Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional analysis of the sub-system of energy and infrastructure of conventional rail

The paper deals with the functional analysis used to classify and to determine the functions and safety requirements of a complex system. In the functional analysis, the solution for the targeted problem is modelled and decomposed into finer granularity in order to identify all functions, interfaces and requirements. The proposed approach is based on the functional decomposition and the safety analysis and proof to allow systems requirements capture, analysis and validation. The consistency of system requirements and their relation are validated by a formal proof technique. The functional analyses based on functional decomposition and requirements proof have been conducted to analyse the European Conventional Railways System specification. The approach is illustrated by a sub-system of conventional rail to analyze the constituents and the essential requirements needed to achieve interoperability within the trans-European rail system.
Data Mining Techniques

Methods for knowledge discovery in data bases (KDD) have been studied for more than a decade. New methods are required owing to the size and complexity of data collections in administration, business and science. They include procedures for data query and extraction, for data cleaning, data analysis, and methods of knowledge representation. The part of KDD dealing with the analysis of the data has been termed data mining. Common data mining tasks include the induction of association rules, the discovery of functional relationships (classification and regression) and the exploration of groups of similar data objects in clustering. This review provides a discussion of and pointers to efficient algorithms for the common data mining tasks in a mathematical framework. Because of the size and complexity of the data sets, efficient algorithms and often crude approximations play an important role.
Eyebrow recognition: a new biometric technique

Eyebrow is presented as a new biometric for personal identification. Based on feature strings which are extracted from eyebrow images, an eyebrow recognition method is described in detail and analyzed in experiments on a small eyebrow database taken from 32 persons. The results have shown that the presented method can reach the highest accuracies of 93.75% and 90.63% as well as the lowest accuracies of 87.50% and 81.25%, respectively, in two small-scale experiments. Since the recognition accuracies may be higher by improving the current method or introducing other ones, eyebrow is likely to work as a good biometric in the future.
Security in signalling and digital signatures

In the signalling protocols defined for N-ISDN, no provision was made for security functions. Without this feature, the only way, for customers, to ensure the security of their communications, was to rely on the application layer. This is in strong contrast for instance with services like GSM or DECT, where security is part of the service. The goal of the B-ISDN is to be "the" network supporting all kind of services, and to be able of interacting with all non B-ISDN services. Now that a new generation of signalling protocols for B-ISDN is in preparation within CCITT, there exists an opportunity to improve the situation by making a provision for security functionalities at signalling level. In this document we investigate which security functions could be offered in signalling, if it is preferable to do this, and how the security services to be offered should be implemented. 2
Text Mining Aplicado a la Clasificación y Distribución Automática de Correo Electrónico y Detección de Correo SPAM

The Text Mining is the most recent area in investigation of the prosecution of texts. She is defined as the process of discovery of patterns and new knowledge in a collection of texts, that is to say, The Text Mining is the process in charge of the discovery of knowledge that they didn't exist explicitly in any text of the collection, but that they arise of relating the content of several of it. In our development project we apply the Text Mining for the creation of an Anti-SPAM, the same one that this designed for use of the Algorithm of Naive Bayes, and the algorithms of they Kmean and association rules. Having as main objective to detect the mail garbage or SPAM that a user or possesses an electronic mail address receives.
Fundamentals of global positioning system receivers : a software approach

Preface. Preface to the First Edition. Chapter 1. Introduction. Chapter 2. Basic GPS Concept. Chapter 3. Satellite Constellation. Chapter 4. Earth-Centered, Earth-Fixed Coordinate System. Chapter 5. GPS C/A Code Signal Structure. Chapter 6. Receiver Hardware Considerations. Chapter 7. Acquisition of GPSb C/A Code Signals. Chapter 8. Tracking GPS Signals. Chapter 9. GPS Software Receivers. Chapter 10. Acquisition of Weak Signals. Chapter 11. Tracking Weak Signals. Chapter 12. GPS Receiver-Related Subjects. Index.
Assembly code conversion through pattern mapping between two VLIW DSP processors: a case study

We investigate a new pattern mapping method to convert the assembly code between two VLIW digital signal processors. The method is so named because the pattern of the code is kept unchanged during the conversion process in order to manage complexity. As a case study, we first manually convert the assembly code of a typical DSP application from a Texas Instruments TIC62, the source processor, to a high level intermediate code. We then feed the intermediate code to the SC140 compiler backend to generate the assembly code of the target SC140 processor, which is executed on the SC140 simulator. The result thus obtained compares favorably with that obtained directly by compiling and executing the C code on the SC140 system in terms of both validity and total execution cycles.
Computer Arithmetic and Validity - Theory, Implementation, and Applications

