Miracle-dz/UniFAR-FTUs huggingface dataset:
Ontology-Based Analysis Of eService Bundles For Networked Enterprises

Model-based approaches to developing multi-enterprise e-Business initiatives help involved enterprises understand the initiatives by creating a shared understanding as a basis for profitability assessment. Still, when developing a business model where multiple potential enterprises may participate in offering a service bundle, complexity increases, and the need arises for automated support for the selection of services to include in the service bundle, implying also a selection of partners to work with. To put it differently, given a set of potential services to include in a business model, we need tools to configure one or more feasible service bundles, and to reason about the pros and cons of service bundles. Then the business analysis can be completed by calculating profitability of these service bundles. The configuration process takes into consideration inherent dependencies between available services. Its output is a set of suggested service bundles, based on these dependencies as well as possibly other given requirements related to service properties as price, quality and more. In this paper we present a methodology for doing all the above. We discuss and exemplify theoretical fundaments for such a methodology, in the framework of an e-Business analysis.
Energy-Aware Virtual Machine Consolidation for Cloud Data Centers

One of the issues in virtual machine consolidation (VMC) in cloud data centers is categorizing different workloads to classify the state of physical servers. In this paper, we propose a new scheme of host's load categorization in energy-performance VMC framework to reduce energy consumption while meeting the quality of service (QoS) requirement. Specifically the under loaded hosts are classified into three further states, i.e., Under loaded, normal and critical by applying the under load detection algorithm. We also design overload detection and virtual machine (VM) selection policies. The simulation results show that the proposed policies outperform the existing policies in Cloud Sim in terms of both energy and service level agreements violation (SLAV) reduction.
Flavonoid levels in roots ofMedicago sativa are modulated by the developmental stage of the symbiosis and the root colonizing arbuscular mycorrhizal fungus

Abundant data on the effect of flavonoids on spore germination, hyphal growth and root colonization by AMF are available. Moreover, the flavonoid pattern in mycorrhizal roots changes, thus flavonoids have been suggested as arbuscular mycorrhizal signalling compounds. In our work we studied the accumulation of flavonoids in roots of Medicago sativa i) after the exposure of uncolonized roots to sterile solutions containing Glomus intraradices tissue, ii) at three different stages of colonization by G. mosseae, iii) colonized by G. mosseae, G. intraradices or Gigaspora rosea. We could show that flavonoid accumulation in M. sativa roots i) is induced before root colonization, pointing towards the presence of a fungal-derived signal, ii) depends on the developmental stage of the symbiosis and iii) depends on the root-colonizing arbuscular mycorrhizal fungus. The data presented indicate not only a time-specificity of the flavonoid accumulation during the mycorrhizal association, but also an arbuscular mycorrhizal fungal-specificity. The possible functions of the flavonoid pattern changes are discussed.
PEMILIHAN KARIR SEBAGAI AKUNTAN PUBLIK BAGI MAHASISWA PERGURUAN TINGGI SWASTA DENGAN PENDEKATAN THEORY OF PLANNED BEHAVIOUR

The purpose of this study is to see how the attitude, subject norms, perceived behavior control and intention to behavior for a career as a public accountant in the perception of accounting students at private universities in Jakarta by using the approach of The Theory of Planned Behaviour (TPB). Data collected for processed were total of 106 questionnaires. Data processed by using Stata, showed that attitude, subject norms and perceived behavior control has a weak correlation and no significant effect among those variables, on student intention became public accountants, and to the behavior of a career as a public accountant through intention as mediating variable. However, the relationship between intention on student become a public accountant to the behavior of a career as a public accountant has a strong relationship and have a significant impact. It can be concluded that the respondents' interest in working as a public accountant only temporarily as a stepping stone to other professions
Estimation of Attentiveness of People Watching TV Based on Their Emotional Behaviors

We propose a method for estimating the attentiveness of viewers watching TV on the basis of their emotional behaviors. Such behaviors are usually hard to perceive and have in the past required contact-type equipment to measure them. We devised a novel attentiveness estimator that uses three visual features that are correlated with emotional behaviors: the viewer's head motion, blink interval, and eye movement. The main contribution of this paper is that the method automatically obtains these features from ordinary noncontact-type sensors. In addition, the method considers not only the viewer's emotional behaviors but also content features which affect the behaviors. The temporal window pattern in a video sequence is used to describe temporally local features. Experimental results indicate the possibility of recognizing TV viewers' attentiveness from certain visible emotional behaviors measured by common home electronics.
Analysis of HCV’s Linearity Using Support Vector Machine (SVM)

