Miracle-dz/UniFAR-FTUs huggingface dataset:
The PHANToM Haptic Interface: A Device for Probing Virtual Objects

1. Abstract This paper describes the PHANToM haptic interface - a device which measures a user’s finger tip position and exerts a precisely controlled force vector on the finger tip. The device has enabled users to interact with and feel a wide variety of virtual objects and will be used for control of remote manipulators. This paper discusses the design rationale, novel kinematics and mechanics of the PHANToM. A brief description of the programming of basic shape elements and contact interactions is also given.
Assessing the Frequency of Empirical Evaluation in Software Modeling Research

Researchers in software modeling often publish new tools or methodologies that claim to offer some advantage to the modeling community. There are different methods by which those claims can be evaluated. In this paper, we examine the degree to which such claims are supported by various types of empirical evaluation. We surveyed five editions of the MoDELS conference from 2006-2010, as well as the primary conference that focuses on empirical software engineering (the International Symposium on Empirical Software Engineering and Metrics), to understand the frequency with which empirical evaluation has been reported in the software modeling community. Our summary of 266 MoDELS papers found that 195 (73%) of the publications performed no empirical evaluation. This paper summarizes our findings from that survey and offers recommendations for improving the awareness and need for empirical evaluation in software modeling research.
A COMPARISON OF FREE-FORM STUDENT EVALUATIONS ON RateMyProfessors . com AND A UNIVERSITY-BASED SYSTEM

Student evaluations of teaching (SETs) have been around for decades. The debate on their validity and usefulness has raged just as long, with respected researchers on both sides of the table. The author is less concerned with numerical averages computed from SETs than with the substance of students’ free-form responses to open-ended questions. This paper analyzes free-form responses posted on the popular website RateMyProfessors.com and compares them to analogous responses on a university webbased course evaluation system designed by the author. It examines differences between the two and the types of information that can be gleaned from such sources to improving teaching.
A Comparison of Bias Reduction Methods: Clustering versus Propensity Score Subclassification and Weighting

ABSTRACT Propensity score (PS) adjustments have become popular methods used to improve estimates of treatment effects in quasi-experiments. Although researchers continue to develop PS methods, other procedures can also be effective in reducing selection bias. One of these uses clustering to create balanced groups. However, the success of this new method depends on its efficacy compared to that of the existing methods. Therefore, this comparative study used experimental and nonexperimental data to examine bias reduction, case retention, and covariate balance in the clustering method, PS subclassification, and PS weighting. In general, results suggest that the cluster-based methods reduced at least as much bias as the PS methods. Under certain conditions, the PS methods reduced more bias than the cluster-based method, and under other conditions the cluster-based methods were more advantageous. Although all methods were equally effective in retaining cases and balancing covariates, other data-specific conditions may likely favor the use of a cluster-based approach.
Toward a completely automatic neural-network-based human chromosome analysis

The application of neural networks (NNs) to automatic analysis of chromosome images is investigated in this paper. All aspects of the analysis, namely segmentation, feature description, selection and extraction, and classification, are studied. As part of the segmentation process, the separation of clusters of partially occluded chromosomes, which is the critical stage that state-of-the-art chromosome analyzers usually fail to accomplish, is performed. First, a moment representation of the image pixels is clustered to create a binary image without a need for threshold selection. Based on the binary image, lines connecting cut points imply possible separations. These hypotheses are verified by a multilayer perceptron (MLP) NN that classifies the two segments created by each separating line. Use of a classification-driven segmentation process gives very promising results without a need for shape modeling or an excessive use of heuristics. In addition, an NN implementation of Sammon's mapping using principal component based initialization is applied to feature extraction, significantly reducing the dimensionality of the feature space and allowing high classification capability. Finally, by applying MLP based hierarchical classification strategies to a well-explored chromosome database, we achieve a classification performance of 83.6%. This is higher than ever published on this database and an improvement of more than 10% in the error rate. Therefore, basing a chromosome analysis on the NN-based techniques that are developed in this research leads toward a completely automatic human chromosome analysis.
Parenting Style Dimensions As Predictors of Adolescent Antisocial Behavior

