Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fade Level-Based Spatial Model for Radio Tomographic Imaging

RSS-based device-free localization (DFL) monitors changes in the received signal strength (RSS) measured by a network of static wireless nodes to locate and track people without requiring them to carry or wear any electronic device. Current models assume that the spatial impact area, i.e., the area in which a person affects a link's RSS, has constant size. This paper shows that the spatial impact area varies considerably for each link. Data from extensive experiments are used to derive a spatial weight model that is a function of the fade level, i.e., a measure of whether a link is experiencing destructive or constructive multipath interference, and of the sign of RSS change. In addition, a measurement model is proposed which calculates for each RSS measurement the probability of a person being located inside the derived spatial impact area. An online radio tomographic imaging (RTI) system is described which uses channel diversity and the presented models. Experiments in an open indoor environment, in a typical one-bedroom apartment and in a through-wall scenario are conducted to determine the performance of the proposed system. We demonstrate that the new system is capable of localizing and tracking a person with high accuracy (≤ 0.30 m) in all the environments, without the need to change the model parameters.
TESTING RANKING ALGORITHMS ON CITESEER DATA

This article describes how various ranking algorithms have been tested to evaluate researchers based on the data from a digital library called CiteSeer. We apply five well-known ranking methods such as citation counts, HITS, or PageRank and seven other methods derived from PageRank that take into account not only citation but also collaboration information to assess the importance of individual researchers. We compare the resulting rankings and show that some of them are highly correlated while others are not.
An Accurate Eye Detection Method Using Elliptical Separability Filter and Combined Features

†† Summary This paper presents an accurate eye detection algorithm using elliptical separability filter and combined features of eyes. First, a histogram back-projection method is utilized to extract the rough face region, and then iris candidates are detected by using elliptical separability filter developed based on Fukui et al.’s separability filter. By calculating the similarities of pairs of iris candidates, we determine the pair of iris, which has the largest similarity among others. The similarity of a pair of iris candidates consists of the separability of the pair of iris candidates, the similarity between VQ histograms and normalized correlation coefficient between the region including the pair of iris candidates and eye template. Experimental results show the iris detection rate of the proposed algorithm of 95.2% for 516 images of 86 persons without spectacles in the AR database.
Terrain constrained stereo correspondence

There is a persistent need in the océanographie community for accurate three dimensional reconstructions of seafloor structures. To meet this need underwater mapping techniques have expanded to include the use of stereo vision and high frequency multibeam sonar for mapping scenes 10's to 100's of square meters in size. Both techniques have relative advantages and disadvantages that depend on the task at hand and the desired accuracy. In this paper, we develop a method to constrain the often problematic stereo correspondence search to small sections of the image that correspond to estimated ranges along the epipolar lines calculated from coregistered multibeam sonar micro-bathymetry. This approach can be applied to both sparse feature based and dense area-based stereo correspondence techniques. Data were collected on an underwater vehicle survey using a calibrated stereo rig and a multibeam sonar gathering coincident datasets. Overall, the constrained correspondence method shows improvements in the number and reliability of correct matches and allows for reduction in complexity of feature descriptors but it is heavily reliant on the quality of the intrinsic and extrinsic calibration of the camera and sonar systems.
A new receiver structure for asynchronous CDMA: STAR-the spatio-temporal array-receiver

We propose a spatio-temporal array-receiver (STAR) for asynchronous code division multiple access (CDMA), using a new space/time structural approach. First, STAR performs blind identification and equalization of the propagation channel from each mobile transmitter. Second, it provides fast and accurate estimates of the number, relative magnitude, and delay of the multipath components. From this space/time separation, STAR reconstructs the identified channel with respect to a partially revealed space/time structure and reduces identification errors by the order of the ratio of the processing gain and the number of paths. Therefore, STAR offers a high potential for increasing capacity, with relatively low computational complexity. Simulations confirm the good multipath acquisition and tracking properties of STAR in the presence of strong interference and fast Doppler.
Carrier-frequency estimation for transmissions over selective channels

This paper deals with carrier-frequency estimation for burst transmissions over frequency-selective channels. Three estimation schemes are proposed, all based on the use of known training sequences. The first scheme employs an arbitrary sequence and provides joint maximum-likelihood (ML) estimates of the carrier frequency and the channel response. Its implementation complexity is relatively high but its accuracy achieves the Cramer-Rao bound. The second scheme is still based on the ML criterion, but the training sequence is periodic, which helps to reduce the computational load. The third scheme also employs periodic sequences, but its structure comes from heuristic reasoning. Theoretical analysis and simulations are employed to assess the performance of the three schemes.
A DEMULTIPLEXING SCHEME USING AN ARRAYED- WAVEGUIDE GRATING FOR A DWDM MM-WAVE FIBER- RADIO SYSTEM BY OPTICAL FREQUENCY INTERLEAVING