The series is devoted to the publication of monographs and high-level textbooks in mathematics, mathematical methods and their applications. Apart from covering important areas of current interest, a major aim is to make topics of an interdisciplinary nature accessible to the non-specialist. The works in this series are addressed to advanced students and researchers in mathematics and theoretical physics. In addition, it can serve as a guide for lectures and seminars on a graduate level. The series de Gruyter Studies in Mathematics was founded ca. 35 years ago by the late Professor Heinz Bauer and Professor Peter Gabriel with the aim to establish a series of monographs and textbooks of high standard, written by scholars with an international reputation presenting current fields of research in pure and applied mathematics. While the editorial board of the Studies has changed with the years, the aspirations of the Studies are unchanged. In times of rapid growth of mathematical knowledge carefully written monographs and textbooks written by experts are needed more than ever, not least to pave the way for the next generation of mathematicians. In this sense the editorial board and the publisher of the Studies are devoted to continue the Studies as a service to the mathematical community. Please submit any book proposals to Niels Jacob. Titles in planning include Wolfgang Herfort, Karl H. Hofmann, and Francesco G. Russo, Periodic Locally Compact Groups: A Study of a Class of Totally Disconnected Topological Groups (2018) Mark M. Meerschaert, Alla Sikorskii, and Mohsen Zayernouri, Stochastic and Computational Models for Fractional Calculus, second edition (2018) Flavia Smarazzo and Alberto Tesei, Measure Theory: Radon Measures, Young Measures, and Applications to Parabolic Problems (2019) Elena Cordero and Luigi Rodino, Time-Frequency Analysis of Operators (2019) Kezheng Li, Group Schemes and Their Actions (2019; together with Tsinghua University Press) Mariusz Lemanczyk, Ergodic Theory: Spectral Theory, Joinings, and Their Applications (2020) Marco Abate, Holomorphic Dynamics on Hyperbolic Complex Manifolds (2021) Miroslava Antic, Joeri Van der Veken, and Luc Vrancken, Differential Geometry of Submanifolds: Submanifolds of Almost Complex Spaces and Almost Product Spaces (2021) Kai Liu, Ilpo Laine, and Lianzhong Yang, Complex Differential-Difference Equations (2021) Rajendra Vasant Gurjar, Kayo Masuda, and Masayoshi Miyanishi, Affine Space Fibrations (2022)
HIV/AIDS and Use of Condom: The Role of Counsellors

Abstract This paper examines the use of condom in this period of HIV/AIDS. HIV/AIDS is a disease transmitted through two main channels; sexual intercourse and blood transfusion. More than 90% of the Nigerian population accept the fact that AIDS is real, deadly and incurable. They do also believe that there are preventive measures to AIDS including the use of condom. Despite the acceptance and awareness of HIV/AIDS, people still engage in multiple sexual partners, casual sex and unprotected sex. This paper advocates the use of condom in every sexual encounter, and outlines that professional counselors can use in promoting the use of condom such as encouraging men and women to use condoms and organizing talks, seminars and symposium on the use of condoms.
Computer Techniques for the Automatic Segmentation of 3D MR Brain Images

The segmentation of magnetic resonance (MR) brain images is an important problem in medical imaging. Accurate segmentation of MR brain images allows a detail study of 3D brain tissue anatomy. It is also of great interest in the study of many brain disorders, where accurate volumetric measurement of the disorders is often required. In view of the importance of the task, much effort has been spent on finding accurate and efficient algorithms for the MRI segmentation problem. This chapter attempts to give the readers an overview of the MR brain segmentation problem, the various image artifacts that are often encountered, and describe some of the current approaches in this area, as well as our own work. To facilitate discussion, we broadly divide current MR brain image segmentation algorithms into three categories: classification-based, region-based, and contour-based methods, and discuss the merits and limitations of these approaches. Following a review of existing methods, we describe our approach for MR brain image segmentation in detail. Our approach is based on a clustering-for-classification framework, using a novel variant of the fuzzy c-means algorithm. We show that by incorporating two key ideas into the clustering algorithm, we are able to take into account the local spatial context, to compensate for the intensity nonuniformity artifact and the partial volume averaging artifact, and to reduce the influence of image noise, during the segmentation process. Extensive experiment results on both simulated and real MR brain images are given to illustrate the effectiveness and robustness of our approach. We conclude this chapter by pointing to some possible future directions in this area.
A quality improvement model to address delays in commencement of radiotherapy in Botswana

