Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of Clone Detection Tools

: Code clones are code portions which are similar in syntax or semantics. Copy-paste activity is the main reason for introducing clones in a software system. These clones must be identified and removed from a system to improve the quality of a software system. Various clone detection tools have been proposed that provide assistance to professionals in identifying code clones and once identified clones can be removed from software systems. These clone detection tools implement different clone detection techniques and have different approach in detection of clones. This study presents an investigation of clone detection tools to understand the performance of each tool and to judge the usefulness and accuracy of clone detection tools. This study can be helpful while making a selection of a particular tool for detection of clones in a software system.
Seizure-Induced Neuronal Injury: Vulnerability to Febrile Seizures in an Immature Rat Model

Febrile seizures are the most common seizure type in young children. Whether they induce death of hippocampal and amygdala neurons and consequent limbic (temporal lobe) epilepsy has remained controversial, with conflicting data from prospective and retrospective studies. Using an appropriate-age rat model of febrile seizures, we investigated the acute and chronic effects of hyperthermic seizures on neuronal integrity and survival in the hippocampus and amygdala via molecular and neuroanatomical methods. Hyperthermic seizures–but not hyperthermia alone–resulted in numerous argyrophilic neurons in discrete regions of the limbic system; within 24 hr of seizures, a significant proportion of neurons in the central nucleus of the amygdala and in the hippocampal CA3 and CA1 pyramidal cell layer were affected. These physicochemical alterations of hippocampal and amygdala neurons persisted for at least 2 weeks but were not accompanied by significant DNA fragmentation, as determined by in situend labeling. By 4 weeks after the seizures, no significant neuronal dropout in these regions was evident. In conclusion, in the immature rat model, hyperthermic seizures lead to profound, yet primarily transient alterations in neuronal structure.
Automatic Color Palette Creation from Words

We present an automatic framework to extract color palettes from words. This is a novel approach in comparison to existing solutions, e.g. manual creation or extraction from images. The associations between words and colors are deduced from a large database of 6 million tagged images using a scalable data-mining technique. The palette creation can be constrained by the user to achieve a desired hue template. We first focus on single words and then extend to entire texts. We compare our results against Adobe Kuler, a widely used online platform of manually created color palettes. We show that our approach performs slightly better than its non-automatic counterpart in terms of user’s preference rankings. This is a good result because our method is fully automatic whereas Kuler relies on users’ palettes that are manually created and annotated.
A Comparison between a Combined Exercise and Recreation Therapy Intervention and an Exercise Only Intervention in Post-Treated Breast Cancer Patients

This study investigated the effects of combining exercise and recreation therapy as a comprehensive intervention to mitigate breast cancer treatment side effects. Fourteen post treated breast cancer patients were randomly assigned to either an exercise only (EX only) or exercise + recreation therapy (EX + RT) group. The EX only group participated in an individualized exercise prescription 3 days/week for eight weeks. The EX + RT group received the same exercise prescription plus an additional 30 minutes of recreation therapy (Biofeedback) 3 days/week for eight weeks. The results revealed no significant differences in the changes in VO 2max or fatigue between the EX + RT and EX only groups. There was, however, a significant difference in the changes in quality of life (QOL) between groups (p=.009). This finding supports the benefits of combining exercise and recreation therapy as a well rounded intervention in the management of breast cancer patient QOL. iii ACKNOWLEDGEMENTS In my six years of undergraduate and graduate work at UNC-Chapel Hill, this was by far the most challenging project that I had the pleasure of undertaking. Yet as demanding as this thesis was, and despite the numerous times that I wished I had chosen another career path, I truly enjoyed it. I learned so much and am indebted to so many people for helping me along the way. First, I would like to thank the love of my life, my wife Katie. Thanks for all of your love, support, patience, and of course…the homemade mac & cheese. I really needed it on those long nights that were my literature review. Also, without you, I don't think I would have been able to edit my power point presentations for my proposal or defense. I am, after all, computer illiterate. Thanks to my mom and dad as well, Connie and Big Jamie, for raising me to be the good ole country boy that I am today. Also, thanks for helping pay me pay off my student loans – only $15,000 to go! To Abby and Mika, my two sisters, keep studying hard in school and make the right choices in life. I know you both will. To John and Chris, thanks for being the best in-laws anyone could hope for (even though you two pull for FSU, you are forgiven). John, without your help, I'd still be trying to figure out how to affix page numbers this very document. …
Implementation of message-passing algorithms for the acquisition of spreading codes

