Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Real-Time, Nonintrusive Estimation of Driver Workload in a Simulated Environment

The aim of this research is to work towards building an open-source, platform-independent algorithm capable of predicting driver workload in real-time and in a non-intrusive way. To work towards a system that can also be implemented in on-road settings, we aimed at using off-the-shelf, non-intrusive sensors that could be implemented into the steering wheel and dashboard of current and future generations of cars, making them non-intrusive. In order to build the initial predictive model, a driving simulator experiment was performed. Nineteen participants were required to drive a virtual replication of the Dutch A67 C-ITS corridor between Eindhoven and Venlo. We attempted to induce driver workload by varying weather, traffic composition, traffic density and by asking participants to perform various manoeuvres such as lane changing, merging and exiting. We measured heart rate, skin response, blink and performance measures. Results show that within individuals and within the experimental group, workload was predictable with a high correct rate in both individual models as well as group models. We also evaluated how well the models would generalise when used outside of the experimental setting. Preliminary results for this generalisation are poor. We discuss possible reasons for this and next steps we are planning to take to increase this performance.
Combining Centering-Based Models of Salience and Information Structure for Resolving Intersentential Pronominal Anaphora

In many computational approaches for resolving intersentential pronominal anaphora, the degree of salience of entities is identified by their degree of givenness in the addressee‟s discourse model, so that given (i.e. known, familiar) entities are assigned the highest degree of salience. The most salient entities are chosen as antecedents of pronouns. Centering-based resolution models also adopt this approach (Grosz et al., 1995). A different point of view is taken by Hajičová et al. (1990) who assume that discourse elements in the focal part of an utterance in Information Structure terms have the highest degree of salience. These elements often correspond to new information. Analysing Danish discourse we found that these apparently contrasting interpretations of salience are both valid, but in different contexts. We propose a unified approach combining Centering-based models of salience with Hajičová et al.‟s proposal.
Lecture Notes for Advanced Web Security 2013 Part 1 | Electronic Payments

Electronic or digital payment systems can be defined as a way to pay for something without transferring physical items, such as bills or metallic coins. With that definition, electronic payments are not new, but have been around at least since 1871 when Western Union introduced money transfers using telegraphs. There is today a plethora of ways of paying without using physical bills and coins. Covering all protocols, platforms and hardware solutions would require a course in itself. Instead, a few different aspects will be covered, highlighting the possibilities and the limitations of some different protocols.
Scalable graphical models for social networks

This thesis tackles the problems of efficiently learning large probabilistic models for sparse relational data. Recent dramatic increases in the collection of social network data and the rapid growth in probabilistic and statistical approaches to tractable machine learning made it possible to analyze networks with millions of people. There are many questions one could ask about the formation, properties and dynamics in social networks. This thesis considers the following three questions: (1) given a set of interactions between people, what can be learned about the relations of these people without knowing the true underlying social network; (2) given additional information about each individual in the network, what can be done to improve understanding of their relations; (3) what are the dynamics underlying the formation and the evolution of social networks. We introduce new algorithms and models for learning about relations in a social network and evolution of those relations over time. We present a scalable search procedure for learning Bayesian Networks from the binary events data, i.e. this structure learning algorithm is based solely on the information about people's participation in the set of given events. We present learning results on very large (up to three million nodes) Bayesian Networks and show how they can be used to understand more about the underlying social networks. We extend this model by incorporating information about individuals, such as their affiliation and interests. We use block modeling to both improve the quality of our Bayesian Networks and learn more about group interaction patterns. Finally, we introduce a generative mechanism that provides an explanation of the social network evolution. This dynamic generative model is of exploratory nature. The described models and learning algorithms have one thing in common: they are all motivated by real life phenomena.
Multi-dimensional structural data integration for proactive cyber-defence

The current cyber defences at technical and operational levels have consistently proven inefficient to counter the ever-growing sophistication of the adversary and modern cyber-attacks. Given the interconnectedness of modern societies, physical and cyber events, building proactive cyber defence models that consider the interconnectedness of events and activities across the physical, social and economic realities of cyberspace is an important task that helps detect early warning signs of cyber-attacks and predict the future occurrences of cyber-attacks. The concept of The Entangled cyberspace as introduced in this paper, is a cyber-defence analytical framework that captures the effects of activities on one layer of cyberspace, on the events that emerge on other layers of cyberspace. This article describes cyberspace from an analytical perspective and identifies primary sources of data and information from various layers of cyberspace. The framework provides a solid foundation for building proactive cyber defence models from a seemingly entangled cyberspace.
Design and Implement Hierarchical Topic Knowledge Map for Chinese News with Multi-Document Summarization

