Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical Wireless Mesh Networks Scalable Secure Framework

Wireless Mesh Networks (WMNs) are more scalable than any other wireless networks, because of its unique features such as interoperability, integration and heterogeneous device support. Lacks of robust existing services in WMNs all the features are more vulnerable to various types of attacks. Hence, protect the scalability of WMNs against adversary nodes is a major issue. In this paper, we design Scalable Secure Framework (SSF) to address the scalability issue in WMNs. SSF is designed two algorithms: router authentication and deauthentication on backbone mesh to protect against unauthorized access and colluding attackers. SSF also secures integration and interoperability features of WMN by enhancing security features in 802.11s and Wi-Fi. Eventually security analysis results show that SSF effectively protects against imprinting, replay attack and node deprivation attacks.
Graph-Based Process Planning for Rotational Part Machined with Tolerancing

This paper investigates a methodology and corresponding graph modeling of process planning for cylindrical machined parts with tolerancing. Methods and techniques for representing possible process plans, reducing the complexity and eliminating over-toleranced plans are developed. The method first maps each feature of a part into feasible finishing processes that are capable to achieve the specified tolerances associated with the feature. All possible process plans are then developed by expanding preceding processes of each finishing process. The expanded processes form a graph, or a forest, with processes as nodes and process sequence as links. Processes with same specifications can be further merged and pruned to reduce the complexity of the graph. Tolerance stack-up of each possible plan for simplified results is also further computed by tolerance chart such that over-toleranced plans are eliminated. As there are often many feasible plans for machining a part, the qualified plan that satisfies design specifications is achieved by traversal through the graph imposing tolerance chart. An example is also demonstrated to illustrate the approach and the model. The merit of this method is to employ a unified graph model for representing and reasoning.
A Review of Snake Models in Medical MR Image Segmentation

Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal of the current status of semi-automated and automated methods for the segmentation of MR images with important issues and terminologies. Advantages and disadvantages of various segmentation methods with salient features and their relevancies are also cited.
Dynamic Adaptive Workflow Scheduling for Instance Intensive Cloud Applications

Abstract - Large scale data intensive business and scientific computations from various scientific endeavors are composed as workflows that access shared data, shared pool of resources on demand. Predicting the dynamic properties of the resources and coordinated control of resources and workflows is critical especially selection of algorithms for scheduling cloud workflows in assorted environments built on different system architectures is the most challenging. Most of the cloud applications are data intensive containing large datasets having huge number of workflow instances running on a cloud computing environment which lead to an ever growing need for optimal scheduling of task among the cloud network devices Also cloud computing technology rely on different system infrastructures in the form of grid structures, or actually distributed services (service-based). In cloud computing infrastructure with a “pay per use” context (business-based) the execution cost should be considered which rely on the actual execution time. Each of these different infrastructures demands various workflows scheduling algorithm. The investigation of cloud workflow systems, is a timely issue and worthwhile for increasing performance efforts. The intent of this research work is to evaluate the limitation of existing algorithms and to work on suitable scheduling mechanisms for cloud workflows.
Two-Way Interactive Television: An Emerging Technology for University Level Business School Instruction.

Abstract In this study, we examine data from a public, upper division university to help answer several questions related to the use of two-way interactive television for university level business instruction. The study explores differences between distance learners and their oncampus counterparts in terms of age, gender, overall academic performance, and performance in a specific interactive course. The findings suggest that remote classes are more likely to comprise slightly older students, with a greater proportion of females than oncampus classes. The differences in overall academic performance and in classroom performance were not statistically significant, suggesting that there is no perceptible drop-off in academic performance that can be systematically related to problems with the technology.
Edu‐mining: A Machine Learning Approach

Mining Educational data is an emerging interdisciplinary research area that mainly deals with the development of methods to explore the data stored in educational institutions. The educational data is referred as Edu‐DATA. Queries related to Edu‐DATA are of practical interest as SQL approach is insufficient and needs to be focused in a different way. The paper aims at developing a technique called Edu‐MINING which converts raw data coming from educational institutions using data mining techniques into useful information. The discovered knowledge will have a great impact on the educational research and practices. Edu‐MINING explores Edu‐DATA, discovers new knowledge and suggests useful methods to improve the quality of education with regard to teaching‐learning process. This is illustrated through a case study.
Analyzing Information Systems Security Research to Find Key Topics, Trends, and Opportunities

