Miracle-dz/UniFAR-FTUs huggingface dataset:
Notes On Shortest Path Representation ( Technical Report )

In order to implement Traffic Engineering (TE) by a legacy shortest path routing protocol, such as the Open Shortest Path First (OSPF, [1]) protocol, one has to employ a path set can be turned into a set of shortest paths over properly chosen positive link weights. Such path sets are referred to as shortest path representable (SPR) paths and it has been pointed our previously that not every path set immediately satisfies this property. Our main objective in this paper is to distill and unify the theory of shortest path representability under the umbrella of a novel flow-theoretic framework that is concise enough to be useful both theoretically and practically. In the first part of the paper, we introduce our framework and state a descriptive necessary and sufficient condition to characterize shortest path representable paths. This allows us to reformulate a number of previous findings in the field of OSPF TE and also to deduce a number of new ones. Since a shortest path representation usually contains a huge number of superfluous paths leading to unintended interference in an OSPF TE deployment, the second part of the paper is devoted to the problem of reducing the number of paths in a representation to the bare minimum. To the best of our knowledge, this is the first time that an algorithm is proposed, which is not only able to find a minimal representation in polynomial time but also assures link weight integrality. Moreover, we give a necessary and sufficient condition to the existence of a one-to-one mapping between a path set and its shortest path representation. Finally, we present some simulation studies conducted on random networks to show that the shortest path forwarding paradigm is much more flexible than one would have expected it previously.
International Conference on Parallel Processing UNIFIED STATIC SCHEDULING ON VARIOUS MODELS t

Given a behavioral description of an algorithm represented by a data-flow graph, we show how to obtain a roleoptimal static schedule with the minimum unfolding lactor under two timing models, integral grid model andjractional grid model, and two design styles for each model, pipelined design and non-piplined design. We present a ~lmph2 and unified approach to deal with the four possible combinations. A unified polylomial-time schedtlling algorithm i s presented, which works on the original data-flour graph3 without really unfoldang. The values of the minimum mteoptimnl tinfolding factors for all the four combmotions are also derived.
Studies in topical application of niosomally entrapped Nimesulide.

PURPOSE A niosome based transdermal drug delivery system of Nimesulide (NIM) was developed and extensively characterized and evaluated for in-vitro performance followed by in-vivo evaluation in rats by carrageenan induced rat paw edema method. METHOD Niosomes were prepared by lipid film hydration technique using tweens and spans. Preparation of niosomes was optimized for highest percent drug entrapment (PDE). The prepared niosomes were incorporated into 1 percent carbopol gel base and the system was evaluated for drug diffusion across human cadaver skin (HCS) using modified validated diffusion cell. The drug retention studies in niosomes were performed at refrigerated temperature (2 degrees C - 8 degrees C) and at room temperature (25 degrees C+/-2 degrees C) for the period of 2 months. In-vivo performance of plain drug gel, niosomally-entrapped drug in carbopol gel base and marketed formulation were evaluated using acute rat paw edema method. RESULTS Highest mean percentage edema inhibition (PEI) was observed for niosomal nimesulide gel after 24 hours i.e. 66.68 percent +/- 5.19 percent compared to plain drug gel i.e. 12.57 percent +/- 1.78 percent and marketed NIM formulation i.e. 20.49 percent +/- 0.91 percent. CONCLUSION Findings of this investigation conclusively demonstrate prolongation of drug release and increase in amount of drug retention into the skin and permeation across the skin after niosomal encapsulation of NIM. Developed nimesulide niosomal gel formulation has also demonstrated enhanced anti-inflammatory activity compared to plain drug gel and marketed formulation.
Blind Harmonic Adaptive Decomposition applied to supervised source separation

In this paper, a new supervised source separation system is introduced. The Constant-Q Transform (CQT) of an audio signal is first analyzed through an algorithm called Blind Harmonic Adaptive Decomposition (BHAD). This algorithm provides an estimation of the polyphonic pitch content of the input signal, from which the user can select the notes to be extracted. The system then automatically separates the corresponding source from the audio mixture, by means of time-frequency masking of the CQT. The system has been evaluated both in a task of multipitch estimation in order to measure the quality of the decomposition, and in a task of user-guided melody extraction to assess the quality of the separation. The very promising results obtained highlight the reliability of the proposed model.
Towards SE and EE in 5G with NOMA and Massive MIMO Technologies

Non-Orthogonal Multiple Access (NOMA) has been proposed to enhance the Spectrum Efficiency (SE) and cell-edge capacity. This paper considers the massive Multi-Input Multi-Output (MIMO) with Non-Orthogonal Multiple Access (NOMA) encoding. The close-form expression of capacity of the massive MIMO with NOMA is given here. Apart from the previous Successive Interference Cancellation (SIC) method, the Power Hard Limiter (PHD) is introduced here for better reality implement.
Delays in dwarf novae II: VW Hyi, the tidal instability and enhanced mass transfer models

