Miracle-dz/UniFAR-FTUs huggingface dataset:
User Authentication using Temporal Information

Conventional computer systems authenticate users only at the initial log-in session, which can be the cause of a critical security flaw. To resolve this problem, systems need continuous user authentication methods that continuously monitor and authenticate users based on some biometric trait(s). We propose a new method for continuous user authentication based on a Webcam that monitors a logged in user’s face and color of clothing. Our method can authenticate users regardless of their posture in front of the workstation (laptop or PC). Previous methods for continuous user authentication cannot authenticate users without biometric observation. To alleviate this requirement, our method uses color information of users’ clothing as an enrollment template in addition to their face information. No pre-registration of biometric features are required as they are captured and saved every time the user logs in.
Sensor fault detection for fault tolerant operation of parallel manipulators

A sensor fault detection method intended to allow fault tolerant operation of parallel manipulators is introduced. A class of three-branch parallel manipulators each branch consisting of three main-arm joints supporting a mobile platform through passive spherical end-joints is considered. The method is based on comparison of forward displacement solutions for different combinations of redundant joint sensing. In simulation the fault detection scheme works without error. In application of fault detection for a three-branch hand controller the scheme is found not to be as successful. Data analysis is performed to examine the sources of algorithmic failure. It is concluded that high accuracy in the passive spherical branch end joints and low noise sensors are required to facilitate fault detection.
Optimization of a broadband vector network analyzer calibration

This paper presents a novel, three-stage approach to optimum selection of calibration standard lengths for broadband Vector Network Analyzers (VNA). First, an initial standard D-optimal calibration selection problem is reformulated such as to eliminate redundant locally optimal solutions. Second, good quality basic solution to the calibration selection problem is found, as a result of analytic investigation of the problem properties. Finally, a multistep numeric bi-criterion optimization procedure with variable frequency range is proposed to generate a set of candidate solutions, with different relationship of bandwidth and ripple of the normalized determinant of the Fisher matrix. Example results demonstrate high quality of the solutions found and high efficiency of the proposed optimization-based approach.
Applying Genetic Programming with Substructure Discovery to a Traffic Signal Control Problem

Nowadays the increase of traffic causes numerous serious traffic jams, and traffic signals are desired to work adaptively for dynamic traffic flows. In this paper, we view such a problem of traffic signal control as a multi-agent problem where each signal has a controlling agent, and aim to make the agents work cooperatively depending on the traffic status. To build such an agent program automatically, we introduce genetic programming (GP), an evolutionary method for program construction. In GP, it is known as important to encapsulate the substructures of a program which leads to higher fitness to the environment, and we propose a new encapsulation method using an efficient technique for discovering frequent substructures, which has been recently proposed in the data mining field. We also conducted a simulation with a real traffic data, and confirmed that GP with our encapsulation method outperforms the normal GP. It is also observed that the best individual has a communication part that chooses an appropriate communication area and adapts to the traffic status.
Critères biologiques d’éligibilité pour un traitement anti-EGFR

Le proteasome joue un role central de regulation des proteines activees par les recepteurs cellulaires transmembranaires. La voie du recepteur de l’EGF est cruciale dans le developpement et la progression des cancers epitheliaux. Les chimiotherapies conventionnelles, en association avec un anti-EGFR, ont un effet synergique sur l’inhibition de la croissance et l’activite pro-apoptotique qui ont active la voie autocrine dependante de EGFR a travers une inhibition de Akt plus efficace. Des resistances ont neanmoins ete observees, en particulier en cas de mutations activatrices de l’oncogene KRAS . L’inhibition d’une seule voie de signalisation est souvent inefficace, un phenomene de relais se produisant generalement par l’activation des voies alternatives. Le ciblage de la voie mTOR pourrait suppleer a la resistance aux inhibiteurs de l’EGFR. L’evaluation clinique de cette hypothese pourrait ouvrir la voie aux therapies ciblees combinees dont l’application en cancerologie pourrait depasser largement le champ du cancer colorectal.
Benchmarking Database Systems for the Requirements of Sensor Readings

Abstract Improving energy efficiency in order to reduce CO2 emissions is a permanent challenge in the European space. Smart metering could help for improving energy efficiency by offering information about the way in which the energy is used. Smart metering will be based on large volumes of sensor data, since energy monitoring will bring together sensor data from various critical areas. The main purpose of this paper was to present the selection mechanism for a scalable storage solution, based on the requirements of the DEHEMS (Digital Environment Home Energy Management System) project. With regular sensor readings coming at every 6 seconds, there is an impressive amount of data collected even for the minimal target of about 250 households, 10 sensors per user. With these huge data streams that are non-stationary time-series data, collected at discrete intervals, the DEHEMS project has to offer a solution for storing and retrieving sensor data in a responsive way. We have tested both collection speed and aggregation speed for reasonable data streams of sensor data. The tests were performed on various database models, with their associated representations, including relational databases, key-value stores, column stores, self-tuning databases, as well as time-series enabled database systems. These experiments confirmed that column stores and key-value stores perform better than relational databases, while time-series databases outperform all the others.
The Technical Aspects of Epidural Steroid Injections: A National Survey

