Miracle-dz/UniFAR-FTUs huggingface dataset:
Stable haptic interaction using passive and active actuators

This paper presents a stable control method for a hybrid haptic device comprising a brake and a motor. A review of stability condition via describing function analysis is first presented. The results show that while brakes are intrinsically stable, an active device is limited in terms of stiffness. The stability is however improved if the brake simulates a physical damping. Subsequently, the stability condition is obtained via passivity condition analysis. The results demonstrate that the stiffness is improved by engaging both actuators to create resistive forces and the passivity is respected assuming a passive virtual environment. An energy and a stiffness-bounding algorithms have been developed in order to assure the stability of the coupled system in this case. It has been tested and validated using a 1-DOF hybrid haptic device by the simulation of an unstable and an active virtual environments respectively . Experimental results show that the displayable stiffness is improved under stability conditions using the control method. Furthermore, it allows the hybrid system to simulate nonlinear and unstable virtual environments and the controller remains independent of the virtual environment model.
Contribution of interictal and ictal epileptic sources to scalp EEG

Several in vitro, in vivo, and simulation studies have been performed in the past decades aiming to clarify the interrelations of cortical sources with their scalp and invasive EEG correlates. The amplitude ratio of cortical potentials to their scalp EEG correlates, the extent of the cortical area involved in the discharge, as well as the localization of the cortical source and its geometry, have been each independently linked to the recording of the cortical discharge with scalp electrodes. Simultaneous multiscale EEG recordings with scalp, subdural and depth electrodes, applied in presurgical epilepsy workup, offer an excellent opportunity to address this fundamental issue. Whereas past studies have considered predominantly neocortical sources in the context of temporal lobe epilepsy, the present work addresses deep sources, in mesial temporal and extra-temporal epilepsies. We showed that deep sources, such as those in mesial temporal or fronto-basal regions, are not visible, but are detectable in scalp EEG. Scalp EEG spikes correlate with extensive activation of the cortical convexity and high spike-to-background amplitude ratios
Video summarization and scene detection by graph modeling

We propose a unified approach for video summarization based on the analysis of video structures and video highlights. Two major components in our approach are scene modeling and highlight detection. Scene modeling is achieved by normalized cut algorithm and temporal graph analysis, while highlight detection is accomplished by motion attention modeling. In our proposed approach, a video is represented as a complete undirected graph and the normalized cut algorithm is carried out to globally and optimally partition the graph into video clusters. The resulting clusters form a directed temporal graph and a shortest path algorithm is proposed to efficiently detect video scenes. The attention values are then computed and attached to the scenes, clusters, shots, and subshots in a temporal graph. As a result, the temporal graph can inherently describe the evolution and perceptual importance of a video. In our application, video summaries that emphasize both content balance and perceptual quality can be generated directly from a temporal graph that embeds both the structure and attention information.
Speculative Precomputation on Chip Multiprocessors

Previous work on speculative precomputation (SP) on simultaneous multithreaded (SMT) architectures has shown significant benefits. The SP techniques improve singlethreaded program performance by utilizing otherwise idle thread contexts to run “helper threads”, which prefetch critical data into shared caches and reduce the time the “main thread” stalls waiting for long latency outstanding loads. This technique effectively exploits the parallel thread contexts and the data cache sharing at all levels of the memory hierarchy that SMT provides. Chip multiprocessor (CMP) architectures also feature parallel thread contexts, but do not share caches near execution resources. In this paper, we first investigate SP on a basic CMP and show that while the existing SP techniques can provide performance improvements for single-threaded application on such CMP architectures, they fall short of the benefits provided on SMT architectures due to the reduced degree of cache sharing. We then propose and evaluate several simple enhancements to the basic CMP architecture, which can increase the speedup from using SP by an additional 10 to 12%.
CAN THE TEACHERS OF EARLY CHILDHOOD EDUCATION CONTRIBUTE IN THE EARLY DIAGNOSIS OF THE AUTISTIC SPECTRUM DISORDER

Aim: The aim of this study was to investigate whether contribute to the early diagnosis of Autistic Spectrum Disorder (ASD). This disorder of neurodevelopment arises in the first years of life, characterized by a dyad that involves communication and consequent socialization and on the other hand the presence of repetitive and stereotyped behaviors with repertoire of interests and restricted acti (DSM-5, 2013). In this sense it is necessary to emphasize the pedagogical view of the teachers that attend this age group in which one can observe early characteristics of ASD. To know about the experience of these teachers with Early Childhood Edu students with ASD, we know the characteristics of the disorder, evaluated by levels of training. Method: 300 teachers from the municipal network of Paulínia, Sao Paulo, Brazil; participated in the research through a specific questionnaire Results: it was evidenced that teachers showed knowledge of the main characteristics of the picture, many students are in the stage of oral language acquisition and atypical characteristics can be observed by teachers. The working is between 5 and 15 years old or more. Many said they had worked with students with this disorder, pointed out as more important aspects the presence of expert teachers and school with resource rooms with materials adapted to receive these children. this study it was possible to show that there is a lack of continuous training for teachers, teaching materials and adapted rooms. It should also be noted that if the diagnosis is made in the first 3 years (chronological age in which children are in early and long term interventions, there will be a positive impact on the prognosis of the cases.
Lys-34, Dispensable for Integrase Catalysis, Is Required for Preintegration Complex Function and Human Immunodeficiency Virus Type 1 Replication

