Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple-Implementation Testing of Supervised Learning Software

Machine Learning (ML) algorithms are now used in a wide range of application domains in society. Naturally, software implementations of these algorithms have become ubiquitous. Faults in ML software can cause substantial losses in these application domains. Thus, it is very critical to conduct effective testing of ML software to detect and eliminate its faults. However, testing ML software is difﬁcult, partly because producing test oracles used for checking behavior correctness (such as using expected properties or expected test outputs) is challenging. In this paper, we propose an approach of multiple-implementation testing to test supervised learning software, a major type of ML software. In particular, our approach derives a test input’s proxy oracle from the majority-voted output running the test input of multiple implementations of the same algorithm (based on a pre-deﬁned percentage threshold). Our approach reports likely those test inputs whose outputs (produced by an implementation under test) are different from the majority-voted outputs as failing tests. We evaluate our approach on two highly popular supervised learning algorithms: k-Nearest Neighbor (kNN) and Naive Bayes (NB). Our results show that our approach is highly effective in detecting faults in real-world supervised learning software. In particular, our approach detects 13 real faults and 1 potential fault from 19 kNN implementations and 16 real faults from 7 NB implementations. Our approach can even detect 7 real faults and 1 potential fault among the three popularly used open-source ML projects (Weka, RapidMiner, and KNIME).
Optimal Design of Single Factor cDNA Microarray experiments and Mixed Models for Gene Expression Data

(ABSTRACT) Microarray experiments are used to perform gene expression profiling on a large scale. E-and A-optimality of mixed design was established for experiments with up to 26 different varieties and with the restriction that the number of arrays available is equal to the number of varieties. Because the IBD setting only allows for a single blocking factor (arrays), the search for optimal designs was extended to the Row-Column Design (RCD) setting with blocking factors dye (row) and array (column). Relative efficiencies of these designs were further compared under analysis of variance (ANOVA) models. We also compared the performance of classification analysis for the interwoven loop and the replicated reference designs under four scenarios. The replicated reference design was favored when gene-specific sample variation was large, but the interwoven loop design was preferred for large variation among biological replicates. We applied mixed model methodology to detection and estimation of gene differential expression. For identification of differential gene expression, we favor contrasts which include both variety main effects and variety by gene interactions. In terms of t-statistics for these contrasts, we examined the equivalence between the one-and two-step analyses under both fixed and mixed effects models. We analytically established conditions for equivalence under fixed and mixed models. We investigated the difference of approximation with the two-step analysis in situations where equivalence does not hold. The significant difference between the one-and two-step mixed effects model was further illustrated through Monte Carlo simulation and three case studies. We implemented the one-step analysis for mixed models with the ASREML software. Acknowledgments I would like to thank Dr. Ina Hoeschele and Dr. Keying Ye, who have been there for me every step of the way, teaching, encouraging and helping. I greatly appreciate the time and effort that they have given to me and to my work, I have enjoyed working with them. What they have taught me in the last few years will benefit me all my life, and I am grateful to them forever. I would also like to recognize the contribution of my committee members, Dr. am so thankful to them for agreeing to serve on my committee and for those helpful and constructive suggestions. I would also like to thank Dr. John P. Morgan, my former committee member, for those stimulating discussions about design of experiment with block size two and for providing references that have greatly improved this work.
Head-Driven PCFGs with Latent-Head Statistics

Although state-of-the-art parsers for natural language are lexicalized, it was recently shown that an accurate unlexicalized parser for the Penn tree-bank can be simply read off a manually refined tree-bank. While lexicalized parsers often suffer from sparse data, manual mark-up is costly and largely based on individual linguistic intuition. Thus, across domains, languages, and tree-bank annotations, a fundamental question arises: Is it possible to automatically induce an accurate parser from a tree-bank without resorting to full lexicalization? In this paper, we show how to induce head-driven probabilistic parsers with latent heads from a tree-bank. Our automatically trained parser has a performance of 85.7% (LP/LR F1), which is already better than that of early lexicalized ones.
Myocardial discontinuities: a substrate for producing virtual electrodes that directly excite the myocardium by shocks.

