Miracle-dz/UniFAR-FTUs huggingface dataset:
Incremental Discovery of Sequential Patterns

In this paper incremental discovery of sequential patterns from a large sequence database is studied A sequential pattern has the form where and are subsequences in the database which says that events will be followed by events with some minimum support and con dence We consider the scenario that sequential patterns have previously been discovered and materialized and an update is subsequently made to the database Rediscovering all patterns by scanning the whole database is not acceptable in a dynamic and large database environment We propose an incremental discovery algorithm that produces the updated patterns by scanning only the a ected part of the database and data structures In addition the algorithm handles the dynamism of the minimum support and con dence without recomputation allowing the user to tune these parameters and focus on most interesting patterns at little overhead Experiments and comparisons were conducted to test the e ectiveness of the proposed algorithm
Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors

In this paper, we present two dependency parser training methods appropriate for parsing outputs of statistical machine translation (SMT), which pose problems to standard parsers due to their frequent ungrammaticality. We adapt the MST parser by exploiting additional features from the source language, and by introducing artificial grammatical errors in the parser training data, so that the training sentences resemble SMT output. We evaluate the modified parser on DEPFIX, a system that improves English-Czech SMT outputs using automatic rule-based corrections of grammatical mistakes which requires parsed SMT output sentences as its input. Both parser modifications led to improvements in BLEU score; their combination was evaluated manually, showing a statistically significant improvement of the translation quality.
A global DNA methylation and gene expression analysis of early human B-cell development reveals a demethylation signature and transcription factor network

The epigenetic changes during B-cell development relevant to both normal function and hematologic malignancy are incompletely understood. We examined DNA methylation and RNA expression status during early B-cell development by sorting multiple replicates of four separate stages of pre-B cells derived from normal human fetal bone marrow and applied high-dimension DNA methylation scanning and expression arrays. Features of promoter and gene body DNA methylation were strongly correlated with RNA expression in multipotent progenitors (MPPs) both in a static state and throughout differentiation. As MPPs commit to pre-B cells, a predominantly demethylating phenotype ensues, with 79% of the 2966 differentially methylated regions observed involving demethylation. Demethylation events were more often gene body associated rather than promoter associated; predominantly located outside of CpG islands; and closely associated with EBF1, E2F, PAX5 and other functional transcription factor (TF) sites related to B-cell development. Such demethylation events were accompanied by TF occupancy. After commitment, DNA methylation changes appeared to play a smaller role in B-cell development. We identified a distinct development-dependent demethylation signature which has gene expression regulatory properties for pre-B cells, and provide a catalog reference for the epigenetic changes that occur in pre-B-cell leukemia and other B-cell-related diseases.
Numerical Bifurcation of Hamiltonian Relative Periodic Orbits

Relative periodic orbits (RPOs) are ubiquitous in symmetric Hamiltonian systems and occur, for example, in celestial mechanics, molecular dynamics, and the motion of rigid bodies. RPOs are solutions which are periodic orbits of the symmetry-reduced system. In this paper we analyze certain symmetry-breaking bifurcations of RPOs in Hamiltonian systems with compact symmetry group and show how they can be detected and computed numerically. These are turning points of RPOs and relative period-doubling and relative period-halving bifurcations along branches of RPOs. In a comoving frame the latter correspond to symmetry-breaking/symmetry-increasing pitchfork bifurcations or to period-doubling/period-halving bifurcations. We apply our methods to the family of rotating choreographies which bifurcate from the famous figure eight solution of the three-body problem as angular momentum is varied. We find that the family of choreographies rotating around the $e^2$-axis bifurcates to the family of rotating choreographie.
Noise dynamically suppresses chaos in neural networks

Noise is ubiquitous in neural systems due to intrinsic stochasticity or external drive. For deterministic dynamics, neural networks of randomly coupled units display a transition to chaos at a critical coupling strength. Here, we investigate the effect of additive white noise on the transition. We develop the dynamical mean-field theory yielding the statistics of the activity and the maximum Lyapunov exponent. A closed form expression determines the transition from the regular to the chaotic regime. Noise suppresses chaos by a dynamic mechanism, shifting the transition to significantly larger coupling strengths than predicted by local stability analysis. The decay time of the autocorrelation function does not diverge at the transition, but peaks slightly above the critical coupling strength.
A Novel Design Technique to Develop a Low Cost and Highly Stable Wall Climbing Robot

