Miracle-dz/UniFAR-FTUs huggingface dataset:
Enriched Training Database for improving the WiFi RSSI-based indoor fingerprinting performance

The interest for RF-based indoor localization, and in particular for WiFi RSSI-based fingerprinting, is growing at a rapid pace. This is despite the existence of a trade-off between the accuracy of location estimation and the density of a laborious and time consuming survey for collecting training fingerprints. A generally accepted concept of increasing the density of a training dataset, without an increase in the amount of physical labor and time needed for surveying an environment for additional fingerprints, is to leverage a propagation model for the generation of virtual training fingerprints. This process, however, burdens the user with an overhead in terms of implementing a propagation model, defining locations of virtual training fingerprints, generating virtual fingerprints, and storing the generated fingerprints in a training database. To address this issue, we propose the Enriched Training Database (ETD), a web-service that enables storage and management of training fingerprints, with an additional “enriching” functionality. The user can leverage the enriching functionality to automatically generate virtual training fingerprints based on propagation modeling in the virtual training points. We further propose a novel method for defining locations of virtual training fingerprints based on modified Voronoi diagrams, which removes the burden of defining virtual training points manually and which automatically “covers” the regions without sufficient density of training fingerprints. The evaluation in our testbed shows that the use of automated generation of virtual training fingerprints in ETD results in more than 25% increase in point accuracy and 15% in room-level accuracy of fingerprinting.
A Fuzzy Integral and Microeconomics Based QoS Multicast Routing Scheme in NGI

QoS (Quality of Service) multicast routing is essential in NGI (Next-Generation Internet). Due to the difficulty on exact measurement and complete expression of NGI network status, the QoS multicast routing should be based on the fuzzy information. With the gradual commercialization of the network operation, the users prefer to get the best services with the least cost at the same time the network providers pursue the most profits, thus the so-called win-win should be supported. In this paper, by introducing the microeconomics knowledge and the fuzzy integral, a QoS multicast routing scheme is proposed based on the Prim algorithm. It tries to make both the network provider utility and the user utility achieve or approach the Pareto optimum under the Nash equilibrium along the found route with the user QoS requirements satisfied. Simulation results have shown that the proposed scheme is both feasible and effective with better performance.
Evaluation of Alterations in Behaviour, Cognition, and Neuronal Excitability Induced by Administration of QTracker ® 800 Quantum Dots

Studies of Quantum Dots biodistribution have shown that these nanoparticles accumulate in various organs, including brain parenchyma, possibly causing functional alterations. To investigate its potential neurotoxicity, we administered QDs to young mice and studied their behaviour during the following weeks. Spontaneous locomotor behaviour in the home cage was not significantly altered in treated mice, the Rotarod and Grip Strength Meter tests were normal, whereas memory deficits were found with the Novel Object Recognition test up to three weeks after the injection. We also found a significant increase in the neuronal excitability of QDstreated mice, following the administration of a Pentylenetetrazol challenge.
Dynamic measurement of critical-path timing

A high bandwidth critical path monitor (1 sample/ cycle at 4-5 GHz) capable of providing real-time timing margin information to a variable voltage/frequency scaling control loop is described. The critical path monitor tracks the critical path delay to within 1 FO2 inverter delay with a standard deviation less than 3 FO2 delays over process, voltage, temperature, and workload. The CPM is sensitive to 20 mV/bit A/C and 10 mV/bit DC voltage changes, and less than 10degC/bit temperature changes.
Area-Efficient Error Protection for Caches

Due to increasing concern about various errors, current processors adopt error protection mechanisms. Especially, protecting L2/L3 caches incur as much as 12.5% area overhead due to error correcting codes. Considering large L2/L3 caches of current processors, the area overhead is very high. This paper proposes an area-efficient error protection scheme for L2/L3 caches. First, it selectively applies ECC (error correcting code) to only dirty cache lines and other clean cache lines are protected using simple parity check codes. Second, the dirty cache lines are periodically cleaned by exploiting the generational behavior of cache lines. Experimental results show that the cleaning technique effectively reduces the number of dirty cache lines per cycle. The ECCs of this reduced number of dirty cache lines can be maintained in a small storage. Our proposed scheme is shown to reduce the area overhead of a 1MB L2 cache for error protection by 59% for SPEC2000 benchmarks running on a typical four-issue superscalar processor
Hot topic detection and technology trend tracking for patents utilizing term frequency and proportional document frequency and semantic information

