Miracle-dz/UniFAR-FTUs huggingface dataset:
Transactive Goal Dynamics

Transactive goal dynamics (TGD) theory conceptualizes 2 or more interdependent people as 1 single self-regulating system. Six tenets describe the nature of goal interdependence, predict its emergence, predict when it will lead to positive goal outcomes during and after the relationship, and predict the consequences for the relationship. Both partners in a TGD system possess and pursue self-oriented, partner-oriented, and system-oriented goals, and all of these goals and pursuits are interdependent. TGD theory states that relationship partners’ goals, pursuit, and outcomes affect each other in a dense network of goal interdependence, ultimately becoming so tightly linked that the 2 partners are most accurately conceptualized as components within a single self-regulating system.
Estimation with quantized measurements

An algorithm is described which estimates the state of a linear system from quantized measurements of the output of that system. The estimator is an unbiased minimum variance estimator which is constrained to be recursive. The form of the estimator is linear in terms of the innovation, although the gain does depend on past measurements. The basic estimator is a time-varying filter; a stationary estimator, whose gain is computed prior to the processing of any measurements, is also presented. The performance of this quantized data filter is compared with the performances of both a Kalman filter operating on the linear output and a Kalman filter which processes quantized data. The quantized data filter results in significant performance improvements when a coarse quantization characteristic with few levels is used.
Art and Artificial Life – a Primer

It was not until the late 1980s that the term ‘Artificial Life’ arose as a descriptor of a range of (mostly) computer based research practices which sought alternatives to conventional Artificial Intelligence methods as a source of (quasi-) intelligent behavior in technological systems and artifacts. These practices included reactive and bottom-up robotics, computational systems which simulated evolutionary and genetic processes, and are range of other activities informed by biology and complexity theory. A general desire was to capture, harness or simulate the generative and ‘emergent’ qualities of ‘nature’ - of evolution, co-evolution and adaptation. ‘Emergence’ was a keyword in the discourse. Two decades later, the discourses of Artificial Life continues to have intellectual force, mystique and generative quality within the ‘computers and art’ community. This essay is an attempt to contextualise Artificial Life Art by providing an historical overview, and by providing background in the ideas which helped to form the Artificial Life movement in the late 1980s and early 1990s. This essay is prompted by the exhibition Emergence –Art and Artificial Life (Beall Center for Art and Technology, UCI, December 2009) which is a testament to the enduring and inspirational intellectual significance of ideas associated with Artificial Life.
Combining of random forest estimates using LSboost for stock market index prediction

This research work emphases on the prediction of future stock market index values based on historical data. The experimental evaluation is based on historical data of 10 years of two indices, namely, CNX Nifty and S&P Bombay Stock Exchange (BSE) Sensex from Indian stock markets. The predictions are made for 1–10, 15, 30, and 40 days in advance. This work proposes to combine the predictions/estimates of the ensemble of trees in a Random Forest using LSboost (i.e. LS-RF). The prediction performance of the proposed model is compared with that of well-known Support Vector Regression. Technical indicators are selected as inputs to each of the prediction models. The closing value of the stock price is the predicted variable. Results show that the proposed scheme outperforms Support Vector Regression and can be applied successfully for building predictive models for stock prices prediction.
EFFECT OF USING STEEL SLAG AGGREGATE ON MECHANICAL PROPERTIES OF CONCRETE

This study presents an evaluation of the physical and mechanical properties and characteristics of steel slag aggregate concrete in comparison with the typical crushed limestone stone aggregate concrete. Hardened concrete consist of more than 70% aggregate due to the high demand in building construction and the increase of the amount of disposed waste material, suppliers and researchers are exploring the use of alternative materials which could preserve natural sources and save the environment. In this study, steel slag was used as an aggregate replacement in conventional concrete mixes. Steel slag which is mainly consists of calcium carbonate is produced as a by-product during the oxidation process in steel industry. Steel slag was selected due to its characteristics, which are almost similar to conventional aggregates and the fact that it is easily obtainable as a by-product of the steel industry. As a result, utilization of steel slag will save natural resources and clean environment. Furthermore, results have shown that slag aggregate has better abrasion factor and impact value than conventional aggregate. Thorough investigation of the results have indicated that the amount of increase in compressive strength at age of 7 days are much more than that of age 28 days for all types of aggregate replacement. This indicates that the added slag could work as accelerator at early age while at 28 days age, the effect is reduced. The fine slag replacement scores the highest effect.
Regulating call blocking of mobile routers in wireless cellular networks

