Miracle-dz/UniFAR-FTUs huggingface dataset:
TRB 3 / 2014 Conditioning Probabilistic Relational Data with Referential Constraints

A probabilistic relational database is a compact form of a set of deterministic relational databases (namely, possible worlds), each of which has a probability. In our framework, the existence of tuples is determined by associated Boolean formulae based on elementary events. An estimation, within such a setting, of the probabilities of possible worlds uses a prior probability distribution specified over the elementary events. Direct observations and general knowledge, in the form of constraints, help refining these probabilities, possibly ruling out some possible worlds. More precisely, new constraints can translate the observation of the existence or non-existence of a tuple, the knowledge of a well-defined rule, such as primary key constraint, foreign key constraint, referential constraint, etc. Informally, the process of enforcing knowledge on a probabilistic database, which consists of computing a new subset of valid possible worlds together with their new (conditional) probabilities, is called conditioning. In this paper, we are interested in finding a new probabilistic relational database after conditioning with referential constraints involved. In the most general case, conditioning is intractable. As a result, we restricted our study to probabilistic relational databases in which formulae of tuples are independent events in order to achieve some tractability results. We devise and present polynomial algorithms for conditioning probabilistic relational databases with referential constraints.
Speed control of quadrupedal bounding using a reaction wheel

To date, quadruped speed control has either been achieved with two actuators per leg, or with single actuators and time consuming trial and error experimentation for controller tuning. In this paper, a novel control method is developed that uses only one actuator per leg and yet requires no controller tuning from the user, since the control parameters are computed through analytical expressions derived from the robot dynamics. One further actuator is used to drive a reaction wheel situated on the body. The control method leads to stable bounding gaits with controllable forward speed, and as the control is based on analytical results from the robot dynamics, it is applicable to a range of design parameters, rather than a specific robot. Light, off-the-shelf DC motors are shown to be adequate for successful controller operation. Results are shown of the control applied to a detailed robot model, including leg and toe mass, foot collision, DC motor model, joint friction and a foot-ground friction model allowing foot slipping.
An iterative projections algorithm for ML factor analysis

Alternating minimization of the information divergence is used to derive an effective algorithm for maximum likelihood (ML) factor analysis. The proposed algorithm is derived as an iterative alternating projections procedure on a model family of probability distributions defined on the factor analysis model and a desired family of probability distributions constrained to be concentrated on the observed data. The algorithm presents the advantage of being simple to implement and stable to converge. A simulation example that illustrates the effectiveness of the proposed algorithm for ML factor analysis is presented.
Vision-based system for continuous Arabic Sign Language recognition in user dependent mode

Existing work on Arabic Sign Language recognition focuses on finger spelling and isolated gestures. In this work we extend vision-based existing solutions to recognition of continuous signing. As such we have collected and labeled the first video-based continuous Arabic Sign Language dataset. We intend to make the collected dataset available for the research community. The proposed solution extracts the motion from the video-based sentences by means of thresholding the forward prediction error between consecutive images. Such prediction errors are then transformed into the frequency domain and Zonal coded. We use Hidden Markov Models for model training and classification. The experimental results show an average word recognition rate of 94%, keeping in the mind the use of a high perplexity vocabulary and unrestrictive grammar.
Volatility Modelling