As the stage of bioinformatics has been upgraded, classification of certain pathogen has been improved into a new manner. The main topic of this research is genetic singularity of HCV (Hepatitis C Virus) and our objective is to assay features of the HCV's amino acid under usage of Support Vector Machine (SVM) algorithm. HCV data used in our experiment has 10 kinds of sequences and 257 kinds of data. According to data analysis, some peculiar genetic patterns of HCV’s linearity that discord pre-existing neural network and C5.0 were found.
Mutant Epidermal Growth Factor Receptor (EGFRvIII) Contributes to Head and Neck Cancer Growth and Resistance to EGFR Targeting

Purpose: Epidermal growth factor receptor (EGFR) is overexpressed in head and neck squamous cell carcinoma (HNSCC) where expression levels correlate with decreased survival. Therapies that block EGFR have shown limited efficacy in clinical trials and primarily when combined with standard therapy. The most common form of mutant EGFR (EGFRvIII) has been described in several cancers, chiefly glioblastoma. The present study was undertaken to determine the incidence of EGFRvIII expression in HNSCC and the biological consequences of EGFRvIII on tumor growth in response to EGFR targeting. Experimental Design: Thirty-three HNSCC tumors were evaluated by immunostaining and reverse transcription-PCR for EGFRvIII expression. A representative HNSCC cell line was stably transfected with an EGFRvIII expression construct. EGFRvIII-expressing cells and vector-transfected controls were compared for growth rates in vitro and in vivo as well as chemotherapy-induced apoptosis and the consequences of EGFR inhibition using the chimeric monoclonal antibody C225/cetuximab/Erbitux. Results: EGFRvIII expression was detected in 42% of HNSCC tumors where EGFRvIII was always found in conjunction with wild-type EGFR. HNSCC cells expressing EGFRvIII showed increased proliferation in vitro and increased tumor volumes in vivo compared with vector-transfected controls. Furthermore, EGFRvIII-transfected HNSCC cells showed decreased apoptosis in response to cisplatin and decreased growth inhibition following treatment with C225 compared with vector-transfected control cells. Conclusions: EGFRvIII is expressed in HNSCC where it contributes to enhanced growth and resistance to targeting wild-type EGFR. The antitumor efficacy of EGFR targeting strategies may be enhanced by the addition of EGFRvIII-specific blockade.
A PTAS for planar group Steiner tree via spanner bootstrapping and prize collecting

We present the first polynomial-time approximation scheme (PTAS), i.e., (1+ε)-approximation algorithm for any constant ε> 0, for the planar group Steiner tree problem (in which each group lies on a boundary of a face). This result improves on the best previous approximation factor of O(logn (loglogn)O(1)). We achieve this result via a novel and powerful technique called spanner bootstrapping, which allows one to bootstrap from a superconstant approximation factor (even superpolynomial in the input size) all the way down to a PTAS. This is in contrast with the popular existing approach for planar PTASs of constructing light-weight spanners in one iteration, which notably requires a constant-factor approximate solution to start from. Spanner bootstrapping removes one of the main barriers for designing PTASs for problems which have no known constant-factor approximation (even on planar graphs), and thus can be used to obtain PTASs for several difficult-to-approximate problems. Our second major contribution required for the planar group Steiner tree PTAS is a spanner construction, which reduces the graph to have total weight within a factor of the optimal solution while approximately preserving the optimal solution. This is particularly challenging because group Steiner tree requires deciding which terminal in each group to connect by the tree, making it much harder than recent previous approaches to construct spanners for planar TSP by Klein [SIAM J. Computing 2008], subset TSP by Klein [STOC 2006], Steiner tree by Borradaile, Klein, and Mathieu [ACM Trans. Algorithms 2009], and Steiner forest by Bateni, Hajiaghayi, and Marx [J. ACM 2011] (and its improvement to an efficient PTAS by Eisenstat, Klein, and Mathieu [SODA 2012]. The main conceptual contribution here is realizing that selecting which terminals may be relevant is essentially a complicated prize-collecting process: we have to carefully weigh the cost and benefits of reaching or avoiding certain terminals in the spanner. Via a sequence of involved prize-collecting procedures, we can construct a spanner that reaches a set of terminals that is sufficient for an almost-optimal solution. Our PTAS for planar group Steiner tree implies the first PTAS for geometric Euclidean group Steiner tree with obstacles, as well as a (2+)-approximation algorithm for group TSP with obstacles, improving over the best previous constant-factor approximation algorithms. By contrast, we show that planar group Steiner forest, a slight generalization of planar group Steiner tree, is APX-hard on planar graphs of treewidth 3, even if the groups are pairwise disjoint and every group is a vertex or an edge.
Lineage processing over correlated probabilistic databases