With the development of Internet starting diverse learning chances, but that also caused gradually about the problem of information overload for users. As this study observed that on-line news portals only provide simple topic category mechanism rather than on necessary of afterward development of the event or creation of knowledge. This study utilizes text mining technique to analyze Chinese news collections and to construct Hierarchical Topic Knowledge Map (HTKM) so as to resolve the problem of information representation. According to the evaluated results, most of readers considered the representation of knowledge visualization and HTKM make high convenient on readers with understanding the context of news effectively.
Design Patterns' Model for Application Development in Object Oriented Languages

Design patterns are one of the most efficient ways of application development. Many developers are still reluctant to the use of design patterns and development is carried out with not enough attention paid to the reusability and extensibility of the code. Patterns are not to be restricted in the building of integrated development environments and language libraries. Proposed work presents a model which use combination of multiple design patterns for application development in object oriented programming. The model suggested in this proposed work uses hierarchical abstraction of objects created using factory pattern. Facade pattern is also used which makes functional encapsulation possible. Proposed work also presents the scenarios in which use of patterns is likely to improve the code efficiency and reusability. Along with the factory pattern, singleton pattern may also to be used together in the proposed model for their respective benefits.
Research Article Science Teachers and Scientific Argumentation: Trends in Views and Practice

Department of Science, Technology, Engineering, and Mathematics Education, North CarolinaState University, Campus Box 7801, Raleigh, North Carolina 27695-7801Received 12 August 2010; Accepted 2 August 2012Abstract: Current research indicates that student engagement in scientiﬁc argumentation can fostera better understanding of the concepts and the processes of science. Yet opportunities for students toparticipate in authentic argumentation inside the science classroom are rare. There also is little knownabout science teachers’ understandings of argumentation, their ability to participate in this complexpractice, or their views about using argumentation as part of the teaching and learning of science. In thisstudy, the researchers used a cognitive appraisal interview to examine how 30 secondary science teach-ers evaluate alternative explanations, generate an argument to support a speciﬁc explanation, and investi-gate their views about engaging students in argumentation. The analysis of the teachers’ comments andactions during the interview indicates that these teachers relied primarily on their prior content knowl-edge to evaluate the validity of an explanation rather than using available data. Although some of theteachers included data and reasoning in their arguments, most of the teachers crafted an argument thatsimply expanded on a chosen explanation but provided no real support for it. The teachers also men-tioned multiple barriers to the integration of argumentation into the teaching and learning of science,primarily related to their perceptions of students’ ability levels, even though all of these teachers viewedargumentation as a way to help students understand science. 2012 Wiley Periodicals, Inc. J Res SciTeach 49: 1122–1148, 2012Keywords: argumentation; science teachers; cognitive appraisal interview
Internet traffic classification based on TAN

Aimed at the problems of traditional port-based classification and payload-based classification,such as low accuracy and limited application region,tree augmented naive Bayesian classifier is proposed.The method builds a classification model using the network traffic statistical attributes and Bayesian method based on the statistical theory and classifies unknown traffic.The experiments compared with NB,C4.5,the effects of different sizes of dataset and variant weight on performance are analyzed.The results prove that the classifier has perfect classification capability and higher classification accuracy.
The Design of KBS Based on RDB

In this paper,we combine the relation database and knowledge base with the features of their own,and knowledge is stored into relation database.After studying the requirements of KBS and the compositions of knowledge,this paper gives out a simple and convenient structure of KBS,which based on RDB.We also explain that how to use SQL for the forward reasoning of database with the reference of reasoning mechanism.Finally,an example is given as well.
Design of Self-Regulation Slope Compensation Circuit for Buck DC-DC Converter

This paper gives a design of self-regulation slope compensation circuit applied to buck DC-DC converters. On the basis of the root theory of slope compensation and the stability of current loop, a self-regulation slope compensation circuit is designed, whose compensation amount varies with input and output voltages. The slope compensation circuit improves the output current capability and transient response speed of the system. This circuit is designed on the basis of Samsung BCH4 process, and its performances have been verified by Hspice simulation.
Thermal Analysis of Hollow Core Ventilated Slab Systems

