Miracle-dz/UniFAR-FTUs huggingface dataset:
DynaQoS: Model-free self-tuning fuzzy control of virtualized resources for QoS provisioning

Cloud elasticity allows dynamic resource provisioning in concert with actual application demands. Feedback control approaches have been applied with success to resource allocation in physical servers. However, cloud dynamics make the design of an accurate and stable resource controller more challenging, especially when response time is considered as the measured output. Response time is highly dependent on the characteristics of workload and sensitive to cloud dynamics. To address the challenges, we extend a self-tuning fuzzy control (STFC) approach, originally developed for response time assurance in web servers to resource allocation in virtualized environments. We introduce mechanisms for adaptive output amplification and flexible rule selection in the STFC approach for better adaptability and stability. Based on the STFC, we further design a two-layer QoS provisioning framework, DynaQoS, that supports adaptive multi-objective resource allocation and service differentiation. We implement a prototype of DynaQoS on a Xen-based cloud testbed. Experimental results on an E-Commerce benchmark show that STFC outperforms popular controllers such as Kalman filter, ARMA and adaptive PI by at least 16% and 37% under both static and dynamic workloads, respectively. Further results with multiple control objectives and service classes demonstrate the effectiveness of DynaQoS in performance-power control and service differentiation.
Applying transductive learning for automatic term extraction: The case of the ecology domain

Terms are the basis for general text mining and natural language processing applications. However, the manual term extraction is unfeasible due to the huge number of words presented in a domain corpus and also the human effort required to do the extraction. For the term extraction task, machine learning techniques have been used to perform automatic term extraction (ATE). Inductive learning is commonly used, but it requires a large number of words labeled as terms and non-terms to build a classification model and classify unseen words. A better solution is the use of transductive learning, since it requires a small number of labeled examples to classify words as terms and non-terms. In this paper, we propose the use of transductive learning to ATE. The obtained results demonstrate that the application of transductive learning to ATE produces better results than the results obtained by inductive learning.
The Bonus-crediting Mechanism of Danish Life Insurance Companies An Empirical Analysis

This paper develops and estimates a model for the bonus-crediting mechanism of Danish life insurance and pension companies. The market for pension and life insurance savings contracts is generally highly opaque, but our proposed model is able to explain a significant part of the variation in actual bonus distribution by Danish market participants. The main determinant of bonus policy a is measure of the degree of solvency which we construct from a unique data set that contains information compiled from several public as well as non-public sources. The data set spans the 10-year period from 1991 to 2000 and the model is estimated by way of (non-linear) least squares as well as maximum likelihood.
3G communication encryption algorithm based on ECC-ElGamal

The public key algorithm dedicated to the session key management is not specified in 3G communications. This paper has combined the elliptic curve algebra system with ElGamal encryption algorithm, proposed ECC-ElGamal encryption algorithm and given the feasibility and safety analysis. Applying it into the algorithm of F8 and F9 in 3G communications can better fill the security shortcomings.
Statistical analysis of packet delay in ad-hoc networks of mobile robots

We perform analysis of packet end-to-end delay in order to explain the processes taking place in the network. We build statistical models to describe the packets end-to-end delay distribution. Our experiments show that packet delay in an ad-hoc network of mobile robots depends on the number of hops traveled by the packet. We intend to use this dependency when implementing a modification of the learning model of ant routing algorithms addressed to improve their performance in such demanding environments.
Deformable Motion: Squeezing into Cluttered Environments

We present an interactive method that allows animated characters to navigate through cluttered environments. Our characters are equipped with a variety of motion skills to clear obstacles, narrow passages, and highly constrained environment features. Our control method incorporates a behavior model into well‐known, standard path planning algorithms. Our behavior model, called deformable motion, consists of a graph of motion capture fragments. The key idea of our approach is to add flexibility on motion fragments such that we can situate them into a cluttered environment via constraint‐based formulation. We demonstrate our deformable motion for realtime interactive navigation and global path planning in highly constrained virtual environments.
Method of determining cosmological parameter ranges with samples of candles with an intrinsic distribution

In this paper, the effect of the intrinsic distribution of cosmological candles is investigated. We find that in the case of a narrow distribution the deviation of the observed modulus of sources from the expected central value can be estimated within a ceratin range. We thus introduce lower and upper limits of chi(2), chi(2)(min) and chi(2)(max) to estimate cosmological parameters by applying the conventional minimizing chi(2) method. We apply this method to a gamma-ray burst (GRB) sample as well as to a combined sample including this GRB sample and an SN Ia sample. Our analysis shows that: a) in the case of assuming an intrinsic distribution of candles of the GRB sample, the effect of the distribution is obvious and should not be neglected; b) taking into account this effect would lead to a poorer constraint of the cosmological parameter ranges. The analysis suggests that in the attempt of constraining the cosmological model with current GRB samples, the results tend to be worse than was previously anticipated if the mentioned intrinsic distribution does exist.
Architecture-Independent Modeling of Intra-Node Data Movement

