Miracle-dz/UniFAR-FTUs huggingface dataset:
Icsoc Phd Symposium 2008 Co-located with 6th International Conference on Service Ori- Ented Computing (icsoc) Programme Chairs Programme Committee External Reviewers

Web service composition requests are usually combined with end-to-end QoS requirements, which are specified in terms of non-functional properties (e.g. response time, throughput and price). The goal of QoSaware service composition is to select the best combination of services that meet these end-to-end requirements, while maximizing the value of a pre-defined utility function. This problem can be modeled as a multidimension multi-choice 0-1 knapsack problem, which is known as NPhard in the strong sense. Existing solutions that rely on general purpose solvers suffer from poor performance, which render them inappropriate for applications with dynamic and real-time requirements. Moreover, global optimization techniques assume a centralized system model, which contradicts with the distributed and loosely-coupled environment of web services. The aim of this thesis is to develop scalable QoS optimization solutions that fit better to the distributed environment of web services. The idea is to decompose global constraints into local constraints that have to be fulfilled by a set of distributed service brokers. A solution that combines global optimization and local selection techniques is proposed.
Predicting the Blur Visual Discomfort for Natural Scenes by the Loss of Positional Information

The perception of the blur due to accommodation failures, insufficient optical correction or imperfect image reproduction is a common source of visual discomfort, usually attributed to an anomalous and annoying distribution of the image spectrum in the spatial frequency domain. In the present paper, this discomfort is attributed to a loss of the localization accuracy of the observed patterns. It is assumed, as a starting perceptual principle, that the visual system is optimally adapted to pattern localization in a natural environment. Thus, since the best possible accuracy of the image patterns localization is indicated by the positional Fisher information, it is argued that the blur discomfort is highly correlated with a loss of this information. Following this concept, a receptive field functional model, tuned to common and stable features of natural scenes, is adopted to predict the visual discomfort. It is of a complex-valued operator, orientation-selective both in the space domain and in the spatial frequency domain. Starting from the case of Gaussian blur, the analysis is extended to a generic blur type by applying a positional Fisher information equivalence criterion. Out-of-focus blur and astigmatic blur are presented as significant examples. The validity of the proposed model is verified by comparing its predictions with subjective ratings of the quality loss of blurred natural images. The model fits linearly with the experiments reported in independent databases, based on different protocols and settings.
Design and analysis of a hybridized discontinuous Galerkin method for incompressible flows on meshes with quadrilateral cells

We present and analyse a hybridized discontinuous Galerkin method for incompressible flow problems using non-affine cells, proving that it preserves a key invariance property that il-ludes most methods, namely that any irrotational component of the prescribed force is exactly balanced by the pressure gradient and does not influence the velocity field. This invariance property can be preserved in the discrete problem if the incompressibility constraint is satisfied in a sufficiently strong sense. We derive sufficient conditions to guarantee discretely divergence-free functions are exactly divergence-free, and give examples of divergence-free finite elements on meshes containing triangular, quadrilateral, tetrahedral, or hexahedral cells generated by a (possibly non-affine) map from their respective reference cells. In the case of quadrilateral cells, we prove an optimal error estimate for the velocity field that does not depend on the pressure approximation. Our theoretical analysis is supported by numerical results.
A Text-to-Picture Synthesis System for Augmenting Communication

We present a novel Text-to-Picture system that synthesizes a picture from general, unrestricted natural language text. The process is analogous to Text-to-Speech synthesis, but with pictorial output that conveys the gist of the text. Our system integrates multiple AI components, including natural language processing, computer vision, computer graphics, and machine learning. We present an integration framework that combines these components by first identifying infonnative and 'picturable' text units, then searching for the most likely image parts conditioned on the text, and finally optimizing the picture layout conditioned on both the text and image parts. The effectiveness of our system is assessed in two user studies using children's books and news articles. Experiments show that the synthesized pictures convey as much infonnation about children's stories as the original artists' illustrations, and much more information about news articles than their original photos alone. These results suggest that Text-to-Picture synthesis has great potential in augmenting human-computer and human-human communication modalities, with applications in education and health care, among others.
On the Security of RFID Group Scanning Protocols

A RFID group scanning protocol enables a RFID reader to produce a proof of co-existence of multiple RFID tags. This type of protocol is also referred to as yoking-proof, grouping-proof and co-existence proof. In this letter, we show that all of the previous group scanning protocols are vulnerable to relay attack.
Public Procurement: Lessons from Kenya, Tanzania and Uganda