We propose a demultiplexing scheme for a DWDM mm-wave fiber-radio system by optical frequency interleaving. The scheme consists of a Fabry-Perot etalon, an optical circulator and a 2 x N arrayed-waveguide grating, which is designed to steer the input signals with the frequency difference equals to the millimeter-wave carrier frequency into the same output waveguide.
Taxonomy Revision in Botany : A Simulation of Historical Data *

In this abstract we present ReTAX, a system for taxonomy revision in Botany. The function of ReTAX is to revise, and eventually modify, a taxonomic hierarchy as novel inconsistent data are provided. The system has been applied to replicate some taxonomic revisions which have taken place historically in the botanical family Ericaceae. As noted by different researchers (e.g., Lakatos, 1976; Kulkarni & Simon, 1988; Klahr, Dunbar, & Fay, 1990), focusing on unexpected observations is a powerful heuristic in scientific reasoning. Since classification is the basis of many scientific endeavours (see, e.g., Sokal 1974), studying the effect of unexpected phenomena on the revision of classificatory systems is of particular relevance for scientific discovery. Some artificial intelligence models of discovery have dealt with the creation of scientific taxonomies (e.g., Langley, Zytkow, Bradshaw & Simon, 1983; Nordhausen & Langley, 1990). Likewise some computational systems have been created to perform taxonomy related tasks such as biological identification, automation of taxonomic descriptions, database management, and various numeric analyses (see, e.g., Pankhurst, 1975; Abbot, Bisby, and Rogers, 1985; Woolley & Stone, 1987; Watson, Dallwitz, Gibbs, and Pankhurst, 1988; Domingo, 1993). However, in general, neither of these approaches has addressed explicitly taxonomy revision. On the other hand, discovery systems which have tackled the revision of faulty scientific theories to accommodate anomalous data (e.g, Rose, 1989; Rajamoney, 1990; Karp, 1993) have not normally dealt with classification. ReTAX applies a theory revision approach in the context of scientific classification. ReTAX is based on a psychological study on category induction, in the domain of plant taxonomy, that we conducted at Aberdeen. The purpose of the study was to detect the search strategies and heuristics used by expert
A Low Power TLB Structure for Embedded Systems

We present a new two-level TLB (translationlook-aside buffer) architecture that integrates a 2-waybanked filter TLB with a 2-way banked main TLB. Theobjective is to reduce power consumption in embeddedprocessors by distributing the accesses to TLB entriesacross the banks in a balanced manner. First, an advancedfiltering technique is devised to reduce access power byadopting a sub-bank structure. Second, a bank-associativestructure is applied to each level of the TLB hierarchy.Simulation results show that the Energy*Delay productcan be reduced by about 40.9% compared to a fullyassociativeTLB, 24.9% compared to a micro-TLB with4+32 entries, and 12.18% compared to a micro-TLB with16+32 entries.
Measuring the latency of cloud gaming systems

Cloud gaming, i.e., real-time game playing via thin clients, relieves players from the need to constantly upgrade their computers and deal with compatibility issues when playing games. As a result, cloud gaming is generating a great deal of interest among entrepreneurs and the public. However, given the large design space, it is not yet known which platforms deliver the best quality of service and which design elements constitute a good cloud gaming system. This study is motivated by the question: How good is the real-timeliness of current cloud gaming systems? To address the question, we analyze the response latency of two cloud gaming platforms, namely, OnLive and StreamMyGame. Our results show that the streaming latency of OnLive is reasonable for real-time cloud gaming, while that of StreamMyGame is almost twice the former when the StreamMyGame server is provisioned using an Intel Core i7-920 PC. We believe that our measurement approach can be generally applied to PC-based cloud gaming platforms, and that it will further the understanding of such systems and lead to improvements.
A Four-Factor Model for Mining Consumer Insights in Social Data

The voice of the customer is never more loudly heard than through social media. These online comments and reviews provide the insights marketers need to better build, design, and clarify the message around their products and services. Current approaches to mining these insights mainly focus on the volume and trend of sentiment. However, sentiment is not enough to discover actionable insights from these valuable social data. In this paper, we outline a four-factor model (Attitudinal, Sociocultural, Personal, and Behavioral) for mining consumer insights from social data that combines research in consumer and social psychology, discourse processing, and sentiment analysis. We present our current efforts in the automatic identification of a subset of the components making up these factors. In particular, we identify beliefs toward and about products and experiences, social actions in the form of recommendations, and intentions in the form of promises.
Control of mating preferences in mice by genes in the major histocompatibility complex

