wide surveillance video. Considering the wide area covered by the camera, which makes the detection and tracking of humans, as well as the classification of their motion a complex task and resource consuming, we adopt a particle-based approach to highlight particles of interest and group them based on their motion properties. A cross-influence matrix is computed at the particle level identifying the relevant areas of the video, and pruning static particles and outliers. Based on the motion features of the particles marked as interacting with their neighbors, a learning procedure based on an MLP neural network is implemented, in order to create consistent groups, representing the moving entities to be tracked over time. The method has been tested on two publicly available datasets with different resolutions and motion characteristics.
A SPECTRAL SUBTRACTION RULE FOR REAL-TIME DSP IMPLEMENTATION OF NOISE REDUCTION IN SPEECH SIGNALS

Spectral subtraction is a method for restoration of the spectrum magnitude for signals observed in additive noise, through subtraction of an estimate of the average noise spectrum from the noisy signal spectrum. In this paper we show that, starting from the known minimum mean-square error (MMSE) suppression rules of Ephraim and Malah and under the same modeling assumptions, a simpler suppression filtering rule can be found. Moreover, we demonstrate its performances and compare its computational costs with respect to the reference rule of Ephraim and Malah. This result permits a real time implementation of the exposed theory with an efficient algorithm on the DSP TMS320 C6713B.
Impact of STATCOM on distance relay - Modeling and simulation using PSCAD/EMTDC

With the increase in the number of STATCOM type FACTS devices in transmission lines, operation of distance relays in transmission lines are affected. It is very important that the distance relays do not maloperate under system fault conditions, as this will result in the loss of stability or the security of system, which defeats the main objective of installing a STATCOM. A STATCOM or Static synchronous Compensator is a regulating device used on alternating current electricity transmission networks. An apparent impedance calculation procedure for transmission line incorporating STATCOM based on the power frequency sequence circuits has been explored. The simulation results show the impact of statcom on the Distance protection relay during different fault conditions; the influence of location of STATCOM, the setting of STATCOM control parameters and the operation mode of STATCOM are studied as well. The results are presented in relation to a 138 kv transmission system employing STATCOM. Followed by a review of the effects of a STATCOM connected at the midpoint of a transmission line on the performance of distance protection relays using PSCAD software.
Top Ontology as a Tool for Semantic Role Tagging

This paper deals with the semantic roles in verb valency frames. It examines ontologies, particularly Top Ontology from the EuroWordnet 1,2 project in relation to the tagging of semantic roles of verb complements. We are aiming at a consistent system of semantic role tags that would form a base for lexico-semantic constraints integrated into a natural language parser. A new notation that exploits semantic roles (deep cases) based on the EuroWordNet Top Ontology and the set of the Base Concepts is also presented as well as preliminary statistical results of our research effort.
Performance of SIMO FM-DCSK UWB System Based on Chaotic Pulse Cluster Signals

Recently, an ultra-wideband (UWB) system with frequency-modulated differential chaos shift keying (FM-DCSK) modulation has attracted increasing interest for its many distinctive superiorities over its conventional counterparts, especially in low-rate and low-power wireless personal area network (WPAN) applications. However, some of its drawbacks, such as low energy efficiency, complex implementation and weak multiaccess capacity, have also been noticed, which restrict its further acceptance and applications. To overcome these problems, an architecture, named single-input and multiple-output (SIMO) FM-DCSK UWB system, is introduced in this paper. With chaotic transmitted signals based on a high-order Walsh function and multiple antennas diversity reception, this paper demonstrates the superiorities of the new system in bit error rate (BER) performance as well as in moderation complexity. Furthermore, by transmitting chaotic pulse cluster signals, an improved emission signal structure of the SIMO FM-DCSK UWB system is proposed so as to overcome the delay line implementation constraints and to further enhance the BER performance. Based on this new signal format, a method of combining time division and Walsh function division is introduced into the existing Walsh function division scheme, thereby resolving the inherent obstacle in user capability which was known to be limited by the order of the Walsh function.
Authentication of Scalable Video Streams With Low Communication Overhead

