Miracle-dz/UniFAR-FTUs huggingface dataset:
A review of fetal ECG detection and enhancement methodologies

This paper presents a review of fetal electrocardiogram (FECG) detection and enhancement methodologies developed since 1960. The methods discussed include the subtraction, correlation, orthogonal basis, adaptive filtering and linear combination techniques. Subtraction is the oldest and most straightforward approach. It involves the direct subtraction of a near-thoracic maternal ECG from an abdominally-measured composite of maternal and fetal heart signals. Correlation is used for detection rather than enhancement. Other methods exist which make this technique obsolete. The most current methods for FECG detection and enhancement are the orthogonal basis, adaptive filtering and linear combination methods. These techniques were developed with the idea of producing a scheme which would allow greater flexibility in electrode positioning. An overview is given of the adaptive filter technique and the orthogonal basis methods. Finally, a method using a linear combination of electrodes to enhance FECG signals is discussed. <<ETX>>
Temporal Support in Relational Databases

This paper examines the current state of temporal support in relational databases and the type of situations where we need that support. There has been much research in this area and there were attempts in the American National Standards Institute (ANSI) and the International Organisation for Standardisation (ISO) standards committees in the late 1990s to add an extension called TSQL2 to the existing SQL standard. However no agreement could be reached as it was felt that some of the suggested extensions did not fit well with the relational model, as well as being difficult to implement. TSQL2 was abandoned and since then vendors have added their own data types, and if we are lucky, operators too in an attempt to provide support. However, to novice students and database designers it is often not apparent why some temporal concepts are difficult to deal with in a relational database. In teaching these concepts to students we use a Case Study (based on a real example) which illustrates the problems of providing temporal support by using examples of the data types which could be useful to solve temporal problems and the operators which are necessary to provide this.
Constrained iterative speech enhancement with application to automatic speech recognition

A set of iterative speech enhancement techniques using spectral constraints is extended and evaluated. The approaches apply inter- and intraframe spectral constraints to ensure optimum speech quality across all classes of speech. Constraints are applied on the basis of the presence of perceptually important speech characteristics found during the enhancement procedure. Results show improvement over past techniques for additive white noise distortions. Three points are addressed in the present study. First, a convenient and consistent terminating point for the iterative technique is presented which was previously unavailable. Second, the techniques have been generalized to allow for slowly varying, colored noise. Finally, a comparative evaluation has been performed to determine their usefulness as preprocessors for recognition in extremely noisy environments in the vicinity of 0 dB SNR. <<ETX>>
Multiple choice questions as a ranking tool: a friend or foe?

Traditionally ,Multiple Choice Questions (MCQs) are used to assess knowledge in Medicine (Jeffrey & John, 2001). In Sri Lanka, a common MCQ assessment was recently introduced to evaluate medical students of all faculties of medicine and to tabulate a ranking system. The employment of medical graduates in the state health sector was initially based on a ranking system in the order of merit statistically calculated from a random choice of theory and clinical assessment marks at the final MBBS examination. This required comparison among 6 medical faculties which had non identical syllabuses and their own assessment systems for their graduates. In addition, the exams are usually held at different times of the year as the commencement and conclusion of the medical courses in different faculties vary.
Human Evolutionary Model

The aim of this paper is to propose the Human Evolutionary Model (HEM) as a novel computational model for solving search and optimization problems with one or multiple objectives. The HEM is inspired in human evolution and it will mimic some of its aspects according to the problem characteristics. This model uses intelligence and intuition as its main driving forces, but it is a synergetic computational model that intends to integrate many of the existing and necessary methods for solving complex system problems. This paper is actually a first approach to this method, and we present promising results.
Approaches to adaptive filtering

In this expository paper, several approaches to Adaptive Filtering are discussed. The different methods are divided into four categories of (i) Bayesian Methods, (ii) Maximum Likelihood Methods, (iii) Correlation Methods, and (iv) Covariance-Matching Methods. The relationship between the methods and the difficulties associated with each method are described. New algorithms for the direct estimation of the optimal gain of a Kalman filter are given.
Low-resolution Surface Mapping: a Topological and Geometrical Approach

