Miracle-dz/UniFAR-FTUs huggingface dataset:
Reengineering inspection

A 20-year-old inspection technique has served developers well in the quest for software quality improvement. But radical changes are on the horizon that may seriously steer the future of formal review. D espite many advances in automated verification and validation, human review of software artifacts is still a uniquely important method for software quality improvement. Unlike automated methods such as testing, review does not require an executable or formally specified artifact, enabling quality improvement on upstream work products such as initial requirements documents. This has significant economic implications , since studies show that defects can be one to two orders of magnitude less costly to remove from initial requirements documents than from implemented systems after distribution to the customer. Moreover, review is effective for discovering certain soft, but nevertheless costly, defects such as logically correct but poorly structured code. Indeed, review has a unique educational capability: The process of analyzing and critiquing software artifacts produced by others is a potent method for learning about languages, design techniques, application domains, and so forth. Software review encompasses a broad spectrum of activities, from informal, individual desk checking to review using computer-mediated groupware environments with built-in process models. Formal technical review (FTR) is an umbrella term for review methods involving a structured encounter where a group of technical personnel analyzes an artifact in order to improve both the quality of the product and the review process. Starting in 1976, when Michael Fagan published his seminal article [2], the Fagan Inspection method (including such close variants as Tom Gilb's Inspection [3]) has come to dominate both the theory and practice of review. Indeed, many researchers and practitioners equate the terms " inspection " and " formal technical review. " Inspection and its variants have not enjoyed unwarranted popularity. In addition to Fagan's reports of cost-effective quality improvement at IBM, inspection-based techniques at Hewlett-Packard were calculated to yield a cost savings of $21 million [4]. Others have also reported favorable cost-benefit analyses for inspection. Despite a consistent stream of positive findings over 20 years, industry adoption of inspection appears to remain quite low, although no definitive data exists. For example, an informal USENET survey we conducted found that 80% of 90 respondents practiced inspection irregularly or not at all. Some industry practitioners have found adoption and practice of inspection-based review to be difficult , costly, ineffective, and/or excessively time consuming, despite the prospect of quality …
Inverse Problems in Imaging Systems and the General Bayesian Inversion Frawework

In this paper, first a great number of inverse problems which arise in instrumentation, in computer imaging systems and in computer vision are presented. Then a common general forward modeling for them is given and the corresponding inversion problem is presented. Then, after showing the inadequacy of the classical analytical and least square methods for these ill posed inverse problems, a Bayesian estimation framework is presented which can handle, in a coherent way, all these problems. One of the main steps, in Bayesian inversion framework is the prior modeling of the unknowns. For this reason, a great number of such models and in particular the compound hidden Markov models are presented. Then, the main computational tools of the Bayesian estimation are briefly presented. Finally, some particular cases are studied in detail and new results are presented.
Exact Subspace Clustering in Linear Time

Subspace clustering is an important unsupervised learning problem with wide applications in computer vision and data analysis. However, the state-of-the-art methods for this problem suffer from high time complexity---quadratic or cubic in $n$ (the number of data instances). In this paper we exploit a data selection algorithm to speedup computation and the robust principal component analysis to strengthen robustness. Accordingly, we devise a scalable and robust subspace clustering method which costs time only linear in $n$. We prove theoretically that under certain mild assumptions our method solves the subspace clustering problem exactly even for grossly corrupted data. Our algorithm is based on very simple ideas, yet it is the only linear time algorithm with noiseless or noisy recovery guarantee. Finally, empirical results verify our theoretical analysis.
GutenTag: an NLP-driven Tool for Digital Humanities Research in the Project Gutenberg Corpus

This paper introduces a software tool, GutenTag, which is aimed at giving literary researchers direct access to NLP techniques for the analysis of texts in the Project Gutenberg corpus. We discuss several facets of the tool, including the handling of formatting and structure, the use and expansion of metadata which is used to identify relevant subcorpora of interest, and a general tagging framework which is intended to cover a wide variety of future NLP modules. Our hope that the shared ground created by this tool will help create new kinds of interaction between the computational linguistics and digital humanities communities, to the benefit of both.
Neuromagnetic correlates of visual motion coherence