BACKGROUND Theoretical models suggest that an electrical stimulus causes regions of depolarization and hyperpolarization on either side of a myocardial discontinuity. This study determined experimentally whether an artificial discontinuity gives rise to an activation front in response to an electrical stimulus, consistent with the creation of such polarized regions. METHODS AND RESULTS After a thoracotomy in six dogs, a 504-unipolar-electrode plaque was sutured to the right ventricular epicardium to map activations. From a line electrode parallel to one side of the plaque, 10 S1 stimuli were delivered, followed by S2 and S3 stimuli (S1S1, S1S2, S2S3 interval=300 ms). S1 and S3 stimuli were 25 mA; 5-ms S2 stimuli of both polarities were initially 25 mA and increased in 25 mA increments. The plaque was removed, and a transmural incision was made through the ventricular wall in the middle of the mapped region and sutured closed. The plaque was replaced and the stimulation protocol repeated. Before the incision, S2 stimuli directly activated tissue only near the stimulation site. An activation front arose at the border of the directly activated region and propagated across the plaque. As the S2 stimulus strength was increased, the size of the directly activated region increased. After the incision, sufficiently large S2 stimuli caused direct activation of tissue adjacent to the transmural incision as well as at the stimulation site. Activation fronts that arose adjacent to the transmural incision either propagated proximally toward the stimulation site and collided with the activation front originating from the stimulation wire or propagated distally away from the incision. Minimum S2 stimulus strengths activating areas adjacent to the incision were only 45+/-14% (cathode) and 39+/-18% (anode) of the strengths required to directly activate the same area before the incision was formed (P<.05). CONCLUSIONS Myocardial discontinuities can give rise to activation fronts after a stimulus, suggesting the presence of polarized regions adjacent to the discontinuity.
Delay Analysis in Thermal-Aware Hard Real-Time Computing

In this paper, we study thermal-aware hard realtime computing, where real-time guarantees must be met with out exceeding safe temperature levels within the processor. Dy namic speed scaling is one of the major techniques to manage power s o as to maintain safe temperature levels. As example, we adopt a simple reactive speed control technique in our work. We design a methodology to perform delay analysis for general task arrivals under reactive speed control with First-In-First-Out (FIFO), Static-Priority (SP), and Earliest-Deadline-First (EDF) scheduling. As a special case, we obtain a closed-form delay formula for the leaky-bucket task arrival model. Our data show how simple reactive speed control can decrease the delay of t asks compared with any constant-speed scheme.
Reduced-complexity iterative multi-user detection for turbo coded DS/CDMA systems

A low-complexity iterative multi-user receiver is derived for turbo coded synchronous DS/CDMA systems. The receiver performs two successive soft output decisions, achieved by a soft-input soft-output (SISO) multi-user detector based on probabilistic data association (PDA) and a bank of single-user SISO turbo channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration. The simulations show that the proposed iterative receiver structure offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached.
Hierarchical variance analysis for analog circuits based on graph modelling and correlation loop tracing

Process variations play an increasingly important role on the success of analog circuits. State-of-the-art analog circuits are based on complex architectures and contain many hierarchical layers and parameters. Knowledge of the parameter variances and their contribution patterns is crucial for a successful design process. This information is valuable to find solutions for many problems in design, design automation, testing, and fault tolerance. We present a hierarchical variance analysis methodology for analog circuits. In the proposed method, we make use of previously computed values whenever possible so as to reduce computational time. Experimental results indicate that the proposed method provides both accuracy and computational efficiency when compared with prior approaches.
The prevention of spontaneous apoptosis of follicular lymphoma B cells by a follicular dendritic cell line: involvement of caspase-3, caspase-8 and c-FLIP

Several observations point to a crucial role of microenvironment in the natural history of low-grade B-cell neoplasms. This study shows that the spontaneous apoptosis of follicular lymphoma cells is partially prevented by a follicular dendritic cell line, thus confirming that cellular microenvironment may contribute to the development and/or progression of follicular lymphoma cells. Background Follicular lymphoma, the neoplastic counterpart of germinal center B cells, typically recapitulates a follicular architecture. Several observations point to the crucial role of the cellular microenvironment in the development and/or progression of follicular lymphoma cells in vivo. The aim of our study was to characterize the spontaneous apoptosis of follicular lymphoma cells in vitro, and the modulation of this apoptosis by follicular dendritic cells. Design and Methods We used a cell line derived from follicular dendritic cells to model the functional interactions of these cells and lymphoma cells in co-culture. Follicular lymphoma cells were isolated from tissue biopsies. Apoptosis was quantified by flow cytometry and apoptotic pathways were investigated by western blotting. Results The spontaneous apoptosis of follicular lymphoma cells in vitro involves the activation of caspases-3 and -8 but not of caspase-9, occurs despite persistent high levels of BCL-2 and MCL-1, and is associated with down-regulation of c-FLIPL. Spontaneous apoptosis of follicular lymphoma cells is partially prevented by co-culture with the follicular dendritic cells, which prevents activation of caspase-8, caspase-3 and induces an upregulation of c-FLIPL. Using neutralizing antibodies, we demonstrated that interactions involving CD54 (ICAM-1), CD106 (VCAM-1) and CD40 are implicated in this biological process. Conclusions Follicular dendritic cells constitute a useful tool to study the functional interactions between follicular lymphoma cells and follicular dendritic cells in vitro. Understanding the molecular mechanisms involved in these protective interactions may lead to the identification of therapeutic agents that might suppress the survival and growth of follicular lymphoma cells.
A method of automatic integration test case generation from UML-based scenario