Abstract What are the key topics for Information Systems (IS) security researchers? How have these topics been changing, and what topics are emerging to offer new opportunities for research? We address these questions by analyzing the abstracts of 261 articles focusing on IS security that have appeared in leading IS journals and journals devoted to this area. Using Latent Semantic Analysis (LSA) to analyze the text of these abstracts uncovers five primary research topics: Security Design & Management, Business Operations Security, Behavioral Aspects, Authentication & Integrity Controls, and Prevention & Detection. These five primary topics are aggregates of more granular topics that are utilized to find trends to understand the changing complexion of IS security research. Our study contributes by developing the key topics and their trends in this area using an analytical and replicable method to synthesize the existing research.
The Initial Retrieval Based on Image Segmentation

Visual image, as a kind of rich content and performance of multimedia information, has been tremendously popular for a long time. Using text-based Image Retrieval TBIR (Text-based Image Retrieval, TBIR) during retrieval will provide keywords and description of the image text matching, operation simple and quick. The defects of TBIR also, however, there are the following: (1) image library image all the need for manual annotation, time-consuming and laborious with subjective factors; (2) image semantics is rich, simple key words cannot fully express its meaning and accurate. Image Retrieval Based on regional RBIR (Region-based Image Retrieval, RBIR) first of all, by using image segmentation method, divides an image into several different regions. At last image matching is converted to match between the regions. We just need to user submits a retrieval image, greatly reducing the user's retrieval burden.
Escape Fire: Designs for the Future of Health Care

Donald M Berwick Jossey Bass, $30, pp 352 ISBN 0 7879 7217 7 Also available as an e-book www.josseybass. com Rating:! [Graphic][1] ! [Graphic][2] ! [Graphic][3] This is a collection of 11 speeches that Dr Donald Berwick, cofounder and president of the US Institute for Healthcare Improvement, delivered to the annual meetings of the National Forum on Quality Improvement in Health Care between 1992 and 2002. [][4] Berwick is modest about his institute and his work, asking in the preface to this anthology, “With so much different, why do these speeches strike me as so repetitive? Metaphor after metaphor, list after list, story … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif [3]: /embed/inline-graphic-3.gif [4]: /embed/graphic-1.gif
Title Decisive coalitions and coherence properties

In a seminal contribution, Hansson has demonstrated that the family of decisive coalitions associated with an Arrovian social welfare function forms an ultrafilter. If the population under consideration is infinite, his result implies the existence of nondictatorial social welfare functions. He goes on to show that if transitivity is weakened to quasi-transitivity as the coherence property imposed on a social relation, the set of decisive coalitions is a filter. We examine the structure of decisive coalitions and analogous concepts with alternative coherence properties, namely, acyclicity and Suzumura consistency, and without assuming that the social relation is complete. Journal of Economic Literature Classification No.: D71.
Expert Systems for Evaluating Business Opportunities: Implementing the Management Advisor at Krypton Chemical

This paper investigates issues arising in procuring and implementing a commercial high-end expert system, Palladian's Management Advisor. This system is intended for improving corporate decisions about financial investments in new business opportunities, e.g. projects involving new plants, equipment, products, or marketing expenditures. We look at Krypton Chemical's experiences with the Management Advisor from both the customer's and the vendor's viewpoints. The discussion raises some difficult questions about what it takes to make high-end financial expert systems successful. The paper then concludes with recommendations intended to improve design, marketing, procurement and implementation practices with respect to such systems.
A robust power system stabilizer design based on Lyapunov's approach

In this paper, a robust power system stabilizer (PSS) is designed based on a nonlinear generator model and a simplified exciter/AVR model. The Lyapunov direct method is applied in the design which insures the global stability of the power system under the proposed PSS. The feedback signals applied for the proposed PSS are local. Simulation results are presented which show that the proposed PSS is very effective to damp the prolonged oscillation and the robustness of the PSS.
Modelling Economic Series: Readings in Econometric Methodology

This book helps economists with the difficult task of constructing econometric models and will be especially useful to those taking courses in applied econometrics who need to learn how to evaluate the validity of the theories and techniques they are taught. The volume contains seventeen papers by the leading authorities in the field, divided into four groups, to each of which the editor provides an introduction. The whole volume is prefaced with an editorial discussion of the controversies of the subject. The methods critically discussed include the traditional ones, such as vector auto-regressions; Bayesian techniques; and the comprehensive modelling strategy advocated by reseachers at the London School of Economics. The papers vary in the degree of sophistication used, but anyone reading the book should gain a sound knowledge of the practical difficulties involved in model specification, evaluation, and interpretation.
Research on Algorithm of Function Set Mining Based on Interests