In this paper the Black–Scholes implied volatility and the GARCH volatility are compared. The implied volatility is used in the form of volatility indices. Empirical study of the performance of GARCH in forecasting the implied volatility shows that the GARCH volatility can be used to forecast the implied volatility and is better than the historical volatility. Two different volatility indices (VIX, VDAX) of two different market indices (SPX index in United States and DAX index in Germany) were considered in the empirical study. Introduction The word volatility means rapid or unexpected changes. During the last decades the meaning has become more diversified according to who uses it. For traders volatility means opportunity, because with more volatile markets there is a higher probability of bigger profits whereas with low volatility trading resembles dull sport. For risk managers volatility means danger, because with more volatile markets there is also a higher probability of bigger losses, connected with the fact that mathematical models widely used for risk management could underestimate the risk in the portfolio. For financial theorists volatility often means some parameter or process in mathematical models that has to be chosen to ”fit the real world” properly. Since volatility is directly unobservable, it is no wonder that volatility modelling is a very big challenge. Nowadays the number of volatility models is enormous and is still increasing. Market volatility is currently one of the most investigated phenomena in finance. The intention of this paper is to compare the implied Black–Scholes volatility with the GARCH volatility. The Black–Scholes Volatility In the well known Black–Scholes (BS) model [Black and Scholes, 1973] it is assumed that the price of an underlying asset St follows the geometric Brownian motion given by dSt = μSt dt + σSt dWt, (1) where drift μ is expected return on the asset, volatility σ measures the variability around μ and Wt is the standard Brownian motion. Important implication of this assumption is that the logarithm of the ending price at time T > t is equal to ln(ST ) = ln(St) + (μ− σ/2)(T − t) + σ √ T − t , (2) where is the standard normal random variable. This means that ST given St is log normally distributed. Further it follows that the logarithmic returns rt = ln(St/St1) are normally distributed. This result is however not supported by empirical data studies. Financial time series of logarithmic returns exhibit typical properties [Franke et al., 2007]. Returns rt have in general a leptokurtic distribution, the kurtosis is mostly much greater than 3 that clearly rejects the normal distribution. Typical shape of the distribution is highly peaked and fat-tailed that is characteristic to mixtures of distributions with different variances. Time series of returns tend to form clusters. This suggests that the volatility (or variance) is autocorrelated whilst the time series of returns itself are often uncorrelated. 148 WDS'09 Proceedings of Contributed Papers, Part I, 148–153, 2009. ISBN 978-80-7378-101-9 © MATFYZPRESS
Contextual Identity Recognition in Personal Photo Albums

We present an efficient probabilistic method for identity recognition in personal photo albums. Personal photos are usually taken under uncontrolled conditions -the captured faces exhibit significant variations in pose, expression and illumination that limit the success of traditional face recognition algorithms. We show how to improve recognition rates by incorporating additional cues present in personal photo collections, such as clothing appearance and information about when the photo was taken. This is done by constructing a Markov random field (MRF) that effectively combines all available contextual cues in a principled recognition framework. Performing inference in the MRF produces markedly improved recognition results in a challenging dataset consisting of the personal photo collections of multiple people. At the same time, the computational cost of our approach remains comparable to that of standard face recognition approaches.
Navigation of networked mobile robot using behavior-based model

This paper presents a behavior-based approach for the navigation of networked mobile robot. In the model, a complex navigation task is divided into individual behaviors. Each behavior deals with a different aspect of the network and environment. The predictive filter, stabilization control, and fuzzy logic are employed to design and implement the behavior. The coordination between behaviors is handled by a supervision layer. It determines the priorities of behaviors based on the context and then blends the output of each behavior to generate a crisp output. Experiments shows that the robot can follow user's commands, avoid obstacles, and reach destination while adapt to uncertain elements such as network delay, out-of-order delivery and packet loss.
Understanding Application Behaviours for Android Security: A Systematic Characterization

In contrast to most existing research on Android focusing on specific security issues, there is little broad understanding of Android application run-time characteristics and their security implications. To mitigate this gap, we present the first dynamic characterization study of Android applications that targets such a broad understanding for Android security. Through lightweight method-level profiling, we have collected 33GB traces of method calls and inter-component communication (ICC) from 114 popular Android applications on Google Play and 61 communicating pairs among them that enabled an extensive empirical investigation of the run-time behaviours of Android applications. Our study revealed that (1) the Android framework was the target of 88.3% of all calls during application executions, (2) callbacks accounted for merely 3% of the total method calls, (3) 75% of ICCs did not carry any data payloads with those doing so preferring bundles over URIs, (4) 85% of sensitive data sources and sinks targeted one or two top categories of information or operations which were also most likely to constitute data leaks. We discuss the security implications of our findings to secure development and effective security defense of modern Android applications.
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other

1. Summary. Letx and ybe two random variableswith continuous cumulative distribution functions f and g. A statistic U depending on the relative ranks of the x's and y's is proposed for testing the hypothesisf = g. Wilcoxon proposed an equivalent test in the Biometrics Bulletin, December, 1945, but gave only a few points of the distribution of his statistic.
A Survey-Based Mobilty Model of People for Simulation of Urban Mesh Networks

In this paper a mobility model of people in urban areas for mobile wireless network simulation is presented. A 3-layer hierarchical approach is taken where the highest layer is an activity model that determines the high level activity that the node is performing (e.g., working). The second level is a task model that models the specific task within an activity (e.g., meeting with three people). And the third level is an agent model that determines how the person moves from one location to another. These three models are based on a number of surveys and data sources. The activity model is based on a recent US Department of Labor Bureau of Labor Statistics time use study. Such time use studies gather detailed information about how the interviewees spent their time. The task model mostly focuses on mobility of office workers and is based on the current findings from research on meetings analysis. The agent model is based on the work from urban planning that has collected extensive knowledge of pedestrian flow. The models presented are implemented in a mobility simulator that is integrated with a wireless propagation model (described elsewhere).
Terminal‐Assisted Hybrid MAC Protocol for Differentiated QoS Guarantee in TDMA‐Based Broadband Access Networks

