Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Hammerstein and Wiener systems for nonlinear acoustic echo cancelers in reverberant environments

The aim of this paper is the presentation of a comparative analysis of Hammerstein and Wiener systems used for the problem of compensation of the nonlinear distortion due to non-ideality of amplifiers and loudspeakers in acoustic echo cancellation. The proposed solutions consist in a cascade of a flexible nonlinear function, whose shape can be modified during the learning process, and a linear adaptive filter in different order, respectively. Two different type of flexible nonlinearities are tested. Some numerical results show the effectiveness of the proposed approaches and underline that the Hammerstein system has better performances than the Wiener one.
The quest for open source projects that use UML: mining GitHub

Context: While industrial use of UML was studied intensely, little is known about UML use in Free/Open Source Software (FOSS) projects. Goal: We aim at systematically mining GitHub projects to answer the question when models, if used, are created and updated throughout the whole project's life-span. Method: We present a semi-automated approach to collect UML stored in images, . xmi, and . uml files and scanned ten percent of all GitHub projects (1.24 million). Our focus was on number and role of contributors that created/updated models and the time span during which this happened. Results: We identified and studied 21 316 UML diagrams within 3 295 projects. Conclusion: Creating/updating of UML happens most often during a very short phase at the project start. For 12% of the models duplicates were found, which are in average spread across 1.88 projects. Finally, we contribute a list of GitHub projects that include UML files.
Group Communication Protocols and a Framework for Intrusion-Tolerant Distributed Applications

We present an overview of a suite of protocols for practical intrusion-tolerant group communication. The protocols are very efficient in the normal case of no faults, are reasonably efficient even when faults occur, provide strong reliability guarantees, and operate under realistic timing assumptions. The protocol suite will be implemented in a reusable, reconfigurable, and portable framework called CoBFIT. The framework contains several support features for intrusion tolerance so that it can serve as a foundation for building and evaluating various design choices for intrusion-tolerant group communication protocols and group-communication-based applications. The protocol suite and the CoBFIT framework will constitute the CoBFIT toolkit. The eventual goal is to develop a rich set of group communication services in the CoBFIT toolkit that can be used for embedding intrusion tolerance in several distributed applications.
Mechatronic model and simulation of four-wheel Mecanum vehicle driven by BLDC

The conventional research on Mecanum vehicle mainly focuses on the analysis of its kinematic and dynamic model, while the characteristics of its driving motor are seldom considered. This paper is based on the kinematic and dynamic model of the four-wheel Mecanum vehicle, as well as the mathematical model of brushless DC motor (BLDC); by the combination of these two models, this paper presents the mechatronic modeling and simulation of the omni-directional four-wheel Mecanum vehicle driven by BLDC. This mechatronic model has been implemented with the S-function in Matlab/Simulink in this paper, and a PI controller has been employed to perform a simulation of this model. This model can not only be applied as a pseudo-entity when designing motion controller, but also be used to verify the reasonableness of other control algorithms, which offers a new way of designing and debugging the actual mecanum-wheeled mechatronic system.
The Comparison of Object Recognition and Identification by Using Image Processing Base on the Neural Network, the Hough transform and the Harris Corner Detection

This paper presents an object recognition and identification system using the back propagation neural networks. The performance of Hough Transform and the Harris Corner detection are compared with the following procedures and methods; the webcam is used to capture the object and create an input image, change the color image from RGB to gray scale, resize, learn and recognize the objects by neural network, and separate the objects by the robot arm. Three different types of objects in this study are triangle, rectangle and rigid circle. The object recognition and identification from the neural network, the Hough transform, and the Harris corner detection are compared. The results showed that the neural network gives more accuracy than the Hough transform and the Harris corner detection.
Trust Evaluation Based Content Filtering in Social Interactive Data

A new Cloud-based Trust Awareness and Interaction Model (CTAIM) is proposed for trust evaluation based content filtering in social interactive data. The research is based on diversified information from social interactive data to analyse people's intention and evaluate people's trust. The proposed model is composed of Bayesian content filtering algorithm and Bayesian inference algorithm in Dirichlet distribution, and it's capable to provide 3rd party trustworthiness evaluation according to node behavior and interaction history with high-efficiency, security, and neutrality. Additionally, MapReduce-based computing and HBase storage framework are implemented for parallel computing among mass interactive data.
Characterization of Artifacts Produced by Gel Displacement on Non-invasive Brain-Machine Interfaces during Ambulation