Function mining aims to discover valid functions from various data which seem not related. Nowadays, the results of most mining algorithms are not capable to characterize the things fully, because the algorithms aim at one simple function, meanwhile, another one can achieve this task, but its efficiency is very low because of the too much iteration. The paper presents one new algorithm named interest-based function set mining algorithm (IFSM), it applies the user's experience, expectations and prior knowledge to the mining process. IFSM succeeds in improving the description and enhancing the mining efficiency and quality.
Hardware/software design implementation of feature detection for a reconfigurable processor

Image processing algorithms are suitable for reconfigurable architectures due to their matrix structures, inherent parallelism and need for flexibility and processing speed. This paper describes a method to implement feature detection on the ReConfigurable Processor (RCP). The RCP is an FPGA- based system, which was built by the VLSI-RCP Research Group at UCSD and L3 Communications. The design is based on the Altera FLEX 10K70. The architecture used to implement feature detector on RCP, software and hardware implementation will be discussed.
Web-based interactive visualization of 3D video mosaics using X3D standard

We present a method of 3D image mosaicing for real 3D representation of roadside buildings, and implement a Web-based interactive visualization environment for the 3D video mosaics created by 3D image mosaicing. The 3D image mosaicing technique developed in our previous work is a very powerful method for creating textured 3D-GIS data without excessive data processing like the laser or stereo system. For the Web-based open access to the 3D video mosaics, we build an interactive visualization environment using X3D, the emerging standard of Web 3D. We conduct the data preprocessing for 3D video mosaics and the X3D modeling for textured 3D data. The data preprocessing includes the conversion of each frame of 3D video mosaics into concatenated image files that can be hyperlinked on the Web. The X3D modeling handles the representation of concatenated images using necessary X3D nodes. By employing X3D as the data format for 3D image mosaics, the real 3D representation of roadside buildings is extended to the Web and mobile service systems.
Implementation of a Virtual Crowd Simulation System

This paper introduces a practical implementation of virtual crowd simulation software. Usual commercial crowd simulation softwares are complex and have program-like script interfaces, which makes an animator hard to learn and use them. Based on the observations that most crowd scenes include walking, running and fighting movements, we have implemented a crowd simulation system that automatically generates movements of virtual characters given user's minimal direction of initial configuration. The system was implemented as a plug-in of Maya which is one of the most commonly used 3D software for movies. Because generated movements are based on optically captured motion clips, the results are sufficiently natural.
A Versatile New Synthesis of 3-Aryl-3H-benzofuran-2-ones

: Aromatic or heteroaromatic hydrocarbons are easily alkylated with 3-hydroxy-3H-benzofuran-2-ones under Friedel-Crafts or acid catalysis to afford 3-aryl-3H-benzofuran-2-ones in good yield. Access to the starting 3-hydroxy-3H-benzofuran-2-ones is easily achievable by reaction of suitably substituted phenols with glyoxylic acid.
Application of Shortest-Path Algorithm in Embedded GIS System

The shortest-path is an important issue in GIS network analysis, and its implementation in embedded systems has already been used widely in the mobile-device-based GPS navigation and city emergency response system fields. Based on our analysis and verification of the Dijkstra algorithm’s application to road network analysis, we presented in detail the design and program implementation of the Dijkstra algorithm and its flow chart. In this paper, the shortest-path example based on Dijkstra algorithm，which was developed in the MapXmobile5.0 and EVC4.0 environment, has been applied to embedded GIS system successfully. The comparison between the results from the program and manually obtained results has shown the Dijkstra algorithm’s feasibility and accuracy.
Introduction to Digital Speech Processing

Since even before the time of Alexander Graham Bell's revolutionary invention, engineers and scientists have studied the phenomenon of speech communication with an eye on creating more efficient and effective systems of human-to-human and human-to-machine communication. Starting in the 1960s, digital signal processing (DSP), assumed a central role in speech studies, and today DSP is the key to realizing the fruits of the knowledge that has been gained through decades of research. Concomitant advances in integrated circuit technology and computer architecture have aligned to create a technological environment with virtually limitless opportunities for innovation in speech communication applications. In this text, we highlight the central role of DSP techniques in modern speech communication research and applications. We present a comprehensive overview of digital speech processing that ranges from the basic nature of the speech signal, through a variety of methods of representing speech in digital form, to applications in voice communication and automatic synthesis and recognition of speech. The breadth of this subject does not allow us to discuss any aspect of speech processing to great depth; hence our goal is to provide a useful introduction to the wide range of important concepts that comprise the field of digital speech processing. A more comprehensive treatment will appear in the forthcoming book, Theory and Application of Digital Speech Processing [101].
Effects of Zoning Structure and Network Detail on Traffic Demand Modeling

