Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-channel speech separation using a sparse periodic decomposition

In this paper, we propose a single-channel speech separation method by using a sparse decomposition with a periodic signal model. In our separation method, a mixture of speeches is approximated with periodic signals with time-varying amplitude. The decomposition with the periodic signal model is performed under a sparsity penalty. Due to the sparsity penalty, a segment of the speech mixture is decomposed into periodic signals, each of them is a component of the individual speaker. For speech separation, we introduce the clustering using a K-means algorithm for the set of the periodic signals. After the clustering, each cluster is assigned to its corresponding speaker using codebooks that contain spectral features of the speakers. In experiments, comparison with MaxVQ that performs separation on frequency spectrum domain is demonstrated. The experimental results in terms of signal-to-distortion ratio (SDR) show that our method outperforms MaxVQ with less computational cost for assignment of speech components.
Light-microscopic morphology and ultrastructure of Polychaos annulatum (Penard, 1902) Smirnov et Goodkov, 1998 (Amoebozoa, Tubulinea, Euamoebida), re-isolated from the surroundings of St. Petersburg (Russia)

We isolated the species Polychaos annulatum (Penard, 1902) Smirnov et Goodkov, 1998 from a freshwater habitat in the surrounding of Saint-Petersburg. The previous re-isolation of this species took place in 1998; at that time the studies of its lightmicroscopic morphology were limited with the phase contrast optics, and the electronmicroscopic data were obtained using the traditional glutaraldehyde fixation, preceded with prefixation and followed by postfixation with osmium tetroxide. In the present paper, we provide modern DIC images of P. annulatum. Using the fixation protocol that includes a mixture of the glutaraldehyde and paraformaldehyde we were able to obtain better fixation quality for this species. We provide some novel details of its locomotive morphology, nuclear morphology, and ultrastructure. The present finding evidence that P. annulatum is a widely distributed species that could be isolated from a variety of freshwater habitats.
Iterative Refinement of Transformation Parameters for Image Registration

Image registration is an important process in high-level image interpretation systems developed for civilian and defense applications. Registration is carried out in two phases : namely feature extraction and feature correspondence. The basic building block of feature based image registration scheme involves matching feature points that are extracted from a sensed image to their counter parts in the reference image. Features may be control points, corners, junctions or interest points. The objective of this study is to develop a methodology for iterative convergence of transformation parameters automatically between two successive pairs of aerial or satellite images. In this paper we propose an iterative image registration approach to compute accurate and stable transformation parameters that would handle image sequences acquired under varying environmental conditions. The iterative registration procedure was initially tested using satellite images with known transformation parameters like translation, rotation, scaling and the same method is further tested with images obtained from aerial platform.
Obtaining Human Experience for Intelligent Dredger Control: A Reinforcement Learning Approach

This work presents a reinforcement learning approach for intelligent decision-making of a Cutter Suction Dredger (CSD), which is a special type of vessel for deepening harbors, constructing ports or navigational channels, and reclaiming landfills. Currently, CSDs are usually controlled by human operators, and the production rate is mainly determined by the so-called cutting process (i.e., cutting the underwater soil into fragments). Long-term manual operation is likely to cause driving fatigue, resulting in operational accidents and inefficiencies. To reduce the labor intensity of the operator, we seek an intelligent controller the can manipulate the cutting process to replace human operators. To this end, our proposed reinforcement learning approach consists of two parts. In the first part, we employ a neural network model to construct a virtual environment based on the historical dredging data. In the second part, we develop a reinforcement learning model that can lean the optimal control policy by interacting with the virtual environment to obtain human experience. The results show that the proposed learning approach can successfully imitate the dredging behavior of an experienced human operator. Moreover, the learning approach can outperform the operator in a way that can make quick responses to the change in uncertain environments.
The Effect of U.S. Public-to-Private Leveraged Buyouts on Innovation

With a large sample of public-to-private leveraged buyouts from 1980 to 2006, we find that LBO targets are equally likely to hold patents as other publicly-traded firms. Using a difference-in-differences approach, we find that LBOs reduce patent flows by one third. This reduction results from a 23% decline in new grants and 7% fewer purchases. Around one fifth of patent-holding LBO targets sell patents immediately after their buyout, liquidating an average of 45% of their portfolio. After an LBO, patents are granted at a reduced rate, receive the same level of citations, and make 16% more citations.
Attribute reduction for SIFT local descriptors using PCA and CAIM

