Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Building Virtual Community for Ambient Assisted Living

Elder people are becoming a predominant aspect of our societies. As such, solutions both efficacious and cost-effective need to be sought. This paper proposes a design to construct a virtual ambient assisted living community where dwellers make contributions to the community so as to best utilize resources and minimize costs. We use service oriented architecture (SOA) to orchestrate the available resources inside the community, thus bringing social intelligence to the social computing. We also propose building such a virtual community making use of virtual reality and in the form of serious game [Stuart Rory, 1996]. Daily activities and instruments (such as sensors, cameras, etc.) in real-life may be translated into their virtual community equivalents, and activities happening in the virtual world will trigger corresponding actions in the real world, so that inter-reality may be obtained through this virtual community. We expect such a virtual community could help not only efficiently utilizing the social resources in maintaining the independent living of the elderly people, but also helping these people maintain their connections to the society and bring them entertainment, so that the quality of their living standard may be improved at the same time.
Application of iterative fast Fourier transform for fault finding in linear array antenna with various fault percentage

In this paper, the detection of faulty elements in a linear antenna array with different combination of faulty element; is presented. The task of finding faulty element position and its level of fault in antenna arrays has been solved by using Iterative Fast Fourier Transform (IFFT) technique. A Chebyshev antenna array of 30 elements with specific sidelobe level (SLL) is considered as the basic antenna array and the developed formulation is tested on it. Various combinations of failure have been considered in this work and successfully detected using the developed methodology. All the Simulated results has been explained, tabulated and presented with different figures successfully.
A time series kernel for action recognition

We address the problem of action recognition by describing actions as time series of frames and introduce a new kernel to compare their dynamical aspects. Action recognition in realistic videos has been successfully addressed using kernel methods like SVMs. Most existing approaches average local features over video volumes and compare the resulting vectors using kernels on bags of features. In contrast, we model actions as time series of per-frame representations and propose a kernel specifically tailored for the purpose of action recognition. Our main contributions are the following: (i) we provide a new principled way to compare the dynamics and temporal structure of actions by computing the distance between their auto-correlations, (ii) we derive a practical formulation to compute this distance in any feature space deriving from a base kernel between frames and (iii) we report experimental results on recent action recognition datasets showing that it provides useful complementary information to the average distribution of frames, as used in state-of-the-art models based on bag-of-features.
Survey on Computer Representations of Trees for Realistic and Efficient Rendering

This paper gives an overview of computer graphics representations of trees commonly used for the rendering of complex scene of vegetation. Looking for the right compromise between realism and efficiency has lead researchers to consider various types of geometrical plant models with different types of complexity. To achieve realist plant model, a complex structure of plant with full details is generally considered. In contrast, to promote efficiency, other approaches summarize plant geometry with few primitives allowing rapid rendering. Finally, to find a good compromise, structures with adaptive complexity are defined. Theses different types of representations and the ways to use them are presented, classified and discussed. The proposed classification principles rely on the type of structural details used in the plants representations. Characterization of all these methods is completed with various additional criteria including rendering primitive type, distance validity, interactive possibilities, animation ability and lighting properties.
Suppression of Methane Gas Emissions and Analysis of the Electrode Microbial Community in a Sediment-Based Bio-Electrochemical System

The effects of bioelectrochemical systems (BESs) for the suppression of methane gas emissions from sediment were examined using a laboratory-scale reactor system. Methane gas emissions from acetate were suppressed by approximately 36% from control based on the installation of a BES in which carbon-graphite electrodes were buried in sediment and arbitrarily set at certain oxidative potentials (+300 mV vs Ag/AgCl) using a potentiostat. Meanwhile, methane gas emissions increased in the BES reactor where the electrode potential was set at -200 mV. Results obtained from pyrotag sequencing analysis of the microbial community on the surface of the buried electrodes targeting 16S rRNA genes demonstrated that the genusGeobacterhad drastically propagated in a sample from the reactor where the electrodes were buried. Quantitative analysis of 16S rRNA genes of archaea also revealed that the archaeal population had decreased to approximately 1/6 of its original level on the electrode of the BES set at +300 mV. This implied that the oxidation-reduction potential (ORP) in the sediment was raised to the inhibition level for methanogenesis in the vicinity of the buried electrode. Analysis of electron flux in the experiment revealed that electrons intrinsically used for methanogenesis were recovered via current generation in the sediment where a potential of +300 mV was set for the electrode, although most electrons donated from acetate were captured by oxygen respiration and other electron-accepting reactions. These results imply that BES technology is suitable for use as a tool for controlling re-dox-dependent reactions in natural environments, and that it also brought about changes in the microbial population structure and methanogenic activity in sediment.
Cattell-Horn-Carroll (CHC) Definition Project