The large prevalence of multimedia systems in recent years makes the security of multimedia communications an important and critical issue. We study the problem of securing the delivery of scalable video streams so that receivers can ensure the authenticity of the video content. Our focus is on recent scalable video coding (SVC) techniques, such as H.264/SVC, which can provide three scalability types at the same time: temporal, spatial, and visual quality. This three-dimensional scalability offers a great flexibility that enables customizing video streams for a wide range of heterogeneous receivers and network conditions. This flexibility, however, is not supported by current stream authentication schemes in the literature. We propose an efficient and secure authentication scheme that accounts for the full scalability of video streams, and enables verification of all possible substreams that can be extracted from the original stream. In addition, we propose an algorithm for minimizing the amount of authentication information that need to be attached to streams. The proposed authentication scheme supports end-to-end authentication, in which any third-party entity involved in the content delivery process, such as stream adaptation proxies and caches, does not have to understand the authentication mechanism. Our simulation study with real video traces shows that the proposed authentication scheme is robust against packet losses, incurs low computational cost for receivers, has short delay, and adds low communication overhead. Finally, we implement the proposed authentication scheme as an open source library called svcAuth, which can be used as a transparent add-on by any multimedia streaming application.
Facilitating work discussion groups with staff in complex educational provisions

This paper presents findings from an exploratory study of ‘work discussion groups’ (WDGs) conducted with groups of staff in three complex educational provisions (a special needs setting and two alternative provisions) facilitated by two Educational Psychologists (EPs) using Action Research. The objective was to give the group members tools to understand and develop their own emotional wellbeing and resilience. Four themes emerged from data analysis: ‘Group readiness’ - how the structure of a WDG was initially hard to follow; ‘Being heard’ - wanting to be listened to within the school; ‘Physical space’ - how the schools were physically positioned and located, and ‘Staff wellbeing’ - how the staff were able to consider their own needs. In each group, the facilitators used an ‘adapted WDG model’ to support the group members. This way of working was recognised by participants as a helpful way to come together and share ideas and reflect on practice. This suggests that the findings could have implications for staff wellbeing across complex educational settings.
Recall Error Analysis for Coreference Resolution

We present a novel method for coreference resolution error analysis which we apply to perform a recall error analysis of four state-of-the-art English coreference resolution systems. Our analysis highlights differences between the systems and identifies that the majority of recall errors for nouns and names are shared by all systems. We characterize this set of common challenging errors in terms of a broad range of lexical and semantic properties.
Effects of a Closed Space Environment on Gene Expression in Hair Follicles of Astronauts in the International Space Station

Adaptation to the space environment can sometimes pose physiological problems to International Space Station (ISS) astronauts after their return to earth. Therefore, it is important to develop healthcare technologies for astronauts. In this study, we examined the feasibility of using hair follicles, a readily obtained sample, to assess gene expression changes in response to spaceflight adaptation. In order to investigate the gene expression changes in human hair follicles during spaceflight, hair follicles of 10 astronauts were analyzed by microarray and real time qPCR analyses. We found that spaceflight alters human hair follicle gene expression. The degree of changes in gene expression was found to vary among individuals. In some astronauts, genes related to hair growth such as FGF18, ANGPTL7 and COMP were upregulated during flight, suggesting that spaceflight inhibits cell proliferation in hair follicles.
Pulse-Wave Analysis of Optic Nerve Head Circulation Is Significantly Correlated with Kidney Function in Patients with and without Chronic Kidney Disease

