Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization of Wireless Sensor Network using artificial neural network

In Wireless Sensor Networks (WSN), location estimation is important for routing efficiency and location-aware services. Traditional received signal strength based localizations using propagation-loss model are often erroneous for the low-cost WSN devices. The reason is that the wireless channel is vulnerable to so many factors that deriving the appropriate propagation-loss model for the low cost WSN devices is not possible. Hence, we propose a flexible model based on neural network and grid sensor training phase for accurate localization of sensors. Simulation results show that the location accuracy can be increased by increasing the grid sensor density and the number of access points.
A Simple Approach to Optimized Text Compression's Performance

While the basic of World Wide Web communication data almost of data still be represented by text such as data exchange in Web Services base on XML technology and storage data into relational databases. Unfortunately, these attractive of data come at the expense of performance to transfer data. A way to improve is compression technique. In this paper we present new compression algorithm using capitalization. The mechanism has 3 steps is following: Firstly, remove white space. Secondary, compressing data to UpperCamelCase capitalization style and lastly, to decompress compressed data. Our experiments have shown significant performance gains of our algorithm include reduce data size up to 22% and keep data integrity. In additionally, compressed data is easy to read and understand like naming convention in several programming language.
Decision-Level Fusion Performance Improvement From Enhanced HRR Radar Clutter Suppression

Airborne radar tracking in moving ground vehicle scenarios is impacted by sensor, target, and environmental dynamics. Moving targets can be characterized by 1-D High Range Resolution (HRR) Radar profiles with sufficient Signal-to-Noise Ratio (SNR). The amplitude feature information for each range bin of the HRR profile is used to discern one target from another to help maintain track or to identify a vehicle. Typical radar clutter suppression algorithms developed for processing moving ground target data not only remove the surrounding clutter, but a portion of the target signature. Enhanced clutter suppression can be achieved using a Multi-channel Signal Subspace (MSS) algorithm, which preserves target features. In this paper, we (1) exploit extra feature information from enhanced clutter suppression for Automatic Target Recognition (ATR), (2) present a Decision-Level Fusion (DLF) gain comparison using Displaced Phase Center Antenna (DPCA) and MSS clutter suppressed HRR data; and (3) develop a confusion-matrix identity fusion result for Simultaneous Tracking and Identification (STID). The results show that more channels for MSS increase identification over DPCA, result in a slightly noisier clutter suppressed image, and preserve more target features after clutter cancellation. The paper contributions include extending a two-channel MSS clutter cancellation technique to three channels, verifying the MSS is superior to the DPCA technique for target identification, and a comparison of these techniques in a novel multi-look confusion matrix decision-level fusion process.
Efficient k-Support-Norm Regularized Minimization via Fully Corrective Frank-Wolfe Method

The k-support-norm regularized minimization has recently been applied with success to sparse prediction problems. The proximal gradient method is conventionally used to minimize this composite model. However it tends to suffer from expensive iteration cost as the proximity operator associated with k-support-norm needs exhaustive searching operations and thus could be time consuming in large scale settings. In this paper, we reformulate the k-support-norm regularized formulation into an identical constrained formulation and propose a fully corrective Frank-Wolfe algorithm to minimize the constrained model. Our method is inspired by an interesting observation that the convex hull structure of the k-support-norm ball allows the application of Frank-Wolfe-type algorithms with low iteration complexity. The convergence behavior of the proposed algorithm is analyzed. Extensive numerical results in learning tasks including logistic regression and matrix pursuit demonstrate the substantially improved computational efficiency of our algorithm over the state-of-the-art proximal gradient algorithms.
Advances in News and Blog Analysis with Lydia

Lydia is a system for online text analysis currently focusing on news, blogs and Medline abstracts. The goal of the project is to build a relational model of people, places, and things through natural language processing of the input text and the statistical analysis of entity frequencies and juxtapositions. In this paper we describe our recent development of some new text analysis features of Lydia. This includes sentiment analysis in foreign language content, extraction of relations between entities and detection of “news storms”, i.e. spikes in popularity of entities caused by a common underlying event.
Incorrigible set distributions and unsuccessful decoding probability of linear codes

