Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion detection, object classiﬁcation and tracking forvisual surveillance application

Visual surveillance in dynamic scenes, especially for humans and vehicles, is one of the current challenging research topics in computer vision. It is a key technology to ﬁght against terrorism, crime, public safety and for eﬃcient management of traﬃc. The work involves designing of eﬃcient visual surveillance system in complex environments. In video surveillance, detection of moving objects from a video is important for object classiﬁcation, target tracking, activity recognition, and behavior understanding. Detection of moving objects in video streams is the ﬁrst relevant step of information and background subtraction is a very popular approach for foreground segmentation. In this thesis, we have simulated diﬀerent background subtraction methods to overcome the problem of illumination variation, background clutter, shadows, and camouﬂage. Object classiﬁcation is done using silhouette template based classiﬁcation to categorize objects into human, group of human and vehicle. Detecting and tracking of human body parts is important in understanding human activities. We have proposed two methods to overcome the problem of object tracking in varying illumination condition and background clutter. For target tracking of interested object in the consecutive video frames, we have used normalized correlation coeﬃcient (NCC). NCC is robust to varying illumination condition. Template is updated on every frame to minimize the template drift problem and it also tries to cope with short-lived occlusion and background clutter. In order to extend the surveillance area and overcome occlusion, fusion of data from multiple cameras is employed in our project. We have tracked objects across multiple cameras with non-overlapping FOVs based on object appearances. A brightness transfer function (BTF) is determined from the cumulative histograms of the images. Matching of the object is done, with the help of Bhattacharya distance.
Lower bounds on Hilbert's Nullstellensatz and propositional proofs

The weak form of the Hilbert's Nullstellensatz says that a system of algebraic equations over a field, Q/sub i/(x~)=0, does not have a solution in the algebraic closure iff 1 is in the ideal generated by the polynomials Q/sub i/(x~). We shall prove a lower bound on the degrees of polynomials P/sub i/(x~) such that /spl Sigma//sub i/ P/sub i/(x~)Q/sub i/(x~)=1. This result has the following application. The modular counting principle states that no finite set whose cardinality is not divisible by q can be partitioned into q-element classes. For each fixed cardinality N, this principle can be expressed as a propositional formula Count/sub q//sup N/. Ajtai (1988) proved recently that, whenever p, q are two different primes, the propositional formulas Count/sub q//sup qn+1/ do not have polynomial size, constant-depth Frege proofs from instances of Count/sub p//sup m/, m/spl ne/0 (mod p). We give a new proof of this theorem based on the lower bound for the Hilbert's Nullstellensatz. Furthermore our technique enables us to extend the independence results for counting principles to composite numbers p and q. This results in an exact characterization of when Count/sub q/ can be proven efficiently from Count/sub p/, for all p and q. <<ETX>>
On Applications of Unequally Spaced Fast Fourier Transforms

l = −N/2, . , N/2 − 1, n = 1, . , Nf and its adjoint. Algorithms for the fast application of matrices in (1.3), (1.4) and their adjoints to vectors (as well as their multidimensional generalizations) constitute Unequally Spaced Fast Fourier Transform (USFFT) algorithms. A number of such algorithms has been known in EE and geophysical literature as algorithms for interpolation in the frequency domain (see e.g., [15]). These algorithms were constructed by approximating the ideal filter and were not intended to produce high accuracy although they were adequate in a number of applications. In [11] Press and Rybicki suggested using Lagrange interpolation to replace the function values at an arbitrary point by several function values on an equally spaced grid surrounding
Direction-resolved estimation of multipath parameters for UWB channels: A partially collapsed Gibbs sampler method

We propose a Monte Carlo method for determining the parameters of multipath components (MPCs) for ultra-wideband channels. A partially collapsed Gibbs sampler is used for jointly estimating the number, times-of-arrival, angles-of-arrival, and amplitudes of the MPCs as well as the sounding pulse from signals received by a 2D antenna array. Our system model accounts for propagation delays between the receive antennas. Temporal-angular sparsity of the detected MPCs is ensured by a 2D minimum distance constraint. Numerical results for synthetic and real signals demonstrate the excellent performance and fast convergence of our method.
Pattern-based development of user-friendly web applications

Using patterns to preserve common problem-solving knowledge is a very popular approach. Each computer science community applies its own techniques to document engineering principles for the handling of recurring software development questions using patterns. Thus various pattern collections were evolved for dealing with specific problems of the respective community. As a result comparable patterns or redundant pattern descriptions exist in different collections leading unintentionally to a "reinvention of the wheel" time and again. Taking the development of a chat application as an example, we present an approach for integrating patterns from different software engineering disciplines. We transform problem patterns (problem frames) into solution patterns (design patterns) by using a case-based reasoning methodology to achieve a pattern-based software development process which systematically leads from natural language requirements to semi-formal near code level descriptions. We particularly consider non-functional software properties by combining design patterns of human-computer interaction (HCI) with software engineering (SE) patterns in order to support the systematic development of user-friendly software applications.
Variable Selection for Clustering with Gaussian Mixture Models