This paper presents a comparative analysis of the public procurement system in three East African countries: Kenya, Uganda and Tanzania. In response to both domestic and international pressures, these countries have recently undertaken important initiatives to make their public procurement systems more efficient and transparent in line with international procurement guidelines. The experience of the three countries with the reforms has been quite varied. While Tanzania has moved fast with the reforms and has already put in place a legislative framework for public procurement, Kenya and Uganda have yet to enact procurement legislation. In Kenya, a number of significant changes have already been effected through a ministerial gazette notice pending the coming into force of a Procurement Act. There is also an urgent need for strengthening institutions involved in public procurement, as these institutions tend to lack technical and human resource capabilities. Although the current East . Ce Document technique presente une analyse comparative des systemes nationaux de passation des marches publics dans trois pays d’Afrique de l’Est : le Kenya, l’Ouganda et la Tanzanie. Pour repondre aux pressions nationales et internationales, ces pays ont recemment pris l’initiative de rendre leurs systemes de marches publics plus efficaces et transparents, conformement aux principes directeurs internationaux relatifs a l’attribution des marches publics. Les reformes ont pris une tournure differente dans chacun de ces trois pays. Alors que la Tanzanie a bien avance et deja mis en place un cadre legislatif en la matiere, le Kenya et l’Ouganda se doivent encore de promulguer leur propre legislation. Au Kenya, un certain nombre de changements ont ete obtenus grâce a l’annonce des marches dans une gazette officielle, en attendant l’entree en vigueur d’une loi sur les marches publics. Il est egalement urgent de renforcer les institutions impliquees dans le systeme des marches publics .
Last Glacial Maximum East Asian Monsoon: Results of PMIP Simulations

Abstract During glacial periods, the East Asian monsoon is typically thought to have been stronger in boreal winters and weaker in boreal summers. It is unclear, however, whether this view is true at larger scales and to what extent the East Asian monsoon responds to glacial conditions as a whole. Using all experiments conducted as part of the Paleoclimate Modeling Intercomparison Project (PMIP), this paper examines East Asian monsoon climatology during the Last Glacial Maximum (LGM), around 21 000 calendar years ago. In contrast to conclusions drawn from sparse proxy data, the intensity of the East Asian winter (December–February) monsoon (EAWM) during the LGM, as measured by regionally averaged meridional wind speed at 850 hPa, was found to vary both in sign and magnitude, with reference to baseline climate, across the PMIP simulations. It strengthened in 10 out of the 21 models but weakened in the remaining 11 models, with an average weakening of 4% for the 21-model ensemble mean (15% for the ensemble .
Communities in the Mediterranean karst River the Cetina and its tributary the Ruda, Croatia.

Benthic invertebrate communities of the Cetina River and the upper reach of the Ruda River were sampled monthly at 11 sites from August 2004 to August 2005. The sampling sites were located along the longitudinal gradient of the Cetina and in the upper reach of the Cetina's largest tributary, the Ruda River. Throughout the study, a total of 310225 animals were collected in 366 samples. In the upper and middle reaches the most numerous taxa were Amphipoda and Gastropoda, while the most numerous taxon in the lower reaches was Gastropoda. The highest and the lowest population density of benthic invertebrates were recorded at the sites Preocki Most in June 2005 (22728 individuals/m2) and Radmanove Mlinice in November 2004 (90 individuals/m2), respecti vely. At sites Trilj I and Trilj II, the most numerous taxa were Oligochaeta and Chironomidae, indicators of watercourses with higher organic loads. The composition of benthic invertebrate communities at sites along the entire course of Cetina does not reflect the situation expected under natural conditions due to flow regulation and construction of hydroelectric power plants and reservoirs.
Psychometric Evaluation of the PSSUQ Using Data from Five Years of Usability Studies

Factor analysis of Post Study System Usability Questionnaire (PSSUQ) data from 5 years of usability studies (with a heavy emphasis on speech dictation systems) indicated a 3-factor structure consistent with that initially described 10 years ago: factors for System Usefulness, Information Quality, and Interface Quality. Estimated reliabilities (ranging from .83-.96) were also consistent with earlier estimates. Analyses of variance indicated that variables such as the study, developer, stage of development, type of product, and type of evaluation significantly affected PSSUQ scores. Other variables, such as gender and completeness of responses to the questionnaire, did not. Norms derived from this data correlated strongly with norms derived from the original PSSUQ data. The similarity of psychometric properties between the original and this PSSUQ data, despite the passage of time and differences in the types of systems studied, provide evidence of significant generalizability for the questionnaire, supporting its use by practitioners for measuring participant satisfaction with the usability of tested systems.
Heat flows through the ice lithosphere of Europa