In this paper, we address the problem of scalably evaluating conjunctive queries over correlated probabilistic databases containing tuple or attribute uncertainties. Like previous work, we adopt a two-phase approach where we first compute lineages of the output tuples, and then compute the probabilities of the lineage formulas. However unlike previous work, we allow for arbitrary and complex correlations to be present in the data, captured via a forest of junction trees. We observe that evaluating even read-once (tree structured) lineages (e.g., those generated by hierarchical conjunctive queries), polynomially computable over tuple independent probabilistic databases, is #P-complete for lightly correlated probabilistic databases like Markov sequences. We characterize the complexity of exact computation of the probability of the lineage formula on a correlated database using a parameter called lwidth (analogous to the notion of treewidth). For lineages that result in low lwidth, we compute exact probabilities using a novel message passing algorithm, and for lineages that induce large lwidths, we develop approximate Monte Carlo algorithms to estimate the result probabilities. We scale our algorithms to very large correlated probabilistic databases using the previously proposed INDSEP data structure. To mitigate the complexity of lineage evaluation, we develop optimization techniques to process a batch of lineages by sharing computation across formulas, and to exploit any independence relationships that may exist in the data. Our experimental study illustrates the benefits of using our algorithms for processing lineage formulas over correlated probabilistic databases.
Expression of paragloboside-like lipooligosaccharides may be a necessary component of gonococcal pathogenesis in men

To learn how lipooligosaccharide (LOS) phase variations affect pathogenesis, we studied two male volunteers who were challenged intraurethrally with Neisseria gonorrhoeae that make a single LOS of 3,600 daltons and sequentially followed LOS expression by gonococci as urethritis developed. LOS variation occurred in vivo. Signs and symptoms of gonorrhea began with the appearance of variants making 4,700-dalton LOS that are immunochemically similar to glycosphingolipids of human hematopoietic cells (Mandrell, R.E., J.M. Griffiss, and B.A. Macher. 1989. J. Exp. Med. 168:107) and that have acceptors for sialic acid. A variant that appeared at the onset of leukorrhoea was shed by 34/36 men with naturally acquired gonorrhea at the time they sought medical attention; the other two shed the variant associated with dysuria. None shed the challenge variant. These data show that in vivo phase shifts to higher molecular mass LOS that mimic human cell membrane glycolipids are associated with the development of gonococcal leukorrhea.
A low area FIR filter for FPGA implementation

This paper proposes a high speed and low area architecture for the implementation of a FIR (Finite Impulse Response) filter into a Field Programmable Gate Array (FPGA) device. The new FIR filter type is implemented with no multiplication block, using only adders and shifting registers. This is possible because a coefficient approximation is performed, using an algorithm that computes the coefficients like a sum-of-power-of-two terms.
Multi-display map touring with tangible widget

Many map systems are created to help the user finding a place or define a route to follow. Google Map extends the concept of "surfing the map" by adding a street view that allows the user to explore a place from real pictures, creating the same feeling of walking through the streets. The horizontal 2D map and vertical panoramic street view, however, cause usability problems, while operating with traditional computer mouse and keyboards and presenting by single vertical or horizontal display. This paper presents a new table system composed of a horizontal tabletop screen and a vertical screen. The map view and the street view are displayed on the horizontal and vertical displays of our system respectively. Users can place the tangible pawn on the 2D map to have direct access of the street view from the pawn's point of view. In the user study, we compare our system with a standard computer system in the navigation task. The results reported that our system improves the intuitiveness of use, efficiency of city exploring and ease of remembrance on spaces that are not familiar beforehand. We also discuss limitations of using tangible objects for map navigation.
[Magnetic resonance spectroscopy (MRS) applications in bipolar disorder].

OBJECTIVE Magnetic resonance spectroscopy (MRS) is a noninvasive in vivo imaging technique that can directly assess the living biochemistry in localized brain regions without involving ionizing radiation. This review provides a brief description of spectroscopy, followed by a literature review of the key spectroscopy findings in bipolar disorder. METHOD We conducted a Medline literature review for the period 1966-2003, and included all the controlled studies using MRS in bipolar disorder, as well as other relevant papers with important findings. RESULTS Studies showed an increase in choline (Cho) levels in basal ganglia and cingulate, and a decrease in dorsolateral prefrontal cortical (DLPFC) and hippocampal N-acetyl aspartate (NAA) levels. Frontal lobe phosphomonoester (PME) levels were decreased in the euthymic state and were higher in the manic and depressive states. Myoinositol (mI) was reduced by lithium treatment and this decrease was positively correlated with treatment response. CONCLUSION The findings from MRS studies of bipolar disorder demonstrate alterations in the neurochemistry of key brain regions participating in the fronto-limbic-subcortical circuits implicated in the pathophysiology of the disorder. These findings suggest abnormalities of the membrane phospholipid metabolism, cellular energy metabolism and myelin formation /maintenance in the DLPFC, cingulate, hippocampus and basal ganglia in bipolar disorder. Further studies are needed to distinguish between the changes that are due to the pathophysiology of bipolar disorder and those due to the effects of medications.
Are There Critical Fatigue Thresholds? Aggregated vs. Individual Data