A primary concern of future high performance systems is the way data movement is managed; the sheer scale of data to be processed directly affects the achievable performance these systems can attain. However, the increasingly complex but inherently symbiotic relationships between upcoming scientific applications and high-performance architectures necessitate increasingly informative and flexible tools to ensure performance goals are met.In this work we develop a memory-hierarchy model that quantifies a given application's cache behavior. What makes this work unique is that we instrument code at compile time, gather architecture-independent data at run time using a generic memory-hierarchy model, and delay selecting a particular cache hierarchy (levels, sizes, and associativities) to a post-processing step, where cache performance can be derived rapidly without having to re-run a slow cache simulator. We show that this approach is capable of predicting cache misses to within 13% of what is predicted by a traditional, high-fidelity, but slow cache simulator.
Do Local Social Hierarchies Matter for Mental Health? A Study of Neighborhood Social Status and Depressive Symptoms in Older Adults.

OBJECTIVES Despite a well-established association between relative social position and health, stratification at smaller levels of social organization has received scant attention. Neighborhood is a localized context that has increasing relevance for adults as they age, thus one's relative position within this type of mesolevel group may have an effect on mental health, independent of absolute level of social and economic resources. We examine the relationship between an older adult's relative rank within their neighborhoods on two criteria and depressive symptoms. METHOD Using data from the Chicago Health and Aging Project, neighborhood relative social position was ascertained for two social domains: income and social reputation (number of neighbors one knows well enough to visit). Using multilevel models, we estimated the effect of relative position within the neighborhood on depressive symptoms, net of absolute level for each domain and average neighborhood level. RESULTS Higher neighborhood relative rankings on both income and visiting neighbors were associated with fewer depressive symptoms. Although both were modest in effect, the gradient in depressive symptoms was three times steeper for the relative rank of visiting neighbors than for income. Men had steeper gradients than women in both domains, but no race differences were observed. DISCUSSION These findings suggest that an older adult's relative position in a local social hierarchy is associated with his/her mental health, net of absolute position.
Formation control with pole placement for multi-agent systems

The problem of distributed controller synthesis for formation control of multi-agent systems is considered. The agents (single integrators) communicate over a communication graph and a decentralized linear feedback structure is assumed. One of the agents is designated as the leader. If the communication graph contains a directed spanning tree with the leader node as the root, then it is possible to place the poles of the ensemble system with purely local feedback controller gains. Given a desired formation, first one of the poles is placed at the origin. Then it is shown that the inter-agent weights can be independently adjusted to assign an eigenvector corresponding to the formation positions, to the zero eigenvalue. Then, only the leader input is enough to bring the agents to the desired formation and keep it there with no further inputs. Moreover, given a formation, the computation of the inter-agent weights that encode the formation information, can be calculated in a decentralized fashion using only local information.
Postdiffset: an Eclat-like algorithm for frequent itemset mining

Frequent itemset mining is a major field in data mining techniques. This is because it deals with usual and normal occurrences of set of items in a database transaction. Originated from market basket analysis, frequent itemset generation may lead to the formulation of association rule as to derive correlation or patterns. Association rule mining still remains as one of the most prominent areas in data mining that aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases. Underlying structure of association rules mining algorithms are based upon horizontal or vertical data formats. These two data formats have been widely discussed by showing few examples of algorithm of each data formats. The works on horizontal approaches suffer in many candidate generation and multiple database scans that contributes to higher memory consumptions. In response to improve on horizontal approach, the works on vertical approaches are established. Eclat algorithm is one example of algorithm in vertical approach database format. Motivated to its ‘fast intersection’, in this paper, we review and analyze the fundamental Eclat and Eclat-variants such as tidset, diffset, and sortdiffset. In response to vertical data format and as a continuity to Eclat extension, we propose a postdiffset algorithm as a new member in Eclat variants that use tidset format in the first looping and diffset in the later looping. We pre-sent the performance of postdiffset results in time execution as to indicate some improvements has been achieved in frequent itemset mining.
Image defogging algorithm of single color image based on wavelet transform and histogram equalization

Because of light scattered by the suspended particles in the atmosphere, photographs taken in the foggy day look gray and lack of visibility. In order to unveil the clear image’s structures and colors, we propose a image defogging algorithm of single color image based on wavelet transform and histogram equalization. Firstly, using histogram equalization to enhancement image, then to nonlinear enhancement the approximate coefficients of wavelet transform, and to distribution more uniform gray of image. A large number of experimental results show that the algorithm can enhance the image contrast and get high definition images, and outperforms in visual quality and effectively preserves texture and detail information of original images.
HLA-B*07 is a high risk allele for familial cervical cancer.