Onboard mobile networking is a new communica- tion paradigm where in-vehicle mobile router (MR) connects a large number of passengers to the Internet via cellular (or satellite) networks. All communication to and from the public transport is transparently handled by the MR. In this commu- nication model, a call blocking of the MR would immediately disrupt on-going sessions of potentially large number of on- board passengers. This observation motivates us to investigate techniques that can reduce, and possibly regulate, call blocking probability of MRs. In this paper, we investigate two different techniques to achieve this objective. The first technique, called ca- pacity reservation (CR), reserves a portion of the total base station capacity for exclusive use by the MRs, thus giving them priority over other calls. In the second technique, called probabilistic admission control (PAC), no capacity is reserved, but other on- going calls in the base station can be interrupted to accommodate arrival of MR calls. PAC regulates the interruptions in the system by probabilistically admitting other calls. Performance of our control algorithms are evaluated and compared by discrete event simulation.
Arstieetikat kujundanud dokumendid ja ajavoolud

Artikli sissejuhatavas osas on kasitletud arsti- ja meditsiinieetika maaratlusi ja vajalikkust ning soovitatud neid kutse-eetika kulgi teineteisest eristada. Kirjutise keskseks teemaks on arstieetika alusena aegade jooksul toiminud kultuuriliste ja tervishoiupoliitiliste asjaolude ning mojurite (haiguse moiste, Hippokratese vanne, ristiusk, tsunftihuvid, riigipoliitika, Maailma Arstide Liidu tegevus, patsiendioiguste liikumine ja Euroopa Noukogu tegevus) tutvustus ja nende tahtsuse kirjeldamine. Lahemalt on vaadeldud haiguse moiste kompleksset tahendust ja selles sisalduvaid eetilisi aspekte ning kasitletud arvamusi Hippokratese vande tahtsuse kohta eri ajastutel. Uhtekokku annab artikkel pogusa ulevaate arstieetika ajaloolisest kujunemisest, ehkki arstivannete, eetikakoodeksite ja deklaratsioonide sisu on vaid piiratud ulatuses edasi antud. Viimase teemana on arutletud Eestis praegu kehtiva arstieetika koodeksi taustal inimelu hoidmise kui uhe arstieetika peakusimuse ule. Eesti Arst 2013; 92(7):392–396
A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition

The curse of dimensionality is a well-established phenomenon. However, the properties of high dimensional data are often poorly understood and overlooked during the process of data modelling and analysis. Similarly, how to optimally fuse different modalities is still a big research question. In this paper, we addressed these challenges by proposing a novel two level brain-inspired compression based optimised multimodal fusion framework for emotion recognition. In the first level, the framework extracts the compressed and optimised multimodal features by applying a deep convolutional neural network (CNN) based compression on each modality (i.e. audio, text, and visuals). The second level simply concatenates the extracted optimised and compressed features for classification. The performance of the proposed approach with two different compression levels (i.e. 78% and 98%) is compared with late fusion (class level-1 dimension, class probabilities level-4 dimension) and early fusion (feature level-72000 dimension). The simulation results and critical analysis have demonstrated up to 10% and 5% performance improvement as compared to the state-of-the-art support vector machine (SVM) and long-short-term memory (LSTM) based multimodal emotion recognition systems respectively. We hypothesise that there exist an optimal level of compression at which optimised multimodal features could be extracted from each modality, which could lead to a significant performance improvement.
On the conduction mechanism in polycrystalline silicon thin-film transistors

Physical and electrical analyses were carried out on n-channel polycrystalline silicon thin-film transistors (nTFTs) with active regions as thin as approximately 6 nm. Such thin active regions extinguish the dominating effects of anomalous leakage and allow the conduction energy barrier height to be analyzed as a function of gate voltage in the femtoampere source/drain current regime. Grain size statistics were determined using plan view transmission electron microscopy. It is shown for the first time that in the absence of anomalous leakage, the barrier height does not decrease with decreasing gate voltage. In addition, the maximum measured barrier height is almost independent of active region thickness and grain size statistics. The source/drain current at low lateral field and high vertical field is also independent of channel length for all devices with length varied over an order of magnitude. These important discrepancies with existing TFT conduction theory are discussed within a physics-based model that addresses the effects of disorder-induced localized electron states in the bandgap. Besides describing existing data and well-known TFT behavioral trends, the model predicts a previously unknown relationship between threshold voltage variation, average threshold voltage and the number of grains in the channel. Analysis of data gathered from hundreds of devices of different dimensions across three different grain size distributions not only leads to agreement with the model but also to a remarkable universal behavior linking electrical and physical properties. This study shows the physics of polycrystalline silicon TFT conduction to be of the same form as amorphous and single crystal devices with the degree of disorder as the sliding scale between the two extremes.
Mobility aware application manager for mobile networks

Mobility aware applications have been proposed several times in the past in order to compensate for the weakness of the standard IP model in a mobile environment. Such applications are aware of the network conditions and are able to adapt themselves to such variable conditions. They can even get involved into flow routing and interface management. The solutions proposed by literature are mainly related to applications embedded into mobile nodes. This paper proposes a novel architecture that takes into account mobile network specificities and aims to propose a unified common interface for these applications.
No . 2013 : 11 Concurrent Data Structures for Efficient Streaming Aggregation