Although epidural steroid injections (ESIs) are a common treatment for chronic pain conditions, it is not clear whether there is consensus on their technical aspects. The current literature suggests that variations in technical aspects may affect ESI outcomes. The goal of the survey was to help establish a standard frame of reference for the performance of ESIs. We analyzed survey results from 68 academic anesthesia programs and 28 private practices in the United States. The main finding in this survey is that there is no clear-cut consensus as to the ideal method to perform ESI. There is a wide variation among individual practices in almost every technical aspect of ESI. Private practices use significantly more fluoroscopy than academic centers. The large difference was found in the cervical region where 73% of private practices and only 39% of academic institutions polled perform the ESIs with fluoroscopic guidance (P = 0.005). A similar discrepancy was found in approaches to the epidural space after laminectomy where 61% of private practices, but only 15% of academic centers, use the transforaminal approach. The study results indicate that there is no consensus, and that there is a wide variation in current practices.
Direct-Drive Robots: Theory and Practice

This book describes the design concept and discusses the control issues related to the performance of a direct-drive robot, specifically, a direct-drive mechanical arm capable of carrying up to 10 kilograms, at 10 meters per second, accelerating at 5 G (a unit of acceleration equal to the acceleration of gravity). These are remarkable achievements compared to current industrial robots that move with speeds on the order of 1 meter per second. "Direct-Drive Robot "presents the most current research in manipulator design and control, emphasizing the high-performance direct-drive robot arm in which the shafts of articulated joints are directly coupled to the rotors of motors with high torque. It describes fundamental technologies of key components such as motors, amplifiers and sensors, arm linkage design, and control system design, and makes significant contributions in the areas of power efficiency analysis, dynamic mass balancing, and decoupling theory.The book provides a good balance between theory and practice, covering the practical design and implementation of this special robot as well as the theoretical design tools.Contents: Part I: Direct-Drive Technologies. Introduction. Components. Part II: Arm Design Theory. Power Efficiency. Arm Design for Simplified Dynamics. Actuator Relocation. Design of Decoupled Arm Structures. Part III: Development of the MIT Arm. Mechanisms. Control Systems. Part IV: Selected Papers on Direct-Drive Robot Design and Control.Haruhiko Asada is an Associate Professor, Kyoto University, and Lecturer at MIT He has built two prototypes of the direct-drive arm described here. Kamal Youcef-Toumi is an Assistant Professor, Department of Mechanical Engineering, System Dynamics and Controls Division at MIT. He has worked for three years with Asada on the development of the MIT high speed directdrive robot.
S2k‐Leitlinie zur Therapie der Akne

To optimize the treatment of acne in Germany, the German Society of Dermatology (DDG) and the Association of German Dermatologists (BVDD) initiated a project to develop consensus-based guidelines for the management of acne. The Acne Guidelines focus on induction therapy, maintenance therapy and treatment of post-acne scarring. They include an evaluation of the most commonly used therapeutic options in Germany. In addition, they offer detailed information on how to administer the various treatments and on contraindications, adverse drug reactions, and drug interactions, taking into account gender and special conditions such as pregnancy and lactation. The Acne Guidelines were developed following the recommendations of the Association of Scientific Medical Societies in Germany (AWMF). The treatment recommendations were developed by an expert group and finalized by an interdisciplinary consensus conference. The first choice treatments for acute acne according to acne type are as follows: 1) comedonal acne: topical retinoids; 2) mild papular/pustular acne: fixed or sequential combinations of BPO and topical retinoids or of BPO and topical antibiotics; 3) moderate papular/pustular acne: oral antibiotic plus BPO or plus topical retinoid, or in a fixed combination 4) acne papulo-pustulosa nodosa and acne conglobata: oral antibiotic plus topical retinoid plus BPO or oral isotretinoin. For maintenance treatment: topical retinoid or its combination with BPO. Particular attention should be paid to compliance and quality of life. Additional treatment options are discussed in the main body of the text.
A Three-Dimensional Object-Oriented Distributed Finite Element Solver Based on Mobile Agent Technology

We present an object-oriented distributed finite element method (FEM) solver for three-dimensional scattering problems, implemented on a network of workstations. The solution of the resulting sparse linear system is performed using the conjugate orthogonal conjugate gradient method. The entire implementation is based on the Java programming language, and the distributed solution is achieved via the use of mobile agent technology. Since the paper aims mainly to demonstrate the benefits of using Java and mobile agents as the technologies to develop complex FEM applications and implement them in a distributed environment, its main core is devoted to a thorough description of the distributed-object-oriented implementation, focusing on inter-agent communication and synchronization aspects. Numerical results are presented, which prove that our approach is a promising technique for the efficient solution of complex FEM modeling problems.
CNN cloning template: hole-filler

