Miracle-dz/UniFAR-FTUs huggingface dataset:
Real World Connections in High School Mathematics Curriculum and Teaching

Making real world connections in mathematics curricula and in teaching mathematics is generally viewed favorably within the educational community, however, little empirical research has examined how and why to use real world connections in mathematics education based on the views of experts. This study describes the feasibility of the use of real world connections according to high school mathematics teachers and academicians of mathematics education. Opinions of high school mathematics teachers (n=16) and academicians (n=8) about advantages, disadvantages, and examples of real world connections are elicited and reported. Teachers and academicians report several advantages of the use of real world connections in teaching mathematics as well as its disadvantages and limitations. Suggestions about dealing with limiting factors for using real world connections are also reported. Keywords: Mathematics curriculum, real world connections, mathematics teaching
An object-oriented methodology for the design of control software for flexible manufacturing systems

We describe here a systematic method for the design and modeling of flexible manufacturing systems, using object-oriented concepts and Petri nets. We first define the system components in terms of an object model consisting of hierarchical sets of classes and associations. Then, we model the dynamic aspects of the system using statecharts, including exceptions and abnormal behavior. As a third step, we derive Petri nets from those statecharts to realize the concurrency present in the system. Finally we develop a hierarchy of controllers, corresponding to the layers of the object model, for the independent components of the system based on the Petri nets obtained in the previous step. The approach is systematic and relatively easy to apply. It is illustrated through a realistic example. <<ETX>>
Tracking Target Identification Model Based on Multiple Algorithms

In view of current situation of bad data synchronization, image blurring and tracking station stability in tracking target identification, a kind of tracking target identification model based on multiple algorithms was put forward, firstly establishing the image degradation model, using the wavelet algorithm for image preprocessing, doing image edge segmentation by using Robert algorithm after pretreatment, then using the maximum variance threshold method for image threshold segmentation, then extracting target features from the segmented image, and finally using the ABS algorithm to finish target tracking. Experiments proved the proposed model practical and effective.
Biosensor-Based Video Game Control for Physically Disabled Gamers

As it stands today, PC-based video games are commonly controlled through a combination of pointing device and keyboard input. Although this conventional type of interface has a long history of successful implementation, a small group of people remains excluded due to accessibility issues. This is unfortunate, because several studies have shown that virtual environment emersion can provide great benefits to people who suffer from temporary or permanent physical disabilities. This study is aimed at developing a novel interface system that will engage this group of users in video game play by addressing and eliminating the previously mentioned accessibility issues. Through the combined input from an eye-tracking device and a data glove, people suffering from physical limitations will be given the opportunity to experience and interact with virtual environments just like any other user. During interaction with this newly developed system, eye tracking signals will replace the mouse input for on-screen pointing, and a data-glove which will replace conventional keyboard input for in-game navigation and interaction. It is expected that gamers who suffer from previously limiting physical conditions will be able to interact effectively and pleasantly through the new gaming interface, thereby enabling them to overcome their disabilities and enjoy video games just like any other user.
Learning Visual Object Classifiers with only Positive Images

In this paper, a novel approach is proposed for learning visual object classifiers with only positive images. Both positive and negative examples are collected from the positive images, and the false negative examples are filtered out by the Ramp Loss function, which has a strong ability of suppressing the influence of outliers. Meanwhile, the Latent Structural Support Vector Machines are adopted to estimate the best bounding boxes due to the unavoidable annotation errors. In learning the sub-problems, an extremely fast learning algorithm, CCCP-SGD, is proposed to optimize the Ramp Loss-based SVMs based on the Stochastic Gradient Descent algorithm. Experiments demonstrate that the CCCP-SGD algorithm can reduce the computing time both in the training and predicting phases, especially with a significant speedup in training, whilst it can also yield robust generalization performance when dataset is noisy. Besides, the visual object classifiers learnt by our approach with only positive images almost have the same performance as the classifiers learned with both positive and negative examples in object detection tasks.
Feature space trajectory neural net classifier

A new classifier neural network is described for distortion-invariant multi-class pattern recognition. The input analog neurons are a feature space. All distorted aspect views of one object are described by a trajectory in feature space. Classification of test data involves calculation of the closest feature space trajectory. Pose estimation is achieved by determining the closest line segment on the closest trajectory. Rejection of false class clutter is demonstrated. Comparisons are made to other neural network classifiers, including a radial basis function and a new standard backpropagation neural net. The shapes of the different decision surfaces produced by our feature space trajectory classifier are analyzed.
SOADL-EH: Service-Oriented Architecture Description Language Supporting Exception Handling

To solve the problem of the construction of service-oriented software architecture with fault tolerant, the paper proposes SOADL-EH, a novel service-oriented software architecture description language supporting exception handling. With the capability of modeling normal SOA and the provision of software architecture elements such as exception handling services, exception handling connectors and exception handling configurations, etc., this language can separate clearly the exception handling logic from the normal business logic of the service-oriented software architecture layer, which makes up the shortage in exception handling capability of the existing Architecture description language.
A Novel Strategy for a Vertical Web Page Classifier Based on Continuous Learning Naïve Bayes Algorithm

Abstract Web page classification may be considered as a one of the most challenging research areas. Where the web has a huge volume of unstructured documents of distributed data related to a variety of domains; so, considering one base for the classification task will be extremely difficult. In addition, the web is full of noise that will certainly harm the classifier performance especially if it is found in the classifier training data. Generally, it will be more valued to build a domain-oriented classifiers (vertical classifiers) to classify pages related to a specific domain. This paper analyzes a new way of applying Bayes theorem to build a Domain-Oriented Naive Bayes (DONB) classifier. In addition, a main contribution is to introduce a novel classification strategy by adding the continuous learning ability to bayes theorem to build a Continuous Learning Naive Bayes (CLNB) classifier. Where the overfitting problem has a great impact on most web page classification techniques, continuous learning can be considered as a proposed solution, it allows the classifier to adapt itself continuously for achieving better performance. Both classifiers are tested; experimental results have shown that CLNB demonstrate significant performance improvement over DONB , where its accuracy reaches 94.1% after testing 1000 page. In addition, according to continuous learning, more accuracy enhancement is predicted during future tests.
Disparity estimation using edge model for stereo video compression

Stereo video becomes an important issue with the developments of 3D display technologies. While a stereo system provides the perception of 3D depth, the amount of data for stereo video may be doubled compared to mono video. So an efficient stereo video coding technique is essential. Since the stereo video is taken from the same object in the two different views, most of objects in a stereo pair are translated only to the horizontal direction, while objects in subsequent frames of a mono video can be translated to an arbitrary direction, rotated, and zoomed. Hence, unlike in the mono video, the disparity in a stereo pair can be well estimated by a translational motion or disparity if the object boundary is exactly described. In this paper, we propose an efficient disparity estimation scheme based on a edge model describing object boundary in a block, and apply the estimated disparity to stereo video compression. In addition, a disparity regularization scheme, which is proper for the edge model, is proposed to reduce the bits required for coding the block motion vectors and disparity values. It has been found that the proposed algorithms significantly improve the coding efficiency of stereo video sequences.
A novel multicriteria optimization algorithm for the structure determination of multilayer feedforward neural networks

We propose in this paper a novel prescriptive solution to decide the optimum number of neurons in the hidden-layer of multilayer feedforward neural networks. Our approach uses the unconstrained mixed integer nonlinear multicriteria optimization technique. We validate the algorithm using numerical examples. We extend the above results using fuzzy reasoning and constrained optimization techniques to solve the cross-validation problem in a more effective way than the traditional back propagation algorithm. The main features of our approach are that it is a formal method and it draws results from many fields to combine them for the solution of this NP-complete problem.
Source level debugging of dynamically translated programs

The capability to debug a program at the source level is useful and often indispensable. Debuggers use sophisticated techniques to provide a source view of a program, even though what is executing on the hardware is machine code. Debugging techniques evolve with significant changes in programming languages and execution environments. Recently, software dynamic translation (SDT) has emerged as a new execution mechanism. SDT inserts a run-time software layer between the program and the host machine, providing flexibility in execution and program monitoring. Increasingly popular technologies that use this mechanism include dynamic optimization, dynamic instrumentation, security checking, binary translation, and host machine virtualization. However, the run-time program modifications in a SDT environment pose significant challenges to a source level debugger. Currently debugging techniques do not exist for software dynamic translators. This thesis is the first to provide techniques for source level debugging of dynamically translated programs. The thesis proposes a novel debugging framework, called Tdb, that addresses the difficult challenge of maintaining and providing source level information for programs whose binary code changes as the program executes. The proposed framework has a number of important features. First, it does not require or induce changes in the program being debugged. In other words, programs are debugged is their deployment environment. Second, the framework is portable and can be applied to virtually any SDT system. The framework requires minimal changes to an SDT implementation, usually just a few lines of code. Third, the framework can be integrated with existing debuggers, such as Gdb, and does not require changes to these debuggers. This improves usability and adoption, eliminating the learning curve associated with a new debugging environment. Finally, the proposed techniques are efficient. The runtime overhead of the debugged programs is low and comparable to that of existing debuggers. Tdb's techniques have been implemented for three different dynamic translators, on two different hardware platforms. The experimental results demonstrate that source level debugging of dynamically translated programs is feasible, and our implemented systems are portable, usable, and efficient.
Real Time Semantic Analysis of Streaming Sensor Data

Patni, Harshal Kamlesh. M.S., Department of Computer Science and Engineering, Wright State University, 2011. Real Time Semantic Analysis of Streaming Sensor Data. The emergence of dynamic information sources like social, mobile and sensors, has led to ginormous streams of real time data on the web also called, the era of Big Data [1]. Research studies suggest, these dynamic networks have created more data in the last three years than in the entire history of civilization, and this trend will only increase in the coming years [1]. Gigaom 1 article on Big data shows, how the total information generated by these dynamic information sources has completely surpassed the total storage capacity. Thus keeping in mind the problem of ever-increasing data, this thesis focuses on semantically integrating and analyzing multiple, multimodal, heterogeneous streams of weather data with the goal of creating meaningful thematic abstractions in real-time. This is accomplished by implementing an infrastructure for creating and mining thematic abstractions over massive amount of real-time sensor streams. Evaluation section shows 69% data reduction with this approach. 1 http://gigaom.com/cloud/sensor-networks-top-social-networks-for-big-data-2/
AN ASSOCIATIVE MODEL BASED ON QUANTUM SEARCH ALGORITHMS

In this paper, an algorithm of quantum associative memory is proposed using quantum search algorithms. In the associative memory, the problem is to find the data or the nearest data in the meaning of hamming distance from designated data. If the search data in memorized dataset is contained, the problem becomes data search one. In associative memory, it is difficult to find the nearest data in hamming distance. For searching any item in an unsorted database with N items, a classical takes O(N) steps but Grover’s quantum searching algorithm takes only O( p N) steps on perfect graph. By generalizing the idea, Ventura has proposed the associative memory model, but it does not solve the problem of finding the nearest data. On the other hand, quantum search algorithm with O( p N) steps on hypercube is also proposed. Therefore, the idea in this paper is formalizing the problem as quantum search algorithm in hypercube but not in the conventional perfect graph. First, we perform quantum search algorithm by considering quantum walk on hypercube. Further, it is observed search data or the nearest data by using the conventional algorithm with high probability.
FTA Corpus: a parallel corpus of English and Spanish Free Trade Agreements for the study of specialized collocations

This paper describes the Corpus of Free Trade Agreements (henceforth FTA), a specialized parallel corpus in English and Spanish from Europe and America and a smaller subcorpus in English-Norwegian and Spanish-Norwegian that was prepared and then aligned with Translation Corpus Aligner 2 (Hofland & Johansson, 1998). The data was taken from Free Trade Agreements. These agreements are specialized texts officially signed and ratified by several countries and blocks of countries in the last twenty years. Thus, FTAs are a rich repository for terminology and phraseology that is used in different fields of business activity throughout the world. The corpus contains around 1.37 million words in the English section and 1.48 million words in its Spanish counterpart, plus 60,000 words each in the Spanish-Norwegian and English-Norwegian subcorpus. The corpus is being used primarily to study the terms and specialized collocations that include these terms in this kind of specialized texts. Keywords: specialized collocation, specialized parallel corpus, corpus linguistics, Free Trade Agreement
Design of optical receivers for wireless LAN applications

In this paper we consider the design of broadband optical receivers for use in free-space local area networks. After a brief introduction to the relatively new topic of optical wireless LAN's, our attention turns to the design of receivers for use in these wireless systems. Mathematical models of the noise performance of optical wireless receivers are used to compare two different receiver topologies. This allows us to determine which type of receiver is best suited to a particular operating environment.
Development and validation of mathematics courseware usefulness evaluation instrument for teachers

The primary purpose of this study was to develop an instrument for evaluating the usefulness of mathematics courseware and to provide psychometric evidence of validity and reliability. Throughout four phases of this study, 696 participants were involved and six types of MCs were used. Each participant was required to evaluate the courseware heuristically and complete the Mathematics Courseware Usefulness Evaluation Instrument (MCUE). Based on the theoretical perspective, a hypothesized model with three factors which were usability, functionality and efficiency, five sub-factors and seven criteria were proposed. This study presents some empirical evidence of whether the evaluation model and its underlying metrics are reliable and valid for determining the usefulness of Mathematics Courseware. A pool of evaluation metrics were collected based on the MC preliminary evaluation survey, related articles on MC reviews and based on several existing evaluation instruments. Through several experiments, we validate an eight-dimension usefulness attribute involving Ease of use, Attractiveness, User control, Concept presentation, reinforcement, assessment, accuracy and learning support material and 56 metrics.
A Multi-hop Cooperative Transmission Protocol in Mobile Ad-hoc Wireless Networks

In this paper, we propose a multi-hop cooperative transmission protocol over Rayleigh fading channels. In the proposed protocol, the multi-hop cooperative transmission is used to improve the system performance. Due to broadcast nature, we do not limit the receiving node to be only the next node, but the destination and all the nodes between the transmitting node and the destination. The proposed protocol can hence save the average transmit power, compared with multi-hop direct transmission protocol due to the skipped transmissions from some intermediate nodes or chosen relays. The proposed scheme is implemented and evaluated in mobile ad-hoc wireless networks.
The Measurement and Projection of Shelf Space

Practitioners currently have little to guide them in conducting shelf space surveys and projections. This paper reviews the published literature on the topic of measuring, monitoring, and forecasting shelf space for library collections. Then, it discusses in detail a 1981 survey at the University of Guelph Library. It describes theoretical and practical considerations necessary to plan and implement such a survey, discusses specific steps for conducting a survey, and outlines the results of such studies and how they can be applied. It considers different techniques (including the accuracy of different methods of measuring) and compares results with other surveys.
Image Inpainting Based on Fast Inpainting and Sparse Representation Method

Especially there is a wide interest in handling the outdoor surveillance images in autonomous navigation, remote surveillance, automatic incident detection, vision based driver assistant system and law enforcement services. In each case, there is an underlying object or scene which is wished to be captured, processed, analyzed and interpreted. Live recording and transmission of outdoor surveillance images are often one of a forensic tool but while transmission it may introduce some variations in the pixels and it may visible as missing blocks. Thus it is significant to improve the visual quality of such outdoor surveillance images for efficient analysis and recognition. In this paper, a simple effective inpainting method is proposed by combining fast inpainting and sparse representation method. The proposed method fully considers the complementary between the fast inpainting method and sparse representation inpainting approach. This approach inpaints the small size missing blocks more effectively than the existing inpainting methods. The experimental results on practical images show that the proposed algorithm can achieve a plausible visual performance without discontinuity in boundary and blurring. Keywords:Image Inpainting, Sparse Representation, Fast inpainting
Job Satisfaction Among Library Support Staff in Alabama Academic Libraries

Etude sur le taux de satisfaction professionnelle du personnel de soutien des bibliotheques universitaires de l'etat d'Alabama. Un index descriptif des tâches est utilise comme instrument d'etude et les resultats de satisfaction sont relies a des variables definies: sexe, âge, importance des bibliotheques, niveau d'automatisation. Les besoins portant sur une meilleure remuneration, sur les opportunites de promotions de carriere, et sur la qualite de vie sont mis en evidence
The pocket Oxford dictionary of current English

The bestselling Pocket Oxford Dictionary is now available in a completely revised edition. With 65,000 entries and 75,000 numbered definitions, this new edition has 20% more material than previous versions, containing hundreds of new words--from CFC to ecu, and acid house to Karaoke. Other new features include straightforward definitions in everyday English, spelling help for irregular forms, more example sentences, and notes on usage. In addition, this edition now lists compound words as main headwords, clearly divides word senses, and provides unabbreviated, easy-to-follow etymologies. The most up to date and easy to use dictionary of its size, the Pocket Oxford Dictionary remains the ideal language reference for school, home, or office.
Low Power Digital Design Using Asynchronous Logic

LOW POWER DIGITAL DESIGN USING ASYNCHRONOUS LOGIC by Sathish Vimalraj Antony Jayasekar This thesis summarizes research undertaken at San Jose State University between January 2009 and May 2011, which introduces a new method of achieving low power by reducing the dependency of the clock signal in the design. A clock signal consumes power even when the circuit is idle, but asynchronous circuits by default move into the idle state and involve no transition in the circuit during that state. In addition, in an active system, only the subsystem that is in use dissipates power. This work mainly focused on obtaining low power by implementing asynchronous logic. The work also studied the measure of power consumption using asynchronous logic by designing a simple Display Controller. The Display Controller was designed using Verilog HDL and synthesized using Synopsys Design Compiler. The work also studied the trade-offs in power, area, and design complexity in asynchronous design. The power consumed by the synchronous and asynchronous display controllers was measured, and the asynchronous design consumed about 17% less power than its synchronous counterpart. The area of the asynchronous design was twice that of the synchronous one. Power can be reduced by reducing the dependency of the clock signal in the design by choosing asynchronous logic.