Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Analysis of the Active Object Pattern in Middleware

A number of enterprises are turning towards the Service Oriented Architecture (SOA) approach for their systems due to the number of benefits it offers. A key enabling technology for the SOA-based approach is middleware, which comprises of reusable building blocks based on design patterns. These building blocks can be configured in numerous ways and the configuration options of a pattern can have a profound impact on system performance. A performance analysis methodology which can be used to assess this influence at design time can guide the selection of patterns and their configuration options and thus alleviate the possibility of performance problems arising later in the life cycle. This paper presents a model-based performance analysis methodology for a system built using the Active Object (AO) pattern. The AO pattern is chosen because it lies at the heart of an important class of producer/consumer and publish/subscribe systems. Central to the methodology is a queuing model which captures the internal architecture of an AO-based system. Using an implementation of the queuing model in CSIM, we illustrate the value of the methodology to guide the selection of configuration and provisioning options for a stock broker system.
Using influential nodes of stock network to measure Tehran Stock Exchange index

In the capital market, the stocks which have more impact on the other stocks, are called “influential stocks. ” If we can find the influential stocks of market, we can analyze present and future status of the market only by investigating them. This paper proposes a method for determining the influential stocks and estimating the market index using them. The influential stocks are recognized based on the market correlation-based network. This network is a graph, which the nodes are the existing stocks in the market and the edges are the similarity of the price fluctuations of corresponding stocks. Since the network follows power-law distribution, there are only few nodes with extreme high degree, i.e., influential stocks. The results of the experiments show that the market index calculated using the influential stocks fluctuates very similar to the main index, which includes all the stocks. In addition, the proposed method reduces the sudden and minor fluctuations of the main index.
Target Detection and Pedestrian Recognition in Infrared Images

By improving the local contrast between targets and background in the static infrared images, a simple and effective background model is proposed to detect targets. At the same time, a novel learning algorithm is presented for training a discriminatively trained, part-based model with only positives images, for pedestrian recognition. The background models are constructed based on the static infrared images by morphological operations. Meanwhile, the learning algorithm is based on the ramp loss function, which can filter out the false negatives from the collected negative examples. It has a great advantage on training the deformable part models with latent variables when the dataset has a large number of noisy examples. Experiments manifest that our background model can achieve a high precision in target detection and the discriminative part model trained by the proposed learning approach can recognize the targets well and truly, with the help of target detection.
Workshop on Shared Tasks and Comparative Evaluation in Natural Language Generation Position Papers

Today’s NLG efforts should be compared against actual human performance, which is fluent and varies randomly and with context. Consequently, evaluations should not be done against a fixed ‘gold standard’ text, and shared task efforts should not assume that they can stipulate the representation of the source content and still let players generate the diversity of texts that the real world calls for. 1 Minimal competency The proper point of reference when making an evaluation of the output of a natural language generation (NLG) system is the output of a person. With the exception of the occasional speech error or other predicable disfluencies such as stuttering or restarts, people speak with complete command of their grammar (not to mention their culturally attuned prosodics), and with complete command of their discourse context as it shapes the coherence of what they say and the cohesion of how they say it. Any NLG system today that does not use pronouns correctly (assuming they use them at all), that does not reduce complex NPs when they describe subsequent references to entities already introduced into the discourse, that does not reduce clauses with common subjects when they are conjoined, or that fails to use any of the other ordinary cohesive techniques available to them in the language they are using is simply not in the running. Human-level fluency is the entrance ticket to any comparative evaluation of NLG systems.
Far-Ultraviolet Emission from Elliptical Galaxies at z = 0.33

We present far-UV images of the rich galaxy cluster ZwCl 1358.1+6245, taken with the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope (HST). When combined with archival HST observations, our data provide a measurement of the UV-to-optical flux ratio in eight early-type galaxies at z = 0.33. Because the UV flux originates in a population of evolved, hot, horizontal-branch (HB) stars, this ratio is potentially one of the most sensitive tracers of age in old populations—it is expected to fade rapidly with look-back time. We find that the UV emission in these galaxies, at a look-back time of 3.9 Gyr, is significantly weaker than it is in the current epoch, yet it is similar to that in galaxies at a look-back time of 5.6 Gyr. Taken at face value, these measurements imply different formation epochs for the massive elliptical galaxies in these clusters, but an alternative explanation is a "floor" in the UV emission due to a dispersion in the parameters that govern HB morphology.
A comparison of line extraction algorithms using 2D laser rangefinder for indoor mobile robotics