The recent increase in demand for radiotherapy services has led to significant delays in commencement of radical radiation treatment in most centres. Radiobiological principles suggest that a delay in starting radiotherapy may have a negative impact on tumour local control. To cope with the growing demand for radiotherapy, modern improvement models need to be accepted and adapted in radiotherapy departments. The PLAN DO STUDY ACT (PDSA) model is an example of such an improvement model which explores new possibilities of improvement through experimentation. This study aimed to determine the causes of radiotherapy delays, and to develop and implement improvements for reducing radiotherapy delays from patients’ referral to a radiotherapy department to the start of radiotherapy at Gaborone Oncology in Botswana. The objectives were to determine the causes of radiotherapy delays, develop and implement improvements of reducing radiotherapy delays using the PDSA model for improvement, and evaluate the effectiveness of the model. Patients who had received radical radiotherapy for head and neck, breast and cervix tumours were analysed as they are the commonly treated cancers at Gaborone Oncology. A retrospective survey was conducted for one year to establish the causes of radiotherapy delays from patient referral to the department to the start of radiation treatment. The PDSA model for improvement was then implemented and monitored for evidence of improvement from May to December 2008. The PDSA model showed significant reduction in radiotherapy delays at Gaborone Oncology. The results showed a decrease in radiotherapy delays in head and neck, breast and cervix cancers from an average delay time of 18.5 days in May 2008 to 8.6 days by December 2008.
Near-Real-Time Data Acquisition and Beamforming for UWB See-Through-Wall System

An ultra-wideband See-Through-Wall (STW) imaging radar system has been developed that could allow the acquisition and processing of the collected radar data in real-time or near-real-time environment. In this paper, we have compared the performance of various Synthetic Aperture Radar image formation methods, and we will demonstrate the wall-correction preliminary results. Additionally, the design of a near-real-time FPGA-based beamforming processor will be presented and samples of our theoretical and experimental collected data.
Effect of implementing structured communication messages on the clinical outcomes of unconscious patients

Background: Patient communication is one of the most important factors associated with quality of care and patient safety, especially in Intensive Care Units (ICUs). However, relatively little is known about the different aspects of communication with unconscious patients, and the effect of communication and outcome measures. Aim: This study aimed to examine effects of implementing structured communication messages (SCMs) on the clinical outcomes of unconscious patients. Methods: A quasi-experimental design was utilized. Sixty unconscious patients were selected from three ICUs of Emergency Hospital of Mansoura University and two ICUs at Main Hospital of Mansoura University. Patients were randomly allocated into two groups (intervention and control group) 30 patients in each. Four tools were used for data collection: physiological adverse events (PAE) assessment tool including (hyperthermia, hypothermia, tachycardia, bradycardia, hypertension, hypotension, hypovolemia, hypervolemia, desaturation, bradypnea, ventilatory distress, hyperglycemia or hypoglycemia), Full Outline of Un-Responsiveness (FOUR) scale, Behavioural Pain Scale (BPS), and Motor Activity Assessment Scale (MAAS). Results: The implementation of SCMs was associated with a decreased incidence of PAE and a statistically significant positive effect on level of consciousness revealed by FOUR scale. Patients in the intervention group maintained in MAAS level (2-3) (calm, cooperative and responsive to touch). The BPS in intervention group significantly decreased following the application of SCMs than control group. Moreover, the mean duration of mechanical ventilation and length of stay in ICU were significantly shorter in the intervention group than in the control group. Conclusions: The SCMs developed, has been shown to facilitate the communication with the unconscious patients therefore, it is recommended for use in a nurse’s daily routine of unconscious patients.
Effect of using peer tutoring to support knowledge sharing in Learning Networks: A cognitive load perspective

Hsiao, Y. P., Brouns, F. , & Sloep, P. B. (2010). Effect of using peer tutoring to support knowledge sharing in Learning Networks: A cognitive load perspective. ICO-Toogdag. November, 4, 2010, Amstelveen, The Netherlands: VU Amsterdam.
A simple human mobility model for opportunistic networks

