Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Objective Optimal Experimental Designs for ER-fMRI Using MATLAB

Designs for event-related functional magnetic resonance imaging (ER-fMRI) that help to efficiently achieve the statistical goals while taking into account the psychological constraints and customized requirements are in great demand. This is not only because of the popularity of ER-fMRI but also because of the high cost of ER-fMRI experiments; being able to collect highly informative data is crucial. In this paper, we develop a MATLAB program which can accommodate many user-specified experimental conditions to efficiently find ER-fMRI optimal designs.
Automated Generation of Compact Models for Fluidic Microsystems

Simulation and design of microfluidic systems requires various level models: high-fidelity models (usually 3D) for design and optimization of particular elements and devices, as well as system-level models allowing for VLSI-scale simulation of such systems. For the latter purpose, reduced or compact models are necessary to make such system simulations computationally feasible. In this paper, we present a design methodology and practical approach for generation of compact models of microfluidic elements. In this procedure we use high-fidelity 3D simulations of the microfluidic devices to extract their characteristics for compact models, and subsequently, to validate the compact model behavior in various regimes of operation. The compact models are generated automatically in the formats that can be directly used in SPICE or SABER. As an example of a nonlinear fluidic device, the generation of compact model for “Tesla valve” is described in detail. Tesla valve is one of the no-moving-parts (NMP) valves used in micropumps in MEMS. Its principle of operation is based on the rectification of the fluid, so it may be considered as a “fluidic diode. ”
Assessing the accuracy of remotely sensed data : principles and practices

Introduction Why Accuracy Assessment? Overview Historical Review Aerial Photography Digital Assessments Data Collection Considerations Classification Scheme Statistical Considerations Data Distribution Randomness Spatial Autocorrelation Sample Size Sampling Scheme Sample Unit Reference Data Collection Basic Collection Forms Basic Analysis Techniques Non-Site Specific Assessments Site Specific Assessments Area Estimation/Correction Practicals Impact of Sample Design on Cost Recommendations for Collecting Reference Data ASources of Variation in Reference Data Photo Interpretation vs. Ground Visitation Interpreter Variability Observations vs. Measurements What is Correct? Labeling Map vs. Labeling the Reference Data Qualitative vs. Quantitative Analysis Local vs. Regional vs. Global Assessments Advanced Topics Beyond the Error Matrix Modifying the Error Matrix Fuzzy Set Theory Measuring Variability Complex Data Sets Change Detection Multi-Layer Assessments California Hardwood Rangeland Monitoring Project Case Study Balancing Statistical Validity with Practical Reality Bibliography
Source and Domain‐Specific Summarization

From 1950–1970, research into automatic summarization essentially centered on documents with a general discourse, with two exceptions: Luhn’s pioneering experiments conducted on technical and scientific corpora [LUH 58] and Pollock & Zamora’s research into summarizing chemistry documents [POL 75]. In the 1990s, several researchers started to work on documents containing a specialized discourse, but as a general rule, the research used the same strategies as those used for summarizing documents with a general discourse. In this chapter, four automatic summarization systems for specialized documents will be presented. Yet Another CHemistry Summarizer (Yachs2) is dedicated to documents about organic chemistry; SummTerm is a system which uses semantic resources to generate summaries of medical articles. The third system is a summarizer combining statistical and linguistic algorithms, applied to the domain of biomedical articles. Finally, there is a summarization system for court decisions. With regard to source specific summarization, four systems oriented at summarizing online documents will be presented: web page summarization, microblog (tweet) summarization, email summarization and opinion summarization.
Induction machine drive parameters estimation

A mathematical method to estimate the basic parameters of induction machines, based on available performance characteristics, is described in this paper. The problems associated with the parameter estimation are analyzed through sensitivity functions. The main feature of the proposed procedure is the possibility to estimate the parameters without the measurement of the machine speed. The theoretical study is completed by experiments on a 3KW induction motor which confirm the theoretical results.
The formation of nominal derivatives in the arabic languagewith a view to computational linguistics

This study investigates the formation of nominal derivatives in Arabic by providing a multi-level analysis in the light of state-of-the-art theories and approaches in modern linguistics. Six types of nominal derivative are described and analyzed: the active participle, the passive participle, the form of exaggeration, the instrumental noun, the qualificative adjective, and the locative noun. The study considers the Form I verb stem as input for forming the six types of nominal derivative (the output). A multi-level approach is employed, involving semantics, syntax, morphology and prosodic phonology. The study establishes an Arabic verb classification in which 980 Form I verbs are divided into 44 classes from which nominal derivatives are derived. Verbs are allocated to classes according to their semantic features and syntactic behaviour. Semantically, the verbs in each class share related meanings and semantic functions. In addition, semantic relations such as synonyms, antonyms, polysemy and hyponym are taken into consideration. Syntactically, the verbs in each class share syntactic behaviour in terms of their transitivity and syntactic frames (in which all the verbs of a class can be used alternatively).
Strongly partitioned system architecture for integration of real-time applications