In order to characterize cortical responses to coherent motion we use magnetoencephalography (MEG) to measure human brain activity that is modulated by the degree of global coherence in a visual motion stimulus. Five subjects passively viewed two‐phase motion sequences of sparse random dot fields. In the first (incoherent) phase the dots moved in random directions; in the second (coherent) phase a variable percentage of dots moved uniformly in one direction while the others moved randomly. We show that: (i) visual‐motion‐evoked magnetic fields, measured with a whole‐scalp neuromagnetometer, reveal two transient events, within which we identify two significant peaks – the ‘ON‐M220’ peak approximately 220 ms after the onset of incoherent motion and the ‘TR‐M230’ peak, approximately 230 ms after the transition from incoherent to coherent motion; (ii) in lateral occipital channels, the TR‐M230 peak amplitude varies with the percentage of motion coherence; (iii) two main sources are active in response to the transition from incoherent to coherent motion, the human medial temporal area complex/V3 accessory area (hMT+/V3A) and the superior temporal sulcus (STS), and (iv) these distinct areas show a similar, significant dependence of response strength and latency on motion coherence.
VLC: Beyond point-to-point communication

Due to the large growth of mobile communications over the past two decades, cellular systems have resorted to fuller and denser reuse of bandwidth to cope with the growing demand. On one hand, this approach raises the achievable system capacity. On the other hand, however, the increased interference caused by the dense spatial reuse inherently limits the achievable network throughput. Therefore, the spectral efficiency gap between users' demand and network capabilities is ever growing. Most recently, visible light communication has been identified as well equipped to provide additional bandwidth and system capacity without aggregating the interference in the mobile network. Furthermore, energy-efficient indoor lighting and the large amount of indoor traffic can be combined inherently. In this article, VLC is examined as a viable and ready complement to RF indoor communications, and advancement toward future communications. Various application scenarios are discussed, presented with supporting simulation results, and the current technologies and challenges pertaining to VLC implementation are investigated. Finally, an overview of recent VLC commercialization is presented.
Carrots and sticks fail to change behavior in cocaine addiction

Punishment doesn't work in cocaine addicts Addiction is extremely difficult to treat, particularly cocaine use disorder. Animal experiments have led to the concept of drug addiction as abnormal goal-directed learning and habit formation. Ersche et al. found that overtraining with positive reinforcement such as rewards made cocaine-addicted patients less sensitive to the outcome of their actions. In contrast, overtraining on a punishment paradigm had no effect. Thus, habits may determine the behavior of cocaine users. Science, this issue p. 1468 Habits determine behavior in cocaine use disorder, even in the face of aversive consequences. Cocaine addiction is a major public health problem that is particularly difficult to treat. Without medically proven pharmacological treatments, interventions to change the maladaptive behavior of addicted individuals mainly rely on psychosocial approaches. Here we report on impairments in cocaine-addicted patients to act purposefully toward a given goal and on the influence of extended training on their behavior. When patients were rewarded for their behavior, prolonged training improved their response rate toward the goal but simultaneously rendered them insensitive to the consequences of their actions. By contrast, overtraining of avoidance behavior had no effect on patient performance. Our findings illustrate the ineffectiveness of punitive approaches and highlight the potential for interventions that focus on improving goal-directed behavior and implementing more desirable habits to replace habitual drug-taking.
Applications of magnetooptical waveguides in integrated optics

Magnetooptical garnets combine high Faraday rotation with low optical losses in the near infrared region where optical communication via glass fiber is established. In this spectral range garnets are the only materials discussed to realize nonreciprocal devices as optical isolators and circulators. Although such devices are available as microoptical components, practical versions of their integrated counterparts are still lacking. Numerous concepts have been developed theoretically many of which are tested experimentally. This paper presents an overview of the state of the art of the applications of garnet films in integrated optics. Also the technique of combining garnets with semiconductor materials is shortly discussed.
Control research of network servo system based on Smith predictor

Servo motor can be closed-loop controlled through the network, it brings benefits to some long distance control systems. But the network inevitably introduces time delay to the system. To solve this problem, network servo system based on Smith predictor was designed. Control strategy combines the adaptive least mean square (LMS) delay prediction algorithm and Smith compensator can compensate a certain degree of the network delay. Moreover, the combined algorithm is debugged in a real-world system with an interface that developed by the authors. The experiment results show that: in contrast with traditional PID algorithm, PID network servo system with Smith compensator has little effect by network delay. So the method we proposed shows much more robustness and self-adaptability than the traditional PID algorithm.
Optimum-Path Forest : A Novel and Powerful Framework for Supervised Graph-based Pattern Recognition Techniques