Opportunistic networking has received considerable interest from the research community in recent years. In this kind of network, mobile nodes exploit mobility to communicate with each other even if a route connecting them never exists. The design of efficient forwarding strategies for opportunistic networks is usually a big challenge. In the opportunistic networks research community, evaluation of new forwarding network protocol relies almost completely on simulation. An important component of such a simulator is the mobility model which should ideally mimic the movements of real mobile nodes (MNs). Clearly the value of the validation of forwarding protocol is highly dependent on mobility models used in the simulations especially if the protocol is exploit information on the prior movement and relationships of nodes. In this paper we assess different types of mobility models that are available. Based on this analysis we present alternative mobility models that can be applied to evaluate protocols for opportunistic data forwarding. We propose a “simple human mobility model” that simulates the movement of mobile nodes in a similar manner of humans. We adopt the proposed model for the building of the School of Computer Science, Cardiff University in order to show how it can be configured to incorporate walls and corridors. We briefly describe an implementation of this model in a simulation network environment. A comparison of our model with other mobility models are also presented and discussed in this paper.
CANARY FILES: GENERATING FAKE FILES TO DETECT CRITICAL DATA LOSS FROM COMPLEX COMPUTER NETWORKS

This paper introduces two concepts: Canary Files and a Canary File management system. A Canary File is a fake computer document that is placed amongst real documents in order to aid in the early detection of unauthorised data access, copying or modification. The name originates from canaries, which were used within coalmines as an early warning to miners. This paper also introduces the Serinus System, a Canary File management system designed to address some of the key challenges associated with operating a cyber deception capability. The Serinus System automates Canary Files generation using content and file statistics drawn from three sources: (1) Internet harvested documents, (2) documents collected from across the entire enterprise environment, and (3) documents within the specific target directory. Each data source is allocated a weighting based on the strength of their relationship to the target directory. The weighting is seeded with a random value to avoid discovery by simple statistical based fake file detection systems. Research is continuing to assess the performance of both Canary Files and the Serinus System.
MANAGEMENT HANDBOOK FOR THE ESTIMATION OF COMPUTER PROGRAMMING COSTS

Abstract : Guidelines are presented to help managers estimate the costs of computer programming. The guidelines summarize a statistical analysis of 169 computer programming efforts with equations to estimate man months, computer hours, and months elapsed, and also planning factors such as man months per thousand instructions. Opinions, rules of thumb, and experience data based upon literature search and experience supplement the statistical results. Forms with the guidelines are organized into six sections corresponding to a six-step division of the computer programming process. Advice is given on the integration of cost estimates into a cost analysis to justify and plan ADP projects.
Inferring AS Relationships Beyond Counting Edges

Routing in the Internet is strongly shaped by the business relationships between administrative domains (Autonomous Systems, AS). In this paper we propose new techniques to classify these relationships. Inspired by Lixin Gao’s seminal work on valley-free paths, we explore several ways to measure the importance of an AS which go beyond the original degree-ranking. In addition we study what information can be gathered by parsing the Routing Registry databases. Furthermore we undertake a thorough analysis and experimental comparison of all the proposed approaches known to date. Not surprisingly, the various methods all reveal different views of the business relations. In fact, by using the different measures or even a combination of them, one can tune the ranking of a given AS by a wide margin.
Active Learning Applied To Image Retrieval

Active learning in content-based image retrieval systems is a challenging task. For effective retrieval of visual information, statistical learning plays a pivotal role. Active learning methods have been considered with increased interest in the statistical learning community. This paper provides algorithms within a statistical framework to extend active learning for content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. Active learning in such context optimizes the training data to get best classification with as few as possible user labeling. Experimental results on Corel database show the comparison of 3 classification strategies to evaluate active learning contribution for online CBIR and the improvement in retrieval performance by active learning approach.
A geometrical approach to planning manipulation tasks. The case of discrete placements and grasps

This paper presents a new geometrical formulation of the manipulation task planning problem in robotics. The problem is shown to be a constrained instance of the coordinated motion planning problem for multiple moving bodies. The constraints are related to the placement and the motion of objects, and can be expressed geometrically. We give a general paradigm for building Manipulation Task Planners based on the proposed formulation. A manipulation task appears as a path in the configuration space of the robot and all movable objects. A {\em manipulation path} is a sequence of constrained paths: {\em transit-paths}, where the robot moves "alone'', and {\em transfer-paths}, where the robot holds an object. The approach consists in building a {\em Manipulation Graph} that models the connectivity between certain regions in the global configuration space by transit-paths and transfer-paths. This approach is then applied to the case of a finite number of object placements and grasps. The nodes in the Manipulation Graph correspond to well identified configurations and the edges correspond to paths built from a series of configuration space slices. An implemented system is presented and discussed.