A new technique to acquire pseudo-noise (PN) sequences has been recently proposed in [1] and [2]. It is based on the paradigm of iterative message passing (iMP) to be run on loopy graph. This technique approximates the maximum-likelihood (ML) estimator, providing a sub-optimal algorithm that searches all possible code phases in parallel, at low complexity and fast acquisition time. This work is addressed to the design of the architecture of an iMP detector, following the implementation methodologies typical of standard low-density parity-check (LDPC) decoders, and demonstrates its benefits in terms of acquisition time and complexity, compared with standard techniques.
Comparative Quality Estimation for Machine Translation. An Application of Artificial Intelligence on Language Technology using Machine Learning of Human Preferences

In this thesis we focus on Comparative Quality Estimation, as the automatic process of analysing two or more translations produced by a Machine Translation (MT) system and expressing a judgment about their comparison. We approach the problem froma supervised machine learning perspective, with the aim to learn from human preferences. As a result, we create the ranking mechanism, a pipeline that includes the necessary tasks for ordering several MT outputs of a given source sentence in terms of relative quality. Quality Estimation models are trained to statistically associate the judgments with some qualitative features. For this purpose, we design a broad set of features with a particular focus on the oneswith a grammatical background. Through an iterative feature engineering process, we investigate several feature sets, we conclude to the ones that achieve the best performance andwe proceed to linguistically intuitive observations about the contribution of individual features. Additionally, we employ several feature selection and machine learning methods to take advantage of these features. We suggest the usage of binary classifiers after decomposing the ranking into pairwise decisions. In order to reduce the amount of uncertain decisions (ties) we weight the pairwise decisions with their classification probability. Through a set of experiments, we show that the ranking mechanism can learn and reproduce rankings that correlate to the ones given by humans. Most importantly, it can be successfully compared with state-of-the-art reference-aware metrics and other known ranking methods for several language pairs. We also apply this method for a hybrid MT system combination and we show that it is able to improve the overall translation performance. Finally, we examine the correlation between common MT errors and decoding events of the phrase-based statistical MT systems. Through evidence from the decoding process, we identify some cases where long-distance grammatical phenomena cannot be captured properly. An additional outcome of this thesis is the open source software Qualitative, which implements the full pipeline of rankingmechanismand the systemcombination task. It integrates a multitude of state-of-the-art natural language processing tools and can support the development of new models. Apart from the usage in experiment pipelines, it can serve as an application back-end for web applications in real-use scenaria.
HUBUNGAN PRESTASI AKADEMIK DAN STRATEGI REGULASI DIRI DALAM BELAJAR PADA MAHASISWA TUNA RUNGU

Prestasi akademik (IPK) diuniversitas dianggap sangat penting karena merupakan salah satu syarat dalam karir mahasiswa yang telah lulus atau menjadi pertimbangan untuk melanjutkan pendidikan dijenjang lebih tinggi. Prestasi akademik dapatd ipengaruhi oleh beberapa faktor, salah satunya adalah strategi regulasi diri dalam belajar. Penggunaan strategi regulasi diri dalam belajar bagi mahasiswa tunarungu sangat penting. Hal tersebut dikarenakan mahasiswa tunarungu memiliki hambatan kemampuan pendengarannya, padahal proses pembelajaran diuniversitas banyak dilakukan secara verbal. Penelitian ini menggunakan teknik sampling snowball dengan 33 partisipan mahasiswa tunarungu dari berbagai universitas yang berbeda akreditasi, fakultas, dan semester. Alat ukur yang digunakan adalah Academic Self-Regulation of Learning Scale(A-SRL-S) yang ikembangkan oleh Magno (2010) berdasarkan teori regulasi diri dalam belajar dari Zimmerman. Hasil penelitian menunjukkan bahwa tidak terdapat hubungan antara prestasi akademik dan strategi regulasi diri dalam belajar. Tampaknya, terdapat factor lain yang dapat mempengaruhi prestasi akademik, yaitu factor internal (kondisi fisik atau kesehatan mahasiswa saat mengikuti proses belajar, aspek kecerdasan, bakat atau kemampuan potensial, minat belajar, dan motivasi mahasiswa) dan eksternal (lingkungan sosial dan lingkungan non-sosial). Saran pada penelitis elanjutnya adalah untuk mengeksplorasi lebih dalam faktor-faktor lain yang dapat mempengaruhi prestasi akademik pada mahasiswa tunarungu.
Human Detection in Images via Piecewise Linear Support Vector Machines

Human detection in images is challenged by the view and posture variation problem. In this paper, we propose a piecewise linear support vector machine (PL-SVM) method to tackle this problem. The motivation is to exploit the piecewise discriminative function to construct a nonlinear classification boundary that can discriminate multiview and multiposture human bodies from the backgrounds in a high-dimensional feature space. A PL-SVM training is designed as an iterative procedure of feature space division and linear SVM training, aiming at the margin maximization of local linear SVMs. Each piecewise SVM model is responsible for a subspace, corresponding to a human cluster of a special view or posture. In the PL-SVM, a cascaded detector is proposed with block orientation features and a histogram of oriented gradient features. Extensive experiments show that compared with several recent SVM methods, our method reaches the state of the art in both detection accuracy and computational efficiency, and it performs best when dealing with low-resolution human regions in clutter backgrounds.
Tangled Splines