Stable local feature detection and representation are the fundamental components of target recognition and image retrieval. The traditional SIFT algorithm's descriptor of the feature points is a 128-element vector, and a lot of redundant information is presence. So the brief and effective expression of the image feature information is the key to improve the performance of the algorithm. This paper is to use PCA and CAIM method to extract the more concise and more robust descriptor. Image feature points matching experiments show that the improved algorithm has a higher matching accuracy and faster matching speed.
Evaluating and improving the usability of Mechanical Turk for low-income workers in India

While platforms such as Amazon Mechanical Turk have generated excitement as a potential source of income in developing regions, to date there remains little evidence that such opportunities have transformed livelihoods for low-income workers. In this study, we analyze the usability barriers that prevent those with basic digital literacy skills from accomplishing simple tasks on Mechanical Turk. Based on our observations, we design new user interfaces that reduce the barriers to task comprehension and execution. Via a study of 49 low-income workers in urban India, we demonstrate that new design elements -- including simplified user interfaces, simplified task instructions, and language localization -- are absolutely necessary to enable low-income workers to participate in and earn money using Mechanical Turk. We synthesize our findings into a set of design recommendations, as well as a realistic analysis of the potential for microtasking sites to deliver supplemental income to lower-income communities.
The Impact of a Focus on Change in Technology in Successful Implementation of SAP Enterprise Resource Planning Systems in North and South America

Organizations find the adoption of Enterprise Resource Planning (ERP) as a necessity to enhance success of focus on multiple competitive priorities. With the adoption of ERP comes the potential for success as well as failure. While studies have been conducted on the impact of change management and change to best business practices, the impact of focus on technology and the related correlation to successful ERP implementations remains in question. This research measures the impact of technology as correlated to successful ERP implementations in hopes to contribute to scholarly findings and advice to future practitioners for future success in ERP implementations.
Impact of global seismicity on sea level change assessment

[1] We analyze the effect of seismic activity on sea level variations by computing the time-dependent vertical crustal movement and geoid change due to coseismic deformations and postseismic relaxation effects. Seismic activity can affect both the absolute sea level, changing the Earth's gravity field and hence the geoid height, and the relative sea level (RSL), i.e., the radial distance between seafloor and geoid level. By using comprehensive seismic catalogs we assess the net effect of seismicity on tidal relative sea level measurements as well as on the global oceanic surfaces, and we obtain an estimate of absolute sea level variations of seismic origin. We modified the approach adopted in our previous analysis, considering the issue of water volume conservation by applying the sealevel equation, and we improved our computational methods, enabling us to evaluate the effect of an extremely large number of earthquakes on large grids covering the whole oceanic surface. These new potentialities allow us to perform more detailed investigations and to discover a quantitative explanation for the overall tendency of earthquakes to produce a positive global relative sea level variation. Our results confirm the finding of a previous analysis that on a global scale most of the signal is associated with a few giant thrust events and that RSL estimates obtained using tide gauge data can be sensibly affected by the seismically driven sea level signal. The recent measures of sea level obtained by satellite altimetry show a wide regional variation of sea level trends over the oceanic surface, with the largest deviations from the mean trend occurring in tectonically active regions. While our estimates of average absolute sea level variations turn out to be orders of magnitude smaller than the satellite-measured variations, we can still argue that the mass redistribution associated with aseismic tectonic processes may contribute to the observed regional variability of sea level variations. A detailed study of these tectonic contributions is important to acquire a complete understanding of the global sea level variations and will be the subject of future investigations.
Optimization of Fixed Structure Controllers – Application to the Tuning of a Hard Disk Drive Servo Controller –

This paper presents an algorithm to solve an H∞ optimization problem of fixed-structure controllers. The proposed algorithm first transforms the original fixed-structure controller synthesis problem into an H∞ synthesis problem of static output feedback control, which does not impose any structural constraints except for the one on the controller order. Then, a linearization-based local search algorithm is applied to solve this problem. Based on the proposed H∞ optimization algorithm, this paper demonstrates an intuitive and efficient method to re-tune controller parameters, which were finely tuned by an expert engineer, and improve the control performance. As an application example, the proposed approach is applied to the tuning of a PID (Proportional plus Integral plus Derivative) controller for head positioning of hard disk drives. The effectiveness of the proposed re-tuning method is demonstrated by simulation and experimentation.
1 Example – Power Allocation in Communication Systems

Just as conic programming can be seen as one possible generalization of linear programming, geometric programming (GP) can be motivated as an alternate generalization of LP. Like conic programs, GPs have many important applications – in this lecture we will see examples in communications systems, ecology and machine learning/statistics. After deriving the geometric programming framework, we will turn to some of the algorithmic considerations required for solving such programs efficiently. In particular we will begin our treatment of barrier and interior point methods.
Brushed DC motor controller using robust indirect adaptive control

