Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Mining User-Aware Rare Sequential Pattern

: Sequential pattern mining is exploring enthusiasm for finding the most frequently using patterns from the data sets. We explore the sequential pattern mining using a bitmap representation. Our algorithm incrementally output new frequent itemset in an online fashion using depth-first search strategy. To find out the sequential pattern in data streams, we propose a sequential data mining algorithm using weighted sliding window. SWSS algorithm provides more space for users to specify which sequences they are more interested in. To address the problem of finding frequent and rare itemsets from the data streams, we propose another algorithm called New_SPAM. New_SPAM Algorithm is the combination of both Per_SPAM and Min_SPAM algorithm.
Contribution of body composition and activity behaviors to variation of total energy expenditure in pre-school children

Ba ckground: Although it is widely accepted that the pre-school age is a critical period in the development of obesity, there are few published data on factors contributing to variation of total energy expenditure in this age group.To investigate the contribution of body composition, gender and activity on total energy expenditure (TEE) in pre-school children. M ethods: The total energy expenditure of 89 children (2-6 years old) was measured using the doubly labelled water (DLW) technique. Total and regional body composition were also measured using deuterium dilution and dual energy X-ray absorptiometry (DXA) respectively. Physical activity and sleep patterns were evaluated using an accelerometer. Principal components analysis (PCA) were performed on regional fat mass (FM), regional fat free mass (FFM) and behavioural variables (activity, inactivity and sleep patterns), to generate orthogonal predictors for regression analyses. Results: No significant difference was found between boys and girls for, log weight, height, BMI sds, total FFM and log FM measured by DXA and total FFM and log obtained with deuterium dilution. No significant gender difference was found for regional traits of FFM and FM except for trunk’ FFM (p=0.02) and legs’ FFM (p=0.04), which were higher in boys. FFM and FM measured by DXA explained 70.9% of the variation in TEE, and TEE was significantly lower amongst girls after adjustments for body composition were made (p<0.01). The first component of FFM (PC1-FFM), FM (PC1-FM) and behavioural variables (PC1-BV) were positively (p<0.01) related to TEE and there was a significant negative relationship with PC2- FM (p<0.05) and PC4-BV (p<0.01). Conclusion: Most variation in TEE in this group was explained by difference in FFM and FM. Behavioural factors, particularly time spent in high activities could make an additional contribution of 20.9% in variation of free-living TEE. More research is needed to confirm these findings in other population.
Fast gain calibration in radio astronomy using alternating direction implicit methods: Analysis and applications

Context. Modern radio astronomical arrays have (or will have) more than one order of magnitude more receivers than classical synthesis arrays, such as the VLA and the WSRT. This makes gain calibration a computationally demanding task. Several alternating direction implicit (ADI) approaches have therefore been proposed that reduce numerical complexity for this task from $\mathcal{O}(P^3)$ to $\mathcal{O}(P^2)$, where $P$ is the number of receive paths to be calibrated. Aims. We present an ADI method, show that it converges to the optimal solution, and assess its numerical, computational and statistical performance. We also discuss its suitability for application in self-calibration and report on its successful application in LOFAR standard pipelines. Methods. Convergence is proved by rigorous mathematical analysis using a contraction mapping. Its numerical, algorithmic, and statistical performance, as well as its suitability for application in self-calibration, are assessed using simulations. Results. Our simulations confirm the $\mathcal{O}(P^2)$ complexity and excellent numerical and computational properties of the algorithm. They also confirm that the algorithm performs at or close to the Cramer-Rao bound (CRB, lower bound on the variance of estimated parameters). We find that the algorithm is suitable for application in self-calibration and discuss how it can be included. We demonstrate an order-of-magnitude speed improvement in calibration over traditional methods on actual LOFAR data. Conclusions. In this paper, we demonstrate that ADI methods are a valid and computationally more efficient alternative to traditional gain calibration method and we report on its successful application in a number of actual data reduction pipelines.
Stumbling Giants: The Emptiness, Fullness, and Recursiveness of Strategic Management