On a binary erasure channel (BEC) with erasing probability e, the performance of a binary linear code is determined by the incorrigible sets of the code. The incorrigible set distribution (ISD) {Ii}i=0n enumerates the number of incorrigible sets with size i of the code. The probability of unsuccessful decoding under optimal decoding for the code could be formulated by the ISD and ∈. In this paper, we determine the ISDs for the Simplex codes, the Hamming codes, the first order Reed-Muller codes, and the extended Hamming codes, which are some Reed-Muller codes or their shortening or puncturing versions. Then, we show that the probability of unsuccessful decoding under optimal decoding for any binary linear code is monotonously non-decreasing on ∈ in the interval [0,1].
On the End-to-End Delay Performance of Spatially Correlated Wireless Line Networks

The analytical end-to-end (e2e) performance of a wireless multihop network is largely unknown, because of the interconnections between several factors involved. Customarily, the nodes are often assumed to be spatially uncorrelated so that they can be analyzed in isolation, which is valid when all the traffic flows are independent. In practice, however, most traffic flows are correlated and cause spatial correlation among nodes. The results based on the assumption of spatially uncorrelated nodes may be far from the performance of real networks. In this paper, we aim to study the impact of the spatial correlation on the e2e delay in a wireless line network (WLN). In particular, we use queueing theory to reveal that the burstiness, the temporal correlation of the traffic flow and the underlying medium access control (MAC), together determine the spatial correlation, from which an analysis of the e2e delay of a WLN is accomplished.
EM-Based Channel Estimation for MIMO OFDM System

In this paper, a low complexity adaptive EM-based channel estimation algorithm is proposed for Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems in slow time-varying frequency selective environment. The proposed algorithm was an adaptive channel estimation technique based on an expectation maximization (EM) algorithm for space-time block coded (STBC) MIMO OFDM systems. Simulation results show that in slow fading environment there was no degradation in normalized mean square error (MSE) as we increased the number of users. Comparing the Recursive Least-Squares(RLS) algorithm, the proposed algorithm exploits the structure of Alamouti STBC codes to reduce computational complexity.
Cooperation and coercion

Abstract Coercion is a much-discussed topic in the linguistic literature. This article expands the usual range of cases at the most subtle and the extreme end: it demonstrates how coercion extends into semantic flexibility on the one hand and into idiomaticity on the other. After discussing a broad variety of coercion cases in syntax and morphology and briefly reviewing the equally diverse literature, we identify three mechanisms – selection, enrichment, and override – that have alternatively been proposed to account for coercion effects. We then present an approach that combines all three mechanisms, arguing that they can be unified along a single axis: the degree of top-down influence of complex structures on lexical semantics.
Is alcohol-related flushing a protective factor for alcoholism in Caucasians?

Although alcohol-related flushing seems to be a genetically influenced protective factor for alcoholism in some Asian groups, little is known about whether this is true for Caucasians. The evidence for alcohol-related flushing as a protective factor for the development of alcoholism was examined in a sample of 5831 Australian twins (2041 men, 3790 women) who were administered a structured psychiatric interview. Twin correlations for self-reported adverse alcohol reactions (e.g., "flushing or blushing" and "feeling very sleepy" after drinking 1 or 2 drinks) were modest, suggesting minimal contribution of genetic factors, but when corrected for reliability of measurement, were consistent with moderate heritabilities. In accord with studies examining Asian samples, we found that individuals who experienced adverse reactions after drinking small amounts of alcohol drank less often and slightly less per drinking occasion than those who did not experience adverse reactions. However, those who experienced adverse reactions were more likely to have symptoms of alcoholism and to report a parental history of alcohol problems. We conclude that self-reported alcohol-related flushing is not a protective factor for alcoholism in Caucasians and may be a risk factor.
Hypotheses selection for re-ranking semantic annotations