In this paper, we study the problem of streaming multiway aggregation, where large data volumes are received from multiple input streams. Multiway aggregation is a fundamental computational component in data stream management systems, requiring lowlatency and high throughput solutions. We focus on the problem of designing concurrent data structures for achieving low-latency and high throughput multiway aggregation; an issue that has been overlooked in the literature. Data structures act as articulation points between pipeline stages of streaming aggregation, supporting parallelism and balancing the work between the aggregate stages. By studying the use and limitations of existing aggregate designs and the data structures they use, we motivate the need for new ones. We present two new concurrent data structures and their lock-free linearizable implementations, supporting both order-sensitive and order-insensitive aggregate functions. We also present an extensive evaluation, based on a variety of aggregation queries on two large datasets, one with data extracted from SoundCloud, a music social network, and one with data from a smart grid metering network. In all the experiments, the proposed data structures and methods improved the aggregation performance significantly, up to one order of magnitude, in terms of both processing throughput and latency over the commonly-used techniques based on queues.
Model-Based Dead Time Optimization for Voltage-Source Converters Utilizing Silicon Carbide Semiconductors

Dead time significantly affects the reliability, power quality, and efficiency of voltage-source converters. For silicon carbide (SiC) devices, considering the high sensitivity of turn-off time to the operating conditions (> 5× difference between light load and full load) and characteristics of inductive loads (> 2× difference between motor load and inductor), as well as large additional energy loss induced by the freewheeling diode conduction during the superfluous dead time (∼15% of the switching loss), then the traditional fixed dead time setting becomes inappropriate. This paper introduces an approach to adaptively regulate the dead time considering the current operating condition and load characteristics via synthesizing online monitored turn-off switching parameters in the microcontroller with an embedded preset optimization model. Based on a buck converter built with 1200-V SiC MOSFETs, the experimental results show that the proposed method is able to ensure reliability and reduce power loss by 12% at full load and 18.2% at light load (8% of the full load in this case study).
ReviewA Unified Theory of Gene Expression of metabolic enzymes are often regulated directly by

with other components of the transcription machinery, Cheshire SK10 4TJ promote access to DNA and facilitate the recruitment United Kingdom of the RNA polymerase enzymes to the transcriptional 2 Howard Hughes Medical Institute start site. Three RNA polymerases function in eukaryDivision of Nucleic Acids Enzymology otes (RNAP I, II, and III). Transcription of protein-coding Department of Biochemistry genes is catalyzed by RNAP II. In this review, we will University of Medicine and Dentistry of New Jersey focus on the expression of genes transcribed by RNAP Robert Wood Johnson Medical School II, although many of the basic principles apply to the Piscataway, New Jersey 08854 other polymerases.
P2A-8 Fully Automatic Detection of Left Ventricular Long Axis and Mitral Valve Plane in 3D Echocardiography

Automated segmentation approaches for the left ventricle (LV) in real-time 3D echocardiography (RT3DE) often rely on manual initialization. So far, little effort has been put in automating the initialization procedure to get to a fully automatic segmentation approach We propose a fully automatic method for the detection of the LV long axis (LAX) and the mitral valve plane (MVP) over the full cardiac cycle, for the initialization of segmentation algorithms in 3DE. It assigns probabilities to candidate LV center points through a Hough transform for circles, and detects the LV LAX by combining dynamic programming detections on these probabilities in 3D and 2D + time, to obtain a time-continuous solution. Subsequently, the mitral valve plane is detected in a projection of the data on a plane through the previously detected LAX. The method easily adjusts to different acquisition routines and combines robustness with good accuracy and low computational costs. Automatic detection was evaluated using patient data acquired with the Fast Rotating Ultrasound (FRU-) transducer (11 patients) and with the Philips Sonos 7500 ultrasound system with the X4 matrix transducer (14 patients). For the FRU data, the LAX was estimated with a distance of 2.85 plusmn 1.70 mm (Av plusmn SD) and an angle of 5.25 plusmn 3.17 degrees; the mitral valve plane was estimated with a distance of -1.54 plusmn 4.31 mm. For the matrix data these distances were 1.96 plusmn 1.30 mm with an angle error of 5.95 plusmn 2.11 and -1.66 plusmn 5.27 mm for the mitral valve plane. These results confirm that the method is very well suitable for automatic detection of the LV LAX and MVP. It provides a basis for further automatic exploration of the LV and could therefore replace manual initialization of 3D segmentation approaches.
Transient radiation by periodic structures: accuracy of the (time domain-floquet wave)-FDTD algorithm

