Miracle-dz/UniFAR-FTUs huggingface dataset:
Path Planning Methods in Chemical Engineering

Usually, when the practical motion planning and the shortest path are discoursed, mainly the limited number of tasks is observed. Almost all the tasks associated with the path from one point in 2D or 3D space to another point can be attributed to the usual issue in the practical application. Motion planning and the shortest path have vivid and indisputable importance as human activity in such areas as logistics and robotics. In our work we would like to draw particular attention to the field of application seems to be unnoticeable for the task such as motion planning and the shortest path problem. Due to quite simple examples used, we would like to show that the task of motion planning can be used for simulation and optimization of multi-staged and restricted processes which are presented in chemical engineering accordingly. In the article the simulation and optimization of three important chemical-technological processes for the chemical industry are discussed. The work done gave us the possibility to work out software for simulation and optimization of processes that in some cases facilitates and simplifies the work of professionals engaged in the field of chemical engineering.
Analysis of error sequences for PRML and EPRML signaling performed over Lorentzian channel

It is well-known that PRML and EPRML signaling systems applied to digital magnetic recording suffer in performance due to noise correlation at the output of the channel equalizer. We analyze the error sequences for PRML and EPRML equalized Lorentzian channel in order to determine the channel performance. It is shown that an exact expression for the performance of these channels, in terms of the minimum distance error sequence, can be found. These expressions takes into account the correlation of noise due to equalization. A rigorous analysis of the error sequences is performed to compute the system performance degradations due to noise correlation. The exact expressions for the equalization filter and the output of the low pass filter both in time and frequency domains are also calculated.
Conservative load projection and tracking for fluid-structure problems

The loose coupling of computational fluid dynamics and computational structural dynamics solvers introduces some problems related to the information transfer between the codes. Some techniques developed to solve the problems of the load transfer and interface surface tracking are presented. The main criterion is to achieve conservation of total loads and total energy. The load projection scheme is based on Gaussian integration and fast interpolation algorithms for unstructured grids. The surface tracking algorithm, also based on interpolation, is important for many applications, including aeroelastic deformation of wings due to aerodynamic loads. The methodologies not only improve present fluid-structure interaction simulations, but also increase the range of their applicability. These techniques are of general character and can be used in other multidisciplinary applications as well.
The Calibration of Gravity, Entropy, and Related Models of Spatial Interaction

This paper presents a methodology for deriving best statistics for the calibration of spatial interaction models, and several procedures for finding best parameter values are described. The family of spatial interaction models due to Wilson is first outlined, and then some existing calibration methods are briefly reviewed. A procedure for deriving best statistics based on the principle of maximum-likelihood is then developed from the work of Hyman and Evans, and the methodology is illustrated using the example of a retail gravity model. Five methods for solving the maximum-likelihood equations are outlined: procedures based on a simple first-order iterative process, the Newton—Raphson method for several variables, multivariate Fibonacci search, search using the Simplex method, and search based on quadratic convergence, are all tested and compared. It appears that the Newton—Raphson method is the most efficient, and this is further tested in the calibration of disaggregated residential location models.
Virtual Agents in Brain-Computer Interfaces

The recent development of Brain-Computer Interfaces (BCI) for Virtual Worlds has resulted in a growing interest in realistic visual feedback. In this paper, we investigate the potential role of Virtual Agents in neurofeedback (NF) systems, which constitute an important paradigm for BCI. We discuss the potential of virtual agents to contribute to the success of NF in the specific context of affective BCI. Throughout the paper, we illustrate our presentation with two fully implemented NF prototypes featuring virtual agents. The first is an interactive narrative in which the user empathises with the feature character; the second, an emotion regulation system in which virtual crowd behaviour becomes a metaphor for arousal, as the user attempts to down-regulate their affective state.
Achieving Sustainability Through Sustainable Organizational Evaluation Systems

Organizational evaluation systems become sustainable through being networked, use‐focused, and by undertaking processes aligned with agreed‐upon quality standards. Through being sustainable, organizational evaluation systems can more effectively contribute to the aims and values of sustainable development by undertaking evaluation processes that enable the understanding of complexity, and generate process use, learning loops, and networks of practice. The importance of developing networks of evaluation practice is specifically highlighted in this chapter as it has received less coverage than the importance of use and quality in the literature on evaluation systems.
RequestRodeo: Client Side Protection against Session Riding