AIM The purpose of this study was to investigate 50 women from eight families with familial cervical cancer in Wufeng County, Hubei Province, China, a region with a high incidence of cervical cancer. Eighty-nine healthy women, of similar age, location and ethnicity, were selected as a control group. METHODS Blood samples were collected from both groups, and HLA-A, HLA-B, and HLA-DRB1 genotypes were profiled with the Multi-Analyte Profiling system (xMAP) (Luminex HLA-SSO) using a WAKFlow HLA typing kit. Results were analyzed with Luminex HLA typing software and showed good stability, reproducibility and specificity. RESULTS We found several high risk alleles in women with familial cervical cancer, that associated with the highest risk being HLA-B*07 (OR = 8.7, 95% CI = 1.8-41.1). CONCLUSIONS HLA-B*07 is a high risk allele for cervical cancer, and has strong potential for use as a molecular biomarker.
Children Detection Algorithm Based on Statistical Models and LDA in Human Face Images

Advances in different software and systems, and the everyday increasing demand on internet networks highlights the need for a system being able to give service to its clients based on their age. Children and adolescents are the most vulnerable group in the society. Therefore we have to look for an algorithm that can categorize immature from adult. In this paper, a practical algorithm in children classification from adults by their facial image is proposed. In this algorithm, statistical modelling of the face is used to extract the age dependent face features and then by applying Linear Discriminant Analysis (LDA) on the face parameters, useful specifications are extracted. By transferring into a one dimension feature space Euclidean distance is used as a dissimilarity function. The proposed algorithm obtains accuracy rate of 85% on a standard FG-NET aging face database.
Service Discovery: Access to Local Resources in a Nomadic Environment

We propose a standard level of support for nomadic computing in which a mobile client can move into unfamiliar environments and obtain services for which it has no corresponding client RPC stub . We call this activity service discovery and motivate its importance for mobile computing. This paper describes the general components of service discovery and points out where traditional paradigms of distributed computing fall short of its requirements. We suggest an architecture for an en vironment which uses a directory service based on the ODP trading function and a dynamic interface mechanism for ad hoc client-server interaction.
Regulation of NEIL1 protein abundance by RAD9 is important for efficient base excision repair

RAD9 participates in DNA damage-induced cell cycle checkpoints and DNA repair. As a member of the RAD9-HUS1-RAD1 (9-1-1) complex, it can sense DNA damage and recruit ATR to damage sites. RAD9 binding can enhance activities of members of different DNA repair pathways, including NEIL1 DNA glycosylase, which initiates base excision repair (BER) by removing damaged DNA bases. Moreover, RAD9 can act independently of 9-1-1 as a gene-specific transcription factor. Herein, we show that mouse Rad9−/− relative to Rad9+/+ embryonic stem (ES) cells have reduced levels of Neil1 protein. Also, human prostate cancer cells, DU145 and PC-3, knocked down for RAD9 demonstrate reduced NEIL1 abundance relative to controls. We found that Rad9 is required for Neil1 protein stability in mouse ES cells, whereas it regulates NEIL1 transcription in the human cells. RAD9 depletion enhances sensitivity to UV, gamma rays and menadione, but ectopic expression of RAD9 or NEIL1 restores resistance. Glycosylase/apurinic lyase activity was reduced in Rad9−/− mouse ES and RAD9 knocked-down human prostate cancer whole cell extracts, relative to controls. Neil1 or Rad9 addition restored this incision activity. Thus, we demonstrate that RAD9 regulates BER by controlling NEIL1 protein levels, albeit by different mechanisms in human prostate cancer versus mouse ES cells.
Analysis of Testicular Tissue Specific Expression of Mouse Novel Genes Dnajc5b and Cymg1

: Mouse Dnajc5b and Cymg1 genes are new genes that we cloned specifically in mouse testis. Dnajc5b is a homolog of DNAJ (HSP40), subfamily C, and the second of member 5, so named Dnajc5b, which is located on chromosome 3 of mouse and contains five exons with a total length of 947 bp. The reading frame is 597 bp and encodes a total of 199 amino acids. Dnajc5b was specifically expressed in mouse testis as shown by multi-tissue RT-PCR. Dnajc5b was weakly expressed in the first week and the second week after the mice were born, and the expression was enhanced in the third week. The greatest expression was in the eighth week of sexual maturity. At the same time, in situ hybridization results showed that Dnajc5b gene was specifically expressed in mouse spermatogonia, and its expression was positively correlated with testicular development. Cymg1 (GenBank accession No. AY600990), which has a full length of 0.78 kb, and contains four exons and three introns, was cloned from a mouse testis cDNA library. The gene is located in the 2G3 area of chromosome 2. The full cDNA encompasses the entire open reading frame, encoding 141 amino acid residues. CYMG1 has a 44% (48/108) identity with mouse CRES and 30% (42/140) identity with mouse cystatin C. Northern blot analysis showed that the Cymg1 is specifically expressed in adult mouse testes. Immunohistochemistry revealed that the CYMG1 protein was expressed in mouse testes spermatogonium, spermatocytes, round spermatids, elongating spermatids and spermatozoa. RT-PCR results also showed that Cymg1 was expressed in mouse testes and spermatogonium. The Cymg1 expression level varied in different developmental stages. The Cymg1 expression level in the testes over different developmental stages correlates with the mouse spermatogenesis and sexual maturation process.
Single mode ring resonator with harmonic suppression

