Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust RNN-based pre-classification for noisy Mandarin speech recognition

This paper addressed the problem of speech signal pre-classification for robust noisy speech recognition. A novel RNN-based pre-classification scheme for noisy Mandarin speech recognition is proposed. The RNN, which is trained to be insensitive to noise-level variation, is employed to classify each input frame into the three broad classes of initial, final and pure-noise. An on-line noise tracking and estimation for noise model compensation is then performed. Besides, a broad-class likelihood compensation based on the RNN outputs is also performed to help the recognition. Experimental results showed that a significant improvement on syllable recognition rate has been achieved under non-stationary noise environment.
Chapter . I Semantic . Web . Mining for . Personalized

As citizens are confronted with increasing volumes of information, boundless choices, and endless opportunities in the Web environment, the need for personalised public e-services is more compulsory than ever. This chapter explores the way Semantic Web mining technologies can be incorporated into public e-services domain in order to better meet citizens and authorities requirements. It describes the various steps of the personalisation process and examines techniques in use today to support it. In sequence, it introduces a recommendation scenario for an e-city portal. Finally, the chapter illustrates current trends in the field suggesting directions that may lead to new scientific results in the area.
Blind Password Registration for Verifier-based PAKE

We propose Blind Password Registration (BPR), a new class of cryptographic protocols that is instrumental for secure registration of client passwords at remote servers with additional protection against unwitting password disclosures on the server side that may occur due to the lack of the state-of-the-art password protection mechanisms implemented by the server or due to common server-compromise attacks. The dictionary attack resistance property of BPR protocols guarantees that the only information available to the server during and after the execution of the protocol cannot be used to reveal the client password without performing an offline dictionary attack on a password verifier (e.g. salted hash value) that is stored by the server at the end of the protocol. In particular, at no point in time the server is supposed to work with plain passwords. Our BPR model allows servers to enforce password policies and the requirement on the client to obey them during the execution of the BPR protocol is covered by the policy compliance property. We construct an efficient BPR protocol in the standard model for ASCII-based password policies using some techniques underlying the recently introduced Zero-Knowledge Password Policy Checks (ZKPPC). However, we do not rely on the full power of costly ZKPPC proofs and in fact show that BPR protocols can be modelled and realised simpler and significantly faster (as supported by our implementation) without using them as a building block. Our BPR protocol can directly be used to replace ZKPPC-based registration procedure for existing VPAKE protocols.
Design of Rotary Clock Based Circuits

Rotary clock technique has been shown to reduce the power dissipation of clock distribution by up to 80%. However, to our knowledge, no practical digital synchronous circuit has been designed that utilizes the rotary technique due to the multi-phase nature of rotary clock signals and the strong coupling between a rotary clock network and the circuit it drives. In this paper, we make the first attempt to design rotary based circuit by proposing a unified clock and circuit design methodology. Given a sequential circuit and a clock frequency, our scheme derives a rotary clock network and a functionally equivalent circuit so that they can be integrated to operate reliably at the target frequency. We have applied our scheme to design several rotary clock based DSP modules. Simulation results show that all designs operate correctly with no timing violation. Compared with designs using conventional clock trees, our designs achieve an average clock power saving of more than 70%.
Standardized data for dimming of fluorescent lamps

In another paper by the authors (see ibid., vol.1, p.665-72, 2002), a description is given of standardized data concerning the static properties of electrodes of fluorescent lamps and also of the preheating data for the electrodes. In this publication we explain the physical and engineering principles that are the basis of the new approach to standardized information for dimming of fluorescent lamps. Descriptions with the additional 'heating current' and 'total current' or I/sub LH/ are discussed. Next to these descriptions the latest approach with the sum of squared lead-in wire currents to an electrode is explained: the so-called "SoS lines". This information was generated in a Panel of ELMAPS TC4. It is shown that taking the energy balance around the hotspot of the electrodes as the starting point, relatively simple expressions can be derived for the additional heating that is required if fluorescent lamps are dimmed. As a next step in the standardization process, the data for the "SoS lines" of single capped fluorescent lamps will be included in the IEC 60901 standards.
Unit Roots and Structural Breaks in Panels : Does the Model Specification Matter ?