ABSTRACT Retroviral integrases (INs) function in the context of preintegration complexes (PICs). Two conserved Lys residues in the N-terminal domain of human immunodeficiency virus type 1 (HIV-1) IN were analyzed here for their roles in integration and virus replication. Whereas HIV-1K46A grew like the wild type, HIV-1K34A was dead. Yet recombinant INK34A protein functioned in in vitro integration assays, and Vpr-INK34A efficiently transcomplemented the infectivity defect of an IN active site mutant virus in cells. HIV-1K34A was therefore similar to a number of previously characterized mutant viruses that failed to replicate despite encoding catalytically competent IN. To directly analyze mutant PIC function, a sensitive PCR-based integration assay was developed. HIV-1K34A and related mutants failed to support detectable levels (<1% of wild type) of integration. We therefore concluded that mutations like K34A disrupted higher-order interactions important for PIC function/maturation compared to the innate catalytic activity of IN enzyme.
An Efficient Algorithm for Mining Frequent Itemsets Within Large Windows Over Data Streams

Sliding window is an interesting model for frequent pattern mining over data stream due to handling concept change by considering recent data. In this study, a novel approximate algorithm for frequent itemset mining is proposed which operates in both transactional and time sensitive sliding window model. This algorithm divides the current window into a set of partitions and estimates the support of newly appeared itemsets within the previous partitions of the window. By monitoring essential set of itemsets within incoming data, this algorithm does not waste processing power for itemsets which are not frequent in the current window. Experimental evaluations using both synthetic and real datasets shows the superiority of the proposed algorithm with respect to previously proposed algorithms.
Dynamic optimization for batch processes with uncertainties via approximating invariant

The dynamic optimization problem for batch processes with uncertainties is considered in this paper. The invariant of optimality conditions is analytically derived. However, the invariant usually depends on the unmeasured states and disturbances; hence cannot be directly used for on-line control. To address this difficulty, we propose to approximate the invariant using available measurements, including manipulated variables, so that the optimal control can be derived as a function of available measurements. To this end, off-line experiments are conducted under various operating conditions and numerical regression method is applied to obtain an approximate expression of invariant in terms of manipulated variables and measurements. The approximated optimal control law is then derived by solving the manipulated variables as a function of measurements to keep the approximated invariant at zero, which can be used for on-line implementation. An illustrative example of fed batch reactor is provided to illustrate the proposed approach.
Improving Data Driven Image Geolocation

Hays and Efros [3] proposed an algorithm for automatically estimating where on the earth an image was taken by using a mostly data driven, scene matching approach. Given an input photograph, the system matches that photo against all the other scenes in the database. Their database consists of about 6.5 million geotagged images collected from Flickr. The system relies very little on complex scene understanding and instead uses large amounts of data in the hope that given an image, the system can nd a close match that image to some photos in the database. Once the best image matches are found, the matches are clustered into geographically and the best cluster is chosen as the estimated location.
Representing and Reasoning with Logical and Probabilistic Knowledge on Robots

This paper describes an architecture that enables robots to represent and reason with logic-based and probabilistic descriptions of uncertainty and domain knowledge. An action language is used to describe tightly-coupled transition diagrams of the domain at two different resolutions. For any given goal, reasoning with commonsense knowledge at coarse-resolution provides a plan of abstract actions. To implement each such abstract action, the relevant part of the fine-resolution transition diagram is identified, and used with a probabilistic representation of the uncertainty in sensing and actuation, to obtain a sequence of concrete actions. The outcomes of executing these concrete actions are used for subsequent coarse-resolution reasoning. We illustrate the architecture’s capabilities using examples of a mobile robot finding and moving objects in an indoor domain.
Online psychological treatment for pediatric recurrent pain: a randomized evaluation.