This paper presents a terminal‐assisted frame‐based packet reservation multiple access (TAF‐PRMA) protocol, which optimizes random access control between heterogeneous traffic aiming at more efficient voice/data integrated services in dynamic reservation TDMA‐based broadband access networks. In order to achieve a differentiated quality‐of‐service (QoS) guarantee for individual service plus maximal system resource utilization, TAF‐PRMA independently controls the random access parameters such as the lengths of the access regions dedicated to respective service traffic and the corresponding permission probabilities, on a frame‐by‐frame basis. In addition, we have adopted a terminal‐assisted random access mechanism where the voice terminal readjusts a global permission probability from the central controller in order to handle the ‘fair access’ issue resulting from distributed queuing problems inherent in the access network. Our extensive simulation results indicate that TAF‐PRMA achieves significant improvements in terms of voice capacity, delay, and fairness over most of the existing medium access control (MAC) schemes for integrated services.
Contrast-enhanced CT evaluation of clinically and mammographically occult multiple breast tumors in women with unilateral early breast cancer.

BACKGROUND Magnetic resonance imaging mammography is performed to determine the extent of lesions and to detect occult lesions, but preoperative diagnosis by breast computed tomography (CT) is less common. METHODS We performed a retrospective study of detection of mammographically occult multiple lesions using breast CT. The subjects were 407 female patients (median age: 56 years old; median tumor size: 1.9 cm) with breast cancer who underwent preoperative, contrast-enhanced breast CT. RESULTS CT detected 73 incidental-enhanced breast nodules (median size: 0.8 cm) in 73 patients that were undetectable by conventional methods. Age, size of the main lesion or laterality of lesions did not differ between patients with and without incidental nodules, but the frequency of mastectomy was significantly higher in those with incidental nodules. Of the 73 incidental nodules, 22 (30%) were in the same quadrant as the main lesion, 26 (36%) were in other quadrants and 25 (34%) were in the opposite breast. On qualitative diagnosis by CT, 48 were suspected to be malignant (66%), 17 benign (23%) and eight non-specific (11%). In histological evaluation of 44 of the 48 nodules suspected to be malignant, 24 were malignant (invasive carcinoma: 22, non-invasive carcinoma: 2); of seven of the 17 nodules suspected to be benign, all were benign; and of three of the eight non-specific nodules, one was non-invasive carcinoma. The discovery rate of clinically and mammographically occult multiple lesions by preoperative breast CT was 6%. CONCLUSION We conclude that breast CT is useful for the detection of occult lesions and choice of surgical procedure.
High Quality High Dynamic Range Imaging Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences Zijian Zhu High Quality High Dynamic Range Imaging

A high dynamic range (HDR) image uses a large bit depth up to 32-bit per pixel per color channel. Due to hardware limitation, it can neither be captured by conventional camera in a single photo, nor be displayed on a conventional monitor. In this thesis, a software solution of HDR imaging is introduced from the synthesis to the display of high quality HDR images. Contrary to conventional imaging method, HDR imaging uses multiple exposures. Therefore, the variance of the same pixel in different images is non-linear and difficult to measure. To solve this, a new inter-pixel relationship function (IRF) is proposed using both spatial and temporal correlations. It is widely used in many HDR imaging components. Multiple input images produce a new ghosting artifact due to moving object. A real time de-ghosting method is first proposed using bi-directional comparison and IRF based moving object detection and patching. It is lightweight in terms of both time complexity and physical memory consumption, which makes it suitable for mobile devices. We further extend it by merging the IRF with a histogram intensity mapping and adopting a new threshold model based on statistical study. The extended deghosting scheme is more robust in the scenarios where the moving object occupies larger areas. Noise in the input images will be kept in the synthesized HDR image. A 2D de-noising factor is proposed for the synthesis of 32-bit HDR image, and a noise reduced tonemapping is proposed to map the 32-bit HDR image back to 8-bit for the display based on information content weighting (ICW). Both methods have low time complexity. It is also important to measure if the input images are from the same scene, as huge artifacts may appear if a wrong image is involved in the synthesis process. We proposed a structure similarly based metric which is robust to the images with different exposures. We also proposed a metric for the measurement of two 32-bit HDR images based on their histograms of radiance maps. AMS Classification: 68U10; 94A08 Universal Decimal Classification: 004.932 Library of Congress Subject Headings: High dynamic range imaging; Computational photography; Image enhancement Methods; Image systems Image quality Yleinen suomalainen asiasanasto: digitaalikuvaus; kuvankäsittely
Mutual Authentication Protocol for Networked RFID Systems