Discriminative reranking has been successfully used for several tasks of Natural Language Processing (NLP). Recently it has been applied also to Spoken Language Understanding, improving state-of-the-art for some applications. However, such proposed models can be further improved by considering: (i) a better selection of the initial n-best hypotheses to be re-ranked and (ii) the use of a strategy that decides when the reranking model should be used, i.e. in some cases only the basic approach should be applied.
Understanding the Regional Variability of Eddy Diffusivity in the Pacific Sector of the Southern Ocean

A diagnostic framework is presented, based on the Nakamura effective diffusivity, to investigate the regional variation in eddy diffusivity. Comparison of three different diffusivity calculations enables the effects of locally enhanced tracer diffusion to be distinguished from the streamwise average. It also enables the distinction to be made between locally generated complexity in the tracer structure and that advected into a particular domain. The technique is applied to the Pacific sector of the Southern Ocean. The results highlight the important role that the mean flow plays in determining eddy diffusivity. The effective diffusivity is not simply related to the eddy kinetic energy: in regions of a strong mean flow the eddy diffusivity can be suppressed even in the presence of moderately strong eddy activity; conversely, in a region of weak mean flow the eddy diffusivity can be enhanced even in the presence of only weak eddy activity. This casts doubt on the ability of parameterizations based solely on the eddy kinetic energy to adequately characterize the eddy diffusivity in regions of strongly varying mean flow such as the Southern Ocean. The results are, however, consistent with the eddy transport and mixing variability predicted by potential-vorticity-based arguments.
A PERFORMANCE ANALYSIS OF DIFFERENT SAR TOMOGRAPHIC PROCESSING TECHNIQUES FOR URBAN AREAS

A single SAR image provides 2D reflectivity along slant range and azimuth coordinates. The reflectivity in elevation is not explicitly imaged, as the backscattered echos from multiple targets at the same range distance are superposed into the same range-azimuth resolution cell despite their different elevation coordinates. Layover distortions occur frequently, particularly in urban areas. SAR tomography extends this conventional 2D imaging scenario to 3D, alleviating the layover problem. It forms a synthetic aperture along the elevation direction using a stack of multiple SAR images acquired from different look angles. Various tomographic inversion techniques have been proposed to extract the elevation profiles. The performance of these techniques is influenced by various practical issues, such as a limited number of baselines, lack of uniformity of baselines, decorrelation and other phase noise, etc. In this paper, we present a comparative performance analysis among some of these inversion techniques, viz. beamforming, singular-value-decomposition approaches and the CAPON spectral estimation.
Progressive Coding of a Gaussian Source Using Matching Pursuit

In this paper, the application of matching pursuit (MP) in progressive coding of memoryless Gaussian sources is studied. In addition, a detailed analysis of the rate-distortion performance of our proposed MP encoder is presented, and the distortion of the MP encoder is derived in terms of dictionary size and number of quantization levels and the optimum parameters are calculated. Our analysis is based on a probabilistic model for matching pursuit residual vectors. Our simulation results verify the accuracy of our analysis and show that matching pursuit can produce an embedded bitstream with comparable quality to existing quantizers. The MP encoder outperforms quantizers that are capable of producing embedded bitstreams.
Inhibition of Gene Expression of Organic Cation/Carnitine Transporter and Antioxidant Enzymes in Oxazaphosphorines-Induced Acute Cardiomyopathic Rat Models