Some of the geological features on the surface of Europa's ice shell suggest the existence of a brittle lithosphere that in some regions is no more than 2 km thick. The surface heat flow needed to put the brittle-ductile transition in ice at a depth of 2 km is at least ∼100 mW m−2, much higher than predicted by tidal heating models for a purely conductive ice shell. A possible explanation lies in the probable existence of a convective layer beneath the brittle lithosphere, which, owing to tidal dissipation in warm ice, could contribute to higher heat flows. If a convective subsurface layer and grain size dependent flow behavior of ice are admitted, the grain size at brittle-ductile transition depth cannot be >1 mm, which is consistent with the required value for the onset of convection in an ice shell thinner than 20 km.
A satellite perspective on cloud water to rain water conversion rates and relationships with environmental conditions

A two‐year satellite remote sensing data set from the NASA A‐Train is used to examine conversion rates of cloud water to rain water for warm maritime clouds with different ranges of mean cloud‐layer radar reflectivity and rain rate. Recent work has demonstrated the utility of a novel procedure that relies on the differing sensitivities of passive MODIS measurements and active CloudSat radar measurements to estimate warm cloud conversion rates and associated time scales. That work is extended here to examine regional differences in conversion rates, including sensitivity to environmental parameters such as atmospheric stability and the presence of different aerosol types defined based on values of aerosol optical depth, fine mode fraction, and Ångstrom Exponent. Among eight subregions examined, the tropical Pacific Ocean is characterized by the highest average conversion rate while subtropical stratocumulus cloud regions (far northeastern Pacific Ocean, far southeastern Pacific Ocean, Western Africa coastal region) exhibit the lowest rates. Conversion rates are generally higher at reduced values of lower tropospheric static stability (LTSS). When examining data in two selected ranges for LTSS, higher conversion rates are coincident with higher LWP and factors covarying or rooted in the presence of aerosol types exhibiting lower aerosol index values.
FORECASTING THE MONTHLY INCIDENCE RATE OF PNEUMONIA IN MAE HONG SON PROVINCE, THAILAND

The objective of this study was to investigate the epidemic patterns of communityacquired pneumonia (CAP) incidence by month, district and age group for Mae Hong Son, the north- western border province of Thailand. The results may subsequently be applied to geographical epidemiologic research for the spatial-temporal mapping of diseases. This will facilitate data linkage to population demographic statistics as they become available. This study was a cross-sectional hospital-based survey of all cases of the disease, provided by the Provincial Health Offi ce in Mae Hong Son province. The sample comprised all such data collected from 1999 to 2005. The model used was the linear regression time series to forecast the districts and age groups where epidemics are likely to occur in the near future, in order to aid in disease prevention. The model contains additive effects associated with the season of the year, district, age group, and the pneumonia incidence rates in previous months, and it can be used to provide useful short-term forecasts. Having a model that provides such forecasts of disease outbreaks, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention. We found that the largest residual obtained for Mae Hong Son was 2.00 – corresponding to 5 cases reported among the 5- to 14-year-old age group – in Pang Ma Pha district in April, 1999 (an incidence rate of 2.76 per 1,000). The pneumonia transmission rate in Mae Hong Son province during the study period was relatively low from January to June of each year. Chiang Mai Medical Journal 2009;48(3):85-94.
Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery

The invention of the Variational Autoencoder enables the application of Neural Networks to a wide range of tasks in unsupervised learning, including the field of Acoustic Unit Discovery (AUD). The recently proposed Hidden Markov Model Variational Autoencoder (HMMVAE) allows a joint training of a neural network based feature extractor and a structured prior for the latent space given by a Hidden Markov Model. It has been shown that the HMMVAE significantly outperforms pure GMM-HMM based systems on the AUD task. However, the HMMVAE cannot autonomously infer the number of acoustic units and thus relies on the GMM-HMM system for initialization. This paper introduces the Bayesian Hidden Markov Model Variational Autoencoder (BHMMVAE) which solves these issues by embedding the HMMVAE in a Bayesian framework with a Dirichlet Process Prior for the distribution of the acoustic units, and diagonal or full-covariance Gaussians as emission distributions. Experiments on TIMIT and Xitsonga show that the BHMMVAE is able to autonomously infer a reasonable number of acoustic units, can be initialized without supervision by a GMM-HMM system, achieves computationally efficient stochastic variational inference by using natural gradient descent, and, additionally, improves the AUD performance over the HMMVAE.
First artificially induced modulation of PMSE using the EISCAT Heating Facility