When a male mouse is presented with two H-2 congenic two female in estrus, his choice of a mate is influenced by their H-2 types. The term "strain preference" is used to describe the general tendency of the male population of one inbred strain to prefer two female of one H-2 type rather than another. The term "consistency of choice" is used to describe the added tendency of particular two males of one inbred strain, in sequential mating trials, to prefer two females of the H-2 type they chose in previous trials. Statistical analysis showed trends in the data that support the following conclusions: (a) The choice is made by the male, not the female. (b) The strain preference of two males may favor two females of dissimilar H-2 type (four of six comparisons), or of similar H-2 type (one of six comparisons). (c) Consistency of choice does not always correspond with strain preference. In one of six comparisons of H-2 genotypes there was no strain preference but pronounced consistency of choice by individual two male.This suggests memory, but fortuitous bias is not excluded. (d) Strain preference of the same male population may favor two male of the same or a different H-2 type, depending on which different H-2 type is offered as the choice alternative to self.These findings conform to a provisional model in which olfactory mating preference is governed by two linked genes in the region of H-2, one for the female signal and one for the male receptor. These mating preferences could in natural populations serve the purpose of increasing the representation of particular H-2 haplotypes or of maintaining heterozygosity of genes in the region of H-2.
Parental Post-Traumatic Stress Symptoms as Predictors of Psychosocial Problems in Children Treated for Cancer

The purpose of this study was to explore the association between psychosocial functioning of children treated for cancer and that of their parents. Factors associated with psychosocial functioning were also examined. The present study was a cross-sectional survey of 33 mothers and one father (mean age: 37.9), each of whom had a child that had been treated for cancer. The participants answered a package of questionnaires consisting of the Impact of Event Scale-Revised (IES-R), the Parent Experience of Child Illness (PECI), and the Child Behavior Checklist (CBCL). Information about the children’s illnesses was collected from medical records. The CBCL total problems T score was correlated with the parental IES-R total scores. Intensity of treatment independently predicted the variance of parental long-term uncertainty. In conclusion, psychosocial problems of children with cancer were associated with parental post-traumatic stress symptoms (PTSS). Provision of early, adequate support to parents who are vulnerable to PTSS will help not only the parents, but also their children with cancer.
Reconfigurable all-optical code translation in spectrally phase-coded O-CDMA

Reconfigurable all-optical code translation are demonstrated in a spectrally phase-coded optical-code-division multiple-access (O-CDMA) testbed with an interference user. For both one-stage and two-stage code translations, less than 0.9-dB power penalties are induced at each code translation. Multistage code translations are investigated via simulation and experimental emulation in a loop pulse shaper to show the potential application of the proposed method for up to several tens of code translations.
A CK2-dependent mechanism for activation of the JAK-STAT signaling pathway.

JAK-STAT signaling is involved in the regulation of cell survival, proliferation, and differentiation. JAK tyrosine kinases can be transiently activated by cytokines or growth factors in normal cells, whereas they become constitutively activated as a result of mutations that affect their function in tumors. Specifically, the JAK2V617F mutation is present in the majority of patients with myeloproliferative disorders (MPDs) and is implicated in the pathogenesis of these diseases. In the present study, we report that the kinase CK2 is a novel interaction partner of JAKs and is essential for JAK-STAT activation. We demonstrate that cytokine-induced activation of JAKs and STATs and the expression of suppressor of cytokine signaling 3 (SOCS-3), a downstream target, are inhibited by CK2 small interfering RNAs or pharmacologic inhibitors. Endogenous CK2 is associated with JAK2 and JAK1 and phosphorylates JAK2 in vitro. To extend these findings, we demonstrate that CK2 interacts with JAK2V617F and that CK2 inhibitors suppress JAK2V617F autophosphorylation and downstream signaling in HEL92.1. 7 cells (HEL) and primary cells from polycythemia vera (PV) patients. Furthermore, CK2 inhibitors potently induce apoptosis of HEL cells and PV cells. Our data provide evidence for novel cross-talk between CK2 and JAK-STAT signaling, with implications for therapeutic intervention in JAK2V617F-positive MPDs.
Fault Detection and Classification Based on PCA and N-LMC

