Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Indoor Localization Techniques

Localization is the technique to determine the position of people or assets. The position information enables location-based protocols to navigate, to track or to monitor a person or an asset. Recently, indoor localization systems have been designed to provide location information of persons and devices in the indoor environment. The techniques used for location detection in the outdoor environment (like GPS) cannot be used in the indoor environment because there is no line-of sight communication possible and no sky-view in indoor environment. In big cities with plenty of high rise buildings GPS cannot work properly. The deployment of a system for obtaining location information in the indoor environment is a challenging task because of a large number of obstacles and interference of different frequencies. In this paper we studied the existing approaches and classify them based on the enabling technology. We further compared the existing approaches based on some parameters (like cost, accuracy) and compiled the result in tabular format. Keywords— GPS, Indoor Localization, Indoor Positioning System,Wireless Sensor Network.
OBSERVATIONS OF V592 CAS—AN OUTFLOW AT OPTICAL WAVELENGTHS

We present new red optical spectra of V592 Cas aimed at exploring the properties of the outflow of this system in a spectral region where the underlying white dwarf and the accretion disk do not contribute significantly to the observed absorption components of the Hα and He i line profiles. We use the Hα emission line to study the wind, which appears as pronounced blueshifted P Cygni absorption troughs whose low velocity end contaminates the blue side of the emission line profile. The wind appears to be episodic in nature, with multiple events reaching velocities of 5000 km s−1 in Hα. Similar (but weaker) wind signatures appear in the He i 5876 Å line but are absent in He i 6678 Å. Our data suggest that during wind episodes the wind is phase dependent and is visible for half of the orbit of the system. Considering that V592 Cas is viewed almost face-on, the symmetry axis of the outflow cannot be orthogonal to the disk and/or the outflow must have some other inherent asymmetry in outflow geometry. A possible origin of the wind is in a disk hotspot, either at the initial impact point of the accretion stream on the disk edge or as a result of disk overflow (similar to SW Sextantis stars). Simultaneous optical photometry during one night of our spectroscopic observations indicate that there is no clear relationship between the optical brightness variations and the strength of the outflow in this system.
An Application of Spatial Econometrics in Relation to Hedonic House Price Modelling

This paper applies spatial econometrics in relation to hedonic house price modelling. We present and use some basic acknowledged spatial model alternatives and a battery of relevant tests. Geographically weighted regression, semiparametric analysis, and the mixed spatial Durbin model are also applied. The purpose is to detect missing spatial variables, misspecified functional form and spatial heterogeneity in estimated parameters. Such misspecifications have been shown to give spurious results in relation to some frequently used directional based tests. We achieve significant model improvement, so the paper should be of general interest as an example of practical econometric modelling within the field.
System for people with hearing impairment to solve their social integration

The deaf have the right to live a fair life and do their tasks without any difficulty exactly like everyone else. There are 360 million people (328 million adults and 32 million children) worldwide who have disabling hearing loss (Over 5% of the world's population) (WHO, 2015). Disabling hearing loss refers to hearing loss greater than 40 decibels (dB) in the better hearing ear in adults and a hearing loss greater than 30 dB in the better hearing ear in children(WHO, 2015). The majority of people with disabling hearing loss live in low- and middle-income countries (WHO, 2015). This work presents a mobile application that aims to make the communication between the deaf and other people easy, thus helping them to be more productive and better integrated into their communities.
Plasma Biomarkers in a Mouse Model of Preterm Labor

Preterm labor (PTL) is frequently associated with inflammation. We hypothesized that biomarkers during pregnancy can identify pregnancies most at risk for development of PTL. An inflammation-induced mouse model of PTL was used. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry was used to analyze and compare the plasma protein (PP) profile between CD-1 mice injected intrauterine with either lipopolysaccharide (LPS) or PBS on d 14.5 of gestation. The median differences of normalized PP peaks between the two groups were determined using the Mann-Whitney U test and the false discovery rate. In a second series of experiments, both groups of mice were injected with a lower dose of LPS. A total of 1665 peaks were detected. Thirty peaks were highly differentially expressed (p < 0.0001) between the groups. Two 11 kDa protein peaks were identified by MALDI-TOF/TOF-MS and confirmed to be mouse serum amyloid A (SAA) 1 and 2. Plasma SAA2 levels were increased in LPS-treated animals compared with controls and in LPS-treated animals that delivered preterm vs. those that delivered at term. SAA2 has the potential to be a plasma biomarker that can identify pregnancies at risk for development of PTL.
Does Machine Learning Really Work?