So far, Brain-Machine Interfaces (BMIs) have been mainly used to study brain potentials during movement-free conditions. Recently, due to the emerging concern of improving rehabilitation therapies, these systems are also being used during gait experiments. Under this new condition, the evaluation of motion artifacts has become a critical point to assure the validity of the results obtained. Due to the high signal to noise ratio provided, the use of wet electrodes is a widely accepted technic to acquire electroencephalographic (EEG signals). To perform these recordings it is necessary to apply a conductive gel between the scalp and the electrodes. This work is focused on the study of gel displacements produced during ambulation and how they affect the amplitude of EEG signals. Data recorded during three ambulation conditions (gait training) and one movement-free condition (BMI motor imagery task) are compared to perform this study. Two phenomenons, manifested as unusual increases of the signals' amplitude, have been identified and characterized during this work. Results suggest that they are caused by abrupt changes on the conductivity between the electrode and the scalp due to gel displacement produced during ambulation and head movements. These artifacts significantly increase the Power Spectral Density (PSD) of EEG recordings at all frequencies from 5 to 90 Hz, corresponding to the main bandwidth of electrocortical potentials. They should be taken into consideration before performing EEG recordings in order to asses the correct gel allocation and to avoid the use of electrodes on certain scalp areas depending on the experimental conditions.
Social Intelligence in Conversational Computer Agents

I. Introduction The purpose of this work is to endow an embodied conversational computer agent with the ability to establish and maintain an ongoing social relationship with a user. This ability is not only important in entertainment applications (e.g., as in Tamagotchis and Furbies which are specifically designed to establish ongoing relationships with their users) and affect support systems (such as computer therapists or frustration management systems), but plays a crucial role in any application in which we want to manage how a user interacts with an agent. If we want our users to feel comfortable with our agents, trust them or be persuaded or comforted by them, then we must understand how humans perform these functions and endow our agents with similar behavior. In this work I am particularly interested in embodied conversational agents (Cassell, Bickmore et al. 1999), which are agents that use natural speech and an animated humanoid representation to interact with a user. I believe that most of the behaviors that people use to influence each other socially are conveyed either through language or nonverbal behavior in face-to-face interaction, and thus it is crucial that agents have these communication channels at their disposal for effecting the same results. Embodied conversational agents also leverage the knowledge all users in a language community have about how to engage in face-to-face conversation, making them potentially more natural and easy to use than any other form of human-computer interface. Adding social skills to these agents will serve to make them even more natural and easy to use. People use many linguistic strategies to achieve interpersonal goals, such as building rapport, establishing credibility and trust, effecting persuasion, and befriending. One example strategy is small talk; "light" conversation about neutral topics (e.g., weather, immediate context) (Laver 1981) which is used to build rapport and trust, provide time to "size" a stranger up, and mitigate positive and negative face threats (Goffman 1983). Even in business meetings or sales encounters it is customary to begin with some amount of small talk before "getting down to business" (at least in American culture). Small talk is not a random phenomena used to fill idle time, but is a linguistic behavior that can be used strategically in a conversation, for example, to reduce a client's fear before asking them to sign a contract. Recent work has shown that people already respond socially to computers (Reeves and Nass …
Distinct Mutants of Retrograde Intraflagellar Transport (IFT) Share Similar Morphological and Molecular Defects

A microtubule-based transport of protein complexes, which is bidirectional and occurs between the space surrounding the basal bodies and the distal part of Chlamydomonas flagella, is referred to as intraflagellar transport (IFT). The IFT involves molecular motors and particles that consist of 17S protein complexes. To identify the function of different components of the IFT machinery, we isolated and characterized four temperature-sensitive (ts) mutants of flagellar assembly that represent the loci FLA15, FLA16, and FLA17. These mutants were selected among other ts mutants of flagellar assembly because they displayed a characteristic bulge of the flagellar membrane as a nonconditional phenotype. Each of these mutants was significantly defective for the retrograde velocity of particles and the frequency of bidirectional transport but not for the anterograde velocity of particles, as revealed by a novel method of analysis of IFT that allows tracking of single particles in a sequence of video images. Furthermore, each mutant was defective for the same four subunits of a 17S complex that was identified earlier as the IFT complex A. The occurrence of the same set of phenotypes, as the result of a mutation in any one of three loci, suggests the hypothesis that complex A is a portion of the IFT particles specifically involved in retrograde intraflagellar movement.
Paper on Joint Data Hiding and Compression Scheme based on SMVQ and Image Inpainting Ms