This paper presents an experimental evaluation of different line extraction algorithms on 2D laser scans for indoor environment. Six popular algorithms in mobile robotics and computer vision are selected and tested. Experiments are performed on 100 real data scans collected in an office environment with a map size of 80m /spl times/ 50m. Several comparison criteria are proposed and discussed to highlight the advantages and drawbacks of each algorithm, including speed, complexity, correctness and precision. The results of the algorithms are compared with the ground truth using standard statistical methods.
Performance Evaluation of a Genetic Algorithm Based Approach to Network Intrusion Detection System

The purpose of the work described in this paper is to provide an intrusion detection system (IDS), by applying genetic algorithm (GA) to network intrusion detection system. Parameters and evolution process for GA are discussed in detail and implemented. This approach uses information theory to filter the traffic data and thus reduce the complexity. We use a linear structure rule to classify the network behaviors into normal and abnormal behaviors. This approach applied to the KDD99 benchmark dataset and obtained high detection rate up to 99.87% as well as low false positive rate 0.003%. Finally the results of this approach compared with available machine learning techniques.
Social Class, Classism, Stigma, and College Students’ Attitudes Toward Counseling

This study tested two competing theoretically and empirically derived models of college students’ attitudes toward seeking counseling. It extends the literature in this area by assessing the influence of objective and subjective social class, classism, and stigma on attitudes. We used structural equation modeling to analyze self-reported archival data from 2,230 incoming college students at a large, public research university in the Eastern United States. The results demonstrated the superiority of the direct and indirect effects of social class over the competing indirect effects model of social class. The results further indicated that objective social class related to attitudes toward seeking professional help indirectly through subjective social class, classism, and stigma. Finally, the results also showed that objective social class, subjective social class, and classism operated differently in the model. We discuss study limitations, future directions for research, and recommendations for practice.
Association between socioeconomic status and adverse events following immunization at 2, 4, 6 and 12 months

Using a population-based self-controlled case series design, we examined data on children born between the years 2002 and 2009 in the province of Ontario, Canada. We specifically examined how socioeconomic status (SES) influences rates of adverse events following immunization (AEFI), defined as emergency room visits and / or hospital admissions. For vaccination at 2, 4 and 6 mo combined, the relative incidence of AEFI (95% CI) in the first 72 h after vaccination was 0.69 (0.67 to 0.71). For all three vaccinations combined, we observed no relationship between the relative incidence of an event and quintile of socioeconomic status (p = 0.1433). For the 12-mo vaccination alone, the relative incidence of events (95% CI) on days 4 to 12 following immunization was 1.35 (1.31 to 1.38). We observed a significant relationship between socioeconomic status and vaccination at 12 mo, with lower SES being associated with a higher relative incidence of events (p = 0.0075). When the lowest 2 quintiles of income combined were compared with the highest 3 quintiles, the relative incidence ratio (95% CI) was 0.94 (0.89 to 0.99, p = 0.02). These results translate to 150 additional adverse events in the lower SES quintiles as compared with the higher SES quintiles for every 100,000 children vaccinated, or 1 additional event for every 666 individuals vaccinated. Future studies should explore potential explanations for this observation.
Classification of voiced and non-voiced speech signals using empirical wavelet transform and multi-level local patterns

This paper presents a novel algorithm for classification of voiced and non-voiced speech segments in noisy environment. Empirical wavelet transform (EWT), an adaptive technique for analyzing non-stationary signals, is employed in the pre-processing stage for suppression of noise in speech signals. In this work, multi-level local patterns (MLP), modified version of 1D-local binary patterns (LBP) are used as features. Multi-level local patterns capture the local variations in non-stationary signal by performing comparisons in neighborhood of a sample. Finally, the comparative information thus generated is encoded into multiple states and histogram of MLPs corresponding to short segments of speech signal is computed. Nearest neighbor classifier utilizes the histogram features for classification of speech segments. Experimental evaluation of proposed approach is carried out on the publicly available CMU-Arctic database. The results of our experiments show improvement in classification accuracy with the use of EWT. Further, the MLP based approach clearly yields superior performance than the LBP based approach.
Survey Results on Threats To External Validity, Generalizability Concerns, Data Sharing and University-Industry Collaboration in Mining Software Repository (MSR) Research