Aim. To determine whether there is a significant correlation between the optic nerve head (ONH) circulation determined by laser speckle flowgraphy (LSFG) and kidney function. Materials. Seventy-one subjects were investigated. The estimated glomerular filtration rate (GFR) and serum creatinine, cystatin C, and urinary albumin excretion were measured. The ONH circulation was determined by an analysis of the pulse wave of LSFG, and this parameter was named blowout time (BOT). Chronic kidney disease (CKD) was defined to be present when the estimated GFR was <60 mL/min per 1.73 m2. Pearson's correlation coefficients were used to determine the relationship between the BOT and the kidney function. We also examined whether there were significant differences in all parameters in patients with and without CKD. Results. BOT was significantly correlated with the level of creatinine (r = −0.24, P = 0.04), the estimated GFR (r = 0.42, P = 0.0003), cystatin C (r = −0.29, P = 0.01), and urinary albumin excretion (r = −0.29, P = 0.01). The BOT level in subjects with CKD was significantly lower than that in subjects without CKD (P = 0.002). Conclusion. BOT in ONH by LSFG can detect the organ damage such as kidney dysfunction, CKD.
Face typing: Vision-based perceptual interface for hands-free text entry with a scrollable virtual keyboard

We present a novel vision-based perceptual user interface for hands-free text entry that utilizes face detection and visual gesture detection to manipulate a scrollable virtual keyboard. A thorough experimentation was undertaken to quantitatively define a performance of the interface in hands-free pointing, selection and scrolling tasks. The experiments were conducted with nine participants in laboratory conditions. Several face and head gestures were examined for detection robustness and user convenience. The system gave a reasonable performance in terms of high gesture detection rate and small false alarm rate. The participants reported that a new interface was easy to understand and operate. Encouraged by these results, we discuss advantages and constraints of the interface and suggest possibilities for design improvements.
A SPOKEN DIALOG SYSTEM WITH AUTOMATIC RECOVERY MECHANISM FROM MISRECOGNITION

We proposed a novel dialog strategy which can recover from mis- recognition through a spoken dialog. To recover from the misrecog- nition without confirmation, our system kept multiple understanding hypotheses at each turn and 'searched' for a globally optimal hypothesis across user's utterances in a whole dialog. As for a dialog strategy, we introduced a new criterion based on 'efficiency for convergence' and 'consistency with understanding hypotheses' to select an appropriate system response. Using such criterion, the system removes the ambiguity without making the user feel unnatural in relation to the response conflicting with actual user intent. We also proposed to adopt the repetition utterance detection to update the understanding hypotheses. We developed a spoken dialog system using these techniques and showed some dialog examples in which misrecognition was naturally corrected. We also showed that our strategy was efficient in terms of the number of turns.
Fast continuous collision detection among deformable models using graphics processors

We present an interactive algorithm to perform continuous collision detection between general deformable models using graphics processors (GPUs). We model the motion of each object in the environment as a continuous path and check for collisions along the paths. Our algorithm precomputes the chromatic decomposition for each object and uses visibility queries on GPUs to quickly compute potentially colliding sets of primitives. We introduce a primitive classification technique to perform efficient continuous self-collision. We have implemented our algorithm on a 3:0 GHz Pentium IV PC with a NVIDIA 7800 GPU, and we highlight its performance on complex simulations composed of several thousands of triangles. In practice, our algorithm is able to detect all contacts, including self-collisions, at image-space precision in tens of milli-seconds.
Towards a Model-Driven Process for Designing ReSTful Web Services

Representational State Transfer (ReST) architecture provides a set of constraints that drive design decisions towards architectural properties such as interoperability, evolvability and scalability. Designing a ReSTful service API involves finding resources and their relationships, selecting uniform operations for each resource, and defining data formats for them. It is often a non-trivial exercise to refine a functional specification, expressed in terms of arbitrary actions, to a resource-oriented, descriptive state information content. We argue that this process can be described as a series of model transformations, starting from service functionality and gradually refining the phase products until a ReSTful service API is reached. This paper outlines the process phases, transformations and intermediate models based on our experiences in developing ReSTful services and service APIs at Nokia Research Center. The process captures our understanding on how to systematically transform functional specifications into ReSTful Web service interfaces.