Zusammenfassung Allgemeine Konzepte und Rezepte des strategischen Managements sind meistens entweder einseitig oder leer, Reflex auf einen horror vacui der Träger strategischer Entscheidungen. Diese Entscheidungen und die Orientierung an einmal dieser, einmal jener Managementmode werden in diesem Beitrag als Entfaltung der Raradoxie des Entscheidens interpretiert, einschließlich der Oszillation zwischen kontextabhängig wechselnder Fokussierung der Themen und der strategischen Aufmerksamkeit. Es wird ein Konzept rekursiver, supplementärer Füllung einer notwendigen Leere von Strategien im Zuge ihrer Implementation und Realisierung vorgestellt, unter Rekurs auf Alfred Schütz, Anthony Giddens, Jaques Derrida, Donald Schöns Begriff »knowledge-in-action« und Eric Leiters Idee einer strategischen Ambiguität. Strategisches Management ist, so gesehen, ein permanentes Tasten und Stolpern. Fiktionen der Fülle und Verläßlichkeit strategischer Konzepte geben dann Halt.
Deconvolution methods for ultrasonic NDT

Ultrasonic testing is the method for volume nondestructive testing for industrial materials like steel. It is long established and widely used. However, as the demands on parts integrity increase in various industrial applications the demand on measurement sensitivity is lifted correspondingly. E.g. the energy sector needs more and more high pressure tubing, which in turn leads to higher demands in terms of integrity. In order to increase sensitivity of any measurement system it is necessary to remove unwanted noise from the signals. This would lead to better signal to noise ratio and thus allows higher amplification of signals or lower assessment thresholds. Although there are many denoising techniques available (e.g. wavelet denoising, see [1,10], anisotropic diffusion [14], variational methods [11] or hybrid techniques [5]), the specific problems and the high noise level require adapted denoising and detection methods. In this work we present two deconvolution methods that are both adapted to the applied special ultrasonic pulses. These two methods can be applied in a preprocessing step in order to solve the inverse problem of flaw detection as well as for pure denoising purposes or for efficient storing of the measured ultrasonic data. The first method is a special matching pursuit (MP) algorithm in order to deconvolve the mixed data (signal and noise), and thus to remove the unwanted noise. The second method is based on the approximate Prony method (APM). Both methods employ some prior knowledge about the measured ultrasonic signal. We assume here that the impulse response of the ultrasonic transducer can be estimated or computed in advance. If the impulse response can only be estimated, we offer an iteration method for adjusting the parameters in the used Gaussian echo model. The MP algorithm is F. Boßmann · G. Plonka · T. Peter Institute for Numerical and Applied Mathematics, University of Göttingen, Lotzestraße 16-18, 37083 Göttingen, Germany E-mail: {f.bossmann,plonka,t.peter}@math.uni-goettingen.de O. Nemitz · T. Schmitte Salzgitter Mannesmann Forschung GmbH, Ehinger Straße 200, 47259 Duisburg, Germany E-mail: {o.nemitz,t.schmitte}@du.szmf. de 2 Florian Boßmann et al. used to derive a sparse representation of the measured data by a deconvolution and subtraction scheme. An orthogonal variant of the algorithm (OMP) is presented as well. The APM technique also relies on the assumption that the desired signals are sparse linear combinations of (reflections of) the transmitted pulse. Several test results show that the methods work well even for high noise levels. Further, an outlook for possible applications of these deconvolution methods is given.
ELODIE: A spectrograph for accurate radial velocity measurements