A CNN (cellular neural network) template for hole-filling is reported. There are many holes in Japanese characters and the CNN described can be used in addition to a connected-component-detector CNN for Japanese character recognition. It is expected that the hole-filler can probably also be used for other 2-D image recognition problems. >
Application of Virtual Network Electron Microscopy in Materials Science

This paper first introduces the combination of virtual network and electronic scanner microscope, and uses nonlinear Burgers method to establish virtual network partial differential equations and the algorithm of scanning electron microscopy, and uses MATLAB software to draw the image of algorithm. It verifies the reliability of program. Finally, by using virtual network technology of scanning electron microscopy we obtained the contrast curve diagram of polypyrrole and sulfonated graphene, the image is displayed by three dimension of the virtual network. This method is extended to the teaching arrangement of the historical course and historical events. It provides a new idea and reference for the application of computer in teaching.
Fast Adaptive Depth Estimation Algorithm Based on K-means Segmentation

A fast depth estimation algorithm based on the K-means image segmentation is proposed in this paper. Traditional global-based depth estimation methods using graph-cuts made good performance on the depth map estimation, however, the time cost is a big problem for real time application. A fast segment- based method was discussed in this paper, aiming to reduce time cost and at the same time maintain or even improve the performance of depth map estimation. Firstly, the reference image is segmented by K-means method and then mark each segment as different types. Secondly, apply different matching methods for each kind of segment to get the initial matching cost. Thirdly, correct the depth values of unreliable pixels in each segments. Finally, depth values of each segments are determined by using the final matching cost. The experience results demonstrate the superior performance of the proposed algorithm.
Etiología viral en la neumonía del adulto adquirida en la comunidad en un hospital del sur de Chile

Background There is paucity of information about viral etiology of community acquired pneumonia in adults. Aim To investigate the viral etiology of pneumonia among hospitalized patients. Material and methods All adults with pneumonia that were hospitalized were prospectively enrolled at Puerto Montt hospital. A microbiological and viral assessment was carried out. Viral assessment included direct immunofluorescence of nasopharyngeal aspirates for influenza A and B virus and serum samples obtained during the acute phase of the disease and during convalescence for Hanta virus. Results Between April 1 2005 and March 31 2006,159 adults aged 62 ± 20 years (58 % males), were admitted to the hospital for pneumonia. Mean hospital stay was 11.9 ± 8.6 days. Four patients had Hantavirus acute infection. Other viruses were identified in twelve patients (7.7%). Nine had influenza A, one syncytial respiratory virus, one syncytial and influenza A virus and one varicella zoster virus. Excluding patients with Hantavirus, no significant differences in age, clinical presentation, chest X ray findings, laboratory results and mortality were observed between patients with bacterial or viral etiology of the pneumonia. Conclusions Viral etiology was confirmed in 10% of adult patients hospitalized with community acquired pneumonia.
Neural Networks: A Review from a Statistical Perspective

This paper informs a statistical readership about Artificial Neural Networks (ANNs), points out some of the links with statistical methodology and encourages cross-disciplinary research in the directions most likely to bear fruit. The areas of statistical interest are briefly outlined, and a series of examples indicates the flavor of ANN models. We then treat various topics in more depth. In each case, we describe the neural network architectures and training rules and provide a statistical commentary. The topics treated in this way are perceptrons (from single-unit to multilayer versions), Hopfield-type recurrent networks (including probabilistic versions strongly related to statistical physics and Gibbs distributions) and associative memory networks trained by so-called unsupervised learning rules. Perceptrons are shown to have strong associations with discriminant analysis and regression, and unsupervized networks with cluster analysis. The paper concludes with some thoughts on the future of the interface between neural networks and statistics.
Color and shape classification with competing paradigms: neural networks versus trainable table classifiers

The pixel-wise classification of CCD colour Images Into previously learned colour classes at video-rate is a demanding vision task, both with regard to the complicated cluster shapes encountered in natui- al scenes and to the required computing power for real-time operation. We discuss two classical solutions based on an algorithmic statistical classifier and on a Neural Network paradigm and propose an alternative simple and low-cost classifier based on approbriately trained look-up-tables. Two different learningrules for the supervised training of this LUT classifier are presented for the colour classification of both synthetic and natural blotechno1ojr scenes. The proposed LUT classifier shows all the positive features of a (simulated) 3-layer perceptron Neural Network, but performs 60.000 times faster with simple, commercially available components.
Semantic Grid and sensor Grid: Insights into the e-Research ecosystem