In this paper the proposed method aims to develop a low cost and efficient wall climbing robot that can climb on almost all surfaces. To ensure mechanical stability a centrifugal impeller is used and positioned above the robot that helps to generate an isolated low pressure area that makes adhesion to the vertical wall possible. When the impeller works, the sealing used in our robot reshapes to the shape of the contacting surface, maintaining the low pressure area inside which is a main advantage that eliminates the need for a perfect sealing as required by other vacuum powered wall climbing robots. To control the robot we use an ATmega8 micro controller along with RF wireless transceiver module and some discrete components. The experiment results verified the feasibility of the robot and it can make wall to floor and floor to wall transitions.
A NOTE ON THE SEVERITY OF RUIN IN THE RENEWAL MODEL WITH CLAIMS OF DOMINATED VARIATION

Abstract. This paper investigates the tail asymptotic behavior ofthe severity of ruin (the deﬁcit at ruin) in the renewal model. Underthe assumption that the tail probability of the claimsize is dominat-edly varying, a uniform asymptotic formula for the tail probabilityof the deﬁcit at ruin is obtained. 1. Model and main resultThroughout this paper, for any 0 • a < b < 1 the integral symbolR ba is understood asR ( a;b ] butR 1a =R ( a;1 ) : For a given distributionfunction (d.f.) F with ﬁnite mean „ and support [0 ;1 ), we denote itstail by F ( x ) = 1 iF ( x ) and its equilibrium d.f. by(1.1) F e ( x ) =1 „ Z x 0 F ( t )d t; x ‚ 0 : The symbol F ⁄n represents the n -fold convolution of F with F ⁄ 0 beingdegenerate at 0.The following renewal risk model has received extensive attentionin risk theory; see Embrechts et al.[2], Rolski et al.[9] and Asmussen[1] for reviews. In this model the successive claims, Z k ;k ‚ 1, forma sequence of independent, identically distributed (i.i.d.) and non-negative random variables (r.v.’s) with common d.f.
Gamification: A New Paradigm for Online User Engagement

The trend of employing game mechanisms and techniques in non-game contexts, gamification, has dramatically increased in recent years. Gamification can be viewed as a new paradigm for enhancing brand awareness and loyalty, innovation, and online user engagement. With the novelty and potential of gamification, until now there is limited understanding and research in this area. Particularly, previous literature falls short in explaining the antecedents of engagement, the mechanisms, and the impacts of gamification. Hence, in this study, we attempt to achieve three objectives. First, we provide an initial review of concepts and example cases related to gamification and summarize sample applications based on their objectives, design elements, rewards, and outcomes. Second, we articulate potential theories that can be extended to understand the motivations, design mechanisms, and impacts of gamification. Last, we provide directions for future research in this area by outlining salient research questions on various aspects of gamification.
The Middleton Class B Model and Its Mixture Representationyz

|The Middleton class B model has been shown in the literature as an appropriate model to describe certain non-Gaussian interference phenomena. However, its use is often limited because the probability density function has a very complicated form. In this paper, we derive a mixture representation for the Middleton class B model where the density function is expressed as a weighted sum of Chi-distributions with positive and monotonically decreasing coeecients. Therefore , the user can choose a nite linear combination of these simple distributions to approximate the Middleton class B density function to any desirable accuracy. The results presented in this paper help to extend the applicability of the Middleton class B model in practice. y Original manuscript was submitted as a correspondence item to the IEEE Transactions on In
Stereo Panning Information for Music Information Retrieval Tasks

Recording engineers, mixers, and producers play important yet often overlooked roles in defining the sound of a particular record, artist, or group. The placement of different sound sources in space using stereo panning is an important component of their work. Stereo panning information typically is not utilized in music information retrieval (MIR) tasks such as genre and artist classification. A set of audio features is proposed that can be used to characterize stereo panning information and contrast two different methods of calculation. These features are shown to provide statistically important information for nontrivial audio classification tasks and are compared with the traditional mel-frequency cepstral coefficients for different MIR tasks. They can also be viewed as a first attempt to capture extramusical information related to the production process through music information retrieval techniques.
Leading Change Management Projects in International Cross-Cultural Settings By Charles Repoux Master of Science