The term Session Riding denotes a class of attacks on web applications that exploit implicit authentication processes. There are four distinct methods of implicit authentication found in today’s web applications: Cookies, http authentication, IP address based access control and client side SSL authentication. As many web applications fail to protect their users against Session Riding attacks we introduce RequestRodeo, a client side solution to counter this threat. With the exception of client side SSL, RequestRodeo implements protection against the exploitation of implicit authentication mechanisms. This protection is achieved by removing authentication information from suspicious requests.
Practical uses of location and event data as Linked Open University Data

Linked Data is a practical application of the Semantic Web technologies for connecting data worldwide. The Open Data pursuit has achieved remarkable progress in Europe as well, and studies have shown that it has a positive impact on the quality of education at university level too. Publishing information about university or college course, their corresponding places and related events, such as exams in Linked Data format allows the event information to be aggregated, filtered and delivered to potential participants: students and lecturers via multiple channels and devices. In the previously published version of our Linked Open University Data model organisational hierarchy, staff and publication data were modelled as Linked Data. With this model one can describe faculties, professors, their teaching and research activities, etc. as Linked Data giving a skeleton of human organisation of a university. In this paper we extend the model with temporal and location data including course schedule, event data and indoor location data. To this end we present the state of the current semantic representation formats for course data, event data and indoor location data and describe our approach for creating a unified schema for Linked Open University Data. We have reviewed several overlapping RDF schema and vocabulary, their potential combinations and usability in practice. Finally a formal representation of the model is presented as an OWL 2 ontology. We also provide some use cases where this machine readable data demonstrates its benefits, as well as some RDF data excerpt based on our model and some example SPARQL query Proceedings of the 1 International Conference and Exhibition on Future RFID Technologies Eszterhazy Karoly University of Applied Sciences and Bay Zoltán Nonprofit Ltd. for Applied Research Eger, Hungary, November 5–7, 2014. pp. 151–159 doi: 10.17048/FutureRFID.1. 2014.151
A new system for reading handwritten zip codes

A new method of reading the handwritten zip codes in the U.S. Postal Services CD-ROM database is presented. Zip code images are binarized, segmented and recognised. A recognition driven method for splitting multiple connected digits has been developed; for grouping together of broken digits, the system targets components with near-touching stroke tips, 5-hats, and 4-Ls. The digit recogniser is a majority vote combination of 3 neural networks with a zero rejection performance of 96.53% on the 2711 imperfectly segmented digits in the cedarbs test set. With digit splitting capability disabled, the system performance on the 930 whole zip codes of the test set is 61.0% correct with no errors when up to two rejected symbol positions are allowed. With digit splitting enabled the performance rises to 66.3%.
A MATLAB-Based Study on Approximation Performances of Improved Algorithms of Typical BP Neural Networks

BP neural networks are widely used and the algorithms are various. This paper studies the advantages and disadvantages of improved algorithms of five typical BP networks, based on artificial neural network theories. First, the learning processes of improved algorithms of the five typical BP networks are elaborated on mathematically. Then a specific network is designed on the platform of MATLAB 7.0 to conduct approximation test for a given nonlinear function. At last, a comparison is made between the training speeds and memory consumption of the five BP networks. The simulation results indicate that for small scaled and medium scaled networks, LM optimization algorithm has the best approximation ability, followed by Quasi-Newton algorithm, conjugate gradient method, resilient BP algorithm, adaptive learning rate algorithm. Keywords: BP neural network; Improved algorithm; Function approximation; MATLAB
Extendable Quantum-Dot Cellular Automata Decoding Architecture Using 5-Input Majority Gate

This paper presents a decoder with enable input. This decoder is developed using quantum-dot cellular automata (QCA). QCA opens a completely radical way of microelectronics development and a potential replacement of CMOS based electronics. It ensures highly compact circuits, faster processing speeds, low power consumption. The use of clock in QCA provides power gain which is an important feature and this feature is not available in CMOS electronics. The proposed decoding architecture is designed using 5-input majority gate to keep a regularity so easily extendable for 3:8 or 4:16 decoders and also easy to connect with other circuits.
Efficient Pattern-Based Query search in Text Documents