The bre{fed echelle spectrograph of Observatoire de Haute{Provence, ELODIE, is presented. This instrument has been in operation since the end of 1993 on the 1.93 m telescope. ELODIE is designed as an updated version of the cross{correlation spectrometer CORAVEL, to perform very accurate radial velocity measurements such as needed in the search, by Doppler shift, for brown{dwarfs or giant planets orbiting around nearby stars. In one single exposure a spectrum at a resolution of 42000 (=) ranging from 3906 A to 6811 Ai s recorded on a 10241024 CCD. This performance is achieved by using a tan = 4 echelle grating and a combination of a prism and a grism as cross{disperser. An automatic on{line data treatment reduces all the ELODIE echelle spectra and computes cross{correlation functions. The instrument design and the data reduction algorithms are described in this paper. The eciency and accuracy of the instrument and its long term instrumental stability allow us to measure radial velocities with an accuracy better than 15 m s 1 for stars up to 9th magnitude in less than 30 minutes exposure time. Observations of 16th magnitude stars are also possible to measure velocities at about 1 km s 1 accuracy. For classic spectroscopic studies (S=N>100) 9th magnitude stars can be observed in one hour exposure time.
Motion capture studies of action-sound couplings in sonic interaction

Combining terminology from (Schae er,1966) and (Cadoz,1988), we maydi erentiate three di erent action-sound types, as presented in (God˝y,2006): impulsive, sustained and iterative. As shown in Figure1, each ofthe action-sound types may be identi ed from the energy pro les of boththe action and the sound.
Turbulence-induced secondary motion in a buoyancy-driven flow in a circular pipe

We analyze the results of a direct numerical simulation of the turbulent buoyancy-driven flow that sets in after two miscible fluids of slightly different densities have been initially superimposed in an unstable configuration in an inclined circular pipe closed at both ends. In the central region located midway between the end walls, where the flow is fully developed, the resulting mean flow is found to exhibit nonzero secondary velocity components in the tube cross section. We present a detailed analysis of the generation mechanism of this secondary flow which turns out to be due to the combined effect of the lateral wall and the shear-induced anisotropy between the transverse components of the turbulent velocity fluctuations.
Hyrarchical Classification of Images to Predict Privacy Policy to Uploaded Images on Content Sharing Site

Social Network is an e-service which is booming for sharing contents. Reliable communication is done with social networking sites. Though these sites are a new attacking area for hackers for hacking; they are able to misuse the data through these sites. Some users over CSS affect user’s privacy on their personal contents, where some users keep on sending unwanted comments and messages by taking advantage of the user’s inherent trust in their relationship network. Towards addressing this need, we propose a Content-Predicated Relegation system to avail users to get automatically set privacy of their images. We examine the role of gregarious context, image content, and metadata as possible bespeakers of user’s privacy predilections. Our solution relies on an image relegation framework for image categories which may be associated with homogeneous policies and on a policy presage algorithm to automatically engender a policy for each incipiently uploaded image.
( Preprint ) AAS 15-201 MARS DOUBLE-FLYBY FREE RETURNS

A subset of Earth-originating Mars double-flyby ballistic trajectories is documented. The subset consists of those trajectories that, after the first Mars flyby, perform a half-revolution transfer with Mars before returning to Earth. This class of free returns is useful for both human and robotic Mars missions because of its low geocentric energy at departure and arrival, and because of its extended stay time in the vicinity of Mars. Ballistic opportunities are documented over Earth departure dates ranging from 2015 through 2100. The mission is viable over three or four consecutive Mars synodic periods and unavailable for the next four, with the pattern repeating approximately every 15 years. Over the remainder of the century, a minimum Earth departure hyperbolic excess speed of 3.16 km/s, a minimum Earth atmospheric entry speed of 11.47 km/s, and a minimum flight time of 904 days are observed. The algorithm used to construct these trajectories is presented along with several examples.
CVSSearch: Searching thr ough SourceCodeusingCVS Comments

CVSSearch is a tool that searches for fragments of source code by using CVS comments. CVS is a version control system that is widely used in the open source community [10]. Our search tool takes advantage of the fact that a CVS comment typically describes the lines of code involved in the commit and this description will typically hold for many future versions. In other words, CVSSearch allows one to better search the most recent version of the code by looking at previous versions to better understand the current version. In this paper, we describe our algorithm for mapping CVS comments to the corresponding source code, present a search tool based on this technique, and discuss preliminary feedback.
Comparison of approaches to deal with matrix effects in LC-MS/MS based determinations of mycotoxins in food and feed