One key to success for high quality enterprise information systems development is to validate the customers' requirements sufficiently at the early stage. Scenarios are an effective means to an end because they make it possible to represent various situations of system usage. Most scenarios are defined by using a natural language or such a formal language as Unified Modeling Language (UML) and describe normal, alternative, and exceptional service flows from the point of view of system usage. As a result, scenarios make it easy for the customers to confirm their requirements intuitively because of the concreteness. On the other hand, based on the V-model, which is well-known software development process and denotes the correspondence of requirement analysis stage to integration test stage, it is desirable that the testers should test the system by using the test cases derived from the validated scenarios. We have proposed a UML-based requirements analysis (RA) model with automatic prototype system generation for enterprise Web application development. This paper proposes a way to efficiently create reliable test cases from the scenarios that have been validated by the customers using the prototype system which was generated by the RA model.
The sympathetic nervous system in white adipose tissue regulation

Sympathetic stimulation has long been recognized to mobilise fatty acids from white adipose tissue. However, it is now apparent that adipose tissue is not only concerned with energy storage as fat, but is a major endocrine and secretory organ. This change has resulted from the identification of leptin as a hormone of energy balance secreted by white adipose tissue. The sympathetic system is a key regulator of leptin production in white fat. Sympathomimetic amines, cold exposure or fasting (which lead to sympathetic stimulation of white fat), decrease ob gene expression in the tissue and leptin production. On the other hand, sympathetic blockade often increases circulating leptin and ob gene expression, and it is postulated that the sympathetic system has a tonic inhibitory action on leptin synthesis. In rodents this action is through stimulation of b3-adrenoceptors. The adrenal medulla (as opposed to the direct sympathetic innervation) has been thought to play only a minor role in the catecholaminergic regulation of white adipose tissue. However, in rodents responses of the leptin system to adrenergic blockade vary with the method used. Changes in leptin and ob gene expression are considerably less using methods of blockade that only effect the terminal adrenergic innervation, rather than medullary secretions as well. Stimulation of the leptin system increases sympathetic activity and hence metabolic activity in many tissues. As well as leptin, other (but not all) secretions from white adipose tissue are subject to sympathetic regulation. In obesity the sympathetic sensitivity of adipose tissue is reduced and this factor may underlie the dysregulation of leptin production and other adipose tissue secretions.
Policy developments in the area of old-age pensions: the Open Method of Coordination: a tool to influence national pension policies?

Demographic change is a threat many countries face (Eckardt, 2005) and most pension systems are functioning in a way in which those who work pay the retirement provision for those who are retired. The circumstance of demographic change, so the trend that people tend to get older and fewer babies are born (European Commission, n.d.), may be seen as a call to adjust pension systems. Moreover, as we live in times of greater mobility concerning labour, especially across the European Union (EU), it is of great importance to know in how far pension regulations among the member states differ. This greater mobility can amongst others be explained by the four freedoms: free movement of people, goods, services and capital. These freedoms established by the European Union and its member states facilitate that people start working in other countries than their origin and thus are subject to different pension policies. That is why this study aims at developing an insight on how social policies within the member states have changed over the last decade and if the influence of European governance changed them in a manner that pension policy is regulated in a similar or even equal way. Hence, this thesis tries to answer the question: “What is the role of the Open Method of Coordination in fostering Europeanization in the area of old-age pensions in the United Kingdom, Germany and Sweden in the period between 1999 and 2010? ” The selection of three countries is based on the welfare state typology of Esping-Andersen, which are liberal, conservative and social. The United Kingdom (UK) represents the liberal welfare state, Germany the conservative and Sweden the social. The Open Method of Coordination (OMC) on pensions and the objectives of the Laeken Summit are outlined within the paper. The OMC on pensions required the member states to provide a National Strategy Report (NSR) for 2002 and 2005. In the analytical part, the paper is limited to two goals of the Laeken Summit (objective 5 and 10). Moreover, National Reform Programmes (NRPs) are used for the analysis. With the help of the theory of Europeanization it was found out that the OMC on pensions drives Europeanization of national pension policies a little bit further. However, it turned out that this research field is very complex and due to the fact that the OMC on pensions is rather vague, giving an explicit answer is difficult. In sum, the UK, Germany and Sweden largely argue that changes in the policy area of old-age pensions are done mostly because of demographic changes and not because of the OMC as such.
Local gradient histogram features for word spotting in unconstrained handwritten documents