Antisocial behavior is strongly associated with academic failure in adolescence. There is a solid body of evidence that points to parenting style as one of its main predictors. The objective of this work is to elaborate a reduced, valid, and reliable version of the questionnaire by Oliva et al. (2007) to evaluate the dimensions of parenting style and to analyze its psychometric properties in a sample of Spanish adolescents. To that end, the designed questionnaire was applied to 1974 adolescents 12–18 years of age from Asturias (Spain). Regarding construct validity, the results show that the model that best represents the data is composed of six dimensions of parenting style, just as in the original scale, namely affection and communication; promotion of autonomy; behavioral control; psychological control; self-disclosure; and humor. The psychological control factor negatively correlates with the other factors, with the exception of behavioral control, with which it positively correlates. The remaining correlations among the factors in the parenting style questionnaire are positive. Regarding internal consistency, the reliability analysis for each factor supports the suitability of this six-factor model. With regard to criterion validity, as expected based on the evidence available, the six dimensions of parenting style correlate in a statistically significant manner with the three antisocial behavior measures used as criteria (off-line school aggression, antisocial behavior, and antisocial friendships). Specifically, all dimensions negatively correlate with the three variables, except for psychological control. In the latter case, the correlation is positive. The theoretical and practical implications of these results are discussed.
Evolution of female multiple mating: A quantitative model of the “sexually selected sperm” hypothesis

Explaining the evolution and maintenance of polyandry remains a key challenge in evolutionary ecology. One appealing explanation is the sexually selected sperm (SSS) hypothesis, which proposes that polyandry evolves due to indirect selection stemming from positive genetic covariance with male fertilization efficiency, and hence with a male's success in postcopulatory competition for paternity. However, the SSS hypothesis relies on verbal analogy with “sexy‐son” models explaining coevolution of female preferences for male displays, and explicit models that validate the basic SSS principle are surprisingly lacking. We developed analogous genetically explicit individual‐based models describing the SSS and “sexy‐son” processes. We show that the analogy between the two is only partly valid, such that the genetic correlation arising between polyandry and fertilization efficiency is generally smaller than that arising between preference and display, resulting in less reliable coevolution. Importantly, indirect selection was too weak to cause polyandry to evolve in the presence of negative direct selection. Negatively biased mutations on fertilization efficiency did not generally rescue runaway evolution of polyandry unless realized fertilization was highly skewed toward a single male, and coevolution was even weaker given random mating order effects on fertilization. Our models suggest that the SSS process is, on its own, unlikely to generally explain the evolution of polyandry.
Symbol Recognition: Cognitive Approach

The field of Computer Science has been solving issues related to the domains of data, information, knowledge and intelligence, obviously in a chronological manner. Among these the issue of Symbol Recognition has received lot of attention. The procedure of analyzing and recognizing symbols involves various stages. A number of algorithms have been devised and implemented for the purpose of symbol recognition but usually focus on complex features and properties. In this paper, we propose a cognitive model for the recognition of offline machine drawn symbols which uses minimal amount of data. The algorithm proposed is independent of the size/slant of the symbol.
Involvement of Intermediate Sulfur Species in Biological Reduction of Elemental Sulfur under Acidic, Hydrothermal Conditions

ABSTRACT The thermoacidophile and obligate elemental sulfur (S8 0)-reducing anaerobe Acidilobus sulfurireducens 18D70 does not associate with bulk solid-phase sulfur during S8 0-dependent batch culture growth. Cyclic voltammetry indicated the production of hydrogen sulfide (H2S) as well as polysulfides after 1 day of batch growth of the organism at pH 3.0 and 81ï¿½C. The production of polysulfide is likely due to the abiotic reaction between S8 0 and the biologically produced H2S, as evinced by a rapid cessation of polysulfide formation when the growth temperature was decreased, inhibiting the biological production of sulfide. After an additional 5 days of growth, nanoparticulate S8 0 was detected in the cultivation medium, a result of the hydrolysis of polysulfides in acidic medium. To examine whether soluble polysulfides and/or nanoparticulate S8 0 can serve as terminal electron acceptors (TEA) supporting the growth of A. sulfurireducens, total sulfide concentration and cell density were monitored in batch cultures with S8 0 provided as a solid phase in the medium or with S8 0 sequestered in dialysis tubing. The rates of sulfide production in 7-day-old cultures with S8 0 sequestered in dialysis tubing with pore sizes of 12 to 14 kDa and 6 to 8 kDa were 55% and 22%, respectively, of that of cultures with S8 0 provided as a solid phase in the medium. These results indicate that the TEA existed in a range of particle sizes that affected its ability to diffuse through dialysis tubing of different pore sizes. Dynamic light scattering revealed that S8 0 particles generated through polysulfide rapidly grew in size, a rate which was influenced by the pH of the medium and the presence of organic carbon. Thus, S8 0 particles formed through abiological hydrolysis of polysulfide under acidic conditions appeared to serve as a growth-promoting TEA for A. sulfurireducens.
A Monoclonal Antibody against the c-erbB2 Protein Enhances the Cytotoxicity of c / 5-Diamminedichloroplatinum against Human Breast and Ovarian Tumor Cell