By using traffic analysis zones (TAZs), centroids, and a road network as the inputs, traffic demand modeling aggregates trips from the locations of individual tripmakers to TAZ centroids and estimates trips generated between TAZs on the network. Like spatial analysis, traffic demand modeling is subject to the modifiable areal unit problem (MAUP). In this paper we report the findings of a simulation study, which uses eleven zoning structures and two levels of network detail to assess the effects of TAZs, centroids, and network detail on statewide traffic demand modeling in Idaho. First, trips generated between smaller TAZs have shorter trip lengths, higher proportions of interzonal trips, more accurate estimated volume-to-ground-count ratios, and lower percentage root mean square errors (ERMS) between estimated volumes and ground counts. Second, the effect of centroid locations is mixed and generally slight with small TAZs. Third, the level of network detail impacts ERMS values in two ways: larger TAZs produce lower ERMS values than smaller TAZs on the less detailed network, and the detailed network outperforms the less detailed network, regardless of the size of TAZs.
Design of a Single-Phase Rectifier with Improved Power Factor and Low THD using Boost Converter Technique

The method of using Boost type of converter was proposed for a 300W single-phase rectifier in this paper. By designing the necessary techniques and methodology, the overall Power Factor (PF) and Total Harmonic Distortion would be improved to the expectation. The cause of having low PF and high THD for a diode-capacitor type of rectifiers is related to non-linearity of the input current. Method of re-shaping the input current waveform to be similar pattern as the sinusoidal input voltage is done by the Boost converter and the related controls that act as a Power Factor Correction (PFC) circuit. The results of the designed system were compared against with and without PFC control. The international standard IEC 61000-3-2 on harmonics was used as the reference to determine the performance of the project.
Communication Architecture for Biodiversity Information Retrieval(CABIR)

This paper focused on biodiversity database integration. Firstly, the problems are studied and explained. They are divided into four broad categories, which are technical, political, syntactical and semantical. Following this, the approaches to build a database integration system were reviewed after which, the mediator based approach was selected. A new database integration system, which is called CABIR (Communication Architecture for Biodiversity Information Retrieval) was built and discussed thoroughly in this paper. A performance test was also conducted to measure the efficiency of the CABIR system. The development of CABIR system is expected to contribute in the field of biodiversity as this system could link distributed biodiversity databases regardless of the heterogeneity and the platform they were built upon.
Extracting Data Records Based on Global Schema

With the rapid increasing of web data, deep web is the fastest growing web data carrier. Therefore, the research of deep web, especially on extracting data records from Result pages, has already become an urgent task. We present a data records extraction based on Global Schema method, which automatically extracts the query result records from web pages. This method first analyzes the Query interface and result records instances to build a Global Schema by ontology. Then, the Global Schema is used in the process of extracting data records from result pages and storing these data in a table. Experimental results indicate that this method is accurate to extract data records, as well as to save in a table with a Global Schema.
CircRNAwrap – a flexible pipeline for circRNA identification, transcript prediction, and abundance estimation

Circular RNA (circRNA) is a recently described RNA molecule formed by backsplicing, with the 3′ and 5′ ends linked covalently. The study of circRNAs using RNA‐Seq data enables the analysis of genome‐wide endogenous circular transcripts. Although several algorithms for circRNA analysis have been developed, they have thus far had limited application. Additionally, approaches for prediction and validation of the composition of exons in circRNAs are still being developed. In this study, we measured the effectiveness of existing tools on collected and simulated data. Furthermore, we carried out a wide‐ranging study of circRNA workflows, which we named circRNAwrap. Application of circRNAwrap on the included datasets reveals that our novel protocol can assist researchers in the study of circRNA biology.
Unconstrained Handwritten Digit Recognition: Experimentation on MNIST Database

The performance of a character recognition system depends heavily on what features are being used. Though many kinds of features have been developed and their test performances on standard database have been reported, there is still room to improve the recognition rate by developing improved features. In this paper, we propose a Two-dimensional Principal Component Analysis (2D-PCA) for efficient handwritten digit recognition. 2D-PCA is based on 2D image matrices rather than 1D vectors so that image matrix does not need to be transform into a vector prior to feature extraction as done in PCA.1 For subsequent classification purpose we have used Generalized Regression Neural Network (GR.NN). A test performed on the MNIST handwritten numeral database showed a better recognition rate is among the best on the MNIST database.