The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created. ABSTRACT In an increasingly complex world for Multinational Companies, it is difficult for managers to keep a firm grasp over the global projects they are tasked to implement. Many of them lead teams operating across country borders, creating a need to increasingly take diverse national cultures into account in their operations. This extra dimension of International culture adds a layer of complexity that has been well studied in the past, though never in the context of Change Projects. This paper aims to look at how national cultural considerations should factor in when implementing discreet change projects in an organization. The paper first lays out the historic work that has been carried out in cross-cultural organization research, to create a foundation for the definitions related to national culture. Then, using Kotter's widely used framework for "Leading Change", it examines how assumptions were initially built into the theory, and how cultural considerations can help to rectify implementation of this framework. Finally, the paper takes a look at how two comparable alliances-between Nissan and Renault and between Mitsubishi Motors Company and Daimler Chrysler-used distinct approaches to cultural understanding in the context of the Kotter framework. This paper reveals that in the case of the Renault-Nissan alliance, executives were sensitive to the Japanese culture and were successful at leveraging certain of its aspects to turn the company around. In the contrasting case, executives imposed DaimlerChrysler's management principles to lead the turnaround. They disregarded many aspects such as the need for teamwork and reverence of hierarchy in the Japanese culture, and failed to generate buy-in from their counterparts. Thanks to this analysis this paper concludes that National culture is a key element to take into account when implementing Change Projects across borders. In addition, this case comparison does show that it is not only possible to manage National cultural differences, but it is far more exciting and rewarding to leverage them. Although this is not a radical idea, it is at least comforting to witness this phenomenon in Change Projects as well. ACKLOWLEDGEMENTS I would like to thank my thesis advisor, professor Neal Hartman, for his support and guidance during this process. Professor Hartman gave me the autonomy to research a …
Intra-class retrieval of non-rigid 3 D objects : Application to Face Recognition

As the size of the available collections of 3D objects grows, database transactions become essential for their management, with the key operation being retrieval (query). Large collections are also pre-categorized into classes, so that a single class contains objects of the same type (e.g., human faces, cars, four-legged animals). It is shown that general object retrieval methods are inadequate for intra-class retrieval tasks. We advocate that such intra-class problems require a specialized method that can exploit the basic class characteristics in order to achieve higher accuracy. A novel 3D object retrieval method is presented which uses a Parameterized Annotated Model of the shape of the objects in a class incorporating its main characteristics. The annotated subdivision-based model is fitted onto objects of the class using a deformable model framework, converted to a geometry image and transformed into the wavelet domain. Object retrieval takes place in the wavelet domain. The method does not require user interaction, achieves high accuracy, it is efficient for use with large databases, and it is suitable for non-rigid object classes. We apply our method to the face recognition domain, one of the most challenging intra-class retrieval tasks. We utilized the Face Recognition Grand Challenge database, yielding an average verification rate of 95.2% at 10−3 false accept rate.
A Distributed Multi-Session Dialog Manager with a Dynamic Grammar Parser

In recent years the Spoken Language Processing fiel d has been rapidly growing. Several humanmachine systems with different characteristics have be n developed, most of them without a distributed an scalable architecture. For instance, Olympus framew ork at the current version does not support multi-s ession. In addition, it uses the Phoenix parser without a d ynamic grammar. In this paper we design a distribut ed, robust, scalable and multi-session architecture app lied to a spoken dialog system along with a dynamic and self-learning Natural Language Understanding (NLU) mechanism. It is based on an extension of the basic Olympus framework. The implementation we propose, c alled OlympusP2P is built on a distributed and high ly context-sensitive framework for applications that a im at interacting with users by using natural langu a es. OlympusP2P will soon available for researcher and a pplication developer.
Ausarbeigung zur Studienarbeit “Ranking Integrated Search Results in Columba”

Data integration projects in the life sciences often gather data on a particular subject from multiple sources. Some of these sources overlap to a certain degree. Therefore, integrated search results may be supported by one, few, or all data sources. To reflect these differences, results should be ranked according to the number of data sources that support them. How such a ranking should look like is not clear per se. Either, results supported by only few sources are ranked high because this information is potentially new, or such results are ranked low because the strength of evidence supporting them is limited. We present two scoring schemes to rank search results in the integrated protein annotation database Columba. We define a surprisingness score, preferring results supported by few sources, and a confidence score, preferring frequently encountered information. Unlike many other scoring schemes our proposal is purely data-driven and does not require users to specify preferences among sources. Both scores take the concrete overlaps of data sources into account and do not presume statistical independence. We show how our schemes have been implemented efficiently using SQL.
Spectrally Compatible Iterative Water Filling