Hollow core ventilated slab systems actively utilize building thermal mass through air channels inside precast floor slabs to meet any heating and cooling requirements. Various configurations of hollow core ventilated slab systems have been employed in northern/western Europe, Australia, and Middle East region. Compared to conventional air systems, hollow core slab systems offer some benefits including better thermal comfort, reduced heating and cooling energy consumption, and improved ventilation control. Most of the models reported for ventilated slab systems are based on simplified thermal analysis and do not take account the multi-dimensional heat transfer associated with hollow cores with floor slabs. The research study outlined in the PhD dissertation starts by the development of a comprehensive simulation environment to accurately assess the thermal performance of hollow core ventilated slab systems. Specifically, a transient multi-dimensional numerical solution is developed and validated suitable for the thermal analysis of hollow core ventilated slab systems. The simulation environment is then used to perform a series of parametric analyses to evaluate the performance of ventilated slab systems under various design and operating conditions. In particular, the effects on energy efficiency performance of the ventilated slab systems are considered for a wide range of parameters including convective heat transfer inside hollow cores, supply air inlet temperatures, air mass flow rates, hollow core depths, and hollow core diameters. In addition and in order to reduce computational efforts, the use of 2-D model instead of 3-D
Study and Implementation of Gain Boost Class-CInverter in CMOS 50nm Technology

This paper describes the Gain boost class–C inverter circuit, which is used in place of OTA (Operational Transconductance Amplifier) block in ΣΔ modulator . The gain boost class-C inverter behaves as a low voltage, subthreshold amplifier and boosts its DC gain for the high precision requirement. First a traditional cascade class-C inverter is presented, another inverter circuit present in this paper is “Gain boost class-C inverter”. It is implemented in 50nm CMOS technology and simulation is done using the LTSpice simulation tool.
CDMA Adaptive Watermarking Algorithm Based on Wavelet Basis

A new digital CDMA watermarking algorithm based on orthogonal wavelet basis is proposed in this paper.Harr wavelet basis is changed into a multilevel orthogonal sequence by scaling and translation,which is used to encode the binary image.Then the CDMA encoded watermark is adaptively embedded into the third level detail sub-images of DWT domain.Theoretical analysis and experimental results show that the capacity of the hidden information is raised and the security is enhanced.Compared with Hadamard sequence and improved gold sequence in the simulation,the multilevel sequence performs better than binary sequence in attack-resistance.
Measuring the Social Determinants of Subjective Well-being of Working Women with special reference to Balangoda Divisional Secretariat

Subjective well-being (SWB) is widely considered an essential ingredient of the good life, and represents a hedonic concept with roots in the mid-seventies, when Andrews and Whitey (1976) introduced a well-being structure consisting of three factors such as cognitive evaluation, negative effect and positive effect. According to Diener (1984), subjective well-being covers two main components: affective, including negative and positive emotions; and cognitive, pertaining to satisfaction with life. Negative emotions and satisfaction with life are distinct measures and although positive emotions are related to the latter (Diener et al, 1999). Therefore, subjective well-being can be defined in terms of high levels of positive emotion and satisfaction with life, and low levels of negative emotion. When people describe what they most want out of life, happiness is almost always on the list. Scientists rely primarily on surveys to assess happiness in individuals, but must take into account the fact that people’s levels of subjective well-being are influenced by both internal factors such as personality and outlook, and external factors such as the society in which they live. In recent years, cultural differences in subjective well-being have been explored, following the realisation that there are profound differences in what makes people happy (Diener & Suh, 2000). A growing numbers of scholars have attempted to study the subjective well-being of women, because role of the women in the society and their contribution for the family and economy is very important and significant. A woman can be considered as a predominant character in any society. She plays an important role in the family by encouraging the husband, children and other family members. Women also provide great service in strengthening the household economies and enhancing the welfare of family members.
DEVELOPMENT OF A FAULT LOCATION AND IDENTIFICATION SYSTEM FOR UNDERGROUND POWER CABLES BASED ON WAVELET-ANFIS METHOD