A monoclonal antibody ("IAli 250) specific to an extracellular epitope of the c-erbB-2 protein (gplSS) inhibited the in vitro proliferation of human breast tumor cell lines that overexpress c-erbB-2 in a dosedependent manner. Treatment of cells with combinations of CM-diammedichloroplatinum (CDDP) and l'Ali 250 resulted in a significantly en hanced cytotoxic effect. This synergistic cytotoxicity was apparent over a wide range of antibody concentrations (200 pg/ml-100 Â«Â¿g/ml) including concentrations that showed no inhibitory effect alone. TAb 250 did not increase the cytotoxic effect of CDDP in a cell line exhibiting no detect able level of gpl85. Athymic mice bearing s.c. xenografts of human tumor cells expressing high levels of gpl85 showed a greatly enhanced inhibition of tumor growth when treated with TAb 250 and CDDP compared to treatment with the antibody or CDDP alone. This effect was specific inasmuch as TAb 250 did not enhance the growth-inhibitory effect of CDDP on tumor xenografts which were not expressing gplSS.
Holistic Network Defense : Fusing Host and Network Features for Attack Classification

Current defensive systems focus primarily on network data, and are plagued by a high false positive rate and/or duplicate alerts with no ranking of importance. This work presents a hybrid network-host monitoring strategy, fusing data from both the network and the host to recognize malware infections. This research seeks to categorize systems into one of three classes: Normal, Scanning, and Infected. The objective is accomplished by fusing data from multiple network/host sensors, extracting features from network traffic using the Fullstats Network Feature generator and from the host using text mining, using the frequency of the 500 most common strings and analyzing them as word vectors. Hybrid method results outperformed both host only and network only classification. This approach reduces the number of alerts while remaining accurate compared with the commercial IDS SNORT. These results improve the relevance of alerts so that most typical users could understand alert classification messages.
Multilingual Corpus Development for Opinion Mining

Opinion Mining is a discipline that has attracted some attention lately. Most of the research in this field has been done for English or Asian languages, due to the lack of resources in other languages. In this paper we describe an approach of building a manually annotated multilingual corpus for the domain of product reviews, which can be used as a basis for fine-grained opinion analysis also considering direct and indirect opinion targets. For each sentence in a review, the mentioned product features with their respective opinion polarity and strength on a scale from 0 to 3 are labelled manually by two annotators. The languages represented in the corpus are English, German and Spanish and the corpus consists of about 500 product reviews per language. After a short introduction and a description of related work, we illustrate the annotation process, including a description of the annotation methodology and the developed tool for the annotation process. Then first results on the inter-annotator agreement for opinions and product features are presented. We conclude the paper with an outlook on future work.
On The Equivalence of Projections in Relative (α- Entropy and Rényi Divergence

The aim of this work is to establish that two recently published projection theorems, one dealing with a parametric generalization of relative entropy and another dealing with Rényi divergence, are equivalent under a correspondence on the space of probability measures. Further, we demonstrate that the associated “Pythagorean” theorems are equivalent under this correspondence. Finally, we apply Eguchi's method of obtaining Riemannian metrics from general divergence functions to show that the geometry arising from the above divergences are equivalent under the aforementioned correspondence.
ONTROL MAC P ROTOCOL ( IAPCMP ) FOR MANET S

Power Control in Mobile Ad Hoc networks is a critical issue, since nodes are powered by batteries.The main idea of power control schemes is to use different power levels for RTS/CTS and DATA/ACK. These schemes may degrade network throughput and reduce energy efficiency of the network. In this paper we have evaluated the performance of Improved Autonomous Power Control MAC Protocol (IAPCMP),that allows nodes to dynamically adjust power levels for transmission of DATA/ACK according to the distance between the transmitter and its neighbors.In IAPCMP power level for transmission of RTS/CTS is also adjustable. This also used maximum power level for transmitting DATA/ACK periodically to make neighboring nodes aware about ongoing transmission. The performance of IAPCMP is evaluated through the metrics namely, packet delivery ratio and rate of energy efficiency.The simulation results show significant improvement in protocol.
How Brand Names Affect the Price Setting of Carmakers Producing Twin Cars