Electric motors play an important role in industry as well as our day-to-day life. They are used to generate electrical power in power plants and provide mechanical work in industries. They are also an indispensable part of our daily lives. Electric motors are very important pieces of equipment in our everyday lives. The brushed dc motor is considered to be basic electric motors.
Utilizing Temporal Information for Taxonomy Construction

Taxonomies play an important role in many applications by organizing domain knowledge into a hierarchy of ‘is-a’ relations between terms. Previous work on automatic construction of taxonomies from text documents either ignored temporal information or used fixed time periods to discretize the time series of documents. In this paper, we propose a time-aware method to automatically construct and effectively maintain a taxonomy from a given series of documents preclustered for a domain of interest. The method extracts temporal information from the documents and uses a timestamp contribution function to score the temporal relevance of the evidence from source texts when identifying the taxonomic relations for constructing the taxonomy. Experimental results show that our proposed method outperforms the state-of-the-art methods by increasing F-measure up to 7%–20%. Furthermore, the proposed method can incrementally update the taxonomy by adding fresh relations from new data and removing outdated relations using an information decay function. It thus avoids rebuilding the whole taxonomy from scratch for every update and keeps the taxonomy effectively up-to-date in order to track the latest information trends in the rapidly evolving domain.
What Accounts for the Rising Sophistication of China&Apos;S Exports?

Chinese exports have become increasingly sophisticated. This has generated anxiety in developed countries as competitive pressure may increasingly be felt outside labor-intensive industries. Using product-level data on exports from different cities within China, this paper investigates the contributing factors to China's rising export sophistication. Somewhat surprisingly, neither processing trade nor foreign invested firms are found to play an important role in generating the increased overlap between China's export structure and that of high-income countries. Instead, improvement in human capital and government policies in the form of tax-favored high-tech zones appear to be the key to the country's evolving export structure. On the other hand, processing trade, foreign invested firms, and government-sponsored high-tech zones all have contributed significantly to raising the unit values of Chinese exports within a given product category.
Predicting the driver's turn intentions at urban intersections using context-based indicators

Many improvements have been made in the area of vehicle safety and pedestrian protection; however, urban intersections are still black spots for Advanced Driver Assistance Systems (ADAS). One of the main reasons is the uncertainty of the future driving direction at intersections. Due to that uncertainty, the early activation of an intersection ADAS will lead to high false positive rates, while, in contrast, a late activation of an intersection ADAS will lead to a low accident-reduction potential. This tradeoff is described as warning dilemma. In order to solve the warning dilemma, an approach to predicting the driver's turn intention at urban intersections is introduced. The novelty of the approach is its context-based prediction of the future driving maneuver several seconds before the driving trajectory changes. To predict maneuvers, indicators are used to encode the context information together with vehicle data. A system setup including prediction results of the system is described.
Comparative study of Full-Bridge and Double Half-Bridge converters

A comparative study of two isolated DC-DC ZVS converters topologies is described in this paper, one of them is the Full-Bridge topology considered the most used in the field of DC-DC power conversion for high power applications, which will be compared with a Double Half-Bridge topology counterpart, both operating in ZVS phase-shifted PWM. Operation stages for both topologies are described, analyzed, designed, simulated and compared, where Double Half-Bridge DC-DC ZVS converter allows to operating from no-load to full-load, as well as it can operate at output voltage full range, at zero voltage commutation.
Implications of the design of monetary policy for financial stability

This paper is a contribution to the literature on the factors behind financial stability, focusing on monetary policy design. In particular, it assesses empirically for a sample of 79 countries in the period 1970 to 2000 whether the choice of the central bank objectives and the monetary policy strategy affect financial stability. We find that focusing the central bank objectives on price stability reduces the likelihood of a banking crisis. This result is robust to several model specifications and groups of countries. As regards the monetary policy strategy, exchange rate targeting significantly reduces the likelihood of a banking crisis for some model specifications and, in particular, for the group of countries in transition.
Highly Efficient Transfection of Human THP-1 Macrophages by Nucleofection