Although the impacts of structural instability on testing for unit root have been studied extensively for univariate time series, such impacts on panel data unit root tests are still relatively unknown. A major issue is the choice of model in accommodating different types of break (instability) prior to testing for unit root. Specifically, researchers must specify a potential break in the intercept, the trend or both before testing for unit root. Model misspecification has been known to have a great impact on the test performance in the univariate case, especially when the selected model fails to accommodate a break in the trend. However, the impact of model misspecification on testing for unit root is still unknown for panel data. This paper has two objectives: (i) it proposes a new test for unit root in the presence of structural instability for panel data. The test allows the intercepts, the trend coefficients or both to change at different date for different individuals. Under some mild assumptions, the test statistics is shown to be asymptotically normal which greatly facilitates valid inferences. (ii) Using the proposed test, this paper provides a systematic study on the impact of structural instability on testing for unit root using Monte Carlo Simulation. Specifically, the impact of model misspecification on the size and the power of the proposed test is discussed in details. Although the test performs reasonably well when the models are correctly specified, Monte Carlo results show that failure to accommodate a break in the trend coefficients can seriously distort the size and the power of the proposed test. In fact, the power of the test decreases when individuals experience a break in the trend coefficients even when the model is correctly specified. This is consistent with the results for univariate time series.
Validation of Meaning in Life Questionnaire in Hindi (MLQ-H)

ABSTRACT The primary focus of the study is to present the psychometric properties of the Hindi version of the Meaning in Life Questionnaire (MLQ-H). The study was conducted in North India, where more than one-third of the population speaks Hindi. A total of 826 participants (females = 426) in the age range of 18–60 years volunteered. Consistent with the original factor structure, MLQ-H showed a two-factor structure explaining 56.42% of variance and confirmatory factor analysis established. Both factors demonstrated high internal consistencies with Cronbach’s α = . 81 (MLQ-P) and . 78 (MLQ-S). Convergent validity was ascertained by correlating with Flourishing Scale (FS) and Scale of Positive and Negative Experience (SPANE). Results demonstrated that MLQ-P positively correlated with SPANE P, SPANE B, and FS, and negatively correlated with SPANE N, whereas the MLQ-S negatively correlated with SPANE B and positively with SPANE N. The results indicate that MLQ-H is a psychometrically sound measure.
Used of Various Edge Detection Operators for Feature Extraction in Video Scene

- This paper presents the implementation of an adaptive edge-detection using Simulink. Simulink is a simulation modeling and design tool and GUI based diagram environment. The Simulink based customizable framework is designed for rapid simulation, implementation, and verification of video and image processing algorithms and systems. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects.The Edge detection process detects outlines of an object, scene text and boundaries between objects and the background in the video image. Edge detection is in the forefront of video processing for object detection, it is crucial to have a good understanding of edge detection methods. Edges characterize boundaries and edge detection is one of the most difficult tasks in image processing hence it is a problem of fundamental importance in image processing.In this work the comparative analysis of various video image edge detection methods is like Sobel, Prewitt, and Canny is presented.
Optimal Life-Cycle Portfolios for Heterogeneous Workers

Household portfolios include risky bonds, beyond stocks, and respond to permanent labour income shocks. This paper brings these features into a life-cycle setting, and shows that optimal stock investment is constant or increasing in age before retirement for realistic parameter combinations. The driver of such inversion in the life-cycle profile is the resolution of uncertainty regarding social security pension, which increases the investor’s risk appetite. This occurs if a small positive contemporaneous correlation between permanent labour income shocks and stock returns is matched by a realistically high degree of risk aversion. Absent this combination, the typical downward sloping profile obtains. Overlooking differences in optimal investment profiles across heterogeneous workers results in large welfare losses, in the order of 15-30% of lifetime consumption.
A Stereological Method for the Quantitative Evaluation of Cartilage Repair Tissue