We present here a novel framework for graph-based pattern recognition techniques called Optimum-Path Forest (OPF), which has been demonstrated to be superior than traditional supervised pattern recognition techniques, such as Artificial Neural Networks using Multilayer Perceptrons and Support Vector Machines, in terms of both accuracy and execution times. The OPF-based classifiers model the problem of the pattern recognition as a computation of an optimum-path forest in a graph induced by the dataset samples, achieving very good results in complex situations, i.e., in which we have a large amount of overlapped regions. Results in several real and synthetic datasets show the robustness of the OPF-based classifiers against the above ones.
An Improved GAC Model Combining with GNGVF

Geodesic active contour (GAC) model is a common used method for image segmentation. But one drawback of this model is that it's difficult to control the number of iterations and sometimes may produce over-segmentation results. In this paper, the generalized GVF in the normal direction (GNGVF) is proposed, and an improved GAC model which combines GAC with GNGVF is proposed. When the distance between the evolution curves produced by successive iterations is smaller than some given threshold, the on-off function will change and different force will affect. The new force can extend the capture range and stop the curve at the boundary stably avoiding over-segmentation. The experimental results show the curve can converge to boundary well.
Zeeman ratchets: Rectification of spin current via magnetic fields

We investigate the possibility of creating directed spin-polarized currents in a two-dimensional electron gas (2DEG) subject to an inhomogeneous magnetic field and an external adiabatic driving. We thereby generalize concepts of quantum charge ratchets to the case with spin. Due to the Zeeman term in the Hamiltonian, spin-up and -down electrons experience different effective potentials, which can be tailored to achieve net spin currents without corresponding charge currents. We consider ballistic, coherent transport in waveguides defined in a 2DEG, where the magnetic field modulation is induced by ferromagnetic stripes on top of the 2DEG.
Musical improvisation: Multi-scaled spatiotemporal patterns of coordination

When jazz musicians perform an improvisational piece of music their behaviors are not fully prescribed in advance. Nonetheless their actions become so tightly coordinated and their decisions so seamlessly intertwined that the musicians behave as a single synergistic unit rather than a collection of individuals. A fundamental aspect of such musical improvisation is the bodily movement coordination that occurs among the performing musicians, with the embodied interaction of musicians both supporting and constraining musical creativity. Here we consider the ability of pairs of piano players to improvise, to spontaneously coordinate their actions with co-performers. We demonstrate the ability of the time-evolving patterns of inter-musician movement coordination as revealed by the mathematical tools of nonlinear time series analyses to provide a new understanding of what potentiates the novelty of spontaneous musical action. Cross wavelet spectral analysis is applied to the musical movements of pairs of improvising pianists, a method that isolates the strength and patterning of the behavioral coordination across a range of nested time-scales. Additionally, cross-recurrence quantification analysis is applied to the series of notes produced by each musician to assess when and how often they visit the same musical states throughout the improvisation. Revealing the sophistication of the previously unexplored dynamics of movement coordination between improvising musicians is an important step towards understanding how creative musical expressions emerge from the spontaneous coordination of multiple musical bodies.
Organization and Postembryonic Development of Glial Cells in the Adult Central Brain of Drosophila

Glial cells exist throughout the nervous system, and play essential roles in various aspects of neural development and function. Distinct types of glia may govern diverse glial functions. To determine the roles of glia requires systematic characterization of glia diversity and development. In the adult Drosophila central brain, we identify five different types of glia based on its location, morphology, marker expression, and development. Perineurial and subperineurial glia reside in two separate single-cell layers on the brain surface, cortex glia form a glial mesh in the brain cortex where neuronal cell bodies reside, while ensheathing and astrocyte-like glia enwrap and infiltrate into neuropils, respectively. Clonal analysis reveals that distinct glial types derive from different precursors, and that most adult perineurial, ensheathing, and astrocyte-like glia are produced after embryogenesis. Notably, perineurial glial cells are made locally on the brain surface without the involvement of gcm (glial cell missing). In contrast, the widespread ensheathing and astrocyte-like glia derive from specific brain regions in a gcm-dependent manner. This study documents glia diversity in the adult fly brain and demonstrates involvement of different developmental programs in the derivation of distinct types of glia. It lays an essential foundation for studying glia development and function in the Drosophila brain.
Nançay "blind” 21 cm line survey of the Canes Venatici group region