Macrophages, as key players of the innate immune response, are at the focus of research dealing with tissue homeostasis or various pathologies. Transfection with siRNA and plasmid DNA is an efficient tool for studying their function, but transfection of macrophages is not a trivial matter. Although many different approaches for transfection of eukaryotic cells are available, only few allow reliable and efficient transfection of macrophages, but reduced cell vitality and severely altered cell behavior like diminished capability for differentiation or polarization are frequently observed. Therefore a transfection protocol is required that is capable of transferring siRNA and plasmid DNA into macrophages without causing serious side-effects thus allowing the investigation of the effect of the siRNA or plasmid in the context of normal cell behavior. The protocol presented here provides a method for reliably and efficiently transfecting human THP-1 macrophages and monocytes with high cell vitality, high transfection efficiency, and minimal effects on cell behavior. This approach is based on Nucleofection and the protocol has been optimized to maintain maximum capability for cell activation after transfection. The protocol is adequate for adherent cells after detachment as well as cells in suspension, and can be used for small to medium sample numbers. Thus, the method presented is useful for investigating gene regulatory effects during macrophage differentiation and polarization. Apart from presenting results characterizing macrophages transfected according to this protocol in comparison to an alternative chemical method, the impact of cell culture medium selection after transfection on cell behavior is also discussed. The presented data indicate the importance of validating the selection for different experimental settings.
Document Counting in Compressed Space

We address the problem of counting the number of strings in a collection where a given pattern appears, which has applications in information retrieval and data mining. Existing solutions are in a theoretical stage. In this pa-per we implement these solutions and explore compressed variants, aiming to reduce data structure size. Our main result is to uncover some unexpected compressibility properties of the fastest known data structure for the problem. By taking advantage of these properties, we can reduce the size of the structure by a factor of 5-400, depending on the dataset.
Regulated expression of galectin‐1 during B‐cell activation and implications for T‐cell apoptosis

Galectin‐1 (GAL‐1), a highly conserved β‐galactoside‐binding protein, has shown immunomodulatory properties. In this study, we investigated the regulation of GAL‐1 expression within the B‐cell compartment usingTrypanosoma cruzi infection as a natural model of in vivo B‐cell activation. GAL‐1 was found to be expressed on activated B cells from T. cruzi‐infected mice, mainly localized at the cytosolic compartment. Expression of this protein was found to be modulated according to the activation state of the cells, revealing a significant increase in stimulated B cells that received signals via cross‐linking of the B‐cell receptor and CD40. It was found that GAL‐1 was secreted by B cells to the extracellular milieu upon activation. Finally, purified GAL‐1 produced by activated B cells induced apoptosis of T cells but not B cells and also influenced interferon‐γ cytokine production. Hence, the present study describes a potential mechanism by which B cells can regulate T‐cell function and survival.
Corpus-based Generation of Easy Help-desk Responses

We present a corpus-based approach for the automatic generation of email responses to helpdesk requests. This is largely an extractive multi-document summarization task. However, in our application users have a very low tolerance for responses that contain incongruous sentences. To address this problem, we propose a method for extracting high-precision sentences for inclusion in a response, and a measure for predicting the completeness of a planned response. The idea is that complete, high-precision responses may be sent to users, while incomplete responses should be passed to operators. Our results show that a small but significant proportion (14%) of our automatically generated responses have a high degree of precision and completeness, and that our measure can reliably predict the completeness of a response.
A Backward Generalization of PCA for Image Analysis

A generalized Principal Component Analysis (PCA) for various types of image-based data is proposed. We discuss two viewpoints of classical PCA, forward and backward stepwise views, pointing out that a backward approach leads to a much more natural and accessible extension of PCA for dimension reduction on non-linear manifolds. In particular, a general framework of composite Principal Nested Spheres is proposed that generalizes PCA in a backward manner and composes one or more such non-linear analyses with Euclidean data. The method works for a variety of application areas, including point distribution models, medial representations, points and normals. In examples from a lung motion study and from a population of prostates, composite PNS is shown to give a more succinct representation than alternative methods in the literature.
Barriers to treatment adherence for children with cystic fibrosis and asthma: what gets in the way?

OBJECTIVES The purpose of this study was to systematically identify barriers to treatment adherence for children with cystic fibrosis (CF) and asthma, as well as to examine the relationship between the number of barriers and adherence. METHODS Participants included 73 children with CF or asthma and their parents. The mean age of the sample was 9.9 years, and 58% were males. RESULTS Results indicated that barriers were quite similar by illness and informant (e.g., parent and child) for the same treatments, but unique barriers were identified for disease-specific treatments. Frequently mentioned barriers across diseases included forgetting, oppositional behaviors, and difficulties with time management. Trends were identified between adherence and barriers, suggesting that a greater number of barriers were related to poorer adherence. CONCLUSION Overall, this study provided evidence that patients and their parents experience specific barriers within the context of their own illness and highlights the need for disease-specific measures and interventions.