Objective To implement stereological principles to develop an easy applicable algorithm for unbiased and quantitative evaluation of cartilage repair. Design Design-unbiased sampling was performed by systematically sectioning the defect perpendicular to the joint surface in parallel planes providing 7 to 10 hematoxylin–eosin stained histological sections. Counting windows were systematically selected and converted into image files (40-50 per defect). The quantification was performed by two-step point counting: (1) calculation of defect volume and (2) quantitative analysis of tissue composition. Step 2 was performed by assigning each point to one of the following categories based on validated and easy distinguishable morphological characteristics: (1) hyaline cartilage (rounded cells in lacunae in hyaline matrix), (2) fibrocartilage (rounded cells in lacunae in fibrous matrix), (3) fibrous tissue (elongated cells in fibrous tissue), (4) bone, (5) scaffold material, and (6) others. The ability to discriminate between the tissue types was determined using conventional or polarized light microscopy, and the interobserver variability was evaluated. Results We describe the application of the stereological method. In the example, we assessed the defect repair tissue volume to be 4.4 mm3 (CE = 0.01). The tissue fractions were subsequently evaluated. Polarized light illumination of the slides improved discrimination between hyaline cartilage and fibrocartilage and increased the interobserver agreement compared with conventional transmitted light. Conclusion We have applied a design-unbiased method for quantitative evaluation of cartilage repair, and we propose this algorithm as a natural supplement to existing descriptive semiquantitative scoring systems. We also propose that polarized light is effective for discrimination between hyaline cartilage and fibrocartilage.
Crystal structure and subunit dynamics of the abalone sperm lysin dimer: egg envelopes dissociate dimers, the monomer is the active species

Lysin is a 16-kD acrosomal protein used by abalone spermatozoa to create a hole in the egg vitelline envelope (VE) by a nonenzymatic mechanism. The crystal structure of the lysin monomer is known at 1.9 A resolution. The surface of the molecule reveals two tracks of basic residues running the length of one surface of the molecule and a patch of solvent-exposed hydrophobic residues on the opposite surface. Here we report that lysin dimerizes via interaction of the hydrophobic patches of monomers. Triton X-100 dissociates the dimer. The crystal structure of the dimer is described at 2.75 A resolution. Fluorescence energy transfer experiments show that the dimer has an approximate KD of 1 microM and that monomers exchange rapidly between dimers. Addition of isolated egg VE dissociates dimers, implicating monomers as the active species in the dissolution reaction. This work represents the first step in the elucidation of the mechanism by which lysin enables abalone spermatozoa to create a hole in the egg envelope during fertilization.
Project-Team Eiffel Cognition and Cooperation in Design

This research aims to study, in computer-supported-collaborative-learning situations, the impact of reﬂection tools that are assumed to help students to develop and improve meta-cognitive skills. The process by which students develop problem solving, decision making and investigation activities in these situations, is determined by the relationship between collaboration, computer tools and meta-cognitive skills. This relationship stems from research from two areas, Collaborative Learning Theory and Meta-cognitive Theory. It will be studied in learning situations using a project-based-learning model. This research is performed in collaboration with the Université de Savoie and the Université de Genève.
Zebrafish as a Potential Model Organism for Drug Test Against Hepatitis C Virus

Screening and evaluating anti- hepatitis C virus (HCV) drugs in vivo is difficult worldwide, mainly because of the lack of suitable small animal models. We investigate whether zebrafish could be a model organism for HCV replication. To achieve NS5B-dependent replication an HCV sub-replicon was designed and created with two vectors, one with HCV ns5b and fluorescent rfp genes, and the other containing HCV's 5′UTR, core, 3′UTR and fluorescent gfp genes. The vectors containing sub-replicons were co-injected into zebrafish zygotes. The sub-replicon amplified in liver showing a significant expression of HCV core RNA and protein. The sub-replicon amplification caused no abnormality in development and growth of zebrafish larvae, but induced gene expression change similar to that in human hepatocytes. As the amplified core fluorescence in live zebrafish was detectable microscopically, it rendered us an advantage to select those with replicating sub-replicon for drug experiments. Ribavirin and oxymatrine, two known anti-HCV drugs, inhibited sub-replicon amplification in this model showing reduced levels of HCV core RNA and protein. Technically, this method had a good reproducibility and is easy to operate. Thus, zebrafish might be a model organism to host HCV, and this zebrafish/HCV (sub-replicon) system could be an animal model for anti-HCV drug screening and evaluation.
Trusted partner identification method through trust values for e-business (B2B) supply chain integrator- A qualitative analysis using Sequential Explanatory Strategy