Author(s): Marrocco, G; Capolino, F | Abstract: Transient radiation by periodic structures using a time domain (TD) transmission line network formalism based on the recently developed time-domain Floquet-wave (TD-FWs) is analyzed. The efficiency and the accuracy of the given method depend on the dimension of the finite-difference time-domain (FDTD) computational domain and, on how many FW modes may be used in the signal reconstruction within the frequency range of interest. This paper emphasizes the accuracy problem by numerical analysis of a simple periodic structure whose analytical solution can be easily computed, and a frequency selective surface (FSS).
Asthma screening of inner city and urban elementary school-aged children

Abstract Objective: Currently, in the United States there is a lack of a standardized method to effectively screen school children with undiagnosed or poorly controlled asthma. The purpose of this proof-of-concept study was to assess the use of the American College of Allergy, Asthma, and Immunology’s (ACAAI) Asthma Screening Questionnaire to identify elementary school-age children at risk for asthma (undiagnosed) or poorly controlled asthma. Methods: Children in grades 3–5 from one urban and two suburban schools completed ACAAI’s 14 question asthma screening questionnaire and had their peak expiratory flow (PEF) measured. Children were considered to have a positive asthma screen and be at risk for having undiagnosed or poorly controlled asthma if they answered ‘yes’ to more than three questions. Children were referred to a physician if they had a positive asthma screen, a previous history of asthma, or a low PEF. Results: Of the 86 participants, 52 were identified as being at risk for asthma. The number was higher among children attending an urban versus suburban school (p = 0.04). The sensitivity and specificity of the screening questionnaire for identifying asthma risk were 90% and 66%, respectively, when the number of ‘yes’ responses for a positive screen was increased from three to five of 14 questions. Conclusions: The ACAAI’s Asthma Screening Questionnaire identified 52 children at risk for undiagnosed or poorly controlled asthma. Our findings support the need to validate this questionnaire to be used in conjunction with PEFR for identifying elementary school children at risk for asthma.
Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements

Many computer vision and image processing applications rely on local features. It is well-known that motion blur decreases the performance of traditional feature detectors and descriptors. We propose an inertial-based deblurring method for improving the robustness of existing feature detectors and descriptors against the motion blur. Unlike most deblurring algorithms, the method can handle spatially-variant blur and rolling shutter distortion. Furthermore, it is capable of running in real-time contrary to state-of-the-art algorithms. The limitations of inertial-based blur estimation are taken into account by validating the blur estimates using image data. The evaluation shows that when the method is used with traditional feature detector and descriptor, it increases the number of detected keypoints, provides higher repeatability and improves the localization accuracy. We also demonstrate that such features will lead to more accurate and complete reconstructions when used in the application of 3D visual reconstruction.
Optimal reconfiguration and distributed generator allocation in distribution network using an advanced adaptive differential evolution

Power loss in an electrical network is unavoidable due to its inherent resistance. However, for economical and efficient operation, the network loss shall be minimized to the extent possible. Construction of the distribution network is usually closed loop, though operation is radial with opening of a suitable sectionalizing switch that disconnects a branch in the loop. This process of reconfiguration i.e. selection of sectionalizing switch is done in a way such that system loss in minimized. Another effective way of reducing power loss is addition of distributed generators (DGs) locally to the system nodes (buses). DG size and location also need to be optimized for minimization of real power loss. This paper presents an application of a metaheuristic to simultaneously allocate DGs and perform reconfiguration of a couple of standard radial distribution networks. Both location and placement of the DG are optimized by the algorithm. As an obvious fact, the optimization problem is a combination of discrete (location) and continuous (rating) variables. Linear population size reduction technique of success history based adaptive differential evolution (L-SHADE) is implemented to perform the optimization task with objective of minimizing network real power loss. The algorithm is tested on standard IEEE 33-bus and 69-bus radial distribution networks. The simulation results are found to be promising and highly competitive when compared with results of other equivalent algorithms.
Gait Analysis on the move: The Infinite Gait Walkway

In order to analyze human gait patterns, highly accurate data must be collected at high frame rates. The state of the art is to deploy a carpet-like structure instrumented with pressure sensors, which allows for measuring position, orientation and pressure of each foot at each step. Since such gait “walkway carpets” are highly expensive1 and also limited in length, we propose an alternative in the form of a wheeled walker equipped with a consumer depth camera. We have designed and implemented algorithms that derive the same set of parameters from the depth data as in a gait walkway system, however without the need for the physical presence of a walkway carpet. Moreover, we are able to provide additional information, due to continuous observation of the gait cycle, i.e. not only when the user steps on the ground. In order to retrieve actual foot pressure information, we use a shoe insole sensor. Our experiments show that the system is able to collect gait relevant data with sufficient accuracy and frame rates. While the feet's position accuracy depends primarily on the noise of the depth sensor and is typically at a precision of less than 3 mm, the orientation accuracy is around 1-2 degrees for typical foot orientations.