This study deals with one of the major concerns in mycotoxin determinations: the matrix effect related to LC-MS/ MS systems with electrospray ionization sources. To this end, in a first approach, the matrix effect has been evaluated in two ways: monitoring the signal of a compound (added to the mobile phase) during the entire chromatographic run, and by classical post-extraction addition. The study was focused on nine selected mycotoxins: aflatoxin B1, fumonisins B1, B2 and B3, ochratoxin A, deoxynivalenol, T-2 and HT-2 toxins and zearalenone in various sample extracts giving moderate to strong matrix effects (maize, compound feed, straw, spices). Although the permanent monitoring of a compound provided a qualitative way of evaluating the matrix effects at each retention time, we concluded that it was not adequate as a quantitative approach to correct for the matrix effect. Matrix effects measured by post-extraction addition showed that the strongest ion suppression occurred for the spices (up to -89%). F.
PathMiner Powered Predictable Packet Processing

Performance advances have made software packet processing a compelling alternative to hardware. However, software still lacks the delay predictability of hardware, an important property for security and quality of service. As a solution, we introduce PathMiner, an analysis tool that automatically builds performance models for software packet processors at the fine granularity of per-packet execution times. PathMiner combines symbolic execution and genetic algorithms in an iterative feedback loop to rapidly mine a packet processor binary for diverse packets that invoke complex execution paths. With these packets, PathMiner trains machine learning models that predict packet execution times and paths based on raw packet header bytes. We implement a prototype of PathMiner and test it by profiling a software IP router. The evaluation shows that PathMiner’s models predict delay with low error – for over 40% of packets they predicted the router’s execution time to within 10 cycles. Closer examination shows that PathMiner’s effectiveness is due to higher execution path coverage than symbolic execution and the capability to generate diverse training samples efficiently. PathMiner takes an important step towards making it practical to predict delay for any software packet processor.
Predation of Gypsy Moth (Lepidoptera: Lymantriidae) Pupae in Three Ecosystems Along the Southern Edge of Infestation

Abstract The predation potential of small mammals, in particular mice, Peromyscus spp. , and invertebrates, was evaluated from 1992 to 1995 near the leading edge of gypsy moth, Lymantria dispar (L.), spread into the southeastern United States. Two study sites were established in each of three geographic areas: the coastal plain, Piedmont, and mountains. All sites were mixed hardwood stands with varying amounts of oak, Quercus spp. , and all were classified for gypsy moth susceptibility. Small mammal density was estimated using Sherman live-traps and pitfall traps within these 4.68-ha sites in early and late summer. Each site contained 75 trapping stations located on a 25-m grid. Predation was measured by offering freeze-dried gypsy moth pupae near trapping stations at four heights (0, 0.25, 1.0, and 2.0 m) on different tree boles. Pupal predation was monitored for three consecutive nights. Vertebrate predation was positively correlated with good mast production in the previous autumn. Predation data showed that when mice were at high densities they were the major source of pupal predation. However, within these southern sites, when densities of Peromyscus spp. were low, predation by invertebrates was occasionally greater than predation by vertebrates. These data suggest that in some years invertebrates may retard gypsy moth buildup when small mammals are scarce due to mast crop failures.
Corruption's Direct Effects on Per‐Capita Income Growth: A Meta‐Analysis

Corruption is a symptom of weak institutional quality and could have potentially adverse effects on economic growth. However, heterogeneity in reported findings makes it difficult to synthesize the evidence base with a view to test competing hypotheses and/or support evidence-based policy and practice. To address this issue, we have extracted 327 estimates of corruption's direct effect on per-capita GDP growth from 29 primary studies, following a peer-reviewed and pre-published systematic review protocol. Precision-effect and funnel asymmetry tests indicate that corruption has a negative effect on per-capita GDP growth after controlling for publication selection bias and within-study dependence. However, multivariate meta-regression analysis results indicate that the overall effect is not robust to inclusion of moderating variables through a general-to-specific procedure for model specification. We report that the marginal effect of corruption on per-capita GDP growth is more adverse when the primary study estimates relate to long-run growth, are based on low-income-country data only, and extracted from journal papers. The effect is less adverse in studies that use the International Country Risk Guide corruption perceptions index and in those reporting estimates from two-stage least-squares estimations.
Status of Marine Environment of Olive Flounder, Paralichythys olivaceus, Culture Ground in Jeju-do - Focus on Kudoa septempunctata positive and negative farm -