Until now static spectrum management has ensured that DSL lines in the same cable are spectrally compatible under worst-case crosstalk conditions. Recently dynamic spectrum management (DSM) has been proposed aiming at an increased capacity utilization by adaptation of the transmit spectra of DSL lines to the actual crosstalk interference. In this paper, a new DSM method for downstream ADSL is derived from the well-known iterative water-filling (IWF) algorithm. The amount of boosting of this new DSM method is limited, such that it is spectrally compatible with ADSL. Hence it is referred to as spectrally compatible iterative water filling (SC-IWF). This paper focuses on the performance gains of SC-IWF. This method is an autonomous DSM method (DSM level 1) and it will be investigated together with two other DSM level-1 algorithms, under various noise conditions, namely, iterative water-filling algorithm, and flat power back-off (flat PBO).
3D SPIHT for multi-lead ECG compression

In this paper we proposed the implementation of 3D Set Partitioning In Hierarchical Trees (SPIHT) algorithm to a multi-lead ECG signal compression. The implementation of 3D SPIHT decorrelates three types of redundancy that commonly found on a multi-lead electrocardiogram (ECG) signal i.e. intra-beat, inter-beat, and inter-lead redundancies. To optimize overall compression performance we also proposed beat reordering and residual calculation technique. Beat reordering rearranges beat order in 2D ECG array based on the similarity between adjacent beats. This rearrangement reduces variances between adjacent beats so that the 2D ECG array contains less high frequency component. Residual calculation optimizes required storage usage further by minimizing amplitude variance of 2D ECG array. The experiments on selected records from St Petersburg INCART 12-lead Arrhythmia Database show that proposed method gives relatively low distortion at compression rate 8 and 16.
BER Analysis for Controller Area Network Impaired by the Impulse Noise in Cyber-Physical Systems

The physical space and the cyber space are deeply coupled in Cyber-physical systems (CPS). The computing components and the physical components are connected via the communication network. However, highly dynamics of the physical environments may lead to unpredictable performance of the network. In order to achieve the best synthesized performance of CPS, the physical impairments on communication must be quantitatively analyzed carefully. The paper introduces a mathematical model of the impulse noise under the realistic channels. The model takes different parameters of the impulse noise into consideration, especially the impulse width. The probability density function of the receiving signals embracing the impact of the noise is derived. Then the model is applied to Controller Area Network (CAN). The relations between the bit error rate (BER) of CAN and the parameters of the impulse noise, which is not well addressed in previously published studies, are established. Compared with the existing models of the impulse noise, the new model not only includes most of these models, but considers the bursty nature of the impulse noise. The results of the quantitative analysis under different physical scenarios are helpful to improve the synthesized performance of CPS via accurate compensation mechanisms.
Prevalence of overweight among preschool children in the United States, 1971 through 1994.

OBJECTIVE To examine the prevalence of overweight among US preschool children 2 months through 5 years of age between the years 1971 through 1974 and 1988 through 1994. DESIGN Nationally representative cross-sectional surveys with a physical examination, including measurement of stature, length, and weight. Between 1200 and 7500 children younger than 6 years were examined in each of four different surveys during 1971 through 1974 (first National Health and Nutrition Examination Survey [NHANES I]), 1976 through 1980 (NHANES II), 1982 through 1984 (Hispanic Health and Nutrition Examination Survey), and 1988 through 1994 (NHANES III). RESULTS The prevalence of overweight increased among some sex and age groups of preschool children between 1971 through 1974 and 1988 through 1994. More than 10% of 4- and 5-year-old girls were overweight in 1988 through 1994 compared with 5.8% in 1971 through 1974. However, there was no change during this period in the prevalence of overweight among 1- and 2- to 3-year-old children. During 1988 through 1994, the prevalence of overweight among children 2 months through 5 years of age was consistently higher in girls than boys. Mexican-American children had a higher prevalence of overweight than non-Hispanic black and non-Hispanic white children. These results parallel what has been reported for older children and adults in the United States. CONCLUSION These results show that in the last 20 years the prevalence of overweight has increased among 4- and 5-year-old children but not among younger children. These findings suggest that efforts to prevent overweight, including encouragement of physical activity and improved diets, should begin in early childhood.
2 Sensors on Racks 2 . 1 Data Center Cooling Basics

The IT industry is the fastest growing sector in US energy consumption. Improving data center energy efficiency is a pressing issue with significant economic and environmental consequences. Heat distribution is a key operationa l parameter that affects data center cooling and energy consumption. However, typical data centers lack effective fine grained sensing systems to monitor heat distribution at a large scale. In this paper, we motivate the use of sensor networks as a dense instrumentation technology to understand and control cooling in data centers. We present Microsoft Research Genomote sensors designed for data center monitoring, and the RACNet for reliable data acquisition. We describe lessons learned from early pilot deployments, and discuss architectural and technical challenges in develop ing data center sensor networks.