Summary This article is concerned with variable selection for cluster analysis. The problem is regarded as a model selection problem in the model‐based cluster analysis context. A model generalizing the model of Raftery and Dean (2006, Journal of the American Statistical Association 101, 168–178) is proposed to specify the role of each variable. This model does not need any prior assumptions about the linear link between the selected and discarded variables. Models are compared with Bayesian information criterion. Variable role is obtained through an algorithm embedding two backward stepwise algorithms for variable selection for clustering and linear regression. The model identifiability is established and the consistency of the resulting criterion is proved under regularity conditions. Numerical experiments on simulated datasets and a genomic application highlight the interest of the procedure.
Elucidating the Skin Delivery of Aglycone and Glycoside Flavonoids: How the Structures Affect Cutaneous Absorption

Flavonoids are bioactive phytochemicals that exhibit protective potential against cutaneous inflammation and photoaging. We selected eight flavonoid aglycones or glycosides to elucidate the chemistry behind their skin absorption capability through experimental and computational approaches. The skin delivery was conducted using nude mouse and pig skins mounted on an in vitro Franz cell assembly. The anti-inflammatory activity was examined using the O2•– and elastase inhibition in activated human neutrophils. In the equivalent dose (6 mM) application on nude mouse skin, the skin deposition of naringenin and kaempferol was 0.37 and 0.11 nM/mg, respectively, which was higher than that of the other flavonoids. Both penetrants were beneficial for targeted cutaneous therapy due to their minimal diffusion across the skin. The absorption was generally greater for topically applied aglycones than glycosides. Although naringenin could be classified as a hydrophilic flavonoid, the flexibility of the chiral center in the C ring of this flavanone could lead to better skin transport than the flavonols and flavones with a planar structure. An optimized hydrophilic and lipophilic balance of the flavonoid structure was important for governing the cutaneous delivery. The hydrogen bond acceptor and stratum corneum lipid docking estimated by molecular modeling showed some relationships with the skin deposition. The interaction with cholesteryl sulfate could be a factor for predicting the cutaneous absorption of aglycone flavonoids (correlation coefficient = 0.97). Baicalin (3 µM) showed the highest activity against oxidative burst with an O2•– inhibition percentage of 77%. Although naringenin displayed an inhibition efficiency of only 20%, this compound still demonstrated an impressive therapeutic index because of the high absorption. Our data are advantageous to providing the information on the structure–permeation relationship for topically applied flavonoids.
A model for enriching trajectories with semantic geographical information

The collection of moving object data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data in different application domains. Trajectory data are normally available as sample points, and do not carry semantic information, which is of fundamental importance for the comprehension of these data. Therefore, the analysis of trajectory data becomes expensive from a computational point of view and complex from a user's perspective. Enriching trajectories with semantic geographical information may simplify queries, analysis, and mining of moving object data. In this paper we propose a data preprocessing model to add semantic information to trajectories in order to facilitate trajectory data analysis in different application domains. The model is generic enough to represent the important parts of trajectories that are relevant to the application, not being restricted to one specific application. We present an algorithm to compute the important parts and show that the query complexity for the semantic analysis of trajectories will be significantly reduced with the proposed model.
Imaging of dynamic MR-derived tissue models containing optical voids

The occurrence of optical voids can introduce model inconsistencies into diffusionbased imaging methods. For this report, we have investigated the ability to measure various features of dynamic behavior from a time-varying image series, using tissue-like models containing an optical void. Results show that whereas such structures can significantly influence image results from time-averaged measurements, measures of dynamic features are much less influenced.
A Laboratory Investigation on the Rheological Properties of Asphalt Binder Containing Rediset

Rediset is a chemical warm mix asphalt additive that can reduce the viscosity of asphalt binder at a given temperature, hence reducing the mixing and compaction temperatures of asphalt mixes. This paper evaluates the viscosity, rutting and fatigue parameters of conventional asphalt binder blended with 0%, 1%, 2%, 3%, and 4% Rediset using the Rotational Viscometer and the Dynamic Shear Rheometer. In addition, aging factors were calculated to evaluate binder properties under unaged and short-term aged conditions. Statistical analyses of the data showed that using Rediset to decrease the viscosity of the asphalt binder at high temperatures does not adversely effect the fatigue and rutting behavior of the asphalt binder subjected to different aging conditions.
Rapid adaptation of n-gram language models using inter-word correlation for speech recognition