Text mining is a technique that helps the user to find useful information from a large amount of digital text document. It is a challenging issue to find accurate knowledge (or features) in text documents to help users to find what they want. Most existing text mining methods adopted term-based approaches, but they all suffer from the problem of polysemy and synonymy. Text mining is a technique that helps the user to find useful information from a large amount of digital text document. It is a challenging issue to find accurate knowledge (or features) in text documents to help users to find what they want. Most existing text mining methods adopted term-based approaches, but they all suffer from the problem of polysemy and synonymy. The effective usage and updating of discovered patterns is still an open research issue. Pattern deploying and pattern evolving method has also been proposed in order to refine the patterns that help in improving the effectiveness of pattern discovery. There are two phases that we need to consider when we use pattern-based models in text mining: one is how to discover useful patterns from digital documents, and the other is how to utilize these mined patterns to improve the system's performance. The new approach use pattern (or phrase)-based approaches which perform better in comparison studies than other term-based methods. It uses a pattern taxonomy model. In pattern taxonomy model, given documents are separated into different paragraphs. Keywords— Pattern based approach, pattern Taxonomy model, pattern mining, Information retrieval I. INTRODUCTION Due to the rapid growth of digital data made available in recent years, knowledge discovery and data mining have attracted a great deal of attention with an imminent need for turning such data into useful information and knowledge. In the past decade, a significant number of data mining techniques have been presented in order to perform different knowledge tasks. With a large number of patterns generated by using data mining approaches, how to effectively use and update these patterns is still an open research issue. Text mining is therefore a step in knowledge discovery process in Databases and Datasets. Many data mining techniques have been proposed for mining useful patterns in text documents. It is a challenging issue to find accurate knowledge (or features) in text documents to help users to find what they want. In existing, Information Retrieval (IR) provided many term-based methods to solve this challenge. The term-based methods suffer from the problems of polysemy and synonymy. Polysemy stands for a word having different meanings, and synonymy stands for different words having the same meaning. The Research Work use pattern (or phrase)-based approaches which perform better in comparison studies than other term-based methods.
Intrusion detection by random dispersion and voting on redundant Web server operations

Until now, conventional approaches to the problem of computer security and intrusion tolerance have either tried to block intrusions altogether, or have tried to detect an intrusion in progress and stop it before the execution of malicious code could damage the system or cause it to send corrupted data back to the client. The goal of this thesis is to explore the question of whether voting, in conjunction with several key concepts from the study of fault-tolerant computing namely masking, redundancy, and dispersion can be effectively implemented and used to confront the issues of detecting and handling such abnormalities within the system. Such a mechanism would effectively provide a powerful tool for any high-security system where it could be used to catch and eliminate the majority of all intrusions before they were able to cause substantial damage to the system. There are a number of subgoals that pertain to the issue of voting. The most significant are those of syntactic equivalence and tagging. Respectively, these deal with the issues of determining the true equivalence of two objects to be voted on, and "marking" multiple redundant copies of a single transaction such that they can be associated at a later time. Both of these subgoals must be thoroughly examined in order to design the optimal voting system. The results of this research were tested in a simulation environment. A series of intrusions were then run on the voting system to measure its performance. The outcome of these tests and any gains in intrusion tolerance were documented accordingly. Thesis Supervisor: William Weinstein Title: Senior Researcher, Charles Stark Draper Laboratory Thesis Supervisor: Howard E. Shrobe Title: Principal Research Scientist, MIT Artificial Intelligence Laboratory
An Algorithm for Computing Fingertip Positions of Multifingered Hand

A multifingered hand is more capable of manipulating an object than a typical one degree of freedom gripper. The latter requires parallel faces of an object, while the former dose not. Each finger of a multifingered hand can change its fingertip positions as far as geometry allows. This also implies much sophisticated planning is required to determine fingertip positions appropriate to a given task. Most studies related to a grasp so far, however, pay little attention to this problem. This paper proposes an algorithm that computes fingertip positions from a statics point of view in two dimensions. Since a moment equilibrium equation contains the product of position and force, taking fingertip positions as a variable together with fingertip forces involves nonlinear constraints which are hard to solve. We show that the effect of changing a fingertip position on an edge is statically equivalent to the effect of changing fingertip forces of two fingers fixed at both ends. This equivalency reduces the problem to a nonlinear programming problem that can be solved the same way as linear programming. The mutal dependency of two or more fingers is also examined.
Scalability Analysis of Gleipnir: A Memory Tracing and Profiling Tool, on Titan