In this study, we monitored the status of marine environment of olive flounder, Paralichythys olivaceus, culture ground in Jeju-do, Republic of Korea. It reported the consumption of raw olive flounder meat containing of Kudoa, Kudoa septempunctata, could induce vomitting and diarrhea in Japan. The Kudoa is a new mycosporean species, researchers found Kudoa from the muscles of olive flounder cultured at western Japan and imported from Jeju-do. We choose two Kudoa positive farms and two negative farms in the mid of concern about the relation between Kudoa and habitat. We found two marine invasive species at the water-pumping seabed at one of the Kudoa positive farm. The concentration of pH and DO at on-growing flounder farms showed the decreasing pattern along side the raceway (influent sea waters ＞ on growing sea waters ＞ outfluent sea waters). The TN and TP values increased gradually following to the raceway (influent sea waters ＜ on growing sea waters ＜ outfluent sea waters). The concentration of COD and SS were in the range of 0.100 – 2.581 ㎎·L-1, 1.00 – 12.70 ㎎·L-1, respectively. The calculated residence time was 4hr 32minutes at F1, 11hr 21minutes at F2, and 9hr 50minutes at F3, respectively. It was calculated same distance of 4 km away from effluent pipes. Although direct relation between Kudoa and marine environment could not define well based on this study result, the more studies on marine environmental stressors for olive flounder are required to conduct as a reliable method including socio-economic group and environmental group.
Correlation Networks for Speaker Normalization in Automatic Speech Recognition

In this paper, we propose using common representation learning(CRL) for speaker normalization in automatic speech recognition (ASR). Conventional methods like feature space maximum likelihood linear regression (fMLLR) require two pass decode and their performance is often limited by the amount of data during test. While i-vectors do not require two-pass de-code, a signiﬁcant number of input frames are required for estimation. Hence, as an alternative, a regression model employing correlational neural networks (CorrNet) for multi-view CRL is proposed. In this approach, the CorrNet training methodology treats normalized and un-normalized features as two parallel views of the same speech data. Once trained, this network generates frame-wise fMLLR-like features, thus overcoming the limitations of fMLLR/i-vectors. The recognition accuracy us-ing the proposed CorrNet-generated features is comparable with the i-vector model counterparts and signiﬁcantly better than the un-normalized features like ﬁlterbank. With CorrNet-features, we get an absolute improvement in word error rate of 2.5% for TIMIT, 2.69% for WSJ84 and 3.2% for Switchboard-33hour over un-normalized features.
Fabrication of Metal Matrix Composites under Intensive Shearing

Current processing methods for metal matrix composites (MMC) often produces agglomerated reinforced particles in the ductile matrix and also form unwanted brittle secondary phases due to chemical reaction between matrix and the reinforcement. As a result they exhibit extremely low ductility. In addition to the low ductility, the current processing methods are not economical for producing engineering components. In this paper we demonstrate that these problems can be solved to a certain extent by a novel rheo-process. The key step in this process is application of sufficient shear stress on particulate clusters embedded in liquid metal to overcome the average cohesive force of the clusters. Very high shear stress can be achieved by using the specially designed twin-screw machine, developed at Brunel University, in which the liquid undergoes high shear stress and high intensity of turbulence. Experiments with Al alloys and SiC reinforcement reveal that, under high shear stress and turbulence conditions Al liquid penetrates into the clusters and disperse the individual particle within the cluster, thus leading to a uniform microstructure.