In this paper, we study the fast adaptation problem of n-gram language model under the MAP estimation framework. We have proposed a heuristic method to explore inter-word correlation to accelerate MAP adaptation of n-gram model. According to their corre-lations, the occurrence of one word can be used to predict all other words in adaptation text. In this way, a large n-gram model can be efﬁciently adapted with a small amount of adaptation data. The proposed fast adaptation approach is evaluated in a Japanese newspaper corpus. We have observed a signiﬁcant perplexity reduction even when we have only several hundred adaptation sentences.
Locating sensors in the forest: A case study in GreenOrbs

As a large scale real sensor network system, GreenOrbs reveals that locating sensor nodes in the forest still faces great challenges because of volatile and fluctuating environmental factors. In this paper, we present a novel localization scheme, EARL, which provides accurate reference nodes and good ranging quality. We exam the range quality along routing paths by taking complex environmental factors into account, such as forest density, temperature and humidity. To improve localization accuracy, we use power scanning technique to judge the accuracy reference nodes and further calibrate the bad nodes through reverse-localization. To overcome the error propagation, we assign different weights to the range measurement according to the ranging quality. We implemented our localization scheme in GreenOrbs testbed, and evaluate through extensive experiments. The results demonstrate that EARL outperforms the current localization approaches with better accuracy. The localization accuracy achieved by our method is around 20% higher than best existing methods.
A framework for acquisition and application of software architecture evolution knowledge: 14

Software systems continuously evolve as a consequence of frequent changes in their functional requirements and the environment surrounding them. Architecture-centric software evolution (ACSE) enables changes in software structure and behaviour while abstracting the complex implementation-specific details. However, due to recurring evolution there is a need for solutions that enable a systematic reuse of frequent changes in software architectures. In recent years, architecture change patterns and evolution styles proved successful in promoting reuse expertise to tackle architecture evolution. However, there do not exist any solutions that enable a continuous acquisition and application of architecture evolution knowledge to systematically address frequent changes in software architectures. In this paper, we propose a framework PatEvol that aims to unify the concepts of i) software repository mining and ii) software evolution to enable acquisition and application of architecture evolution knowledge. In the proposed PatEvol framework, we present knowledge acquisition (architecture evolution mining) to enable post-mortem analysis of evolution histories to empirically discover evolution-centric knowledge. Furthermore, we support reuse of discovered knowledge to enable knowledge application (architecture evolution execution) that enables evolution-off-the-shelf in software architectures. Tool support facilitates the knowledge acquisition and knowledge application processes in the PatEvol framework.
Using Enterprise Architecture Models for System Quality Analysis

Enterprise architecture is a model-based approach to business-oriented IT management. To promote good IT decision making, an enterprise architecture framework needs to explicate what kind of analyses it supports. Since creating enterprise architecture models is expensive and without intrinsic value, it is desirable to only create enterprise architecture models based on metamodels that support well-defined analyses. This paper presents the content and extension of a metamodel which supports creating models containing the information necessary to conduct system quality analyses, specifically with respect to availability, accuracy, confidentiality and integrity. The metamodel is an extension and formalization of the metamodel underlying the ArchiMate modelling language for enterprise architecture. The use of the extended metamodel is demonstrated in a case study where the availability, accuracy, confidentiality and integrity of the two service oriented architecture (SOA) platforms Sun JCaps and PrOSeRO were evaluated.
Experimental investigation of a dual-band handset MIMO antenna using a spatial fading emulator

There have been a significant number of investigations into handset MIMO antennas applicable for cellular mobile radios [1], [2]. Some measurement apparatuses have been proposed for evaluating MIMOs or diversity arrays for a handset terminal [3], [4]. A spatial fading emulator consists of a number of transmitting antennas in order to reproduce a multipath fading channel in the spatial domain [4]. However, there has been little study of the effectiveness of the emulator in an actual cellular environment. This paper presents the experimental investigation of a dual-band handset MIMO antenna using a spatial fading emulator in a street microcell environment to compare with experimental data of a radio propagation test. Four handset arrays, which included two monopole antennas with dual-band operation, were used for the test, thus permitting the evaluation of 2-by-2 MIMO characteristics. The propagation test was conducted in a central downtown area of Aalborg city in Denmark. Comparison between the measured results obtained by the emulator and the propagation confirmed the effectiveness of the emulator.
Effi cacy of a prophylactic adjuvanted bivalent L 1 virus-like-particle vaccine against infection with human papillomavirus types 16 and 18 in young women : an interim analysis of a phase III double-blind , randomised controlled trial