A single-side-access ring resonator for bandpass filter is presented. The characteristics of the resonator were investigated in terms of width and gap of the ring line and coupled-lines on microstrip. It is found that the frequency response and bandwidth of the resonator can be controlled by controlling the width and gap of the ring elements. The resonator was tested on Tachonic substrates and simulated using em fullwave simulator for verification. The response showed that at higher side of out-of-band frequency response, the resonator suffered with spurious effect. To improve the effect, a 3rd order low pass filter was introduced which eventually modifies the ring structure. To validate the concept, the modified ring resonator was fabricated on Tachonic and the results showed improvement of spurious effect as compared to the nominal ring resonator. The rejection level of 30 dB was found at 4.34 GHz compared to the nominal design at 4.99 GHz with parasitic resonance at 2fo had been successfully suppressed more than 20 dB. Based on this modified structure, the size had been reduced by 13.42 % compared to the nominal ring resonator.
Second-order surface analysis using hybrid symbolic and numeric operators

Results from analyzing the curvature of a surface can be used to improve the implementation, efficiency, and effectiveness of manufacturing and visualization of sculptured surfaces. We develop a robust method using hybrid symbolic and numeric operators to create trimmed surfaces, each of which is solely convex, concave, or saddle and partitions the original surface. The same method is also used to identify regions whose curvature lies within prespecified bounds.
QuASE: A Tool Supported Approach to Facilitating Quality-Related Communication in Software Development

The paper describes the current state of the ongoing project QuASE. This project aims at facilitating quality-related communication in software development by the following means: a communication platform providing view harmonizing mechanisms for the different parties involved in a software process, decision making support related to quality issues, reuse of experience from former communication, prediction of quality-related experience. We describe usage scenarios for this approach, and outline its core concepts as well as the current progress of its implementation.
Classifying Questions in Question Answering System Using Finite State Machines with a Simple Learning Approach

Question Classification plays a significant part in Question Answering system. In order to obtain a classifier, we present in this paper a pragmatic approach that utilizes simple sentence structures observed and learned from the question sentence patterns, trains a set of Finite State Machines (FSM) based on keywords appearing in the sentences and uses the trained FSMs to classify various questions to their relevant classes. Although, questions can be placed using various syntactic structures and keywords, we have carefully observed that this variation is within a small finite limit and can be traced down using a limited number of FSMs and a simple semantic understanding instead of using complex semantic analysis. WordNet semantic meaning of various keywords to extend the FSMs capability to accept a wide variety of wording used in the questions. Various kinds of questions written in English language and belonging to diverse classes from the Conference and Labs of the Evaluation Forum’s Question Answering track are used for the training purpose and a separate set of questions from the same track is used for analyzing the FSMs competence to map the questions to one of the recognizable classes. With the use of learning strategies and application of simple voting functions along with training the weights for the keywords appearing in the questions, we have managed to achieve a classification accuracy as high as 94%. The system was trained by placing questions in various orders to see if the system built up from those orders have any subtle impact on the accuracy rate. The usability of this approach lies in its simplicity and yet it performs well to cope up with various sentence patterns. 1 This work was supported by national funds through FCT – Fundacao para a Ciencia e a Tecnologia, under project PEstOE/EEI/LA0021/2013
Harmonizing Services for LOD Vocabularies: A Case Study

Vocabularies are more and more (re)-used in the Linked Data ecosystem. However, managing the prefixes associated to their Uniform Resource Identifiers (URIs) is still cumbersome and namespaces are sometimes referring to different pair 〈prefix, URI〉. In this paper, we propose to align two well-known services with the aim of managing and harmonizing vocabularies' namespaces. We use prefix.cc that provides a look up service for namespaces in general and Linked Open Vocabularies (LOV) that extracts vocabularies metadata. Our method enables to identify three different scenarios: (i) con flicts between prefix.cc and LOV; (ii) prefixes in LOV not present in prefix.cc and (iii) URIs in prefix.cc that are actually LOV-able vocabularies. We describe how we solve each of these issues, with actions ranging from updating the different services to contacting the editors of the vocabularies to fix clashes among prefixes. Finally, we present the new LOV API that enables to check whether those namespaces in prefix.cc can actually be vocabularies to be inserted in the LOV ecosystem or not.