In this paper we tackle the problem of mapping a surface acquired from a real object onto a piece of the plane, taking into account the topological and geometrical properties of the surface, as well as the speci-ficity of low-resolution acquisitions. We first describe the general background of surfaces unfolding and cutting. We then introduce the cutting process used to manage the topological constraint of the one-to-one mapping, with some speedup improvements. Specific geometrical constraints linked to the low resolution context are detailed, and some experimental results on real and synthetic data are finally presented.
Autonomic Service Control In Next Generation Networks

Current standardization efforts aim towards a unifying platform for fixed and mobile telecommunication services. The IP multimedia subsystem is advocated as the candidate for building Next Generation Networks (NGNs). However, the direction taken in standardization is towards a rather static architecture with centralized features. The downside is an expected increase in service management complexity and the need for highly specialized infrastructures. This paper presents an approach for improving service quality, scalability and reliability while facilitating service management towards self-managing Next Generation Networks. To approach this we utilize and combine functionality available in the network using a Peer-to-Peer based service composition mechanism. The construction of composed services is based on a service chain principle and incorporates information about available services, Quality of Service (QoS) and applicable Servie Level Agreements (SLAs).
Design of Intelligent Comic Make System for Educational Application Based on Comic Script Creation

A comic book with rich picture and storyline, which needs to combine the storyboard creation and visual picture design. In the comic production process requires a lot of manpower and time cost to complete the work. This study presents an intelligent comic production system (ICPS) in which cartoons are subdivided into many design elements and integrated into the framework of Creative Design Resource Integration (CDRIM). By analyzing the creative requirements of cartoon scripts, ICPS reconstructs the new comic design elements and completes the new Comics. The comic design of the paper is to let the author use the text script directly to produce a sub-mirror screen and the role of dialogue in the system. ICPS model to help cartoonists to achieve another comic creation, the use of writing scripts to produce comics, can reduce the traditional cartoon design process of human, capital and time costs. The system provides professional cartoonist design elements during the design of the comic context, as well as non-professional one creative cartoon design training courses.
Exploratory visualization of temporal geospatial data using animation

Niets uit deze uitgave mag worden vermenigvuldigd en/of openbaar gemaakt worden door middle van druk, fotokopie of op welke andere wijze dan ook zonder voorafgaande schrifttelijke toestemming van de auteur. All rights reserved. No part of this publication may be reproduced in any form, by print, photoprint, microfilm or any other means, without written permission of the author. The financial support to undertake this work was made possible through the ITC/DGIS fund. Who modeled in me the zeal for pursuit of knowledge Learn from the mistakes of others-you can never live long enough to make them all yourself-John Luther Over the span of time that I spent working on this thesis I had the privilege of meeting and working with many individuals from all around the world. I am indebted to their friendship, advice, encouragement and criticism, aspects that have enormously contributed to my successful stay and study in the Netherlands. Though I might not be able to name all of these wonderful people by name, I dearly extend my thanks and appreciation to each one of them. I am also indebted to the financial support from the ITC/DGIS fund that enabled me to undertake this research study. To this respect, I thank the office of the research coordinator specially Elisabeth Kosters and Loes Collenbrander. I would also like to extend my sincere gratitude and appreciation to my supervisor and promoter Menno-Jan Kraak and Ferjan Ormeling for their invaluable advice, guidance, and support throughout the research period. I am grateful to Connie Blok for her inspiration and research collaboration that immensely contributed to my involvement in cartographic visualization research. I appreciate the support that I received from the cartography and Allan. My sincere thanks and appreciation also goes to Alan MacEachren, Donna Peuquet, and Andrew Turk, who took time off their valuable schedules during their visits to ITC to discuss and read through portions of my work. Their comments and advice are highly appreciated. Corne van Elzakker did a great job of ensuring that the Usability Laboratory was well equipped and in good working condition. Thanks also for being so eloquent in your lecturers and for the many logistical undertakings on my behalf. The Geoinformatics students (2001/2) who volunteered as test subjects for some aspects of this study contributed greatly to the completion of this work. Willy Kock and Wim Feringa also offered great assistance by providing and pre-processing some …
Differential Inference Testing A Practical Approach to Evaluate Anonymized Data