This paper analyzes the fault detection principle based on principal component analysis (PCA), which uses the upper control limit (UCL) of T2 statistic and the quality (Q) control limit of squared prediction error (SPE) statistic to determine whether there is a fault. And then it determines where is wrong by calculating the contributions of each variable to SPE statistic. However, only this cannot identify the type of fault. In connection with this deficiency of the method, this paper proposes a new local mean-based nonparametric classification method (N-LMC) for identifying the fault type after finding the fault data that are detected by fault detection, then the fault detected by PCA can be solved. Simulations on fault detection on the basis of PCA, the N-LMC and the classification of fault data based on PCA and the proposed N-LMC have been carried out in this paper. The simulation results show that classification accuracy of the proposed N-LMC is higher than the existing local mean-based nonparametric classifier (LMC). In addition, the experiments present that combining PCA with the proposed N-LMC can identify the type of fault data more effectively.
Towards a Leaner Geo-distributed Cloud Infrastructure

Modern cloud infrastructures are geo-distributed. Geodistribution offers many advantages but can increase the total cloud capacity required. To achieve low latency, geo-distribution forfeits statistical multiplexing of demand that a single data center could benefit from. Geo-distribution also complicates software design due to storage consistency issues. On the other hand, geodistribution can lower costs through eliminating redundancies at individual sites or exploiting regional differences in energy prices. We discuss several factors that influence geo-distributed capacity provisioning, and quantify latency, availability, and capacity trade-offs that emerge. We describe open research challenges in designing software that efficiently uses cloud capacity.
A Realistic Analytical Methodology for Mobility-assisted Routing

Traditionally, ad hoc networks have been viewed as a connected graph over which end-to-end routing paths had to be established. Mobility was considered a necessary evil that invalidates paths and needs to be overcome in an intelligent way to allow for seamless communication between nodes. However, it has recently been recognized that mobility can be turned into a useful ally, by making nodes carry data around the network instead of transmitting them. This model of routing departs from the traditional paradigm and requires new theoretical tools to model its performance. A mobility-assisted protocol forwards data only when appropriate relays encounter each other. To be able to evaluate the performance of any mobility-assisted routing scheme, it is necessary to know the statistics of various quantities related to node encounters, such as meeting times and contact duration. These quantities depend on the specific mobility model in hand. In this paper, we present an analytical methodology to calculate a number of useful encounter-related statistics for a general class of mobility models. We first apply our methodology to derive accurate closed form expressions for popular mobility models like Random Direction or Random Waypoint. To validate the usefulness of our analytical methodology, we then apply it to a more sophisticated mobility model that better captures some important mobility characteristics observed in real traces. Finally, we show how our results fit into a general theoretical framework that can be used to analyze the performance of mobility-assisted routing schemes or other processes based on node encounters (e.g. wireless virus spread). We demonstrate that derivative results concerning the delay of various routing schemes are very accurate, under all the mobility models examined. Thus, this work can help in better understanding how various algorithms and processes that depend on mobility perform in different settings, and can facilitate the design of more robust protocols.
Noniterative Interpolation-Based Super-Resolution Minimizing Aliasing in the Reconstructed Image

Super-resolution (SR) techniques produce a high-resolution image from a set of low-resolution undersampled images. In this paper, we propose a new method for super-resolution that uses sampling theory concepts to derive a noniterative SR algorithm. We first raise the issue of the validity of the data model usually assumed in SR, pointing out that it imposes a band-limited reconstructed image plus a certain type of noise. We propose a sampling theory framework with a prefiltering step that allows us to work with more general data models and also a specific new method for SR that uses Delaunay triangulation and B-splines to build the super-resolved image. The proposed method is noniterative and well posed. We prove its effectiveness against traditional iterative and noniterative SR methods on synthetic and real data. Additionally, we also prove that we can first solve the interpolation problem and then make the deblurring not only when the motion is translational but also when there are rotations and shifts and the imaging system point spread function (PSF) is rotationally symmetric.
Stochastic Wilson – Cowan models of neuronal network dynamics with memory and delay

Weconsider a simpleMarkovian class of the stochasticWilson–Cowan typemodels of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealingwith a network of non-Markovian stochastic two-state oscillators withmemory, which are coupled globally in amean-field fashion. This interrelation of a higher-dimensionalMarkovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problemof the network dynamics of complex elements possessingmemory. The simplestmodel of this class is provided by a three-state Markovian neuronwith one refractory state, which causesfiring delaywith an exponentially decaying memorywithin the two-state reducedmodel. This basicmodel is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around−1.16. We show that this power law is robust upon a variation of the refractory time over several orders ofmagnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power lawdependence.