This paper proposes a methodology for identifying hot topics and tracking technology trends from the patent domain. The methodology uses frequency information in combination with the International Patent Classification (IPC) to capture semantic information on word categorization, doing so in a way that heretofore has not been employed for topic detection and trend tracking. Term Frequency and Proportional Document Frequency (TF*PDF) is employed as a means to detect hot topics from patents, and IPCs are used to calculate semantic importance of terms based on the IPCs where terms are distributed. Aging Theory is also used to calculate the variation of trends over time. Four types of trends including very stable trends, stable trends, normal trends, and unstable trends are defined and evaluated based on TF*PDF and TF*PDF combined with Aging Theory. Experiment results show that for very stable trends, the combination of TF*PDF and Aging Theory achieves 0.976% in Precision; for stable trends and all trends, TF*PDF achieves 0.959% and 0.84% in Precision, respectively. By applying TF*PDF in consideration of semantic information, we also show a new criteria for weighting hot topics and technology trend tracking.
Policy Shaping Politics: Monetary Policy Deliberations in Congressional Hearings, 1976-2008

The focus of this paper is on the relationship of the Federal Reserve vis-a-vis Congress, and in particular on the motivations of Members of Congress (MCs) as they oversaw the policy making decisions of the Fed from 1976 to 2008. We examine the evolution of congressional oversight of the Fed in order to better understand the thinking of MCs. Our approach is unusual in that it measures statistically the deliberations of Members of Congress in the House and Senate banking committees during the oversight hearings on monetary policy for eight periods (61 hearings) from 1976 to 2008. The reason for choosing this span of the history of US monetary policy is that it coincides with the Great Inflation of the 1970s, the radical action taken to cure that problem (initiated by the so-called Volcker Revolution of 1979), the subsequent period of stability and low inflation and ends with the early days of the current financial crisis. This was a period during which monetary policy also came to the forefront as the tool of macroeconomic stabilization. Some of our findings include: (1) MCs generally showed little interest in the detail of monetary policy making, seemingly willing to leave these details to the Fed; (2) MCs were actively engaged in challenging the Fed in the areas of governance, accountability and transparency; (3) the degree of challenge from Congress to the Fed appears to be negatively related to the success of the Fed in pursuing low inflation and stable economic growth; and (4) MCs of both parties failed to devote much attention to financial stability and bank regulation in the 1990s and early 21st century.
Remembrance of Local Information Status for Enforcing Robustness of Policy-Exchanged Strategies for Trust Negotiation

Trust Negotiation, as a complex access control approach, can enable two unknown entities to establish a bilateral trust relationship. The complexity of Trust Negotiation may be ascribed to its support for the use of different strategies. Currently, a variety of strategies have been designed for Trust Negotiation, and the majority can support the exchange of authorisation policies during the conduction of Trust Negotiation. However, innate vulnerability issues still exist within these strategies including (1) there is no approach for automatic detection of Policy Cyclic Dependencies and (2) there is no approach for defending against Repetitive Credential Request Attacks. This paper proposes a solution design based on the idea of the remembrance of local information status aiming to address the two vulnerability.
Individual and social preferences under risk: laboratory evidence on the group size effect

In this paper we investigated group size impact on social risk aversion when a majority rule is applied. We used the well-known Holt and Laury's (2002) mechanism to elicit individuals and social risk attitudes. We observed a risk shift in small group and a vanishing of such effect as group size increase.
Multi-agent Paradigm and Conceptual Graphs in Information Retrieval Model

With the growing amount of on-line information and its dynamic nature, users' burden of retrieving information has become heavier and existing passive working is too inefficient to meet users' needs. An intelligent information retrieval model based on multi-agent paradigm and conceptual graphs is proposed. The model (IIR agent) has two layers of group agent and personal agent. Subagents of the IIR agent are also identified so that they can be designed and implemented separately. The system represents queries and documents in conceptual graph (CG), which brings semantic in some functions, such as intelligent search, auto-notification, navigation guide and personal information management. CG-based model improves ranking of documents returned from WWW search engines and makes passive working mode more efficient
Generation Scheduling for Power Systems with Demand Response and a High Penetration of Wind Energy