In order to protect individuals' privacy, data have to be ``well-sanitized'' ( ``well-anonymized'') before sharing them, i.e. one has to remove any personal information before sharing data. However, it is not always clear when data shall be deemed well-sanitized. In this paper, we argue that the evaluation of sanitized data should be based on whether the data allows the inference of sensitive information that is specific to an individual, instead of being centered around the concept of re-identification. We propose a framework to evaluate the effectiveness of different sanitization techniques on a given dataset by measuring how much an individual's record from the sanitized dataset influences the inference of his/her own sensitive attribute. Our intent is not to accurately predict any sensitive attribute but rather to measure the impact of a single record on the inference of sensitive information. We demonstrate our approach by sanitizing two real datasets in different privacy models (k-anonymity, l-diversity, and differential privacy) and evaluate/compare each sanitized dataset in our framework.
Data Integrity and Security in Cloud Environment Using AES Algorithm

Cloud computing is the recent emergent technology of IT industry. Almost every enterprise application is moved to cloud which raised the concern about the integrity and privacy of data of client as well as enterprise officials. The main goal of cloud compting is how to secure, protect the data and process. AES Algorithm is of the out sourced data in cloud enviroment the "effective automatic data reading protocol" and multi server data compression algorithm effecently check.
Approximate answers in intelligent systems

This dissertation investigates the problem of approximate query answering in the context of bibliographic and relational database systems. A bibliographic database is a collection of documents (i.e., books, proceedings, reports) indexed by keywords. The user searches for the documents of his interest by specifying a set of keywords. Thus, a user's query request is inherently vague. Bibliographic databases are commonly referred to in the literature as information retrieval (IR) systems. A relational database system is a collection of relations. The user searches for the tuples of his interest by specifying a query in SQL--a high level query language which is precise. However, many modern applications (e.g., geographical information systems and medical applications) require the system to implement some notion of approximation to facilitate the user's querying process. A relational database extended to allow approximate queries is commonly referred to in the literature as a cooperative database system. Our work proposes the application of Bayesian belief networks for generating approximate answers in the context of IR and cooperative database systems. Further, we also propose a fuzzy set model for cooperative databases. The network model we propose for IR is an alternative to the Turtle & Croft Inference Network Model and overcomes important drawbacks of that model. For instance, our model subsumes all classic models in IR while theirs does not. Further, our model can be extended with information from responses to previous query requests to yield improved retrieval performance. We also propose a second belief network model which can include information about relevant documents provided by the user--a process usually referred to as user relevance feedback. We show that this network model can be extended with information from previous feedback cycles to yield improved retrieval performance when compared to strategies based on the Rochio formulation. In the context of cooperative databases, we propose a belief network model which can be successfully used to merge semantic metric distances, complex queries, and a ranking strategy in consistent fashion. Through examples, we illustrate the main advantages of this model. The fuzzy set model we propose for cooperative databases is based on two basic principles that can be easily grasped by the user. As a result, the user is able to mentally mimic the system behavior to gain greater understanding of the ranking.
Design and analysis of a novel cable-actuated palletizing robot

To meet the requirements in terms of large workspace, low inertia, and high degree of accuracy, a novel palletizing robot is introduced in this article. Utilizing spatial hybrid cable-actuated serial–parallel structure and parallelogram mechanism, the robot is able to achieve favorable potentials for stiffness, modularity, and reconfigurability. The kinematics and statics of the robot are investigated, and an algorithm is subsequently proposed to calculate the workspace of the limited degree of freedom cable-actuated serial–parallel manipulator. Then the workspace of the robot under different loads is calculated, and the topological properties of the workspace under different loads are compared and analyzed in detail. The results demonstrate that the proposed structure significantly enlarges the workspace and can also complete palletizing tasks effectively.
Learning Analytics: From Big Data to Meaningful Data

This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field, and identify some of the trends in recent research. As the field continues to expand,it seems that there are at least three directions of vigorous growth: the inclusion of multimodal data (gesture, eye-tracking, biosensors, etc.), the diversification of learning environments (MOOCs, classrooms, and hands-on learning environments.), and new types of research questions as researchers begin to consider a broader set of learning-related constructs (moving away, for example, from the focus on student retention.)
A GLOBAL SEARCH FOR UNIVERSAL MODELS OF EDUCATION AND TRAINING IN ELECTRONIC RECORDS MANAGEMENT