OBJECTIVE To evaluate the efficacy of a distance treatment delivered through Internet and telephone for pediatric recurrent pain. METHODS Forty-seven participants (9-16 years of age) were randomly assigned to either an Internet-based treatment or a standard medical care waitlist. Treatment employed a Web-based manual for children and parents with weekly therapist contact by telephone or e-mail. At 1- and 3-month follow-ups, participants were assessed on the outcome variables of pain and quality of life. A 50% reduction in diary pain scores was considered clinically significant. RESULTS Significant between-group differences were found: 71 and 72% of the treatment group achieved clinically significant improvement at the 1- and 3-month follow-ups, respectively, whereas only 19 and 14% of the control group achieved the criterion. No significant differences were found on the quality of life variable. CONCLUSIONS Distance methods have considerable potential for making effective treatments more accessible with lower associated costs.
Is Malnutrition Associated with Crowding in Permanent Dentition?

Evidence suggests that energy-protein malnutrition is associated with impaired growth and development of facial bones. The objective of this study was to investigate the association between nutritional status and reduced space for dental eruption (crowding) in permanent dentition. A cross-sectional study with probabilistic sampling design was used. We evaluated 2,060 students aged 12 to 15 years enrolled in schools in the northeast of Brazil. Crowding was defined according to World Health Organization (WHO) as misalignment of teeth due to lack of space for them to erupt in the correct position. Nutritional status was evaluated by means of body mass index and height-for-age, using the WHO’s reference curves. Parents and adolescents responded to a questionnaire about demographic, socioeconomic, biological and behavioral characteristics. The associations were estimated by odds ratio (OR) in multivariate logistic regression analysis (alpha = 0.05). Confounding and effect-modification were taken into account. An association between low height-for-age (z-score < −1SD) and crowding was only observed in adolescents with a prolonged history of mouth breathing (OR = 3.1). No association was observed between underweight and crowding. Malnutrition is related to crowding in permanent dentition among mouth-breathing adolescents. Policy actions aimed at reducing low height-for-age and unhealthy oral habits are strongly recommended. However, further studies are needed to increase the consistency of these findings and improve understanding of the subject.
Accumulation of Trace Metals by Mangrove Plants in Indian Sundarban Wetland: Prospects for Phytoremediation

The work investigates on the potential of ten mangrove species for absorption, accumulation and partitioning of trace metal(loid)s in individual plant tissues (leaves, bark and root/pneumatophore) at two study sites of Indian Sundarban Wetland. The metal(loid) concentration in host sediments and their geochemical characteristics were also considered. Mangrove sediments showed unique potential in many- fold increase for most metal(loid)s than plant tissues due to their inherent physicochemical properties. The ranges of concentration of trace metal(loid)s for As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb and Zn in plant tissue were 0.006–0.31, 0.02–2.97, 0.10–4.80, 0.13–6.49, 4.46–48.30, 9.2–938.1, 0.02–0.13, 9.8–1726, 11–5.41, 0.04–7.64, 3.81–52.20 μg g −1respectively. The bio- concentration factor (BCF) showed its maximum value (15.5) in Excoecaria agallocha for Cd, suggesting that it can be considered as a high-efficient plant for heavy metal bioaccumulation. Among all metals, Cd and Zn were highly bioaccumulated in E. agallocha (2.97 and 52.2 μg g −1 respectively. Our findings suggest that the species may be classified as efficient metal trap for Cd in aerial parts, as indicated by higher metal accumulation in the leaves combined with BCF and translocation factor (TF) values.
Path Planning and Autonomous Navigation using AMCL and AD*

Path planning and autonomous navigation are some of the most important challenges in mobile robotics. These are difficult tasks because the robot has to accurately and safely perform autonomous maneuverings. This paper presents a methodology to efficiently plan the trajectory of a robot in dynamic and complex environments, which it should traverse autonomously. A planner based in the AD* algorithm is used to plan a less costly trajectory to the destination. The methodology enables the robot to reach the goal using a local planner, which is applied to determine the speed and steering of the robot. Experimental results show that the planner is reliable for simulated and real tasks, as the robot has reached the goal while safely avoided obstacles.
A preliminary review on metrics for modular snake robots locomotion

Without changing its mechanical structure, a modular snake robot (MSR) can move using different gaits. In order to evaluate their locomotion, different metrics according to specific research goals have been developed in the last decades. However, there is a lack of homogeneity in the use of these metrics between robot types and the tasks executed. In this paper, a set of metrics is presented. These metrics were divided in performance and efficiency metrics to capture such characteristics in a MSR. Related work on metrics for this kind of robots was reviewed in detail. A description of each metric was provided. Friction coefficients, translational speed, orientation of the velocity vector and a stability margin, define the first set of metrics aimed to measuring the robot's performance. On the other hand, energy efficiency, mechanical energy efficiency and dissipated power conform the set of efficiency metrics. Hence, a metric framework for MSR's locomotion was presented. The use of this framework is oriented to spatial motion of modular snake robots.
Stock Market Prediction from News on the Web and a New Evaluation Approach in Trading