We discuss the multi-wavelength predictions of the two models proposed for SU UMa stars, i.e. the enhanced mass transfer (EMT) and the tidal thermal instability (TTI) models. We focus on the systematic differences of the suggested scenarios before discussing the model predictions together with the observations of the best-studied SU UMa system, VW Hyi. We find that assuming the standard form of the viscosity parameter α, both models predict only outbursts being triggered at the inner edge of the accretion disc. In the TTI model the superoutbursts are triggered when the outer radius of the disc reaches a certain value, i.e. the 3:1 resonance radius. In contrast, the EMT scenario predicts superoutbursts when the disc mass exceeds a critical value. This causes the EMT model to be much more sensitive to mass transfer variations than the TTI model. In both models we find the predicted UV and EUV delays in agreement with the observations of VW Hyi for αh/αc < 4. In addition both models can generate precursor outbursts which are more pronounced at short wavelengths, in agreement with observations. Variations found in the observed light curve of single systems (e.g. VW Hyi) as well as the difference between ordinary SU UMa stars and ER UMa systems are a natural outcome of the EMT model while the TTI model fails to explain them.
An optimal algorithm for bandit convex optimization

We consider the problem of online convex optimization against an arbitrary adversary with bandit feedback, known as bandit convex optimization. We give the first $\tilde{O}(\sqrt{T})$-regret algorithm for this setting based on a novel application of the ellipsoid method to online learning. This bound is known to be tight up to logarithmic factors. Our analysis introduces new tools in discrete convex geometry.
Impact of Urban Sprawl on Public Health: An Analysis of Lahore - Pakistan

3 Abstract: Through the history, the human population has lived a rural lifestyle. Urbanization is now a rising trend seen all over the world, especially in an alarming rate in developing countries. This makes cities grow both in number and in physical size. The subject of urbanization and urban sprawl has drawn attention from ecologists, urban planners, civil engineers, sociologists, administrators, policy makers and finally to common urban or rural resident. Urban sprawl is to be the fastest growing threat to their local environment and quality of life. This paper aims to analyze the problems of urban sprawl that is facing by the residents and the health impacts of urban sprawl. The researcher tries to describe the relationship between urban sprawl and public health. The present study is conducted in Ravi Town Lahore. The target population of the study was consisted of those who were residents of this locality both male and female are included in the study. The sample was 120 respondents those selected through convenient sampling technique i-e non-probability sampling, due to unavailability of sampling frame. A survey Method is used as a technique of data collection, semi-structured interview schedule was developed to collect the data because most of the respondents were illiterate. The findings of the present study described, majority of the respondents reported that motor vehicle leads to air pollution and health facilities were not properly available in that locality that was far from the locality, so that is why people have less access to the health facilities. It was observed that most of the respondents reported physical health problems like diarrhea, malaria and the main problem was obesity/overweight. The study suggests policy measures and guideline to the health of the people who live in sprawling areas of Lahore.
A Comparative Study of Histogram Equalization (HEQ) for Robust Speech Recognition

The performance of current automatic speech recognition (ASR) systems often deteriorates radically when the input speech is corrupted by various kinds of noise sources. Quite a few techniques have been proposed to improve ASR robustness over the past several years. Histogram equalization (HEQ) is one of the most efficient techniques that have been used to reduce the mismatch between training and test acoustic conditions. This paper presents a comparative study of various HEQ approaches for robust ASR. Two representative HEQ approaches, namely, the table-based histogram equalization (THEQ) and the quantile-based histogram equalization (QHEQ), were first investigated. Then, a polynomial-fit histogram equalization (PHEQ) approach, exploring the use of the data fitting scheme to efficiently approximate the inverse of the cumulative density function of training speech for HEQ, was proposed. Moreover, the temporal average (TA) operation was also performed on the feature vector components to alleviate the influence of sharp peaks and valleys caused by non-stationary noises. All the experiments were carried out on the Aurora 2 database and task. Very encouraging results were initially demonstrated. The best recognition performance was achieved by combing PHEQ with TA. Relative word error rate reductions of 68% and 40% over the MFCC-based baseline system, respectively, for clean- and multi- condition training, were obtained.
Correct modelling of geometry and materials properties in the thermo-mechanical finite-elements-simulation of chip scale packages