Does machine learning really work? Yes. Over the past decade, machine learning has evolved from a field of laboratory demonstrations to a field of significant commercial value. Machine-learning algorithms have now learned to detect credit card fraud by mining data on past transactions, learned to steer vehicles driving autonomously on public highways at 70 miles an hour, and learned the reading interests of many individuals to assemble personally customized electronic newsAbstracts. A new computational theory of learning is beginning to shed light on fundamental issues, such as the trade-off among the number of training examples available, the number of hypotheses considered, and the likely accuracy of the learned hypothesis. Newer research is beginning to explore issues such as long-term learning of new representations, the integration of Bayesian inference and induction, and life-long cumulative learning. This article, based on the keynote talk presented at the Thirteenth National Conference on Artificial Intelligence, samples a number of recent accomplishments in machine learning and looks at where the field might be headed. [Copyright restrictions preclude electronic publication of this article. ]
GPCore – a generic framework for genetic programming

Complex engineering tasks are rarely unique in their solution. The question is not to determine a single solution – it is more to retrieve an optimal solution. Automated, software-based optimization technologies turned out to be a very promising and applicable solution for the class of non-deterministic optimization problems. In this paper a generic framework for the application of genetic programming will be introduced. The framework is based on the Backus-Naur representation, which can be seen as a meta-programming language. According to specific demands on engineering problems, various detail solutions have been evolved in this context. Finally, the application of the developed framework in load identification will be presented. An example of an evolutionary optimization within the analysis of measured data will be given. By means of two encapsulated optimization routines structural responses re-corded at instrumented bridges are analyzed to determine gross weights, velocities, axle loads as well as axle spacings of passing vehicles. Most significant aspects of the developed framework will be covered within the example: Problem decomposition, problem space definition based on the meta-language, genotype generation, examples of crucial cross-over and mutation operations, fitness evaluation and entire operation of the optimization process.
Semantic Link Analysis for Finding Answer Experts

Recommending unanswered questions to answer experts is an important mechanism in User-Interactive Question Answering (UIQA) services and is helpful to reduce asker's waiting time and obtain high-quality answers. In this paper, we address the task of identifying answer experts in UIQA services with semantic information extracted from user interaction behaviors. We first construct the user question-answer interaction graph through direct semantic links and latent links extracted from the records of question sessions and user profiles. After that, two expert-finding approaches are developed by employing the semantic information in the so-called propagation link analysis method and in the language model, respectively. Experimental results on Yahoo! Answers dataset show that the extracted semantic information indeed improves the performance of both propagation and language model for the task of answer experts finding.
NitrogenMovementbetween Hostand Tumorin Mice Inoculatedwith EhrlichAsciticTumorCells1

Tumors function as a nitrogen trap, and they compete with the host for nitrogen compounds. In experiments with whole animals infected with Ehrlich ascitic tumor cells, the glutamine, glutamate, asparagine, and aspartate concentrations were de termined for host plasma, ascitic liquid, and tumor cells, through out the period of tumor growth. Concentration gradients of glutamine or asparagine were created from the host tissues towards the ascitic liquid. The countergradient step from ascitic liquid to tumor cells may be overcome by an active transport process with an apparent Kmfor glutamine of 3.1 x 10~4 M. On the other hand, a reverse flux of glutamate and aspartate was seen to take place from cells to plasma. In vitro incubations of tumor cells with near physiological concentrations of glutamine, or asparagine plus glucose, confirmed the host-to-tumor nitrogen movement previously deduced from the relative amino acid con centrations in plasma, ascitic liquid, and tumor cells. The ammonemia detected in tumor-bearing mice at the terminal stage could result from the hydrolysis of glutamine, which was rapidly metabolized by the tumor cells.
Route swap processes and convergence measures in dynamic traffic assignment

Dynamic traffic assignment algorithms typically proceed by iterating between route swapping and dynamic network loading. This chapter considers various route swap processes and investigated their convergence to equilibrium (assuming that the route cost vector is a monotone function of the route flow vector). Pairwise swapping (in which swapping can occur between each pair of routes) is shown to converge even with an arbitrary exponent on the cost differences (in the dynamic model and hence also in the steady state model). When swapping is only to the least costly route (for that origin destination (OD) pair), convergence is shown in the steady state model. Various forms of convergence measure were considered; this form is suggested by the route swap process. Equivalences were established between the different forms in that if one converged to zero (for a particular route swap process) then so would the other. These equivalences are independent of whether the swap process is continuous or discrete (i.e. the integral can be replaced with a sum).
Joint Eurographics -ieee Tcvg Symposium on Visualization (2003) Interactive Feature Specification for Focus+context Visualization of Complex Simulation Data