Application performance is hindered by a variety of factors but most notably driven by the well know CPU-memory speed gap (also known as the memory wall). Understanding application s memory behavior is key if we are trying to optimize performance. Understanding application performance properties is facilitated with various performance profiling tools. The scope of profiling tools varies in complexity, ease of deployment, profiling performance, and the detail of profiled information. Specifically, using profiling tools for performance analysis is a common task when optimizing and understanding scientific applications on complex and large scale systems such as Cray s XK7. This paper describes the performance characteristics of using Gleipnir, a memory tracing tool, on the Titan Cray XK7 system when instrumenting large applications such as the Community Earth System Model. Gleipnir is a memory tracing tool built as a plug-in tool for the Valgrind instrumentation framework. The goal of Gleipnir is to provide fine-grained trace information. The generated traces are a stream of executed memory transactions mapped to internal structures per process, thread, function, and finally the data structure or variable. Our focus was to expose tool performance characteristics when using Gleipnir with a combination of an external tools such as amore » cache simulator, Gl CSim, to characterize the tool s overall performance. In this paper we describe our experience with deploying Gleipnir on the Titan Cray XK7 system, report on the tool s ease-of-use, and analyze run-time performance characteristics under various workloads. While all performance aspects are important we mainly focus on I/O characteristics analysis due to the emphasis on the tools output which are trace-files. Moreover, the tool is dependent on the run-time system to provide the necessary infrastructure to expose low level system detail; therefore, we also discuss any theoretical benefits that can be achieved if such modules were present. « less
Cloud Based Remote Access Using Virtual Destop

Desktop virtualization includes a suite of possible approaches for vitualizing user access to desktops and applications. The premise of desktop virtualization is to decouple the location of the execution of the application from where the client resides, allowing new client computing paradigms. A viewer is provided on the cellular phone that enables the user to see and manipulate the desktop of various remote systems. The system to be accessed must be running a VNC server and it must be attached to a network. In this architecture, a mobile user exploits virtual machine (VM) technology to rapidly instantiate customized service software on a nearby cloudlet, and then uses that service over a wireless LAN . A proxy is used to send the image of the desktop to the cellular phone, to convert different devices, to suppress network traffics, and to support recovery from an unscheduled disconnection. To reduce user effort and solve problems inherent to the cellular phone’s small screen, several functions are provided on the cellular viewer.
Markov random field based image segmentation with adaptive neighborhoods to the detection of fine structures in SAR data

In the Markov random field (MRF) region label approach for synthetic aperture radar (SAR) image segmentation small structures may be lost. This is due to the filtering effect of the MRF region label model, which is desirable in homogeneously labelled areas like agricultural regions. End-users also interested in resource management, may wish to preserve the small structures such as small roads and rivers. To this end, the neighborhood set used in the MRF region label model has been made adaptive, based on a simple Bayesian network (BN). Results using synthetic aperture radar (SAR) data show that an important improvement of the representation of small structures is possible if they can be detected to some extent using the maximum likelihood approach.
Nondegeneracy of harmonic maps from \begin{document}$ {{\mathbb{R}}^{2}} $\end{document} to \begin{document}$ {{\mathbb{S}}^{2}} $\end{document}

We prove that all harmonic maps from \begin{document}$ {{\mathbb{R}}^{2}} $\end{document} to \begin{document}$ {{\mathbb{S}}^{2}} $\end{document} with finite energy are nondegenerate. That is, for any harmonic map \begin{document}$ u $\end{document} from \begin{document}$ {{\mathbb{R}}^{2}} $\end{document} to \begin{document}$ {{\mathbb{S}}^{2}} $\end{document} of degree \begin{document}$ m\in\mathbb Z $\end{document} , all bounded kernel maps of the linearized operator \begin{document}$ L_u $\end{document} at \begin{document}$ u $\end{document} are generated by those harmonic maps near \begin{document}$ u $\end{document} and hence the real dimension of bounded kernel space of \begin{document}$ L_u $\end{document} is \begin{document}$ 4|m|+2 $\end{document} .
The occupied child and engaged teaching: environmental qualities supporting emergent reading in Kenya

Emergent reading is a ‘make or break it’ benchmark for success at later reading and academic achievement. However, without proper nurturing of the environments and experiences that support physical, social emotional, language, literacy, and cognitive development, many children face early disadvantages and begin school with learning gap. This study sought to establish environmental features that facilitate utilization of learning experiences for teaching emergent reading in Early Childhood Development and Education (ECDE) centres in Kenya. This study used the survey research design. The Ficus Upshot Model of reading development guided the study. Data was collected from 95 randomly selected ECDE teachers using the questionnaire and observation checklist. Data was analyzed both quantitatively and qualitatively. The study found out that the classroom features were neither sufficiently exposed to children nor adequately utilized and so did not absolutely smooth the progress of acquisition of emergent reading skills.