The first part of the work reported here is dedicated to the 3D finite-elements modelling of CSP. It will take into account both thermal-mechanical characteristics of the assembly materials and geometric factors. Here an approach of modular and parametric modelling with standardized modules linked via contact elements is proposed. Also the aspects of CAD systems for parameterized modelling are treated. The modular concept of modelling also will allow for efficient calculations with a variable number of bumps. The second part of the paper is dedicated to the materials descriptions, which is necessary for the simulation of CSP assemblies. Measured materials data as well as suitable models for numerical representations are discussed. The relevant thermo-mechanical properties of package and assembly materials are presented. Besides actual solder alloys also polymers like moulding compounds are treated. In order to calibrate and check the simulation results, an ESPI sensor was used for measuring the thermal deformations of specimens under thermal loads in comparison to finite elements simulations. FE-models validated by experimental results present the deformations and stress state of the package under thermal cycling.
Beamforming networks using spatial covariance features for far-field speech recognition

Recently, a deep beamforming (BF) network was proposed to predict BF weights from phase-carrying features, such as generalized cross correlation (GCC). The BF network is trained jointly with the acoustic model to minimize automatic speech recognition (ASR) cost function. In this paper, we propose to replace GCC with features derived from input signals' spatial covariance matrices (SCM), which contain the phase information of individual frequency bands. Experimental results on the AMI meeting transcription task shows that the BF network using SCM features significantly reduces the word error rate to 44.1% from 47.9% obtained with the conventional ASR pipeline using delay-and-sum BF. Also compared with GCC features, we have observed small but steady gain by 0.6% absolutely. The use of SCM features also facilitate the implementation of more advanced BF methods within a deep learning framework, such as minimum variance distortionless response BF that requires the speech and noise SCM.
Parameter independent vector control of brushless Doubly-fed reluctance generators

The paper is concerned with voltage vector oriented control of a brushless doubly-fed reluctance generator (BDFRG) having grid-connected wind turbines as one of the main target applications. By using a fractional inverter, this promising generator technology could offer competitive performance and similar cost savings to its commercially popular slip-ring cousin, the doubly-fed induction generator (DFIG), but with the additional bonuses of maintenance-free operation and high reliability of brushless structure. The presented simulation and laboratory test results for an entirely machine parameter independent speed and reactive power control algorithm under various loading conditions of the BDFRG prototype, including those typically encountered in wind energy conversion systems, have been shown to be in good agreement clearly demonstrating the controller effectiveness and accuracy of the simulation model.
A design system for RFIC: challenges and solutions

The expansion of the market for portable wireless communication devices has given a tremendous push to the development of a new generation of low-power radio frequency integrated circuit (RFIC) products. In this fast-growing environment where time-to-market constraints force tight schedules, having a good design methodology, innovation computer-aided design (CAD) tools, and a well-integrated design system are key factors for success. In this paper, we describe a design system developed to provide the designer with everything necessary to accurately predict the behavior of RFIC devices, including layout and package parasitic effects. We show how important a well-defined and integrated system is to manufacturing a design that meets specifications at the minimum cost, in the minimum time. A close link between schematic, models, and layout is of paramount importance to ensure the accuracy need for low-power RF design. We give an overview of the advanced methods and tools currently available for simulation and noise analysis of RF devices. Finally, we show a design example that obtained first-silicon success.
COPULA AND TOMOGRAPHY

Abstract: An important problem in statistics is determining a joint pr obability distribution from its marginals. In 2D case, the marginal probability density functions f1(x) and f2(y) are related to their joint distributionf (x,y) via the horizontal and vertical line integrals. So, the prob lem of determiningf (x,y) from f1(x) and f2(y) is an ill-posed inverse problem. In statistics the notion of c pulais exactly introduced to obtain a solution to this problem. Interestingly, this is also a problem encountered in X ray tomography image reconstruction where f (x,y) is an image representing the distribution of the material de nsity and f1(x) and f2(y) are the horizontal and vertical line integrals. In this paper, we try to link the notion of copula to X ray Computed Tomography (CT) and to see if we can use the methods used in each domain to t he other one.
Analysis of Regime Switching Behaviour of Indian Stock Markets

I consider the problem of detecting and predicting regime switching behaviour in the context of Indian Stock Market data. First I discuss detection of volatility change points using the LRT and the Binary Segmentation procedure of Vostrikova (1981). The detected volatility changes are correlated with important national and international events during that time. Then I analyse regime switching behaviour using Hidden Markov Models. I use a Bayesian route and use the Sampling Importance Resampling methodology to obtain the approximate posterior distributions
Market anomalies, asset pricing models, and stock returns: evidence from the Indian stock market