Mining Software Repositories (MSR) is an applied and practise-oriented field aimed at solving real problems encountered by practitioners and bringing value to Industry. Replication of results and findings, generalizability and external validity, University-Industry collaboration, data sharing and creation dataset repositories are important issues in MSR research. Research consisting of bibliometric analysis of MSR paper shows lack of University-Industry collaboration, deficiency of studies on closed or propriety source dataset and lack of data as well as tool sharing by researchers. We conduct a survey of authors of past three years of MSR conference (2012, 2013 and 2014) to collect data on their views and suggestions to address the stated concerns. We asked 20 questions from more than 100 authors and received a response from 39 authors. Our results shows that about one-third of the respondents always make their dataset publicly available and about one-third believe that data sharing should be a mandatory condition for publication in MSR conferences. Our survey reveals that more than 50% authors used solely open-source software (OSS) dataset for their research. More than 50% of the respondents mentioned that difficulty in sharing Industrial dataset outside the company is one of the major impediments in University-Industry collaboration.
Gibberellin Is Involved in Inhibition of Cucumber Growth and Nitrogen Uptake at Suboptimal Root-Zone Temperatures

Suboptimal temperature stress often causes heavy yield losses of vegetables by suppressing plant growth during winter and early spring. Gibberellin acid (GA) has been reported to be involved in plant growth and acquisition of mineral nutrients. However, no studies have evaluated the role of GA in the regulation of growth and nutrient acquisition by vegetables under conditions of suboptimal temperatures in greenhouse. Here, we investigated the roles of GA in the regulation of growth and nitrate acquisition of cucumber (Cucumis sativus L.) plants under conditions of short-term suboptimal root-zone temperatures (Tr). Exposure of cucumber seedlings to a Tr of 16°C led to a significant reduction in root growth, and this inhibitory effect was reversed by exogenous application of GA. Expression patterns of several genes encoding key enzymes in GA metabolism were altered by suboptimal Tr treatment, and endogenous GA concentrations in cucumber roots were significantly reduced by exposure of cucumber plants to 16°C Tr, suggesting that inhibition of root growth by suboptimal Tr may result from disruption of endogenous GA homeostasis. To further explore the mechanism underlying the GA-dependent cucumber growth under suboptimal Tr, we studied the effect of suboptimal Tr and GA on nitrate uptake, and found that exposure of cucumber seedlings to 16°C Tr led to a significant reduction in nitrate uptake rate, and exogenous application GA can alleviate the down-regulation by up regulating the expression of genes associated with nitrate uptake. Finally, we demonstrated that N accumulation in cucumber seedlings under suboptimal Tr conditions was improved by exogenous application of GA due probably to both enhanced root growth and nitrate absorption activity. These results indicate that a reduction in endogenous GA concentrations in roots due to down-regulation of GA biosynthesis at transcriptional level may be a key event to underpin the suboptimal Tr-induced inhibition of root growth and nitrate uptake. These findings may have important practical implications in effective mitigation of suboptimal temperature-induced vegetable loss under greenhouse conditions.
Closing the Reading Achievement Gap: The Impact of a Multitiered Response to Intervention Framework in Kindergarten

The purpose of this quantitative, quasi-experimental, ex post facto study was to examine the impact the Response to Intervention (RTI) framework had on kindergarten reading scores as measured by the standardized test for the achievement of reading early literacy assessment (STAR-ELA). This study employed an ex post facto design utilizing a retrospective cohort. Two 2 × 2 mixed-subjects factorial analysis of variances (ANOVAs) were used in addressing the study’s three research questions. First, the study evaluated the combined effectiveness of Tier 1 and Tier 2 reading interventions on nonclassified kindergarten students’ reading achievement to determine if the implementation of RTI impacted the reading scores of kindergarten students. Findings reveal that Tier 1 and Tier 2 RTIs were effective in enhancing students’ reading scores. Second, the study compared the efficacy of Tier 1 and Tier 2 interventions separately to determine if there was any relationship between the type of RTI employed and the resulting improvements in reading achievement. Findings show that Tier 2 students exhibited significantly greater improvement than Tier 1 students. Finally, this study investigated the potential role of gender in moderating the effect of Tier 2 interventions on reading achievement. The data examined displayed that both males and females in Tier 2 RTI showed approximately equal and statistically significant gains in STAR-ELA scores. Recommendations are that further studies should include students who are classified with an individualized education plan, in addition to English language learners, to reveal how interventions can be effective with different populations. In addition, further research should be conducted on Tier 3 interventions. Document Type Dissertation Degree Name Doctor of Education (EdD) Department Executive Leadership First Supervisor Jeff Wallis Second Supervisor Winsome Gregory Subject Categories Education This dissertation is available at Fisher Digital Publications: https://fisherpub.sjfc. edu/education_etd/366 Closing the Reading Achievement Gap: The Impact of a Multitiered Response to Intervention Framework in Kindergarten
A filtering strategy for interest point detecting to improve repeatability and information content