In this paper we address the problem of securing networked RFID applications. We develop and present a RFID security protocol that allows mutual authentication between the reader and tag as well as secure communication of tag data. The protocol presented uses a hybrid method to provide strong security while ensuring the resource requirements are low. To this end it employs a mix of simple one way hashing and low-cost bit wise operations. Our protocol ensures the confidentiality and integrity of all data being communicated and allows for reliable mutual authentication between tags and readers. The protocol presented is also resistant to a large number of common attacks.
An automatic ontology-based approach to enrich tables semantically

This work aims at building automatically a thematic data warehouse composed of heterogeneous XML documents extracted from the Web. We focus on the data tables contained in these documents. This article presents how we enrich semantically those tables by means of tags and values coming from¡ the ontology of the application. First results are given for a set of real data of the e.dot project.
Interval-valued Fuzzy Generalized Bi-ideals of Ordered Semigroups Redefined

In order to find more general forms of an interval valued (∈,∈∨ q)-fuzzy generalized bi-ideal in ordered semigroups, we have introduced the notion of an interval valued k (, q) ∈∈∨  -fuzzy generalized bi- ideal in ordered semigroups and investigated several properties. We have dealt with characterizations of an interval valued k (, q) ∈∈∨  -fuzzy generalized bi-ideal. In this article, we try to obtain a more general form than interval valued (∈,∈∨q)-fuzzy generalized bi-ideals in ordered semigroups. The notion of an interval valued k (, q) ∈∈∨  -fuzzy generalized bi-ideals is introduced and several properties are investigated. Characterizations of an interval valued k (, q) ∈∈∨  -fuzzy generalized bi-ideal are established. A condition for an interval valued k (, q) ∈∈∨  -fuzzy generalized bi-ideal to be an interval valued fuzzy generalized bi-ideal is provided. Using implication operators and the notion of implication-based an interval valued fuzzy generalized bi-ideals, characterizations of an interval valued fuzzy generalized bi-ideal and an interval valued k (, q) ∈∈∨  -fuzzy generalized bi-ideal are considered.
Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.
Ant clustering based text detection in natural scene images

Text pictures in natural scene are necessary clues for several image-based applications like scene understanding, content-based image retrieval, helpful navigation, and automatic geocoding. However, locating text from a fancy atmosphere with multiple colors may be a difficult task. Although there are various techniques implemented for the detection of the text in natural scenes. The work implemented in paper(Text string detection from natural scenes by structural based partition and grouping) is based on Gradient based Partition and Color based Partition but the techniques implemented here provides less efficiency and the chances of error rate is more hence have less accuracy. But the technique implemented in this paper for the detection of texts in natural scenes is based on Ant based clustering. By using Ant clustering the performance of the technique for the detection of text has been increased.
A Proactive Concept for QoS Supports in Wireless Networks

∗ With a Fellowship of the Alexander -von-Humboldt Foundation Abstract. The End-to-End Quality of Service (end -to-end QoS) is an important factor in the design of the next generation of mobile wireless networks. In this paper, we propose a proactive concept for QoS supports in wireless multimedia communication networks. The concept is based on a traffic scheduling mechanism, a compensation model for wireless loss, a bandwidth estimator for verifying the wireless link condition and the available bandwidth. In this concept, a QoS proxy is located at the base station of the wireless networks and a QoS agent is in the mobile endsystem. The user feedback is realized by a user interface and is used for adjusting the needed QoS required by the user itself. The concept is furthermore characterised by the gathering of queue lengths of packet flows and the calculating of the loss probability for QoS monitoring in QoS proxy. A rate control protocol for TCP friendly flows is devel oped for achieving end -to-end QoS guarantee .
Study of radiation effects on PIN photodiodes with deep-trap levels using computer modeling

In the present work, a complete numerical analysis of the influence of deep-trap levels on the dark current of silicon PIN photodiodes under 1 MeV neutron radiation was done. Results corroborate that energy levels near the mid-gap affect to a great extent the dark current. Radiation tolerances of undoped and gold-doped devices were compared through simulations. It has been concluded that gold in silicon reduces the neutron-induced damage. Finally, a model to calculate the dark current of irradiated devices doped with deep-impurities is presented.