In developed countries, education and training for records practitioners and other key players on electronic records management (ERM) are provided by the universities, professional organisations, private consultants and individual archival institutions, or through collaboration between the various organisations. However, evidence from the review of literature suggests that in many countries especially those in Asia, the present situation is characterised by a lack of local expertise, experience and facilities. As a result, records practitioners are sent to developed countries to acquire knowledge and skills on ERM, or foreign experts are brought in to conduct in-service training for government record keepers. According to the literature, these issues have already been addressed in the UK and Europe where education and training programmes on ERM have been developed to provide the key players with the required knowledge and skills. Pursuance to this development, an international survey was conducted to identify universal models of education and training programmes in ERM. This article reports and discusses the findings of the survey questionnaire of the national archival institutions and related professional associations world wide for administrators, archivists, information managers, IT specialists and records managers.
A Hardware Design of High-throughput and Resource-saving Image Convolution

This paper proposes a hardware design of high-throughput and resource-saving image convolution. The key part of the design is consist of two aspects, buffer and computing part. For the buffer part, serial shifting register chain has been applied to buffer some of the pixels so that large number of buffer resources could be saved, thus realizing data multiplex; as for computing part, logic resource consumed is not much but time consumed for the serial convolution operation is too long. Since buffer part consumes little resource, logic duplication can be used to realize parallel design, thus accelerating the convolution operation, which reduces the time consumed largely and makes the throughput higher. In one word, this design not only accelerates the convolution operation, but also reduces the consumed resources.
Multilevel Encryption for Ensuring Public Cloud

cloud computing is a new era of the modern world. The cloud computing flexibility is a function of the allocation of resources on authority's request. The improvement of the cloud technology also increases the security issues twice. The problems on the cloud computing are data privacy and data stealing. This paper has proposed Multi level of Encryption algorithms used to secure the data. Compared between other encryption methods, these methods have very secured level. This proposed method is complicated to understand the cipher text compared with the other methods.
Turbo multiuser detection with integrated channel estimation for differentially coded CDMA systems.

This thesis is concerned with iterative joint multiuser detection (MUD) and channel esti­ mation for the uplink of asynchronous direct-sequence code-division multiple-access (DSCDMA) systems in multipath channels. For the base station of a CDMA system, it is shown that it is possible to design a receiver tha t can recover the multiuser information symbols of all the users within its own cell without any prior knowledge of the multipath channel or the spreading codes of users outside the cell. In this thesis, for two different scenarios, we propose two receiver structures that take all the necessary signal processing operations into account simultaneously. In other words, the proposed iterative receivers can jointly perform channel estimation, channel equalization, MUD, and channel decoding. The proposed iter­ ative processing algorithms allow earlier stages of a receiver (e.g., the channel estimator) to refine their processing based on soft information obtained from later stages (e.g., the channel decoder) to provide a refine estimate of some signal or channel parameters. First, a turbo (iterative) receiver structure is proposed for the uplink of coded CDMA systems in the presence of unknown interference. The proposed receiver consists of a first stage that performs soft interference cancellation and group-blind linear minimum meansquare-error (MMSE) filtering, followed by a second stage that performs channel decoding. The proposed group-blind linear MMSE filter suppresses the residual multiple-access inter­ ference (MAI) from known users based on the spreading codes and the channel character­ istics of these users, while suppressing the interference from other unknown users using a
Cloud Computing Online Scheduling

Cloud computing has gained a lot of attention to be used as a computing model for a variety of application domains. Task scheduling is the fundamental issue in this environment. To utilize cloud efficiently, a good task scheduling algorithm is needed to assign tasks to resources in cloud. Cloud task can be divided into two categories such as on-line mode service and the batch mode service. In this paper, online cloud task scheduling based on virtual machine adaptive fault tolerance and load balancing using ant colony algorithm is proposed. The main contribution of this work is that load balancing factor is added and the system tolerates the faults by tacking the decision on the basis of reliability of the virtual machines in scheduling process. The proposed scheduling strategy was simulated using the Cloudsim toolkit package. Experimental results show that the proposed algorithm achieved the better load balance than Join-shortest-queue (JSQ) and Modified Ant Colony Optimization (MACO) algorithms.
Control of 2R underactuated manipulator with friction

Manipulators with free joints are typical underactuated mechanisms. The constraints are second-order nonholonomic and control of such systems is quite difficult. Many researches have been made on control of such systems without considering friction at free joints. In this paper, we analyze the behaviors of 2R underactuated manipulators with friction at free joints by the averaging method in response to a periodic input. We define an energy-like function from analyses of frictionless systems and utilize it to the system with friction for feedback stabilization onto an invariant elliptic manifold. We also propose a control method to stabilize it to a stable manifold for systems with friction. The effectiveness of the method is verified by experiments.