Scientific researchers have often been the early adopters and co-creators of new technology. Through programmes like e-Science and cyberinfrastructure, the last decade has seen many emerging technologies harnessed for application in a range of research disciplines. Here we discuss some of the technologies that have been promoted, including Grid, Semantic Web and Web 2.0, informed by experience of a diverse range of examples. Our aim is to achieve insights into the e-Research ecosystem to guide our future journey.
Maternal cells are not resp for erythema tox neon

Letters to the Editor are welcomed for publication (subject to editing). Letters must be signed by all authors, typewritten double spaced, and must not exceed two pages of text including references. Two copies of all letters should be submitted along with one copy on disk. Letters should not duplicate material submitted or published in other journals. Prepublication proofs will not be provided.
A Design Space Exploration Algorithm Incompiling Window Operation onto Reconfigurable Hardware

Abstract Window operations which are computationally intensive and data intensive are frequently used in image compression, pattern recognition and digital signal processing. Reconfigurable hardware boards provide a convenient and flexible solution to speed up these algorithms. In this paper, we design a three-level memory structure to realize inner-loop and outer-loop data reuse in window operations completely, and use shifted registers to make hardware design simpler. Then, we present a design space exploration algorithm to get a high-performance design without going through the time-consuming hardware design process for each different algorithm. By finding the three upper bounds according to area constraints, memory bandwidth constraints and on-chip memory constraints, the block structure of the design which can fully utilize the available resources on the board is determined.
Role of maternal adiposity prior to and during pregnancy in cognitive and psychiatric problems in offspring

The purpose of this review is to summarize studies that have examined associations between maternal adiposity prior to and during pregnancy and cognitive and psychiatric problems in offspring. Of the 11 studies published since a 2011 systematic review, four examined cognitive outcomes alone, four assessed psychopathology exclusively, and three reported on both cognitive and psychiatric endpoints. Ten studies provided evidence of a link. These data suggest that the offspring of women who are overweight or obese during pregnancy are at increased risk for cognitive deficits, externalizing problems (particularly attention-deficit/hyperactivity disorder), and internalizing psychopathology in childhood and adolescence; however, the effect sizes were small to medium and a definitive causal association remains to be proven.
Clients satisfaction with family planning services and associated factors among family planning users in Hossana Town Public Health Facilities, South Ethiopia: Facility-based cross-sectional study

Client satisfaction is considered as one of the desired outcomes of health care and it is directly related with utilization of health services. It reflects the gap between the expected and the experience of the service from the client’s point of view. The objective of this study was to assess clients’ satisfaction with family planning services and associated factors. Facility-based cross-sectional study that involved an exit interview was conducted from February to March, 2014 in public health facilities in Hossana town. The data were collected from 324 respondents selected by systematic sampling technique using pre-tested structured interviewer administered questionnaire. Of the total of 324 study subjects, 75.3% of the respondents reported that they were satisfied with services they received. In multivariate analysis, satisfaction of clients was higher for women who reported their waiting time to be 30 min and less (AOR=5.5 [95% CI=1.918, 15.77]), for those whom privacy was ensured during exams and procedures (AOR=5.08 [95%CI=2.270, 11.387]), told how to use the method (AOR=3.431[1.206, 9.761]), had history of unintended pregnancy (AOR 2.803[1.058, 7.426]), repeat users (AOR=3.041[1.37, 6.737]), convenient opening hours (AOR= 4.730[1.217, 18.383]) and lower for those women who perceived health facilities not clean (AOR= 0.192[0.056, 0.658]) and those who had experienced methods side effect (AOR=0.280 [95%CI= [. 121, 0.645]. This study revealed that clients’ satisfaction with family planning service was low. The frequency of visit, waiting time, cleanness of health facilities, history of side effect, history of unintended pregnancy, and information on how to use methods, privacy during examination and procedure and convenience of opening hour were the predictors of client satisfaction. Key words: Family planning, client satisfaction, Hossana town.
A comparison of four techniques for measuring central adiposity in postpartum adolescents.

Objective : To develop a reliable office technique for measuring central body fat in postpartum adolescents, we compared: first, a direct sonographic measurement of visceral adiposity to measurements of visceral and subcutaneous abdominal adiposity by computed tomography (CT); and second, skinfold caliper and sonographic measurements of subcutaneous adipose tissue distribution to CT measurements of visceral and subcutaneous abdominal adiposity. Methods : Postpartum adipose tissue distribution was assessed in 15 teenagers by measuring the thickness of the subcutaneous fat at six body sites with skinfold calipers and ultrasound. Visceral adiposity was measured directly by ultrasound and CT. Taking the CT measurements as the standards, Pearson correlations and regression analyses were used to compare ultrasound measurement of visceral adiposity and the skinfold caliper and sonographic measurements of subcutaneous adipose tissue distribution. Results : All of the adiposity measurements correlated significantl.