In this article we propose a local descriptor for an unconstrained handwritten word spotting task. The presented features are inspired by the SIFT keypoint descriptor, widely employed in computer vision and object recognition, but underexploited in the handwriting recognition field. In our approach, a sliding window moves from left to right over a word image. At each position, the window is subdivided into cells, and in each cell a histogram of orientations is accumulated. Experiments using two different word spotting systems hidden Markov models and dynamic time warping demonstrate a very significant improvement when using the proposed features with respect to the state-of-the-art ones.
Face Tracking in the Compressed Domain

A compressed domain generic object tracking algorithm offers, in combination with a face detection algorithm, a low-compu-tational-cost solution to the problem of detecting and locating faces in frames of compressed video sequences (such as MPEG-1 or MPEG-2). Objects such as faces can thus be tracked through a compressed video stream using motion information provided by existing forward and backward motion vectors. The described solution requires only low computational resources on CE devices and offers at one and the same time sufficiently good location rates.
Constructions of E_{vc} and E_{fbc} for groups acting on CAT(0) spaces

If G is a group acting properly by semisimple isometries on a proper CAT(0) space X, then we build models for the classifying spaces E_{vc} and E_{fbc} under the additional assumption that the action of G has a well-behaved collection of axes in X. (This hypothesis is described in the paper.) We conjecture that the latter hypothesis is satisfied in a large range of cases. Our classifying spaces resemble those created by Connolly, Fehrman, and Hartglass for crystallographic groups G.
Phoneme and word based model for tamil speech recognition using GMM-HMM

Speech is the standard means of communication among people. Automatic Speech Recognition (ASR) applications facilitate the users to interact with machines through speech and perform their tasks effortlessly. Speech Recognition applications in native languages will enable illiterate and semi-illiterate people to use computer services without any/little knowledge to operate computers and to lead better life. In the proposed work, speaker independent isolated- phoneme and word recognition systems have been developed for the Indian regional language Tamil. The Hidden Markov Tool Kit (HTK) was used for developing speaker independent phoneme and word based Tamil speech recognition system. The work involves main tasks like Feature Extraction, Acoustic Model Building and Decoding. Mel-Frequency Cepstral Coefficients (MFCC) is extracted from the speech utterances and Hidden Markov Model (HMM) used to build the acoustic model. In building acoustic model, Multivariate Gaussian Mixture Model with different number of components is used to estimate the state emission probabilities and finally Viterbi Decoder employed to recognize the test speech utterances. A small vocabulary of 50 words which are collected from 10 native speakers of Tamil language was used to build and test the model. The performance of both phoneme and word based models have been analyzed and the recognition accuracy and word error rate of the models are discussed.
Multivariate Stochastic Volatility Models with Dynamic Correlations : A Monte Carlo Particle Filtering Approach

This paper proposes Multivariate Stochastic Volatility models with Dynamic Correlations (MSVDC) based on the Monte Carlo particle filter, proposed by Kitagawa (1996) and Gordon et al. (1993), and a self-organizing state space model, proposed by Kitagawa (1998) and Yano (2008). In our MSVDC, we estimate dynamic correlations of system errors and measurement errors. In empirical analysis, we estimate the time-varying interaction of credit risk (credit default swap) and market risk (stock price index) using MSVDC. We conclude the correlations of returns and volatilities make higher in financial crises. Our finding indicates that it is inadequate to estimate the interaction of credit and market risks based on invariant parameters.