It is well documented that high therapeutic doses of oxazaphosphorines, cyclophosphamide (CP) and ifosfamide (IFO), are associated with cardiomyopathy. This study investigated whether oxazaphosphorines alter the expression of organic cation/carnitine transporter (OCTN2) and antioxidant genes and if so, whether these alterations contribute to CP and IFO-induced cardiotoxicity. Adult male Wistar albino rats were assigned to one of six treatment groups namely, control, L carnitine, CP, IFO, CP plus L carnitine and IFO plus L carnitine. In cardiac and kidney tissues, CP and IFO significantly decreased mRNA and protein expression of OCTN2. Oxazaphosphorines significantly increased serum acyl-carnitine/free carnitine ratio and urinary carnitine excretion and significantly decreased total carnitine in cardiac tissues. Interestingly, carnitine supplementation completely reversed the biochemical and gene expression changes-induced by oxazaphosphorines to the control values, except OCTN2 expression remained inhibited by IFO. Data from this study suggest that: (1) Oxazaphosphorines decreased myocardial carnitine content following the inhibition of OCTN2 mRNA and protein expression in cardiac tissues. (2) Oxazaphosphorine therapy increased urinary loss of carnitine secondary to the inhibition of OCTN2 mRNA and protein expression in proximal tubules of the kidney. (3) Carnitine supplementation attenuates CP but not IFO-induced inhibition of OCTN2 mRNA and protein expression in heart and kidney tissues.
A Polyaxonal Amacrine Cell Population in the Primate Retina

Amacrine cells are the most diverse and least understood cell class in the retina. Polyaxonal amacrine cells (PACs) are a unique subset identified by multiple long axonal processes. To explore their functional properties, populations of PACs were identified by their distinctive radially propagating spikes in large-scale high-density multielectrode recordings of isolated macaque retina. One group of PACs exhibited stereotyped functional properties and receptive field mosaic organization similar to that of parasol ganglion cells. These PACs had receptive fields coincident with their dendritic fields, but much larger axonal fields, and slow radial spike propagation. They also exhibited ON-OFF light responses, transient response kinetics, sparse and coordinated firing during image transitions, receptive fields with antagonistic surrounds and fine spatial structure, nonlinear spatial summation, and strong homotypic neighbor electrical coupling. These findings reveal the functional organization and collective visual signaling by a distinctive, high-density amacrine cell population.
Dietary Diversity in Urban and Rural China: An Endogenous Variety Approach

In the canonical consumer demand problem, an agent makes a decision about quantities to consume, under the assumption that all possible varieties are available and can be accessed at zero cost. Quantities of each budget item are adjusted to achieve maximum utility subject to the budget constraint. As a result, utility and expenditure reflect aggregations of quantity and, implicitly, variety. In reality, the cost of accessing variety may not be zero. In this paper we study the consumer’s choice problem using an endogenous variety approach, allowing variety access cost to influence consumption. We develop a conceptual framework for the problem and test its predictions empirically by comparing patterns of dietary diversity over time among a large sample of urban and rural Chinese consumers. We find that access costs, reflecting differences in infrastructure and household storage technologies, influence dietary diversity.
Fast image analysis using Kohonen maps

The following paper considers image analysis with Kohonen feature maps. These types of neural networks have proven their usefulness for pattern recognition in the field of signal processing in various applications. The paper reviews a classification approach, used in medical applications, in order to segment anatomical objects such as brain tumors from magnetic resonance imaging (MRI) data. The same approach can be used for environmental purposes, to derive land-use classifications from satellite image data. These applications require tremendous processing time when pixel-oriented approaches are chosen. Therefore the paper describes implementation aspects which result in a stunning speed-up for classification purposes. Most of them are based on geometric relations in the feature-space. The proposed modifications were tested on the mentioned applications. Impressive speed-up times could be reached independent of specific hardware. <<ETX>>
Pre-Attentive Processing of Sound Duration Changes: Low Resolution Brain Electromagnetic Tomography Study