Visualization of high-dimensional, large data sets, resulting from computational simulation, is one of the most challenging fields in scientific viualization. When visualization aims at supporting the analysis of such data sets, feature-based approches are very useful to reduce the amount of data which is shown at each instance of time and guide the user to the most interesting areas of the data. When using feature-based visualization, one of the most difficult questions is how to extract or specify the features. This is mostly done (semi-)automatic up to now. Especially when interactive analysis of the data is the main goal of the visualization, tools supporting interactive specification of features are needed. In this paper we present a framework for flexible and interactive specification of high-dimensional and/or complex features in simulation data. The framework makes use of multiple, linked views from information as well as scientific visualization and is based on a simple and compact feature definition language (FDL). It allows the definition of one or several features, which can be complex and/or hierarchically described by brushing multiple dimensions (using non-binary and composite brushes). The result of the specification is linked to all views, thereby a focus+context style of visualization in 3D is realized. To demonstrate the usage of the specification, as well as the linked tools, applications from flow simulation in the automotive industry are presented.
Tropospheric ozone over the North Pacific from ozonesonde observations

[1] As part of the Transport and Chemical Evolution over the Pacific (TRACE-P) mission, ozonesondes were used to make ozone vertical profile measurements at nine locations in the North Pacific. At most of the sites there is a multiyear record of observations. From locations in the western Pacific (Hong Kong; Taipei; Jeju Island, Korea; and Naha, Kagoshima, Tsukuba, and Sapporo, Japan), a site in the central Pacific (Hilo, Hawaii), and a site on the west coast of the United States (Trinidad Head, California) both a seasonal and event specific picture of tropospheric ozone over the North Pacific emerges. Ozone profiles over the North Pacific generally show a prominent spring maximum throughout the troposphere. This maximum is tied to the location of the jet stream and its influence on stratosphere-troposphere exchange and the increase in photochemical ozone production through the spring. Prominent layers of enhanced ozone in the middle and upper troposphere north of about 30°N seem to be more closely tied to stratospheric intrusions while biomass burning leads to layers of enhanced ozone in the lower and upper troposphere at Hong Kong (22°N) and Taipei (25°N). The lower free tropospheric layers at Hong Kong are associated with burning in SE Asia, but the upper layer may be associated with either equatorial Northern Hemisphere burning in Africa or SE Asian biomass burning. In the boundary layer at Taipei very high mixing ratios of ozone were observed that result from pollution transport from China in the spring and local urban pollution during the summer. At the ozonesonde site near Tokyo (Tsukuba, 36°N) very large enhancements of ozone are seen in the boundary layer in the summer that are characteristic of urban air pollution. At sites in the mid and eastern Pacific the signature of transport of polluted air from Asia is not readily identifiable from the ozonesonde profile. This is likely due to the more subtle signal and the fact that from the ozone profile and meteorological data by themselves it is difficult to identify such a signal. During the TRACE-P intensive campaign period (February–April 2001), tropospheric ozone amounts were generally typical of those seen in the long-term records of the stations with multiyear soundings. The exception was the upper troposphere over Hong Kong and Taipei where ozone amounts were lower in 2001.
Painterly rendering using human vision

Painterly rendering has been linked to computer vision, but we propose to link it to human vision because perception and painting are two processes that are interwoven. Recent progress in developing computational models allows to establish this link. We show that completely automatic rendering can be obtained by applying four image representations in the visual system: (1) colour constancy can be used to correct colours, (2) coarse background brightness in combination with colour coding in cytochrome-oxidase blobs can be used to create a background with a big brush, (3) the multi-scale line and edge representation provides a very natural way to render finer brush strokes, and (4) the multi-scale keypoint representation serves to create saliency maps for Focus-of-Attention, and FoA can be used to render important structures. Basic processes are described, renderings are shown, and important ideas for future research are discussed.
Towards global consistent pose estimation from images

We propose a method for making globally consistent pose estimates using vision. Lu and Milios (1997) described an approach where the links between poses were estimated using range scanner data. When using point correspondences the length of the links cannot be estimated and the approach of Lu and Milios has to be modified. First, we use the nonlinear orientation part of the pose differences to obtain a reference trajectory. Then the reference trajectory is used to scale and orientate the linear spatial part of the pose differences, such that the positions can be estimated as well. We show the results of an experiment of navigating a robot equipped with an omnidirectional camera on the corridor.
Group Decisions, Contracts and Informational Cascades

We analyze the (Perfect Bayesian) equilibrium in an observational learning model with communication and bilateral incentive contracts when pairs of agents sequentially make decisions based on internal communications and the observed history of decisions by other groups. One of the agents in each pair receives a private noisy signal on an unknown state and we characterize asymptotic learning through the design of efficient bilateral contracts. Long run information aggregation depends not only on the properties of the signal structure but also on the intensity of the conflicts of interest between the informed and uninformed agents. In contrast to the results from the herding literature, we find that information can be asymptotically complete with bounded (private) beliefs while there may be herding even with unbounded beliefs; in the latter case herding occurs when the conflicts are sufficiently high that it is incentive-efficient to divorce decisions from private signals. We derive sufficient conditions on agents' preferences and the signal structure for learning to be asymptotically complete as the number of agent-pairs gets large and illustrate their applications by adapting models from the price-quality discrimination and investment contracting literatures.
Function Level Control Flow Obfuscation for Software Security