The market analysis is one of the important tasks for text mining. Many researchers have proposed methods using text information for analyzing the market. In this situation, news on the Web has an important role to predict stock prices. In this paper, we propose a method to predict the Nikkei Stock Average, which is one of the most important stock market indexes. We also focus on the evaluation of the prediction. In general, the results are evaluated by some criteria such as recall and precision rates. However, the most important point in the stock market prediction task is not always the accuracy of classifiers. We demonstrate the effectiveness of our method with simulated trading on a real stock market. We compare some strategies for the trading, and then discuss relations between the accuracy of classifiers and profit-and-loss. For the purpose, we introduce a criterion computed from the property change graph in each demo-trading. We call it CPC (Criterion based on Property Changes). By using the criterion CPC, we can easily understand the effectiveness of one-day classifiers in terms of the real trading situation.
Memory array protection: Check on read or Check on Write?

This work introduces Check-on-Write: a memory array error protection approach that enables a trade-off between a memory array's fault-coverage and energy. The presented approach checks for error in a value stored in an array before it is overwritten rather than, as currently done, when it is read (check-on-read). This aims at reducing the number and energy of error code checks. This lazy protection approach can be used for caches in systems that support failure-atomicity to recover from corrupted state due to a fault. The paper proposes and evaluates an adaptive memory protection scheme that is capable of both check-on-read and check-on-write and switches between the two protection modes depending on the energy to be saved and fault coverage requirements. Experimental analysis shows that our technique reduces the average dynamic energy of the L1 instruction cache tag and data arrays by 18.6% and 17.7% respectively. For the L1 data cache, this is 17.2% and 2.9%, and the savings are 13.4% for the L2 tag array. The paper also quantifies the implications of the proposed scheme on fault-coverage by analyzing the mean-time-to-failure as a function of the transient failure rate.
Analysis of the upper massif of the craniofacial with the radial method – practical use

Introduction The analysis of the upper massif of the craniofacial (UMC) is widely used in many fields of science. The aim of the study was to create a high resolution computer system based on a digital information record and on vector graphics, that could enable dimension measuring and evaluation of craniofacial shape using the radial method. Material and methods The study was carried out on 184 skulls, in a good state of preservation, from the early middle ages. The examined skulls were fixed into Molisson's craniostat in the author's own modification. They were directed in space towards the Frankfurt plane and photographed in frontal norm with a digital camera. The parameters describing the plane and dimensional structure of the UMC and orbits were obtained thanks to the computer analysis of the function recordings picturing the craniofacial structures and using software combining raster graphics with vector graphics. Results It was compared mean values of both orbits separately for male and female groups. In female skulls the comparison of the left and right side did not show statistically significant differences. In male group, higher values were observed for the right side. Only the circularity index presented higher values for the left side. Conclusions Computer graphics with the software used for analysing digital pictures of UMC and orbits increase the precision of measurements as well as the calculation possibilities. Recognition of the face in the post mortem examination is crucial for those working on identification in anthropology and criminology laboratories.
DualNet : A Coordinated View Approach to Network Visualization

Visualizing network data, from tree structures to fully connected graphs, is a difficult problem in information visualization. A large part of the problem is that in network data, you not only have to visualize the attributes specific to each data item, but also the attributes of links specifying how those items relate to each other. Current approaches to resolving these difficulties focus on clustering, filtering and using various layout methods. Such approaches, however, do not allow users to cross reference different aspects of the data with each other. In this paper, we present a tool called DualNet which addresses this problem by allowing users to navigate multiple coordinated views of the same network. We evaluate the tool with a case study involving an email communication network and find that multiple coordinated views improve navigation and provide additional insight in networks with multiple node and link types.
Unified path planner for parking an autonomous vehicle based on RRT

Maneuvering autonomous vehicles in constrained environments, such as autonomous vehicle parking, is not a trivial task and has received increasing attention from both the academy and industry. However, the traditional methods divide the problem into parallel parking, perpendicular parking, and echelon parking, then different methods are applied for the parking motion planning. In this paper a Rapidly-exploring Random Tree (RRT) based path planner is implemented for autonomous vehicle parking problem, which treats all the situations in a unified manner. As the RRT method sometimes generates some complicated paths, a smoother is also implemented for smoothing generated paths. The proposed algorithm is verified in simulation and generates applicable solutions for the proposed application scenarios.
Image Recognition System using Geometric Matching and Contour Detection

Image recognition plays an important role in a wide range of applications from biomedical imaging and security systems to scene surveillance and many other fields. This document presents the representation of the recognition of two images through the process of geometric comparison. The geometric comparison is performed by comparing the image with a template through the processes of edge detection, scaling, contour matching and RGB to grayscale conversion. The software utilized is NI vision which is one of applications of the National Instrument’s LabVIEW, used for the image and video processing functions.