A radio spectroscopic driftscan survey in the 21 cm line with the Nancay decimetric radio telescope of 0.08 steradians of sky in the direction of the constellation Canes Venatici covering a heliocentric velocity range of -350 <V-hel <2350 kms(-1) produced 53 spectral features, which was further reduced to a sample of 33 reliably detected galaxies by extensive follow-up observations. With a typical noise level of rms = 10 mJy after Hanning smoothing, the survey is - depending on where the detections are located with regard to the centre of the beam sensitive to M-HI = 1 - 2 10(8) h(-2)M(.) at 23 h(-1) Mpc and to M-HI = 4 - 8 10(7) h(-2)M(.) throughout the CVn groups. The survey region had been previously examined on deep optical plates by Binggeli et al. (1990) and contains loose groups with many gas-rich galaxies as well as voids. No galaxies that had not been previously identified in these deep optical surveys were uncovered in our HI survey, neither in the groups nor the voids. The implication is that no substantial quantity of neutral hydrogen contained in gas-rich galaxies has been missed in these well-studied groups. All late-type members of our sample are listed in the Fisher & Tully (1981b) optically selected sample of nearby late-type galaxies; the only system not contained in Fisher and Tully's Catalog is the SO galaxy NGC 4203. Within the well-sampled CVn group volume with distances corrected for flow motions, the HI mass function is best fitted with the Zwaan et al. (1997) HI mass function (alpha = -1.2) scaled by a factor of f = 4.5 in account of the locally overdense region.
Beating Henry Higgins at His Own Game : A Markovian Approach to Dialectology

1. Introduction The performance of speech recognition algorithms degrades considerably due to speaker variability. Aside from gender, the largest cause for speaker variability is accent. If the accent of a speaker can be determined automatically, then accent-specific speech recognition models can be used, thereby increasing speech recognition accuracy. In this study, the problem of accent classification from a database of Central New York (CNY), North India (IND), and Singapore (SIN)-native English speakers is considered. Linguists have studied regional accents extensively and have described many features particular to the three regions we are considering [1]. The problem of automatic accent classification has received attention within the last decade. Vonwiller, Blackburn, and King used artificial neural networks (ANN) for automatic accent classification [2]. Hansen and Arslan found that energy, duration, and spectral information are good features for accent detection, and that the most distinct features of accent are at the phonemic level. They also formulated a Hidden Markov Model (HMM) classification algorithm [3]. Arslan and Hansen further investigated the HMM for accent classification, using three different scenarios: isolated word – full search, continuous speech – full search, and continuous speech – partial search. In all scenarios, a left-to-right HMM topology with no skip states was used. In tests using speech samples from native speakers of American English, Turkish, Chinese, and German, the HMM algorithm was found to classify better than human classifiers [4]. Teixeira, Trancoso, and Serralheiro applied a parallel set or ergodic nets with context independent HMM units to the problem of English accent identification of speakers from 6 different European countries [5]-[6]. Kat and Fung used phoneme-class based HMMs, rather than phoneme-based HMMs for classification [7]. Chen et al. use a Gaussian mixture model (GMM) to classify different accents in Chinese [8]. We have decided to use two different learning systems to perform the task of accent classification. The first is a HMM with a left-to-right phoneme-based topology. The second is a k-nearest neighbor (KNN) algorithm. We will compare the performance of these two learning systems with the performance of human classifiers.
Handwritten and Typewritten Word and Character Separation in Unconstrained Document Images

Separating handwritten and typewritten text within unconstrained paper documents can provide more accurate and efficient OCR results. This paper presents a technique developed that can isolate both the typewritten and handwritten portions of a document image. The classification between handwritten and typewritten text occurs at both the character and the word level. Characters are grouped into words using a word separation technique with an “island” grouping method. Structural features of handwritten and typewritten characters are examined. The method developed correctly identified with probability close to 100% of the total number of typewritten words in a set of 30 handwritten docu-
Evaluating and comparing algorithms for respiratory motion prediction

In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm—which is one of the algorithms currently used in the CyberKnife—is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient’s respiratory motion trace has strong influence on the outcome of prediction. Further work is needed to determine a priori the suitability of an individual’s respiratory behaviour to motion prediction.