Based on Carroll's (1993) treatise on the factor structure of human cognitive abilities, McGrew (1997) abstracted brief definitions of the narrow and broad CHC abilities. These definitions have now been revised, expanded, and clarified in the table below. The revised "working" definitions are based on a review of ability definitions from a variety of sources, including Carroll (1993), the original ETS Factor Reference Work group publications (Ekstrom et al., 1979), the Encyclopedia of Human Intelligence (Sternberg, 1994), the Dictionary of Psychology (Corsini, 1999), and recent published research.
Innovation, Spillovers and Productivity Growth: A Dynamic Panel Data Approach

This paper examines variation in productivity growth within a given location and between different locations. Implementing a dynamic panel data approach on Swedish micro data, we test the separate and complementary effect of internal innovation efforts and spillovers from the local milieu. Measuring the potential knowledge spillover by access to knowledgeintensive services, the estimation results produce strong evidence of differences in the capacity to benefit from external knowledge among persistent innovators, temporary innovators and non-innovators. The results are consistent regardless of whether innovation efforts are measured in terms of the frequency of patent applications or R&D investments see above see above
HUNDRED THOUSAND DEGREE GAS IN THE VIRGO CLUSTER OF GALAXIES

The physical relationship between low-excitation gas filaments at ∼104 K, seen in optical line emission, and diffuse X-ray emitting coronal gas at ∼107 K in the centers of many galaxy clusters is not understood. It is unclear whether the ∼104 K filaments have cooled and condensed from the ambient hot (∼107 K) medium or have some other origin such as the infall of cold gas in a merger, or the disturbance of an internal cool reservoir of gas by nuclear activity. Observations of gas at intermediate temperatures (∼105–106 K) can potentially reveal whether the central massive galaxies are gaining cool gas through condensation or losing it through conductive evaporation and hence identify plausible scenarios for transport processes in galaxy cluster gas. Here we present spectroscopic detection of ∼105 K gas spatially associated with the Hα filaments in a central cluster galaxy, M87, in the Virgo Cluster. The measured emission-line fluxes from triply ionized carbon (C iv 1549 Å) and singly ionized helium (He ii 1640 Å) are consistent with a model in which thermal conduction determines the interaction between hot and cold phases.
Brachial Artery Constriction during Brachial Artery Reactivity Testing Predicts Major Adverse Clinical Outcomes in Women with Suspected Myocardial Ischemia: Results from the NHLBI-Sponsored Women’s Ischemia Syndrome Evaluation (WISE) Study

Background Limited brachial artery (BA) flow-mediated dilation during brachial artery reactivity testing (BART) has been linked to increased cardiovascular risk. We report on the phenomenon of BA constriction (BAC) following hyperemia. Objectives To determine whether BAC predicts adverse CV outcomes and/or mortality in the women’s ischemic Syndrome Evaluation Study (WISE). Further, as a secondary objective we sought to determine the risk factors associated with BAC. Methods We performed BART on 377 women with chest pain referred for coronary angiography and followed for a median of 9.5 years. Forearm ischemia was induced with 4 minutes occlusion by a cuff placed distal to the BA and inflated to 40mm Hg > systolic pressure. BAC was defined as >4.8% artery constriction following release of the cuff. The main outcome was major adverse events (MACE) including all-cause mortality, non-fatal MI, non-fatal stroke, or hospitalization for heart failure. Results BA diameter change ranged from -20.6% to +44.9%, and 41 (11%) women experienced BAC. Obstructive CAD and traditional CAD risk factors were not predictive of BAC. Overall, 39% of women with BAC experienced MACE vs. 22% without BAC (p=0.004). In multivariate Cox proportional hazards regression, BAC was a significant independent predictor of MACE (p=0.018) when adjusting for obstructive CAD and traditional risk factors. Conclusions BAC predicts almost double the risk for major adverse events compared to patients without BAC. This risk was not accounted for by CAD or traditional risk factors. The novel risk marker of BAC requires further investigation in women.
Efficient segmentation and plane modeling of point-cloud for structured environment by normal clustering and tensor voting

In this paper, we introduce an efficient point-cloud segmentation algorithm, inspired by efficient segmentation (also named as super-pixel extraction). It uses parameterised “normal words” as distance measures, which are obtained by clustering of surface normals. We estimate the surface normals by the sparse tensor voting framework, which enables adaptive structural extraction, even for the case of missing points. The output result is consist of labeled point representations regarding plane assumptions, which is validated by metrics based on information theory. We show the quality of the segmentation results by experiments on real datasets, and demonstrate its potentials in aiding 2.5D topological navigation for structured environments.
Neural Crest-Derived Mesenchymal Cells Require Wnt Signaling for Their Development and Drive Invagination of the Telencephalic Midline