The mechanisms underlying task failure from fatiguing physical efforts have been the focus of many studies without reaching consensus. An attractive but debated model explains effort termination with a critical peripheral fatigue threshold. Upon reaching this threshold, feedback from sensory afferents would trigger task disengagement from open-ended tasks or a reduction of exercise intensity of closed-ended tasks. Alternatively, the extant literature also appears compatible with a more global critical threshold of loss of maximal voluntary contraction force. Indeed, maximal voluntary contraction force loss from fatiguing exercise realized at a given intensity appears rather consistent between different studies. However, when looking at individual data, the similar maximal force losses observed between different tasks performed at similar intensities might just be an “artifact” of data aggregation. It would then seem possible that such a difference observed between individual and aggregated data also applies to other models previously proposed to explain task failure from fatiguing physical efforts. We therefore suggest that one should be cautious when trying to infer models that try to explain individual behavior from aggregated data.
Dynamic Portfolio Choice under Incomplete Information

Under incomplete information, this paper studies the problem of dynamic portfolio choice of an investor who maximizes the power utility of terminal portfolio wealth. It applies stochastic control method to obtain the closed-form solution of optimal dynamic portfolio choice and uses the Bayesian rule to estimate the unknown model parameters to do an empirical study on two different samples of Shanghai Exchange Composite Index. Results show, incomplete information means that the valuation of model parameters exist estimation risk, which leads to the hedge demand of portfolio; the effect of estimation risk is more significant with the increasing of investment horizon, and the decreasing of information and investor's risk-aversion degree; the predictability of return process enhances the effect of estimation risk.
Lock Manager for Own Products

This paper describes implementation and introducing of lock manager to hosting management product as an aspect of scalability the product from single server to multi-server environment. Main goal of the lock manager is controll on access to shared resources. There are also presented a review of existing solutions, which are analyzed by several criteria and major features. This paper also includes results of performance tests of lock manager implementation, description of architecture and prototype of an application based on the lock manager, which demonstrates main usage scenarios.
Interest analysis using social interaction content with sentiments

We introduce a method for learning to predict reader interest. In our approach, interest analysis bases on PageRank and social interaction content (e.g., reader feedback in social media). The method involves automatically estimating topical interest preferences and determining the sentiment for social content. In interest prediction, different content sources of articles and reader feedback representing readers' viewpoints are weighted accordingly and transformed into content-word weighted word graph. Then, PageRank suggests reader interest with the help of word interestingness scores. We present the prototype system, InterestFinder, that applies the method to interest analysis. Experimental evaluation shows that content source and content word weighting, and scores of interest preferences for words inferred across articles are quite helpful. Our system benefits more from subjective social interaction content than objective one in covering general readers' interest spans.
A Three-Layer Model for Software Engineering Metrics

This paper presents a three-layer model that captures the fundamentals of software metrics within a unifying framework. The model readily lends itself for use in both instructional and practitioner environments. The first (lowest) layer of the model consists of the three primitive software engineering metrics: person-months (PM), function-points (FP), and lines of code (LOC). They are presented as "primary" metrics from which other metrics are computed. Time is also included as a fundamental (not necessarily software) primary metric. The second layer consists of general-purpose metrics such as productivity measures, which are computed from the primary metrics, and the third layer consists of special-purpose metrics such as reliability and quality measures. This third layer is inherently extensible
DOA Estimation for Coherent Sources in Impulsive Noise Environments

Direction-of-arrival (DOA) estimation of coherent sources is a significant problem in impulsive noise environments. In this paper, a robust estimation algorithm which combines the ideas of spatial smoothing (SS) and infinity-norm normalization (INF) is presented, referred to as INF-SSR. The proposed algorithm exploits the Root–MUSIC technique to computer the DOA estimates, thus avoiding the peak searching and can be applied to seriously impulsive noise environments compared with the fractional lower order moment spatial smoothing MUSIC algorithm (FLOM-SS). Simulation results demonstrate effectiveness of the proposed algorithm