Data hiding is mainly used to hide the secret data into a cover data like a video file, an audio file, an image, etc. It is popularly used in medical and military applications. Nowadays reversible data hiding is the latest research area in the field of secret data hiding techniques. This paper covers many hiding and compression techniques like vector quantization (VQ), side match vector quantization (SMVQ), histogram shifting technique, locally adaptive data compression technique, and many more. But the topic of our interest is side match vector quantization.
Wage Bargaining and Turnover Costs with Heterogeneous Labour: The No-screening Case

We study the effects of mobility costs in a model of wage bargaining between workers and firms, where there is instantaneous matching, free firm entry, heterogeneous labour, and workers' individual productivities are discovered by firms only after being hired. We derive the employment level and the minimum quality standard, in the market solution and in the socially efficient solution.
Evidence of a Growing Inequality in Work Timing Using a Japanese Time-Use Survey

Using data from a Japanese time use survey, we show a noteworthy increase in the share of employees working unusual hours (late night and early morning) over a period of a decade since the mid 1990s. When controlling for changes in hours worked, however, we find that the notable increase in the fraction of people working unusual hours was for low-income nonregular employees (part time, temporary and contract workers), while relatively higher-income regular employees' work timing remains stable. These observations imply that there is a trend of diversification of work timing in Japan between regular and nonregular employees. A possible explanation is that the increase in the average hours worked per weekday by regular employees, possibly because of the spread of the five-day workweek since the 1990s, increased the demand for services and goods during unusual hours, as they returned home. An Oaxaca-Blinder type decomposition suggests that such an increase in the average hours worked by regular employees explains partially the rise in the employment rate of nonregular employees at unusual times. We also suggest that the negative income effect induced low-wage nonregular employees to take jobs at night to earn a wage premium.
Steady State Analysis of Convex Combination of Affine Projection Adaptive Filters

The aim of the study is to propose an adaptive algorithm using convex combinational approach to have both fast convergence and less steady state error simultaneously. For this purpose, we have used two affine projection adaptive filters with complementary nature (both in step size and projection order) as the component filters. The first component filter has high projection order and large step size which makes it to have fast convergence at the cost of more steady state error. The second component filter has slow convergence and less steady state error due to the selection of small step size and projection order. Both are combined using convex combiner so as to have best final output with fast convergence and less steady state error. Each of the component filters are updated using their own error signals and stochastic gradient approach is used to update the convex combiner so as to have minimum overall error. By using energy conservation argument, analytical treatment of the combination stage is made in stationary environment. It is found that during initial stage the proposed scheme converges to the fast filter which has good convergence later it converges to either of the two (whichever has less steady state error) and towards the end, the final output converges to slow filter which is superior in lesser steady state error. Experimental results proved that the proposed algorithm has adopted the best features of the component filters.
A real-time motion planner with trajectory optimization for autonomous vehicles

In this paper, an efficient real-time autonomous driving motion planner with trajectory optimization is proposed. The planner first discretizes the plan space and searches for the best trajectory based on a set of cost functions. Then an iterative optimization is applied to both the path and speed of the resultant trajectory. The post-optimization is of low computational complexity and is able to converge to a higher-quality solution within a few iterations. Compared with the planner without optimization, this framework can reduce the planning time by 52% and improve the trajectory quality. The proposed motion planner is implemented and tested both in simulation and on a real autonomous vehicle in three different scenarios. Experiments show that the planner outputs high-quality trajectories and performs intelligent driving behaviors.
Accuracy improvements of consumer-grade 3D sensors for robotic applications

Recent advances in development of low-cost 3D sensors, such as Microsoft Kinect, bring attractive opportunities to robot system integrators. The accuracy provided by such sensors is generally unsatisfactory for many robotic applications, but it may be improved through calibration. This paper presents a calibration case study that is based on the sensor calibration procedure involving only a use of a simple checkerboard. It is shown that the calibration enables improving sensor accuracy 3 to 5 times, depending on the anticipated use of the sensor. Additionally, results obtained using different levels of complexity of calibration models reveal that depth measurement correction is an important component of calibration as it may reduce by 50% the errors in sensor reading.
In vivo cartilage deformation after different types of activity and its dependence on physical training status