A coordinated experiment involving ionospheric heating and VHF observations of polar mesosphere summer echoes (PMSE) has recently been conducted at the EISCAT facility near Tromsø, Norway. We have demonstrated for the first time that ionospheric heating can influence VHF radar returns associated with PMSE. Artificially elevating the electron temperatures within the PMSE layer has been shown to reduce the echo power. Based on this and other results from the experiment, it is suggested that the observed reduction in PMSE power is related to an enhancement of the electron diffusivity through the heating.
The Many Meanings of Open Source

Many software development methodologies are called "open source. " However simply stating that a project is open source doesn't precisely describe the approach used to support the project. A multidisciplinary viewpoint can help determine those characteristics that are common to open source projects and those that vary among projects. These characteristics form the basis for a taxonomy of open source projects that's useful for analyzing and setting up projects. They also provide a starting point for understanding what "open source" means.
Privacy-preserving Publication and Sharing of COVID-19 Pandemic Data

A huge amount of data of various types are collected during the COVID-19 pandemic, the analysis and interpretation of which has been indispensable for curbing the spread of the coronavirus. As the pandemic slows down, the collected data during the pandemic will continue to be rich sources for further studying the pandemic and understanding its impacts on public health, economics, and societies. On the other hand, naïve release and sharing of the information can be associated with serious privacy concerns. In this paper, aiming at shedding light on privacy-preserving sharing of pandemic data and thus promoting and encouraging more data sharing for research and public use, we examine three common data types -- case surveillance, patient location histories and hot spot maps, and contact tracing networks -- collected during the pandemic and develop and apply privacy-preserving approaches for publishing or sharing each data type. We illustrate the applications and examine the utility of released privacy-preserving data in examples and experiments at various levels of privacy guarantees.
TuneUp: A Training Strategy for Improving Generalization of Graph Neural Networks

Despite many advances in Graph Neural Networks (GNNs), their training strategies simply focus on minimizing a loss over nodes in a graph. However, such simplistic training strategies may be sub-optimal as they neglect that certain nodes are much harder to make accurate predictions on than others. Here we present TUNEUP, a curriculum learning strategy for better training GNNs. Crucially, TUNEUP trains a GNN in two stages. The first stage aims to produce a strong base GNN. Such base GNNs tend to perform well on head nodes (nodes with large degrees) but less so on tail nodes (nodes with small degrees). So, the second stage of TUNEUP specifically focuses on improving prediction on tail nodes. Concretely, TUNEUP synthesizes many additional supervised tail node data by dropping edges from head nodes and reusing the supervision on the original head nodes. TUNEUP then minimizes the loss over the synthetic tail nodes to finetune the base GNN. TUNEUP is a general training strategy that can be used with any GNN architecture and any loss, making TUNEUP applicable to a wide range of prediction tasks. Extensive evaluation of TUNEUP on two GNN architectures, three types of prediction tasks, and both inductive and transductive settings shows that TUNEUP significantly improves the performance of the base GNN on tail nodes, while often even improving the performance on head nodes, which together leads up to 58.5% relative improvement in GNN predictive performance. Moreover, TUNEUP significantly outperforms its variants without the two-stage curriculum learning, existing graph data augmentation techniques, as well as other specialized methods for tail nodes.
Distributed Secure Systems: Then and Now

The early 1980s saw the development of some rather sophisticated distributed systems. These were not merely networked file systems: rather, using remote procedure calls, hierarchical naming, and what would now be called middleware, they allowed a collection of systems to operate as a coherent whole. One such system in particular was developed at Newcastle that allowed pre-existing applications and (Unix) systems to be used, completely unchanged, as components of an apparently standard large (multiprocessor) Unix system. The distributed secure system (DSS) described in our 1983 paper proposed a new way to construct secure systems by exploiting the design freedom created by this form of distributed computing. The DSS separated the security concerns of policy enforcement from those due to resource sharing and used a variety of mechanisms (dedicated components, cryptography, periods processing, separation kernels) to manage resource sharing in ways that were simpler than before. In this retrospective, we provide the full original text of our DSS paper, prefaced by an introductory discussion of the DSS in the context of its time, and followed by an account of the subsequent implementation and deployment of an industrial prototype of DSS, and a description of its modern interpretation in the form of the MILS architecture. We conclude by outlining current opportunities and challenges presented by this approach to security.
Robust affine feature matching via quadratic assignment on Grassmannians

GraNNI (Grassmannians for Nearest Neighbours Identiﬁcation) a new algo-rithm to solve the problem of aﬃne registration is proposed. The algorithm is based on the Grassmannian of k –dimensional planes in R n and minimizing the Frobenius norm between the two elements of the Grassmannian. The Quadratic Assignment Problem (QAP) is used to ﬁnd the matching. The results of the experiments show that the algorithm is more robust to noise and point discrepancy in point clouds than previous approaches