Limited trust, cooperation and communication have been identified as some of the issues that hinder collaboration among business partners. There is a need to do a research in ensuring the entire supply chain components collaborates in a socially trustful environment. This study will provide an identification method for selecting trusted trading partners using the trust values identified. For research methodology, mixed methods research using Sequential Explanatory Strategy (SES) applied in this study. However, this paper only discuss on the Qualitative analysis. Besides, the qualitative analysis steps and software used also been presented. As a contribution, Trust proposed model presented in this paper. Then it will be transformed into an IT implementable prototype.
Guaranteeing on- and off-chip communication in embedded systems

With the ongoing advancement in VLSI technology, the performance of an embedded system is no longer determined primarily by the number and speed of functional units, but by the communication of data and instructions. This results not only in on-chip memory and caching schemes, but also in new methods for on- and off-chip communication. In this paper we present new communication and arbitration schemes that exploit the characteristics of continuous "media" streams, while minimizing the latency for random (e.g., CPU) memory access to background memory. A key result of the methods is the ability to easily guarantee the bandwidth for real-time tasks in a true multi-processor system.
THE SOLUTION PATH FOR THE BALANCED 2 C-SVM

The support vector machines (SVMs) are among the widely used methods in classi cation problems. When the class sizes are biased, however, the SVMs are known to show undesirable behavior. By applying different penalties on each of the classes, the cost sensitive extension of SVM can handle the problem. Chew et al. [1] proposed 2ν-SVM with parameter ν+ and ν−, which serve as the lower bound of the fraction of the support vectors and the upper bound of the fraction of the bounded support vectors of each class. The 2ν-SVM has a solution surface on two dimensional space determined by ν+ and ν−, which complicates solving the problem. When the SVM is balanced (ν+=ν−), the both bounds become to be similar and hence the problem boils down to a simpler problem. In this project, we want to nd the entire solution path for the balanced 2ν-SVM using the recent observation that the solution path for the SVM is piecewise linear in ν [2] and compare the result to the standard C-SVM in unbalanced dataset.
Development and evaluation of a sensor-based system for remote monitoring and treatment of chronic diseases - the continuous care & coaching platform

The steep increase in the number of people with chronic diseases in the Western world is a long recognised problem which forces us to look for less labour intensive and more cost effective methods to deliver health-care. Wider use of telemedicine services seems to be a solution that can contribute substantially to reduction of costs and maintenance of health service quality at a high level, but its implementation in regular healthcare practice often fails. This is no surprise since designing, building and implementing a successful telemedicine application is no trivial task. The reasons for failure are many, and include technical problems and low us-ability, however there are also organisational factors such as the often disruptive effect the introduction of new technologies can have on existing healthcare processes. This paper presents the experience gathered when building our system: the Continuous Care & Coaching Platform (C3PO). This platform was designed to monitor patients with chronic diseases during daily life and provide them with the support they need to develop and maintain an active lifestyle in order to improve quality of life and offset deterioration of health condition. In this paper we share the lessons learned and present results of evaluation studies using earlier versions of the platform. Innovations in the field of wireless sensor technology as well as changing demands from the users led us to redesign and develop a new version of the platform. This process is described, starting with the gath-ering of requirements using a user-centred design approach and derivation of specifications. The components of the platform are described as well as results of recent evaluation studies. Our evaluations and experience with working with patients and healthcare professionals indicate that there is currently a great need to add in-telligence to the platform. The augmentation of the platform with of a smart autonomous health- and lifestyle coach is the current focus of our research which, we believe, will be a crucial next step towards the future of intelligent telemedicine applications.
A Framework for Efficient Mining of Structural Information to Detect Zero-Day Malicious Portable Executables

An exercising device for simulating hula-hoop rotations includes: a housing having at least a track annularly formed in the housing, at least a ball rolling or rotably moving in the track upon a hula-hoop rotation by a user who wears the housing of the exercising device, and an audio and visual device provided on the housing to indicate or display the whirling movements audiovisually.
Evaluating the impact of the number of access points in mobile robots localization using artificial neural networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.
Quality Assessment Using Data Ontologies

Data integration allows to extend the scenario upon which to make decisions however a critical aspect is to determine the quality of the source data. Then makes sense to have an automatic mechanism to measure the quality of the data source, where levels of quality depends on the amount of data with technical anomalies that exist. This paper presents the work we are developing to provide automatic determination of data anomalies. Aims to develop a flexible process, independent of the application domain and with declarative specification this proposal is based on the use of domain ontology and ontology of process metrics. This work shows the use of such ontologies and describes the proposed metrics.