With renewable energy sources and demand response programs expanding in many power systems, traditional unit commitment and economic dispatch approaches are inadequate. The power system is changing to one where there is control with uncertainty for both generation and load. Alternative power system scheduling methods capable of aggregating the uncertainty of wind power and demand response, while maintaining reliable and economic performance are investigated in this work. The research addresses four aspects of these changes. First , a probabilistic method is proposed to maintain uniform system reliability level in the hour-ahead economic dispatch by quantifying different levels of required spinning reserve. The method considers the probability distributions of wind speed and load forecast errors, as well as outage replacement rates of generators by using the expectation of demand not served (EDNS) as an evaluation index. Second, a probabilistic model of security-constrained unit commitment (SCUC) is proposed to determine the optimal amount of spinning reserve when integrating wind generation. An algorithm, which includes the stochastic wind forecast results into a day-ahead unit commitment and extracts its value for system operation of system, is developed. The proposed model determines the optimal amount of spinning reserve in terms of an optimal trade-off between economic efficiency and system reliability. Third, a new duplex demand response model is proposed to allow demand to bid into both the energy and spinning reserve markets. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under
Spatial and temporal genetic structure of a river-resident Atlantic salmon (Salmo salar) after millennia of isolation

The river-resident Salmo salar (“småblank”) has been isolated from other Atlantic salmon populations for 9,500 years in upper River Namsen, Norway. This is the only European Atlantic salmon population accomplishing its entire life cycle in a river. Hydropower development during the last six decades has introduced movement barriers and changed more than 50% of the river habitat to lentic conditions. Based on microsatellites and SNPs, genetic variation within småblank was only about 50% of that in the anadromous Atlantic salmon within the same river. The genetic differentiation (FST) between småblank and the anadromous population was 0.24. This is similar to the differentiation between anadromous Atlantic salmon in Europe and North America. Microsatellite analyses identified three genetic subpopulations within småblank, each with an effective population size Ne of a few hundred individuals. There was no evidence of reduced heterozygosity and allelic richness in contemporary samples (2005–2008) compared with historical samples (1955–56 and 1978–79). However, there was a reduction in genetic differentiation between sampling localities over time. SNP data supported the differentiation of småblank into subpopulations and revealed downstream asymmetric gene flow between subpopulations. In spite of this, genetic variation was not higher in the lower than in the upper areas. The meta-population structure of småblank probably maintains genetic variation better than one panmictic population would do, as long as gene flow among subpopulations is maintained. Småblank is a unique endemic island population of Atlantic salmon. It is in a precarious situation due to a variety of anthropogenic impacts on its restricted habitat area. Thus, maintaining population size and avoiding further habitat fragmentation are important.
An Adaptive Stereo Algorithm Based on Canonical Correlation Analysis

This paper presents a novel algorithm that uses CCA and phase analysis to detect the disparity in stereo images. The algorithm adapts filters in each local neighbourhood of the image in a way which maximizes the correlation between the filtered images. The adapted filters are then analysed to find the disparity. This is done by a simple phase analysis of the scalar product of the filters. The algorithm can even han- dle cases where the images have different scales. The algorithm can also handle depth discontinuities and give multiple depth estimates for semi- transparent images. I. INTRODUCTION An important problem in most signal processing tasks is to find the best basis to represent the signal. Many unsuper- vised learning methods have been proposed to handle this prob- lem. Hebbian learning methods like Oja's rule (15) and self- organizing feature maps (12) are related to the principal com- ponents of the signal distribution and, hence, base their selec- tion of basis vectors on signal variance. However, when the problem involves an analysis of the re- lations between two sets of data, the principal components of either set are not relevant. In recent years, unsupervised learn- ing algorithms based on mutual information(17) have received an increasing interest. Examples of this approach are the info- max principle (13) and the Imax principle (3). Mutual infor- mation based learning has been used for blind separation and blind deconvolution (5) and disparity estimations in random- dot stereograms (3).
Follistatin Is Induced by Ionizing Radiation and Potentially Predictive of Radiosensitivity in Radiation-Induced Fibrosis Patient Derived Fibroblasts

Follistatin is a potent regulator of the inflammatory response and binds to and inhibits activin A action. Activin A is a member of the TGFβ protein superfamily which has regulatory roles in the inflammatory response and in the fibrotic process. Fibrosis can occur following cell injury and cell death induced by agents such as ionizing radiation (IR). IR is used to treat cancer and marked fibrotic response is a normal tissue (non-tumour) consequence in a fraction of patients under the current dose regimes. The discovery and development of a therapeutic to abate fibrosis in these radiosensitive patients would be a major advance for cancer radiotherapy. Likewise, prediction of which patients are susceptible to fibrosis would enable individualization of treatment and provide an opportunity for pre-emptive fibrosis control and better tumour treatment outcomes. The levels of activin A and follistatin were measured in fibroblasts derived from patients who developed severe radiation-induced fibrosis following radiotherapy and compared to fibroblasts from patients who did not. Both follistatin and activin A gene expression levels were increased following IR and the follistatin gene expression level was lower in the fibroblasts from fibrosis patients compared to controls at both basal levels and after IR. The major follistatin transcript variants were found to have a similar response to IR and both were reduced in fibrosis patients. Levels of follistatin and activin A secreted in the fibroblast culture medium also increased in response to IR and the relative follistatin protein levels were significantly lower in the samples derived from fibrosis patients. The decrease in the follistatin levels can lead to an increased bioactivity of activin A and hence may provide a useful measurement to identify patients at risk of a severe fibrotic response to IR. Additionally, follistatin, by its ability to neutralise the actions of activin A may be of value as an anti-fibrotic for radiation induced fibrosis.
High rate fingerprinting codes and the fingerprinting capacity