The human central auditory system has a remarkable ability to establish memory traces for invariant features in the acoustic environments in order to correct the interpretation of natural acoustic sound heard. Even when no conscious attention is paid to the surrounding sounds, changes in their regularity can cause the listener to redirect his or her attention toward the sound heard (Tervaniemi et al., 2001). When engaged in a conversation, listeners tune in to the relevant stream of speech and filter out irrelevant speech input that may be present in the same environment. Nonetheless, attention might be involuntarily diverted to meaningful items coming from an ignored stream, like in the well-known own-name effect (Moray, 1959). This brings up the question of to what extent speech is processed in the ignored streams. In the past decade, there have witnessed a resurgence in the electrophysiological literature of attempts to understand how the brain processes the speech signal (Kraus et al., 1993, 1996; Molfese, 1985). One of the most used and well known paradigms in electrosphysiological research is the so-called oddball paradigm, in which typically two stimuli are presented, in random order. One of the stimuli occurs less frequently than the other and the subject is required to discriminate the infrequent stimulus (deviant, target or oddball) from the frequent one (standard). Two main types of ERPs have been described in the literature as a response to the detection of the deviant: P300 and the MMN (Aaltonen et al., 1994; Kraus et al., 1993, 1996). If the subject is required to respond overtly --for example, by pressing a button – each time he/she detects the deviant, a positive wave peaking approximately 300 ms after deviant onset is elicited. This wave is called P300 and it is largest over electrode sites in normal adults. Such positivity is thought to reflect voluntary focused attention (context updating, response selection). However, if the subject is not required to respond overtly, and one subtracts the event-related potentials (ERPs) obtained in response to the standard, from the ERPs obtained for the deviant, so-called mismatch negativity (MMN) may be observed, usually peaking between 100 and 300 ms after stimulus onset depending on the characteristics of the difference between standard and deviant stimuli. This component is thought to reflect a pre-attentional detection of deviation, a mismatch between the deviant and the memory trace formed by the standard.
Statistical Calibration by means of Kalman Filter 1 La Taratura Statistica tramite il Filtro di Kalman

Riassunto: Il problema della taratura di uno strumento di misura può essere inquadrato sia in un contesto statistico che in un contesto ingegneristico. Nel primo, il problema viene affrontato distinguendo tra regressione inversa e regressione diretta. I modelli che si ottengono sono modelli statici e sono utilizzati per risalire alle misure ‘esatte’ partendo da misure ‘affette da errore’. In ambito ingegneristico invece, le variabili vengono considerate nell’ordine temporale in cui si osservano. Il filtro di Klaman può essere quindi utilizzato per monitorare l’evolversi delle misure, introducendo così un modello di taratura dinamica.
“ Can you SEE me now ? " : A Study of Mobile Video Calls

Video telephony is increasingly being adopted by end consumers. It is extremely challenging to deliver video calls over wireless networks. In this paper, we conduct a measurement study on three popular mobile video call applications: FaceTime, Google Plus Hangout, and Skype, in both WiFi and Cellular networks. Our study is focused on answering the following questions: 1) how they encode and decode video in realtime under tight resource constraints of mobile devices? 2) how they transmit the encoded video smoothly in face of various wireless network impairments, including bursty loss, highly variable delay and competing cross-traffic? 3) what is their delivered video conferencing quality, both video perceptual quality and video delay, under different real mobile network conditions? 4) how different system architectures and design choices adopted by each system contribute to their delivered quality? Through detailed analysis of measurement results, we obtain valuable insights regarding the unique challenges, advantages and disadvantages of existing design solutions, and possible new directions to deliver high-quality video calls in wireless networks
Statistics of Basic Research in Russia

Statistics of research and development (R&D) is one of the youngest branches of economic statistics in Russia and was developed under the influence of the centralized planning system and financing. Under the conditions of the transition to a market economy, R&D policy cannot be re-organized without a comprehensive evaluation of input and output of the national R&D system. This is why a radical revision of statistics becomes a crucial component for the transformation of the R&D system and the background for the development and implementation of a new R&D policy aimed at maintaining basic research potential. This paper is devoted to the problems of R&D statistics in Russia, its applicability for estimating basic research and comparability of data. The perspectives of Russian R&D statistics, for example, in connection with implementing international statistical standards, is also the focus of this paper.