Transmission lines are the backbone of electrical power systems and other power utilities as they are used for transmission and distribution of power. Power is distributed to the end user through either overhead cables or underground cables. In the case of underground cables, their propensity to fail in service increases as they age with time. The increase in failure rates and system breakdowns on older underground power cables are now adversely impacting system reliability and many losses involved; therefore, it is readily apparent that necessary action has to be taken to manage the consequences of this trend. At any given length of a cable, its deterioration or indication of failure manifests itself through discrete defects. Identification of the type of defects and their locations along the length of the cables is vital in order to minimize the operating costs by reducing lengthy and expensive patrols to locate the faults, and to speed up repairs and restoration of power in the lines. In this paper, a method that combines wavelets and neuro-fuzzy technique for fault location and identification is proposed. A 100km, 220KV, 50Hz power transmission line model was developed and different faults and locations simulated in MATLAB/SIMULINK, and then certain selected features of the wavelet transformed signals were used as inputs for training and development of the Adaptive Network Fuzzy Inference System (ANFIS). The results obtained from ANFIS output were compared with the raw values. Comparison of the ANFIS output values and the actual values shows that the percentage error was established to be less than 2.5%. Thus, it can be concluded that the wavelet-ANFIS technique is accurate enough to be used in identifying and locating underground power line faults.
Usability evaluation of intelligent tutoring system

Face-to-face and one-to-one human tutoring is the best tutoring field. Human tutors are not always and everywhere available and that’s why computer based tutoring is developed. Intelligent Tutoring System (ITS) is the software system developed for tutoring human subjects, when human tutor is not available. ITS performance is not as good as human tutors, but ITS domain is improving and recently gaining much popularity. An ITS development project can involve an interdisciplinary team of experts from the domains of learning sciences, cognitive sciences, software engineering, and Human-computer interaction (HCI). ITS is a software intended to be used by human user; any software development project involves designing of user interfaces. Although ITS development has improved, but most of the development has focused on learning sciences and mostly ignoring the user interfaces. This has resulted in current ITS with efficient learning modules, but less efficient interface design. Performance of a software can be measured by it usability, and one way to define quality of a software is by its “ease of use”. Software that is not easy to use by its user can be considered of lower quality. This paper reviews the literature of ITS and usability; with the intention of indicating the currant gap between ITS development and usability of the system. This article also presents a discussion which can provide future directions in ITS development with usability context.
A potential field approach for collision avoidance in 5-axis milling

Introduction 5-axis surface machining is an essential process in the field of aerospace, molds and dies industries. 5-axis milling is required for the realization of difficult parts such as blades and impellers and is also very convenientto improve quality for the machining of deep molds in plastic injection and casting by reducing tool length. Despite the evolution of CAM software, 5-axis tool path programming requires advanced skills and collision detection remains a challenge during the tool path computation. One can distinguish two kinds of tool collision when addressing machining issues. The first one is local and only involves the active part of the tool, the second one is global and in that case the whole body of the tool, the tool holder and even the spindle can be considered. Literature shows that collisions are often avoided using a geometric point of view. Indeed, the study traditionally starts with a representation of the tool geometry [1][2], then by a geometrical representation of the environment [3][4], thirdly by a collision test between the obstacle and the tool [5][6] and finally by a correction and optimization of the tool axis direction to avoid the obstacle [7]. In the field of robotics, other methods based on potential fields virtually attached to the obstacle are developed. These fields emit a repulsive force on the robot when it enters the neighborhood of the obstacle [8][9]. The aim of this paper is to show the benefit of using potential fields in order to prevent collisions during the computation of the tool axis orientation along a given tool path followed by the center of a ball-end milling tool. Main idea In the proposed approach, 5-axis collision avoidance is managed thanks to repulsive forces deriving from a potential field. The tool is considered as a rigid body moving in 3D space on which repulsive and attractive forces are acting. Repulsive forces are due to potential fields attached to check surfaces and an attractive force exerted by a spring is introduced to restore the tool axis orientation in the programmed configuration. Moreover, a viscous damper is used to allow the system returns to steady state without oscillating. The tool center follows the programmed path on the part surface whereas the tool axis orientation is modified to avoid the obstacle by resolving the fundamental principle of dynamics. Differential equations of the tool motion are solved using an Ordinary Differential Equation solver (ODE). The repulsive force comes from robotics [9] and is formulated as follows: