Miracle-dz/UniFAR-FTUs huggingface dataset:
Web Service Composition Method Based on FAHP and TOPSIS

Since open and dynamic Internet environment increased the uncertainty of decision-making, the composition service selection based on quality of service (QoS) is still challenging. Besides, user’s weight expressed by fuzzy pair-wise comparison matrix is closer to user’s habits. To solve the difficulties above, Web service composition method based on FAHP and TOPSIS (WSCM_FT) is presented to support the hybrid QoS model expressed by real numbers, interval numbers, triangular fuzzy numbers and intuitionistic fuzzy numbers and user’s weight model expressed by fuzzy pair-wise comparison matrix. WSCA_AT includes five main steps: calculating user’s weight, converting hybrid QoS into intervals, weighting normalized decision-matrix, determining the positive and negative ideal solution, and calculating the close-degrees of candidates. Finally, some experiments are given using actual QoS data to demonstrate the benefits and effectiveness of our approach.
Severe wind shear at Hong Kong International Airport: climatology and case studies

Severe wind shear (headwind change of 30 kn or more) at Hong Kong International Airport is documented in this study. Its climatology, including the number of reports from pilots each year, captured by the wind shear alerting service, its cause and its magnitude are presented. The purpose of the study is to document the characteristics of severe wind shear at an operating airport. Some typical cases of severe wind shear are also examined, such as observation by remote‐sensing instruments and flight data analysis. It is found that the shear magnitudes in pilot reports of severe wind shear, as with pilot reports of wind shear in general, are subjective in nature. They may not be consistent with headwind changes as determined from the flight data. Sometimes, the pilot reports of wind shear may be based on wind trend information available onboard for certain fleets of aircraft. The wind shear can be transient in nature, for which an alert beforehand is difficult.
Moodle-Based Learning Model for Paragraph Writing Class

Todays language classroom is vastly different from that of the twentieth century. The trends in language learning are moving forward in a way as to empower language learners to interact with others. Time and place boundaries are transcended by internet-based media to facilitate the interaction they are eager to make. Language teachers must now be able to utilize internet for language learning, especially in writing class because most learners assume that writing skill is the hardest part of language to learn, which require learners to practice intensively in order to gain mastery. Moodle (Modular, Object-Oriented, Dynamic, and Learning Environment) is one of many internet-based media through which teachers can work with students, whether in distance mode or as a supplement to face-to-face teaching. There are four basic things teachers and students can do with Moodle, namely: storing, communicating, collaborating, and evaluating. Considering those potentials, this research aimed at developing a Moodle learning model of Paragraph Writing at the university level. The result of the research was the theoretical model and the iconic Moodle learning model. The theoretical model presents the Moodle features that were selected according to their suitability with the theory of paragraph writing as well as with the CALL principles and Gagnes nine events of instruction. The iconic model was developed by making some revisions based on the results of the expert validation and the user validation. The iconic learning model could be accessed on www.writing2pbi. mdl2.com. DOI: https://doi.org/10.24071/llt.2015. 180201
Realizing Consructivist Objectives through Collaborative Technologies: Threaded Discussions

Two crucial aspects of implementing instructional technologies effectively in language classrooms are having an understanding of the capabilities of various technologies and evaluating the usefulness of the technologies in realizing curricular goals. This paper presents a situated study -- based on a prominent pedagogical framework -- of the implementation of threaded discussions, a widely used instructional technology, to meet constructivist curricular objectives in university ESL classes. The authors use constructivist principles as a framework to evaluate the three-semester process of their implementation of threaded discussions to fulfill constructivist curricular goals. Of particular interest is the extent to which the technology, as mediated by the instructors, promoted selected cognitive and social skills as well as addressed affective factors and individual differences in students.
Geocraft as a Means to Support the Development of Smart Cities, Getting the People of the Place Involved - Youth Included -

Purpose: In this paper we present Geocraft, a Geo-ICT framework meant to provide the information needed to support the development of smart cities in an accessible and user-friendly way. We explored whether Geocraft could be an effective way to get the people of the place, especially youth, involved in geospatial issues. Methodology/Approach: Geocraft is a virtual environment in which we import real geospatial data into the gaming environment of the popular computer game Minecraft. In Geocraft, we can run real-time impact models to virtually simulate and visualise future developments and their implications, providing the user with relevant information during design processes. Geocraft is linked to Spatial Data Infrastructures (SDIs); data generated or added in Geocraft can upgrade existing databases and SDIs. In four use cases, Geocraft is used by children and high school students to address spatial planning challenges with the help of Geocraft. Findings: Geocraft has an appropriate level of abstraction to effectively represent the real world. The use of Geocraft enhances insight in geospatial relations and can raise awareness and insights in a number of geospatial issues. Geocraft can be used to collect the ideas of citizens, in this case children, and engage them in urban planning issues to raise solutions that can reckon on public support. Geocraft can engage thousands of children working on the same geospatial project in the same online Geocraft world. Spatial scenarios designed in Geocraft can be effectively translated into a feasible spatial design and be imported to the digital environment of professional designers. Moreover, Geocraft turned out to be a valuable educational tool to develop typical 21 th century skills: communicating, finding and evaluating information, creating and innovating, collaborating and problem solving. We conclude that as an easy to use smart visualisation tool, in which everybody can build future scenarios, Geocraft can be used to get the people of the place involved with geospatial issues. Research Limitation/implication: We present qualitative research results. In the next step, we will investigate how statistically significant the improvements in learning skills are. Originality/Value of paper: This paper presents a new digital environment facilitating citizen participation and educational processes. We use actual spatial data to transform physical reality into a parallel and playable virtual version of that reality. Herein we can simulate spatial processes and support collaboration. By doing so, we can provide unique visualizations of complex processes, raising insights across the borders of disciplines in an user-friendly way.
Multicriteria Methodology for the NEEDS Project

This report begins with an overview of multicriteria analysis methods, and the basic principles of developing mathematical models for such analysis. An overview of various representation of user preferences is then presented, including methods based on pairwise comparisons of criteria and those based on scalarizing functions. This is followed by a summary of structures of criteria and alternatives. Next, basic properties of multi-criteria analysis are discussed, followed by a more detailed presentation of the similarities of and differences between the main methods based on scalarizing functions. This report concludes that existing methods do not best meet the needs of the NEEDS project, presents the reasons, and proposes a new methodology for development. Depending upon the development and testing of this new methodology, an existing method will also be chosen as a backup for comparative or alternate use.
Statistical multiplexing with arbitrary on/off sources

In an ATM environment many types of traffic, such as voice, data, and video, are to be efficiently transported by the same network. An ATM multiplexer receives cells (fixed size packets of 53 octets length) from a number of different incoming links and then transmits them out onto a single outgoing link. A finite buffer is provided in the multiplexer to accommodate the multiple arrivals of cells. We develop a methodology for characterizing the superposition process of N/spl ges/2 discrete-time arbitrary on/off sources. The superposition is a discrete-time semi-Markov process with O(2/sup 2N/) states. We use the superposition model to analyze a finite-buffer statistical multiplexer with multiple arbitrary on/off input sources. We study the effect of various traffic parameters on the queueing performance.
Do we succeed in developing problem-solving skills - The engineering students' perspective

This paper examines findings of a problem-solving skills survey conducted at RMIT in 2010-2011, involving 320 student respondents. It will discuss the following questions: (1) Are there any differences in perceptions of students from different schools on their problem-solving skills? (2) Do students perceive themselves as better problem solvers as a result of their engineering degree studies? (3) What activities improved students' problem-solving skills the most? The findings suggest an approach to enhance studentperceived effectiveness of their problem-solving skills.
Bio-Inspired Paradigms in Network Engineering Games

Network Engineering Games (NEGs) is a new emmerging branch of game theory that has been developing in Electrical Engineering Departments. It concerns games that arise in all levels of telecommunication networks. There has been a growing interest among researchers in this community in bio-inspired methodologies in recent years. This is due to two reasons. First, many problems in networking have a lot in common with problems encountered in biology. Some examples are (i) propagation of information in networks, that has often a similar dynamics as the propagation of epidemics within the population. (ii) energy management issues in wireless networks and competition over resources are often similar to issues that have been studied by biologists. Secondly, both equilibria concepts as well as replicator dynamics that arise in evolutionary games are quite relevant to NEGs. In this paper we first present an overview of applications and of tools used in network engineering games, we then describe in more depth bio-inspired tools used in or relevant to network engineering games. We present finally an example of a stochastic epidemic game arising in wireless networks that involves competition over the relaying of information
Sharpening of very high resolution images with spectral distortion minimization

This work presents a viable solution to the problem of merging a multispectral image with an arbitrary number of bands with a higher resolution panchromatic observation. The proposed method relies on the generalized Laplacian pyramid, which is a multiscale oversampled structure in which spatial details are mapped on different scales. The goal is to selectively perform spatial-frequencies spectrum substitution from an image to another with the constraint of thoroughly retaining the spectral information of the coarser data. To this end, a vector injection model has been defined: at each pixel, the detail vector to be added is always parallel to the approximation. Furthermore, its components are scaled by factors measuring the ratio of local gains between the multispectral and panchromatic data. Such a model is calculated at a coarser resolution where both types of data are available and extended to the finer resolution by embedding the modulation transfer function of the multispectral scanner into the multiresolution analysis. In this way, the interband structure model can be extended to the higher resolution without the drawback of the poor enhancement occurring when the model assumes MTFs close to be ideal. Results are presented and discussed on very high resolution QuickBird data of an urban area.
No-reference/Blind Image Quality Assessment: A Survey

ABSTRACT In recent years, no-reference/blind image quality assessment (NR-IQA), as a fundamental but challenging research problem, has been attracting significant attention in the field of digital image processing. NR-IQA aims to build a computational model to quantitatively predict the subjective quality from the distorted image itself without any reference image. Although great efforts have been employed to develop various NR-IQA algorithms, due to its intrinsic difficulty, the issues of NR-IQA are still challenging and remain largely unexplored to date. In this paper, we comprehensively review the fundamental developments of NR-IQA with more emphasis on general-purpose NR-IQA algorithms. First, a brief introduction about NR-IQA algorithms is given. Afterwards, distortion-specific and general-purpose NR-IQA algorithms are presented, focusing on the two major aspects of features extraction and quality prediction. The performances of state-of-the-art NR-IQA algorithms on three commonly used benchmark databases are also evaluated. As the field of NR-IQA is still growing rapidly, we highlight some open challenges about the developments of NR-IQA with some further discussions. We hope that the review presented in this paper can provide a good insight into recent developments in NR-IQA for the researchers who are interested in NR-IQA.
Asynchronous Parallel Block-Coordinate Frank-Wolfe

We develop mini-batched parallel Frank-Wolfe (conditional gradient) methods for smooth convex optimization subject to block-separable constraints. Our work includes the basic (batch) Frank-Wolfe algorithm as well as the recently proposed Block-Coordinate Frank-Wolfe (BCFW) method\citep{lacoste2012block} as special cases. Our algorithm permits asynchronous updates within the minibatch, and is robust to stragglers and faulty worker threads. Our analysis reveals how the potential speedups over BCFW depend on the minibatch size and how one can provably obtain large problem dependent speedups. We present several experiments to indicate empirical behavior of our methods, obtaining significant speedups over competing state-of-the-art (and synchronous) methods on structural SVMs.
An Application of Latent Semantic Analysis for Text Categorization

It is a challenge task to discover major topics from text, which provide a better understanding of the whole corpus and can be regarded as a text categorization problem. The goal of this paper is to apply latent semantic analysis (LSA) approach to extract common factors that representing concepts hidden in a large group of text. LSA involves three steps: the first step is to set up a term-document matrix; the second step is to transform the term frequencies into a term-document matrix using various weighting schemes; the third step performs singular value decomposition (SVD) on the matrix to reduce the dimensionality. The reduced-order SVD is the best k-dimensional approximation to the original matrix. The experiment uses more than fifteen hundreds research paper abstracts from a specific field. Because different factor solutions of the LSA suggest different levels of aggregation, this work examines thirteen solutions in the experiment. The results show that LSA is able to identify not only principle categories, but also major themes contained in the text.
Location-Type Choice for Face-to-Face Social Activities and its Effect on Travel Behavior

Face-to-face social activities, such as joint activities with friends or visiting relatives, involve meeting with other persons at a certain time and location. This (social) spatial-choice behavior is critical for successful urban planning. Recently there has been a rapid emergence of research into social interactions in the field of urban planning and transport. This study contributes to our understanding of the relationships between face-to-face social interaction, location-type choice, and travel by presenting analyses based on social-contact diary data gathered for this study in a large-scale survey conducted in the Netherlands. The analysis framework consists of a set of linked linear regression and discrete choice models to predict the location-type choice for a given face-to-face social interaction, the distance to that location, and the transport mode. Furthermore, the model predicts outcomes of a chain of higher-level decisions including the number of face-to-face interactions and the purpose of the interaction. As independent variables, the model system includes sociodemographic and spatial variables. The results indicate that, to a moderate extent the number of face-to-face social interactions, the purpose of the interactions, and the travel distance can be explained by people's personal and residential variables. These variables have a strong impact on the type of location for the interaction and the transport mode used to get there.
Automated Vascular Smooth Muscle Segmentation, Reconstruction, Classification and Simulation on Whole-Slide Histology

Histology of the microvasculature depicts detailed characteristics relevant to tissue perfusion. One important histologic feature is the smooth muscle component of the microvessel wall, which is responsible for controlling vessel caliber. Abnormalities can cause disease and organ failure, as seen in hypertensive retinopathy, diabetic ischemia, Alzheimer’s disease and improper cardiovascular development. However, assessments of smooth muscle cell content are conventionally performed on selected fields of view on 2D sections, which may lead to measurement bias. We have developed a software platform for automated (1) 3D vascular reconstruction, (2) detection and segmentation of muscularized microvessels, (3) classification of vascular subtypes, and (4) simulation of function through blood flow modeling. Vessels were stained for α-actin using 3,3’-Diaminobenzidine, assessing both normal (n=9 mice) and regenerated vasculature (n=5 at day 14, n=4 at day 28). 2D locally adaptive segmentation involved vessel detection, skeletonization, and fragment connection. 3D reconstruction was performed using our novel nucleus landmark-based registration. Arterioles and venules were categorized using supervised machine learning based on texture and morphometry. Simulation of blood flow for the normal and regenerated vasculature was performed at baseline and during demand based on the structural measures obtained from the above tools. Vessel medial area and vessel wall thickness were found to be greater in the normal vasculature as compared to the regenerated vasculature (p < 0.001) and a higher density of arterioles was found in the regenerated tissue (p < 0.05). Validation showed: a Dice coefficient of 0.88 (compared to manual) for the segmentations, a 3D reconstruction target registration error of 4 μm, and area under the receiver operator curve of 0.89 for vessel classification. We found 89% and 67% decreases in the blood flow through the network for the regenerated vasculature during increased oxygen demand as compared to the normal vasculature, respectively for 14 and 28 days post-ischemia. We developed a software platform for automated vasculature histology analysis involving 3D reconstruction, segmentation, and arteriole vs. venule classification. This advanced the knowledge of conventional histology sampling compared to whole slide analysis, the morphological and density differences in the regenerated vasculature, and the effect of the differences on blood flow and function.
Lowering Evolved Artificial Neural Network Overfitting through High-Probability Mutation

Artificial Neural Networks often suffer from overfitting, both when trained through backpropagation or evolved through a Genetic Algorithm. An attempt at mitigating the overfitting of GA-evolved ANNs is made by using High-Probability Mutation (≈0.95) on binary-encoded ANN weights. The benchmark used is predicting the evolution of an Internet social network using real-world data. A lower bound is put on the overfit, and both prediction error and overfit are further broken down according to ANN hidden-layers size.
International Journal of E-Learning and Educational Technologies in the Digital Media (IJEETDM)

The IJEETDM International Journal of E-Learning and Educational Technologies in the Digital Media aims to provide a forum for scientists, engineers, and practitioners to present their latest research results, ideas, developments and applications in the field of computer architectures, information technology, and mobile technologies. Original unpublished manuscripts are solicited in the following areas including but not limited to: Intelligent Tutoring Systems Security Aspects Immersive Learning Computer-Aided Assessment Collaborative Learning Errors in E-Learning-Community Building Accessibility to Disabled Users Context Dependent Learning E-Learning Platforms, Portals Mobile Learning (M-Learning) Learning Organization Standards and Interoperability Virtual Labs and Virtual Classrooms Digital Libraries for E -Learning Joint Degrees Web-based Learning, Wikis and Blogs Authoring Tools and Content Development Synchronous and Asynchronous Learning Medical Applications E-Learning Hardware and Software AV-Communication and Multimedia Ontologies and Meta-Data Standards Simulated Communities and Online Mentoring E-Testing and New Test Theories Supervising and Managing Student Projects Distance Education Pedagogy Enhancement with E-Learning Metrics and Performance Measurement Assessment Methods in Blended Learning Environments Assessment and Accreditation of Courses and Institutions Course Design and E-Learning Curriculae Lifelong Learning: Continuing Professional Training and Development Theoretical Bases of E-Learning Environments International Partnerships in Teaching Distance and E-Learning in a Global Context Cooperation with Industry in Teaching Higher Education vs. Vocational Training Critical Success Factors in Distance Learning Technology Enhanced Learning Interdisciplinary Programs for Distance Education Impact and Achievements of International Initiatives Technology Support for Pervasive Learning E-learning in Electrical, Mechanical , Civil and Information Engineering Groupware Tools Educating the Educators Blended Learning Assessment Software Tools Teacher Evaluation E-Learning Success Cases
A REVIEW ON PARAMETRIC AND NONPARAMETRIC EMPIRICAL LIKELIHOOD METHOD BASED ON INTERVAL-CENSORED DATA

This paper shall review on the estimation of distribution function for both parametric and nonparametric empirical likelihood method. The focus of this review is on empirical likelihood regression method behavior on censored data and how those methods affect the result of the simulation studies. Moreover, we looking into the case which is involve the partly interval censored data. Keywords: Censored data; Empirical likelihood; Parametric estimation; Nonparametric estimation; Approximation of variance.