Purpose – This paper aims to investigate whether the use of conditional and unconditional Fama and French (1993) three-factor and Carhart (1997) four-factor asset pricing models (APMs) captures the role of asset pricing anomalies in the context of emerging stock market like India. Design/methodology/approach – The first step time series regression approach has been used to drive the risk-adjusted returns of individual securities. For examining the predictability of firm characteristics or asset pricing anomalies on the risk-adjusted returns of individual securities, the panel data estimation technique has been used. Findings – Fama and French (1993) three-factor and Carhart (1997) four-factor model in their unconditional specifications capture the impact of book-to-market price and liquidity effects completely. When alternative APMs in their conditional specifications are tested, the importance of medium- and long-term momentum effects has been captured to a greater extent. The size, market leverage and s.
Automatic detection of oil spills in ENVISAT, Radarsat and ERS SAR images

We present a framework for automatic detection of oil spills in SAR images. Multi incident angle and multi polarization SAR data are ingested into the framework in order to optimize revisit times and thereby the temporal and spatial coverage. Dark spots in the images are primarily detected by adaptive thresholding. For each of them a number of features are computed in order to classify the slick as either an oil slick or a 'look-alike' (other oceanographic phenomena which resemble oil slicks). A classification scheme is utilized based on statistical modeling. A data set of about 100 images from each of the sensors ERS, Radarsat and ENVISAT is or will soon be available to train and test the algorithm. In this paper, only results from ERS and Radarsat are reported because the access of ENVISAT images has been delayed.
Capacity and error probability analysis for orthogonal space-time block codes over fading channels

The capacity and error probability of orthogonal space-time block codes (STBCs) are considered for pulse-amplitude modulation/phase shift keying/quadrature-amplitude modulation (PAM/PSK/QAM) in fading channels. The approach is based on an equivalent scalar additive white Gaussian noise channel with a channel gain proportional to the Frobenius norm of the matrix channel for the STBC. Using this effective channel, capacity and probability of error expressions are derived for PSK/PAM/QAM modulation with space-time block coding. Rayleigh-, Ricean-, and Nakagami-fading channels are considered. As an application, these results are extended to obtain the capacity and probability of error for a multiuser direct sequence code-division multiple-access system employing space-time block coding.
The Research of Data Storage and Retrieval Scheme for Wireless Sensor Networks

Recently, several data storage schemes have been developed to store massive sensor data in the wireless sensor networks (WSNs). A crucial task of WSNs is to disseminate useful information to users efficiently and handle the data storage architecture incorporating their extreme resource constraints. A Distributed Index based Multi-resolution Storage Architecture (DIMSA) for data storage and retrieval at multiple levels of detail in WSNs is proposed in this paper. The proposed scheme could automatically disseminate useful information to users in correspondence to the user defined level of detail to save energy. In the condition that some attributes are included in many events, the values for these attributes have to be replicated and stored at different places in the network for each individual event in traditional data-centric storage schemes. This will consume some extra energy. To address this problem, DIMSA deploys an attribute allocation scheme for finding a good distribution of attributes to the sensor networks. In addition, a distributed index scheme is also proposed to avoid query flooding and extra data transmission. Analysis and simulations are conducted to evaluate the performance of the proposed scheme. The results show that DIMSA outperforms the traditional data-centric storage scheme like GHT.
Enabling cross-organisation access to legacy healthcare information systems in ARTEMIS using the IHE RID profile

The localisation of and access to electronically available patient-centric information across the boundaries of healthcare organisations is mostly limited to the field of telemedicine applications today. However, considering the specialisation of medical organisations, the need for cost reduction e. g. by avoiding unnecessary examinations, and the mobility of the population especially at European level, cross-organisational access to medical information related to a particular patient would certainly be beneficial. The EC-funded project ARTEMIS is developing a semantic web based P2P interoperability infrastructure for healthcare information systems. The ARTEMIS P2P network provides a Patient Identification Protocol (PID Protocol) – a mechanism to locate patientrelated documents in conformance with access authorisation and privacy regulations. For the retrieval of such documents, ARTEMIS combines the PID protocol with the Retrieve Information for Display (RID) integration profile proposed by the Integrating the Healthcare Enterprise (IHE) initiative. This profile enables users to retrieve and display patient-related documents on systems other than the document keeping systems. In combination with the ARTEMIS infrastructure, RID enables users to access medical information across boundaries of medical organisations.
1 State of The Art for Volume Rendering Technical Report

The interpretation of 3D scalar fields is considerably difficult because of their intrinsic complexity. In the context of this thesis the term volume rendering refers to the visualization of static 3D scalar fields especially the 3D imaging in medicine. A variety of different approaches have been developed in the past decades for volume rendering. This chapter tries to assess different volume rendering algorithms and draw an overall picture of significant concepts and ideas. It first examines existing volume rendering algorithms and compares advantages and disadvantages of each. Through investigating the current literature and systems, we conclude the current active research topics for volume rendering. Then different approaches are proposed for laying down the problems still existed for volume data information exploration.