Embryonic neural crest cells contribute to the development of the craniofacial mesenchyme, forebrain meninges and perivascular cells. In this study, we investigated the function of ß-catenin signaling in neural crest cells abutting the dorsal forebrain during development. In the absence of ß-catenin signaling, neural crest cells failed to expand in the interhemispheric region and produced ectopic smooth muscle cells instead of generating dermal and calvarial mesenchyme. In contrast, constitutive expression of stabilized ß-catenin in neural crest cells increased the number of mesenchymal lineage precursors suggesting that ß-catenin signaling is necessary for the expansion of neural crest-derived mesenchymal cells. Interestingly, the loss of neural crest-derived mesenchymal stem cells (MSCs) leads to failure of telencephalic midline invagination and causes ventricular system defects. This study shows that ß-catenin signaling is required for the switch of neural crest cells to MSCs and mediates the expansion of MSCs to drive the formation of mesenchymal structures of the head. Furthermore, loss of these structures causes striking defects in forebrain morphogenesis.
Detecting Local Events by Analyzing Spatiotemporal Locality of Tweets

In this paper, we study how to detect local events regardless of the size and the type using Twitter, a social networking service. Our method is based on the observation that relevant tweets are simultaneously posted from the place where a local event is happening. Specifically, our method first extracts the place where and the time when multiple tweets are posted by using clustering techniques and then detects the co-occurrence of key terms in each cluster to find local events. For determining key terms, our method also leverages spatiotemporal locality of tweets. From experimental results on tweet data from 9:00 to 15:00 on October 9, 2011, we confirmed the effectiveness of our method.
Aggressive Optimal Control for Agile Flight with a Slung Load

A possible design method for learning motion control consists of using a model-based optimal control algorithm to initialize the policy of a sampling based reinforcement learning algorithm. In this paper, the initial control trajectory design is performed for a quadrotor with a cable-suspended load using the iterative LQG (iLQG) algorithm. The hybrid model of the quadrotor with the load is introduced, and four sample tasks are presented. These tasks consist of a simple waypoint task as well as a task where the quadrotor and the load have to pass through a small window. The window task requires more aggressive control, exploiting the underactuated system dynamics including system mode switches, where the load is in free fall for some period of time.
Impact of channel estimation error upon sum-rate in amplify-and-forward two-way relaying systems

In this work, we consider the amplify-and-forward (AF) two-way relay network where the two terminals TA, TB exchange their information through a relay node TR in a bi-directional manner and study the impact of the training-based channel estimation upon individual and sum-rate of the two users. We assume that in the multiple-access (MA) phase TA, TB initiate transmission by sending their training symbols to TR, and in the broadcasting (BC) phase TR initiates transmission by sending its own training symbol, followed by an amplified version of the signal received in MA phase. This training symbol facilitates TA and TB to perform self-interference suppression and to estimate the cascaded overall relay channel required for recovery of the data of interest. We derive lower bounds on the training-based individual rates and sum-rate of the two users and investigate the impact of channel estimation errors upon the sum-rate lower bound. Under the total transmit power constraint, we search for the optimal power allocation among the three nodes and optimal power allocation between data and training such that the sum-rate lower bound is maximized. Furthermore, we discuss the relationship between the optimal solutions and the relay location.
Personalising on-line information retrieval support with a genetic algorithm

A genetic algorithm is described that models changing user i nt ests in an on-line information retrieval support system. User interests are represented as a population of qu eries which are issued to a World-Wide Web search engine. User feedback on the queries and their results provi des the fitness of each query. A single point crossover operator recombines query terms and two mutation operators replace query terms with randomly selected words and their synonyms, respectively. Initial user testing has shown that the GA approach is more ef fective in a simple learning task than a non-GA approach.
Chinese Evaluative Information Analysis

Together with the ever-growing amount of Chinese web data, the number of opinions voiced by Chinese users is rapidly increasing, and analyzing them is an important task. This paper introduces a Chinese Evaluative Information Analyzer (CEIA) and proposes a method to improve its performance. We use evaluative information as a unifying term for the information about attitudes, opinions, sentiments and so on. This paper makes three contributions: (i) CEIA can identify and analyze a more diverse and richer set of evaluative information than previous studies for Chinese; (ii) to implement the system, we constructed an original annotated corpus for Chinese evaluative information and built a large sentiment dictionary; (iii) we introduce syntactic dependency, semantic class and distance features to improve the evaluative information extraction. The performance of the system and the effectiveness of the newly introduced features are evaluated in a series of experiments on our Chinese evaluative information corpus. Title and Abstract in Chinese ¥ ¥' 'µ$fÂ ÂI I¤ ‐ d{X‰˚o˙¥'~iUd†—fi ,{µ$u'˝{jfiU •⁄
Multiresolution Decoding Algorithm for Walsh-Hadamard Linear Precoded OFDM