Background: Knowledge of the deformational behaviour of articular cartilage in vivo is required to understand the pathogenesis of osteoarthritis and the mechanical target environment of prospective cartilage transplant recipients. Objectives: To study the in vivo deformational behaviour of patellar and femorotibial cartilage for different types of physiological activities; and to test the hypothesis that in vivo deformation of cartilage is modified by intense physical exercise. Methods: Magnetic resonance imaging and 3D digital image analysis were used to determine cartilage volume before and after physical activity in the patella of 12 volunteers (knee bends, squatting, normal gait, running, cycling). Deformation of femorotibial cartilage was investigated in 10 subjects (knee bends, static compression, high impact loading). Patellar cartilage deformation after knee bends was compared in seven professional weight lifters, seven sprinters, and 14 untrained volunteers. Results: Patellar cartilage deformation was −5.9% after knee bends, −4.7% after squatting, −2.8% after normal walking, −5.0% after running, and −4.5% after cycling. The pattern of patellar cartilage deformation corresponded to the range of motion involved in the particular activity. Tibial cartilage deformation was greatest under high impact loading (−7%), but small for other activities. No significant difference was found between athletes and non-athletic controls. Conclusions: Patellar cartilage deformation shows a “dose dependent” response, where more intense loading leads to greater deformation. Relatively little deformation was observed in the femorotibial joint, except during high impact activities. The findings provide no evidence that adult human cartilage properties are amendable to training effects in vivo.
The Market Value of IT Outsourcing Investment Announcements: An Event-Study Analysis

The market for information technology outsourcing has seen significant growth in the last decade (GartnerGroup, 1998). Companies use IT outsourcing to increase the efficiency of their globalization process, while maintaining core competency strength. As a result, the ability to manage effective IT outsourcing projects is of utmost important to the success of IT managers (Sambamurthy & Zmud, 2000). In addition, the ability to make an informed decision when buying and IT outsourcing is seen as a core capability for IT managers (Feeny and Wilcocks, 1998). However, the proper metrics to use to assess the decision to initiate an IT outsourcing engagement are still somewhat undefined. While the cost savings reaped through IT outsourcing are often attractive, traditional accounting measures may underestimate potential improvements in economic output brought about by an outsourcing engagement, such as streamlined business processes, better quality customer service, and a wider range of knowledge on technological offerings. One way information systems (IS) researchers can assess the business performance of IT outsourcing investments is by using market-based measures such as stock prices. This study addresses the question: Do IT outsourcing investment announcements affect the market value of the firm, and if so, how does the effect differ across the service industry versus the IT industry, and across project type? To answer these questions, we analyze the impact of IT outsourcing investment announcements on the common stock prices of publicly traded firms.
Face recognition based on neighbourhood discriminant preserving embedding

Neighborhood Preserving Embedding (NPE) is an unsupervised linear dimensionality reduction technique which attempts to solve the ldquoout of samplerdquo problem in Locally Linear Embedding (LLE). This is done by introducing a linear transform matrix into LLE, and hence NPE can be perceived as a linear approximation to LLE. In this paper, we modify the original NPE for face recognition by embedding prior class information in the process of neighborhood selection. Intuitively, neighboring points are kept intact if they have the same class label, while avoid points of other classes from entering the neighborhood. We proved experimentally in three face databases, ie. ORL, PIE and FRGC, and with comparisons with other linear and non-linear feature extractors, the intuition underlying the inclusion of class information in NPE works out very advantageously for achieving high recognition performance.
A Component-based Framework for Embedded Digital Instrumentation Software with Design Patterns

The embedded digital instrumentations (EDI) software systems become diversified and more complex with variable requirements. Component-based frameworks (CBF) which are built on object-oriented (OO) technologies provide a better reuse. A CBF for EDI software systems is presented in this paper, and it will be demonstrated that it is convenient to reuse the components and to construct an EDI application. The system architecture and framework design of multimedia instrumentations will be presented as an example. For a maintainable, flexible and extensible design, design patterns are employed in the components and framework development; strategy, observer, command and composite patterns are discussed and implemented in examples.
Multiantenna spectrum sensing of a second-order cyclostationary signal

We consider spectrum sensing of a second-order cyclostationary signal received at multiple antennas. The proposed detector exploits both the spatial and the temporal correlation of the received signal, from knowledge of the fundamental period of the cyclostationary signal and the eigenvalue multiplicities of the temporal covariance matrix. All other parameters, such as the channel gains or the noise power, are assumed to be unknown. The proposed detector is shown numerically to outperform state-of-the-art detectors for spectrum sensing of an OFDM signal, both when using a single antenna and with multiple antennas.
Test and calibration of sonobuoys in the air environment

In this paper, a method for calibrating and testing DIFAR sonobuoy multiplexer without sea or water is proposed. For this purpose; the architecture of DIFAR sonobuoy is introduced, calibration factors are expressed, calibration and test environment in terms of hardware and software are described, calibration and test procedure is explained, and finally, laboratory test results of a sonobuoy calibrated in that environment is given and discussed.