This paper compares several stereo image interest point detectors with respect to their repeatability and information content through experimental analysis. The Harris-Laplace detector gives better results than other detectors in areas of good texture; however, in areas of poor texture, the HarrisLaplace detector may be not the best choice. A featurerelated filtering strategy is designed for the Harris-Laplace detector (as well as the standard Harris detector) to improve the repeatability and information content for imagery with both good and poor texture: (a) the local information entropy is computed to describe the local feature of the image; and (b) the redundant interest points are filtered according to the interest strength and the local information entropy. After the filtering process, the repeatability and information content of the final interest points are improved, and the mismatching then can be reduced. This conclusion is supported by experimental analysis with actual stereo images.
Kinematics simulation and control design of the Agile Wrist in a Dual-arm robotic mechanical systems

In order to improve space positioning accuracy of the Agile Wrist consisting of a modified spherical parallel manipulator, which will influence the result of the Collisions experiment in a robotic mechanical testbed directly, this paper explores the motion control of Agile Wrist. Based on analysis an input - output (I/O) equation of spherical four-bar linkages for forward-displacement of spherical parallel robots, the inverse kinematics derivation is reported here to find the active-joint variables for each possible position and orientation (pose) of the mobile plate, as well as the singularity exist and defines what may be generalized as the workspace boundary. Meanwhile the kinematics simulation by using simulink S-Function combined with Q8 controller was carried out. The results showed that the Kinematics analysis and Control Design of Agile Wrist were correct. The modified spherical parallel manipulator can meet with the demands of Collisions experiment in the robotic mechanical testbed.
Thumb joint angle estimation for soft wearable hand robotic devices

There is a recent increase in development of compact soft wearable robotic devices that are used for rehabilitation and assistance of the hand. In order to rehabilitate or assist natural grasp tasks, the device requires monitoring of hand posture including finger and thumb joint angles. For estimating the finger and thumb joint angles without making the device bulky, bending sensors enable compact design of glove-type hand robotic devices; however, the estimation of the accurate thumb joint angles is challenging due to the highly coupled multi-degree of freedom movement. A bending sensor attached on any hand location tends to be deformed by movement of thumb in all DOFs, i.e., there is significant amount of coupling effect. It is important to find sensor locations that have minimal coupling effect to make the thumb joint angle measurement more accurate. In this paper, we present an experimental study on the optimal sensor location that causes minimal coupling effect on the thumb joint angle measurement.
An Efficient Vein Pattern-Based Recognition System

This paper presents an efficient human recognition system based on vein patterns from the palma dorsa. A new absorption-based technique has been proposed to collect good quality images with the help of a low cost camera and light source. The system automatically detects the region of interest from the image and does the necessary preprocessing to extract features. Euclidean Distance based technique has been used to make a decision on matching. It has been tested on a data set of 1750 image samples collected from 341 individuals. The accuracy of the recognition system is found to be 99.26% with false rejection rate (FRR) of 0.03%.
Performance Analysis of a Constrained Yule-walker Frequency Estimator Performance Analysis of a Constrained Yule-walker Frequency Estimator

SUMMARY The performance of a constrained (that is, minimal order) Yule-Walker (CYW) single tone frequency estimator is studied. A closed form expression for the asymptotic error variance is derived. It is shown that CYW does not satisfactorily utilize the information in data, and estimators with improved performance are proposed. Simulation results which lend support to the theoretical ndings are included.
The Failure of Internal Audit: Monitoring Gaps and a Case for a New Focus

Within the management and organization field, the internal audit function (IAF) plays an important role in enhancing good governance. Given the spate of corporate collapses over the last 20 years, this article draws on a multitheoretical approach to governance and a critical review of the published literature to identify where IAFs have failed, and to provide a new focus to strengthen their role. Common themes regarding monitoring gaps by IAFs were identified as occurring across three governance levels. A contributory cause for these gaps is the poor structural and functional arrangements of the IAF, arising from the considerable flexibility afforded in its setup and delivery of services. A negative consequence of this flexibility is the ability of the board and management to manipulate the role of the IAF to the extent that it is not aligned with the intention of its setup as encapsulated in its definition.