When no channel knowledge is available at the OFDM transmitter, the water pouring strategy is inappropriate and the information sent on one subchannel can irremediably be lost if a deep fade occurs. The role of uniform spreading in Linear Precoded OFDM (LP-OFDM) also known as OFDM-CDMA [1], [2] is to exploit all the frequency diversity of the channel. However, due to the intercarrier interference introduced by the precoder, more complex equalization schemes are required. This paper proposes a new Multiresolution decoding algorithm simple to implement thanks to the Walsh-Hadamard recursive structure. For a target BER, the algorithm refines the accuracy (called here resolution) of the estimated symbols based on a tree-like structured algorithm and can achieve near Maximum Likelihood performance with only two stages. Moreover, some theoretical results are provided to optimize the parameters involved in the detection process.
Evaluating the Potential of Bandwidth Estimators

Many packet probing based available bandwidth estimation techniques have been proposed recently. However, their performance evaluation procedures remain in a coarse-granular fashion, which provide little information about the sources of performance inadequacy. We initiate the effort towards finegranular performance metrics and evaluation procedures that help identify the causes of measurement errors, that can be used to retroactively optimize the design of measurement methods. As the first step to this end, we propose a metric calledsinglehop potential , to assess the capability of bandwidth estimation algorithms to reach the measurement target in an asymptotically accurate manner. We propose off-line methodology to evaluate the single-hop potential of various bandwidth estimators and show how this procedure can help improve the design of measurement techniques.
Timing information in wireless communications and optimal location verification frameworks

The verification of location information in wireless networks is a relatively new area of research, but one of growing importance. In this work we explore two formal theoretical frameworks for an optimal location verification system in which physical-layer timing information is the main observational input. In our first framework, we derive an optimal decision-rule using the system input/output mutual information as the optimization metric. In the second framework, a more traditional Bayesian approach is adopted in which the misclassification error is used as the decision-rule's optimization metric. A verification-performance comparison between time-of-arrival (ToA) information and the more easily determined received signal strength (RSS) information is given. Our key finding is that for ToA accuracies attainable in next generation wireless networks, significant improvement in location verification can be expected relative to current RSS-based techniques. Our results are important for a wide range of emerging wireless networks and services, but especially for emerging Intelligent Transport Systems (ITS), where the authentication of location information is of critical importance to the safety and security of system users.
Exploring the design space of composite visualization

We propose the notion of composite visualization views (CVVs) as a theoretical model that unifies the existing coordinated multiple views (CMV) paradigm with other strategies for combining visual representations in the same geometrical space. We identify five such strategies - called CVV design patterns - based on an extensive review of the literature in composite visualization. We go on to show how these design patterns can all be expressed in terms of a design space describing the correlation between two visualizations in terms of spatial mapping as well as the data relationships between items in the visualizations. We also discuss how to use this design space to suggest potential directions for future research.
Visual Variables in Adaptive Visualizations

Visualizations provide various variables for the adaptation to the usage context and the users. Today’s adaptive visualizations make use of various visual variables to order or filter information or visualizations. However, the capabilities of visual variables in context of human information processing and tasks are not comprehensively exploited. This paper discusses the value of the different visual variables providing beneficial and more accurately adapted information visualizations.
The ade4 Package: Implementing the Duality Diagram for Ecologists

Multivariate analyses are well known and widely used to identify and understand structures of ecological communities. The ade4 package for the R statistical environment proposes a great number of multivariate methods. Its implementation follows the tradition of the French school of "Analyse des Donnees" and is based on the use of the duality diagram. We present the theory of the duality diagram and discuss its implementation in ade4. Classes and main functions are presented. An example is given to illustrate the ade4 philosophy.
A novel visual perception enhancement algorithm for high-speed railway in the low light condition

With the rapid development of high-speed railway, the safety of railway becomes extremely important. Video is a direct and effective manner for monitoring railway environment, but it is easily affected by weather condition and ambient light. Therefore the security risks are hidden in the low light condition and difficult to identify. In this paper, we propose a new visual perception enhancement algorithm VPEA based on Illuminance-Reflectance Model for low light image, and it can be used to produce a clear image from the train-borne video in the low light condition. The experimental results show that VPEA has better practical effect on image enhancement, and VPEA will be used in railway safety check and railway facility inspection in the future.