In the automobile sector, it is a usual practice that independent carmakers engage in the development and production of a common car model, the so-called twin cars. From the point of view of the marketing literature, we claim that carmakers should not charge different brand premia on separate models of a twin car. We use hedonic regressions and panel data estimators to valuate brand premia, by controlling for quality diversity. We find that there are no significant differences between brand premia of separate models of a twin car, even if brand premia may differ across different carmakers.
High Throughput Screening of Co-Expressed Gene Pairs with Controlled False Discovery Rate (FDR) and Minimum Acceptable Strength (MAS)

Many exploratory microarray data analysis tools such as gene clustering and relevance networks rely on detecting pairwise gene co-expression. Traditional screening of pairwise co-expression either controls biological significance or statistical significance, but not both. The former approach does not provide stochastic error control, and the later approach screens many co-expressions with excessively low correlation. We have designed and implemented a statistically sound two-stage co-expression detection algorithm that controls both statistical significance (false discovery rate, FDR) and biological significance (minimum acceptable strength, MAS) of the discovered co-expressions. Based on estimation of pairwise gene correlation, the algorithm provides an initial co-expression discovery that controls only FDR, which is then followed by a second stage co-expression discovery which controls both FDR and MAS. It also computes and thresholds the set of FDR p-values for each correlation that satisfied the MAS criterion. Using simulated data, we validated asymptotic null distributions of the Pearson and Kendall correlation coefficients and the two-stage error-control procedure; we also compared our two-stage test procedure with another two-stage test procedure using the receiver operating characteristic (ROC) curve. We then used yeast galactose metabolism data to illustrate the advantage of our method for clustering genes and constructing a relevance network. The method has been implemented in an R package "GeneNT" that is freely available from the Comprehensive R Archive Network (CRAN): www.cran. r-project.org/.
Characteristics of Social Networks Relevant to Predictions of Social Influence

Understanding social influence and identifying influential members of a community is of interest to the designers and evaluators of various online services such as recommender systems in ecommerce or health promotion programs in healthcare. Various methods have been proposed for the identification of influentials in past research. However, there is limited research on the relationships between these different methods and the role of networks’ topology on these relationships. The main goals of the research in this thesis were to study relationships between measures of network structure, and to characterize different types of network, where the properties of structural measures differ across the network types. Understanding the structure of social networks should lead to more useful and usable social network applications. In the research reported in this dissertation I began by examining the relationship between structural and behavioral measures of social influence, finding that they are relatively independent of each other in the two social networks that were examined. I then focused on social network centrality measures, which are structural measures commonly used to identify central and potentially influential members of a social network. Two new factors representing network topology properties were identified and a set of 62 real-world social networks were grouped into three different types based on their scores on those factors. Correlations amongst various structural influence measures, and the effect of network topology on structural measures of centrality, were also examined. iii A secondary goal of this research was to determine when approximations of computationally complex measures may be used to estimate social influence. Using the factors representing network topology, the correlation between the computationally complex measure of betweenness centrality and the computationally simpler measure of ego betweenness was found to vary depending on network topology, opening the way towards network topology-based selection of centrality-based measures of influence. The research findings presented in this thesis are offered as a first step towards improved methods of identifying influential members in very large social networks.
Incorporating approximate dynamic programming-based parameter tuning into PD-type virtual inertia control of DFIGs

Doubly fed induction generators (DFIGs) are widely used in wind power generation. For controlling DFIGs to maintain network frequency within a safety range, the proportional-derivative (PD) type virtual inertia controllers (VIC) are used in the active power control of DFIGs. However, as is well known, wind power generation conditions change directly with wind conditions in nature. Such changes create great challenge for the VIC design and actually force the control designs to go beyond the traditional problem formulation of using explicit objective functions associated with specific optimality. Controller parameter tuning thus necessarily becomes a part of the controller design. In this paper, we propose an approximate dynamic programming (ADP) structure for online tuning of the PD type virtual inertia controller parameters. The proposed ADP structure naturally takes into account the PD control into design objective and provides the PD controller with online parameter tuning capability through learning. Design and implementation details of the proposed methodology, including neural network weight initialization, design of the reinforcement signal, data preprocessing, and a bound on the online tuned parameters are discussed in this paper. Simulation studies carried out on the Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) software are used to demonstrate the effectiveness and efficiency of the proposed ADP-based online VIC parameter tuning methodology.