Extracting shape information from object boundaries is a well studied problem in vision, and has found tremendous use in applications like object recognition. Conversely, studying the space of shapes represented by curves satisfying certain constraints is also intriguing. In this paper, we model and analyze the space of shapes represented by a 3D curve (space curve) formed by connecting n pieces of quarter of a unit circle. Such a space curve is what we call a Tangle, the name coming from a toy built on the same principle. We provide two models for the shape space of n-link open and closed tangles, and we show that tangles are a subset of trigonometric splines of a certain order. We give algorithms for curve approximation using open/closed tangles, computing geodesics on these shape spaces, and to find the deformation that takes one given tangle to another given tangle, i.e., the Log map. The algorithms provided yield tangles upto a small and acceptable tolerance, as shown by the results given in the paper.
Genetic Network Programming with rules

Genetic network programming (GNP) is an evolutionary approach which can evolve itself and find the optimal solutions. As many papers have demonstrated that GNP which has a directed graph structure can deal with dynamic environments very efficiently and effectively. It can be used in many areas such as data mining, forecasting stock markets, elevator system problems, etc. In order to improve GNPpsilas performance further, this paper proposes a method called GNP with Rules. The aim of the proposal method is to balance exploitation and exploration, that is, to strengthen exploitation ability by using the exploited information extensively during the evolution process of GNP. The proposal method consists of 4 steps: rule extraction, rule selection, individual reconstruction and individual replacement. Tile-world was used as a simulation environment. The simulation results show some advantages of GNP with Rules over conventional GNPs.
Breaking Off Engagement: Readers' Cognitive Decoupling as a Function of Reader and Text Characteristics

Engagement during reading can be measured by the amount of time readers invest in the reading process. It is hypothesized that disengagement is marked by a decrease in time investment as compared with the demands made on the reader by the text. In this study, self-paced reading times for screens of text were predicted by a text complexity score called formality; formality scores increase with cohesion, informational content/genre, syntactic complexity, and word abstractness as measured by the Coh-Metrix text-analysis program. Cognitive decoupling is defined as the difference between actual reading times and reading times predicted by text formality. Decoupling patterns were found to differ as a function of the serial position of the screens of text and the text genre (i.e., informational, persuasive, and narrative) but surprisingly not as a function of reader characteristics (reading speed and comprehension). This underscores the importance of mining text characteristics in addition to individual differences and task constraints in understanding engagement during reading.
DroidSearch: A tool for scaling Android app triage to real-world app stores

The Android platform now features more than a million apps from thousands of developers. This abundance is convenient, as it caters to almost every need. But users and researchers also worry about the security and trustworthiness of these apps. While precise program-analysis tools are helpful in this context, unfortunately they do not scale to the large number of apps present in current app stores. In this work we thus present DroidSearch, a search engine that aids a multi-staged analysis in which fast pre-filtering techniques allow security experts to quickly retrieve candidate applications that should be subjected to further automated and/or manual analysis. DroidSearch is supported by DroidBase, a middleware and back-end database which associates apps with metadata and the results of lightweight analyses on bytecode and configuration files that DroidBase automatically manages and executes. Experiments on more than 235,000 applications from six different application stores including Google Play reveal many interesting findings. For instance, DroidSearch identifies 40 known malware applications in Google Play and detects over 35,000 applications that use both http and https connections for accessing the same resources, effectively rendering the https protection ineffective. It also reveals 11,995 applications providing access to potentially sensitive data through unprotected content providers.
Who's more creative, experts or the crowd?

Prior literature has indicated a remarkable change in the role of the crowd. Gradually, the crowd, in the process of interacting with firms, is no longer limited to providing demand information alone; rather, the crowd sometimes start participating either partially or fully in product innovation. Such change is based on an underlying assumption that the crowd (or customers) would provide creative thinking and thus help firms with product innovation. However, since this assumption has not been formally tested, this paper explores the difference between experts and the crowd in terms of generating creative ideas for products. By launching two experiments on Amazon‟s Mechanical Turk platform and analyzing the resulting data, I found that a difference does exist and is significantly moderated by the extent of information asymmetry embedded across different products.
PepNovo: de novo peptide sequencing via probabilistic network modeling.

We present a novel scoring method for de novo interpretation of peptides from tandem mass spectrometry data. Our scoring method uses a probabilistic network whose structure reflects the chemical and physical rules that govern the peptide fragmentation. We use a likelihood ratio hypothesis test to determine whether the peaks observed in the mass spectrum are more likely to have been produced under our fragmentation model than under a model that treats peaks as random events. We tested our de novo algorithm PepNovo on ion trap data and achieved results that are superior to popular de novo peptide sequencing algorithms. PepNovo can be accessed via the URL http://www-cse.ucsd. edu/groups/bioinformatics/software.html.
Snr Analysis of Dmt Using the Parametric Channel Model

Multicarrier modulation schemes are attractive for transceiver lter design on static frequency selective channels. When the channel is time varying, a straightforward application of such schemes requires channel tracking. If the time variation is relatively slow, it is likely that conventional DMT channel partitioning will not incur drastic reduction in signal to noise ratios (SNRs). We provide an analytic method for determining the SNR on each tone, clearly separating the eeects of intercarrier interference (ICI) and additive noise. We also provide the distribution of SNR as a function of Rayleigh fading. 1
ATOMIC MODELS OF DISLOCATIONS FOR SI AND GAAS

An atomic model of dislocations in face centered cubic crystals with a two- atom basis is proposed. This model has the standard cubic anisotropic elasticity as its continuum limit, and its main ingredients are the elastic stiffness constants and a di- mensionless periodic function that restores the translation invariance of the crystal and influences the dislocation size. Possible applications include semiconductor materials such as silicon and GaAs.
Dynamic scene models for incremental, long-term, appearance-based localisation

In this paper we present a new appearance-based localisation system that is able to deal with dynamic elements in the scene. By independently modelling the properties of local features observed in a scene over long periods of time, we show that feature appearances and geometric relationships can be learned more accurately than when representing a location by a single image. We also present a new dataset consisting of a 6 km outdoor path traversed once per month for a period of 5 months, which contains several challenges including short-term and long-term dynamic behaviour, lateral deviations in the path, repetitive scene appearances and strong illumination changes. We show superior performance of the dynamic mapping system compared to state-of-the-art techniques on our dataset.
XDKinect: development framework for cross-device interaction using kinect

Interactive systems set in multi-device environments continue to attract increasing attention, prompting researchers to experiment with emerging technologies. This paper presents XDKinect--a lightweight framework that facilitates development of cross-device applications using Kinect to mediate user interactions. The main benefits of XDKinect include its simplicity, adaptability and extensibility based on a flexible client-server architecture. Our framework features a time-based API to handle full-body interactions, a multi-modal API to capture gesture and speech commands, an API to utilise proxemic awareness information, a cross-device communication API, and a settings API to optimise for particular application requirements. A study with developers was conducted to investigate the potential of these features in terms of ease of use, effectiveness and possible use in the future. We show several example applications of XDKinect, as well as discussing advantages and limitations of our framework as revealed by our user study and experiments.
A robust numerical scheme for the simulation of nonlinear convection–diffusion–reaction equation

Abstract In this article, the polynomial based differential quadrature method is used to develop a numerical scheme for solving convection–diffusion–reaction model with a general reaction term. The numerical scheme is found applicable to a wide set of problems including diffusion, convection–diffusion and diffusion–reaction. The validation of the method is performed through simulations of Newell-Whitehead, Burger-Fisher, and Burger-Huxley equations. The proposed numerical method is found better than many numerical methods presented in the literature. Vector form of numerical scheme is presented to implement algorithm efficiently. The compatibility, error and computational complexity of the numerical scheme are studied in detail.
Consumers' Privacy Concerns toward Using Location-Based Services: An Exploratory Framework and Research Proposal

Privacy concerns associated with the use of Location-Based Services (LBS) may ultimately prevent consumers from gaining the ‘anytime anywhere’ convenience. Through a psychological control lens, we examine whether individual difference variables such as locus of control (LOC) could have moderating effects on the relationship between privacy concern and three privacy assurance mechanisms in the LBS context. The paper develops a preliminary research model which conceptualizes the moderating effects of LOC by extending Xu and Teo (2004)’s research model. With an explicit focus on LOC, this study will not only add an important piece of information to our understanding of consumers’ reactions to LBS but also can help frame the ongoing policy and scholarly debate surrounding the relative effectiveness of technology, industry self-regulation and government legislation in ensuring consumers’ privacy. We believe that our findings will be able to offer practical implications for the various players in the LBS landscape: merchants, wireless service providers, wireless device manufacturer, privacy advocates and legislators.
Recovering and analyzing 3D models of branched structures using computer vision: a review

With the recent developments of computer vision and automated systems in medical imaging or agriculture, there has been, in the last years, the necessity to adopt methods able to analyze and reconstruct three dimensional network structures, such as blood vessels, plant architecture or root structures, given one or more two dimensional images of the observed scene. This paper reviews recent work on this problem. Each of the examples cited designs a new method, each of which is different from previous methods already proposed. In this paper we review some of the developed methods and, due to the evident heterogenity of the methods, we classify them according to whether they apply a model to two dimensional details in images, or methods which recover a three dimensional representation (point cloud, or mesh), and then fit a network structure model to this representation.