Software released to the user has the risk of reverse engineering attacks. Software control flow obfuscation is one of the techniques used to make the reverse engineering of software programs harder. Control flow obfuscation, obscures the control flow of the program so that it is hard for an analyzer to decode the logic of the program. In this paper, we propose an obfuscation algorithm which obscures the control flow across functions. In our method code fragments from each function is stripped from the original function and is stored in another function. Each function will be having code fragments from different functions, thereby creating a function level shuffled version of the original program. Control flow is obscured between and within the function by this method. Experimental results indicate that the algorithm performs well against automated attacks.
Boosted Exemplar Learning for human action recognition

Human action recognition has been an active research topic in computer vision. How to model all kinds of actions, varying with time resolution, visual appearance, etc., is quite a challenging task for recognition. In this paper, we propose a Boosted Exemplar Learning (BEL) approach to recognize various actions in a weakly supervised manner, i.e., only video-based labels are provided but frame-based ones are not. First, for a given action, each video is described as a set of similarities between its frames and some candidate ones (called as exemplars), which are selected from training videos belonging to the action. Instead of simply using a heuristic distance measure, the similarities are decided by the exemplar-based classifiers through the Multiple Instance Learning (MIL), in which a positive (or negative) video is deemed as a positive (or negative) bag and those similar frames to the given exemplar in Euclidean Space as instances. Second, we formulate the selection of the most discriminative exemplars into a boosted feature selection framework and simultaneously obtain a video-based action detector in the boosted learning process. Experimental results on two publicly available challenging datasets: the KTH dataset and Weizmann dataset demonstrate the validity and effectiveness of the proposed approach.
3 OPIOID PEPTIDES AND THEIR RECEPTORS : OVERVIEW AND FUNCTION IN PAIN MODULATION

Few neurotransmitter systems have fascinated the general public as much as the endorphins, otherwise known as the endogenous opioid peptides. They have been termed the ‘‘heroin within’’ and endowed with the power to relieve pain and allow one to experience ‘‘runner’s high’’ or enjoy the taste of chocolate. Although these powers may or may not withstand close scientific scrutiny, there is little question that endogenous opioid systems play a critical role in modulating a large number of sensory, motivational, emotional, and cognitive functions. As inhibitory neuropeptide transmitters, they fine-tune neurotransmission across a wide range of neuronal circuits, setting thresholds or upper limits. In addition, they have served as prototypes for understanding many structural and functional features of peptidergic systems. Thus, the first neuronal receptor binding assays were conducted on opioid receptors. The first peptides to be discovered and identified after the hypothalamic neurohormones (oxytocin and vasopressin) were the endogenous opioids. The first mammalian cyclic DNA (cDNA) to be cloned was an opioid precursor (proopiomelanocortin), which also served as the prototype for genes that encode multiple active substances and process them in a tissuespecific and situation-specific manner. Scientific studies of these systems during the last 30 years have uncovered a complex and subtle system that exhibits impressive diversity in terms of the number of endogenous ligands (more than a dozen) yet amazing convergence at the level of receptors (only three major types). Based on the results of these studies, the endogenous opioids have been implicated in circuits involved in the control of sensation, emotion, and affect, and a role has been ascribed to them in addiction—not only to opiate drugs, such as morphine and heroin, but also to other highly abused drugs, such as alcohol. This chapter cannot do justice to the rich body of
A selective encryption scheme for H.264 video based on permutation code and dynamic keys

H.264 video coding standard supports a broad range of application and providing its security is an important research topic. In this work, a video encryption algorithm for H.264 is proposed, which combines permutation code algorithm with dynamic keys. This work aims at providing more security for H.264 video using dynamic keys and permutation code algorithm, for confidential video transmission with reliability. The prime concern is that, the added security does not introduce distortion, which means the encrypted video has the same quality as that of the unencrypted video. Simulation experiments and security tests such as key sensitivity and Histogram analysis show that the proposed scheme is secure.
The Politics of Post-War Demobilisation and Reintegration in Nigeria

Contents: Preface Introduction Background to the Nigerian civil war The cause for post-civil war disarmament, demobilisation and reintegration The politics of socio-economic and humanitarian reintegration The politics of military disarmament, demobilisation and reintegration The international politics of rehabilitation, reconstruction and reconciliation Conclusion Appendix Bibliography Index.