Jorma Paavonen, David Jenkins, F Xavier Bosch, Paulo Naud, Jorge Salmerón, Cosette M Wheeler, Song-Nan Chow, Dan L Apter, Henry C Kitchener, Xavier Castellsague, Newton S de Carvalho, S Rachel Skinner, Diane M Harper, James A Hedrick, Unnop Jaisamrarn, Genara A M Limson, Marc Dionne, Wim Quint, Bart Spiessens, Pascal Peeters, Frank Struyf, Susan L Wieting, Matti O Lehtinen, Gary Dubin, for the HPV PATRICIA study group*
Joint source-channel coding for Multiple-Access Wiretap Channels

In this paper, we consider lossy source transmission over a Multiple Access WireTap Channel (MAC-WT). In this model, there are two correlated sources, each of them is available at the corresponding encoder. The receiver tries to reconstruct both sources with desired distortions. The sources should be kept secret from an eavesdropper. We propose a joint source-channel scheme for the MAC-WT. In this scheme, each source sequence is mapped to common and private codewords. The common codeword can be decoded by the eavesdropper. The private codeword needs to be kept secret from the eavesdropper by using Wyner's wiretap coding. We also discuss some special cases of the proposed scheme.
Optimization of Core Point Detection in Fingerprints

This paper compares and documents the work of an optimized fingerprint core point determination algorithm. This work focuses to present an efficient and precise way for the extraction of core point. Core Point is detected using least mean square algorithm. Orientation is figured out via a novel efficient technique. This technique is better in terms of time and accuracy as compared to other two techniques mentioned in this paper. Poin'care index is then used to find out the location of core point. Found point may be slightly in error so further refinement is performed. For further tuning, a small window of specific size (w x w) is cropped around that point. This area is now tuned via PC after making some enhancements to it. The results obtained are very good and are produced efficiently. Proposed algorithm provides the hybrid platform where refinement can be done via any technique.
An Instrumenting Compiler for Enforcing Confidentiality in Low-Level Code

We present an instrumenting compiler for enforcing data confidentiality in low-level applications (e.g. those written in C) in the presence of an active adversary. In our approach, the programmer marks secret data by writing lightweight annotations on top-level definitions in the source code. The compiler then uses a static flow analysis coupled with efficient runtime instrumentation, a custom memory layout, and custom control-flow integrity checks to prevent data leaks even in the presence of low-level attacks. We have implemented our scheme as part of the LLVM compiler. We evaluate it on the SPEC micro-benchmarks for performance, and on larger, real-world applications (including OpenLDAP, which is around 300KLoC) for programmer overhead required to restructure the application when protecting the sensitive data such as passwords. We find that performance overheads introduced by our instrumentation are moderate (average 12% on SPEC), and the programmer effort to port OpenLDAP is only about 160 LoC.
Gas-free single-port transumbilical laparoscopic cholecystolithotomy: preliminary report on eight cases.

BACKGROUND To explore the feasibility and safety of gas-free single-port transumbilical laparoscopic cholecystolithotomy. METHODS An incision of 1.5-2.0 cm was made through all layers of the umbilicus, and a specially designed silicone plug with three 5-mm ports was inserted. The surgical space was created by lifting the right abdominal wall with an abdominal suspension set. A laparoscope, S-type dissector, grasper,electric needle, and needle-holder were used to perform a cholecystolithotomy. The procedure was performed in 8 patients with gall stones. RESULTS All stones were successfully removed. No postoperative complications, such as bleeding or bile leakage, occurred. The operative time was 45-120 minutes (mean 77.5 ± 24). The mean length of hospital stay was 2 days, and no postoperartive analgesics were used. There were no visible scars on the abdominal wall. CONCLUSIONS The gas-free single-port transumbilical laparoscopic approach was safe and feasible for cholecystolithotomy. This approach expands the applications of laparoendoscopic single-site surgery and avoids the use of highly concentrated CO(2) in the body and its potential side effects.
Applications: Generalized Additive Modelling of Mixed Distribution Markov Models with Application to Melbourne's Rainfall

The paper considers the modelling of time series using a generalized additive model with first‐order Markov structure and mixed transition density having a discrete component at zero and a continuous component with positive sample space. Such models have application, for example, in modelling daily occurrence and intensity of rainfall, and in modelling numbers and sizes of insurance claims. The paper shows how these methods extend the usual sinusoidal seasonal assumption in standard chain‐dependent models by assuming a general smooth pattern of occurrence and intensity over time. These models can be fitted using standard statistical software. The methods of Grunwald & Jones (2000) can be used to combine these separate occurrence and intensity models into a single model for amount. The models are used to investigate the relationship between the Southern Oscillation Index and Melbourne's rainfall, illustrated with 36 years of rainfall data from Melbourne, Australia.