Including a unique code in each copy of a distributed document is an effective way of fighting intellectual piracy. Codes designed for this purpose that are secure against collusion attacks are called fingerprinting codes. In this paper we consider fingerprinting with the marking assumption and design codes that achieve much higher rates than previous constructions. We conjecture that these codes attain the maximum possible rate (the fingerprinting capacity) for any fixed number of pirates. We prove new upper bounds for the fingerprinting capacity that are not far from the rate of our codes. On the downside the accusation algorithm of our codes are much slower than those of earlier codes. We introduce the novel model of weak fingerprinting codes where one pirate should be caught only if the identity of all other pirates are revealed. We construct fingerprinting codes in this model with improved rates but our upper bound on the rate still applies. In fact, these improved codes achieve the fingerprinting capacity of the weak model by a recent upper bound. Using analytic techniques we compare the rates of our codes in the standard model and the rates of the optimal codes in the weak model. To our surprise these rates asymptotically agree, that is, their ratio tends to 1 as t goes to infinity. Although we cannot prove that each one of our codes in the standard model achieves the fingerprinting capacity, this proves that asymptotically they do.
A comparison of plagiarism detection tools

In this paper we compare five tools for detecting plagiarism in source code texts: JPlag, Marble, moss, Plaggie, and sim. The tools are compared with respect to their features and performance. For the performance comparison we carried out two experiments: to compare the sensitivity of the tools for different plagiarism techniques we have applied the tools to a set of intentionally plagiarised programs. To get a picture of the precision of the tools, we have run the tools on several incarnations of a student assignment and compared the top 10’s of the results.
An allometric scaling relationship in the brain of preterm infants

Allometry has been used to demonstrate a power–law scaling relationship in the brain of premature born infants. Forty‐nine preterm infants underwent neonatal MRI scans and neurodevelopmental testing at age 2 . Measures of cortical surface area and total cerebral volume demonstrated a power–law scaling relationship (α = 1.27). No associations were identified between these measures and investigated clinical variables. Term equivalent cortical surface area and total cerebral volume measures and scaling exponents were not related to outcome. These findings confirm a previously reported allometric scaling relationship in the preterm brain, and suggest that scaling is not a sensitive indicator of aberrant cortical maturation.
The $\alpha$-$\mu$ Distribution: A Physical Fading Model for the Stacy Distribution

This paper introduces a fading model, which explores the nonlinearity of the propagation medium. It derives the corresponding fading distribution-the alpha-mu distribution-which is in fact a rewritten form of the Stacy (generalized Gamma) distribution. This distribution includes several others such as Gamma (and its discrete versions Erlang and central Chi-squared), Nakagami-m (and its discrete version Chi), exponential, Weibull, one-sided Gaussian, and Rayleigh. Based on the fading model proposed here, higher order statistics are obtained in closed-form formulas. More specifically, level-crossing rate, average fade duration, and joint statistics (joint probability density function, general joint moments, and general correlation coefficient) of correlated alpha-mu variates are obtained, and they are directly related to the physical fading parameters
Analysis of Registration Requirements and Techniques for Imaging Sensor Suites on UVs

Image registration is in some senses the ‘forgotten problem’ in multi-sensor image exploitation. Image registration will, at present, typically involve using a constant registration transform to align images from sensors fixed relative to each other and separated by as small a distance as possible. For more challenging situations in which sensors are more widely spaced and not fixed relative to each other (e.g. teams of Uninhabited Air Vehicles, UAVs) the registration problem becomes far more complex. This paper reports on the progress that has been made under a SEAS DTC project towards understanding the image registration requirements for sensors on Uninhabited Vehicles (UVs) and the development of algorithms suitable for UV applications. A modelling environment has been created that allows a wide variety of scenarios to be examined in terms of their registration requirements, given different mission objectives, environmental conditions and UV sensor suites. The model is described in this paper and example results are presented. Details of new registration algorithms being developed are then given and initial results discussed.