In recent years, the design and development of technologies for real-time systems have been investigated extensively in response to the demand for fast time-to-the-market and flexible application integration. This dissertation proposes a design approach for integrated real-time systems in which multiple real-time applications with different criticalities can be feasibly operated, while sharing computing and communication resources. The benefits of integrated real-time systems are cost reduction in design, maintenance, and upgrades; and easy adoption of Commercial-Off-The-Shelf (COTS) hardware and software components. The integrated real-time applications must meet their own timing requirements and be protected from other malfunctioning applications. To guarantee timing constraints and dependability of each application, integrated real-time systems must be equipped with strong partitioning schemes. Therefore, we name them strongly partitioned integrated real-time systems (SPIRIT). To prove the theoretical correctness of the model and provide a scheduling analysis method, we developed a fundamental two level scheduling theory, an algorithm for integrated scheduling of partitions and communication channels, and aperiodic task scheduling methods. We also augmented the scheduling model with practical constraints, which are demanded by ARINC 653 Integrated Modular Avionics standards. The scheduling algorithms are evaluated by mathematical analysis and simulation studies, and implemented as an integrated scheduling tool suite. To provide a software platform for integrated real-time systems, we developed a real-time kernel, SPIRIT-μKernel, which implements strong partitioning schemes based on the two-level scheduling theory. The kernel also enables a generic mechanism to host heterogeneous COTS real-time operating systems on top of the kernel. The performance of critical parts of the kernel on the prototype kernel platform is measured in the prototype environment of a PowerPC embedded controller. Finally, we propose a real-time Ethernet named Strong Partitioning Real-Time Ethernet (SPRETHER), which is designed for the communication network of integrated real-time systems. To overcome the lack of deterministic characteristics of Ethernet, we use a software-oriented synchronization approach based on a table-driven proportional access method. We performed scheduling analysis work for SPRETHER and measured performance by experiments on a prototype network.
DFSE equalization of dual-h CPM over UHF MILSATCOM channels

To meet the demand for higher data rate MIL-STD-188-181B has added a set of dual-h continuous phase modulation (CPM) waveforms that nearly double the available data rates without requiring additional transmit power. Unfortunately, rates greater than 56 kbit/s are constrained by severe intersymbol interference (ISI) induced by narrow satellite crystal filters. In this paper, we study the application of decision feedback sequence estimation (DFSE) in order to equalize a 64 kbit/s dual-h quaternary full response CPM waveform transmitted over a representative 25 kHz UHF MILSATCOM channel. The performance is evaluated by Monte-Carlo simulation. Results show DFSE equalization offers an effective and computationally manageable approach to higher data rates using legacy waveforms.
Discrete language models for video retrieval

Finding relevant video content is important for producers of television news, documentanes and commercials. As digital video collections become more widely available, content-based video retrieval tools will likely grow in importance for an even wider group of users. In this thesis we investigate language modelling approaches, that have been the focus of recent attention within the text information retrieval community, for the video search task. Language models are smoothed discrete generative probability distributions generally of text and provide a neat information retrieval formalism that we believe is equally applicable to traditional visual features as to text. We propose to model colour, edge and texture histogrambased features directly with discrete language models and this approach is compatible with further traditional visual feature representations. We provide a comprehensive and robust empirical study of smoothing methods, hierarchical semantic and physical structures, and fusion methods for this language modelling approach to video retrieval. The advantage of our approach is that it provides a consistent, effective and relatively efficient model for video retrieval.
Accelerated learning in multi-layer neural networks

The most popular training method for multi-layer feedforward networks has traditionally been the error backpropagation algorithm. This algorithm has proved to be slow in its convergence to the error minimum; thus, several methods of accelerating learning using backpropagation have been developed. These include using hyperbolic tangent activation functions, momentum, adaptive learning rates and fuzzy control of the learning parameters. These methods are looked at in this paper.
The LEM3 System for Non-Darwinian Evolutionary Computation and Its Application to Complex Function Optimization

LEM3 is the newest implementation of Learnable Evolution Model (LEM), a non-Darwinian evolutionary computation methodology that employs machine learning to guide evolutionary processes. Due to a deep integration of different modes of operation and the use of the advanced machine learning system AQ21, the LEM3 system is a highly efficient and effective implementation of the methodology. LEM3 supports different attribute types for describing individuals in the population, such as nominal, rank, structured, interval and ratio, which makes it applicable to a wide range of practical problems. It also implements very efficient methods for switching between different modes of operation and operators controlling the generation of new individuals. This paper describes the underlying LEM3 algorithm, results from LEM3 testing on selected benchmark function optimization problems (with the number of variables varying from 10 to 1000), and its comparison with EA, a conventional, Darwinian-type evolutionary computation program. In every experiment, without exception, LEM3 outperformed EA in terms of the evolution length (the number of fitness evaluations needed to achieved a desired solution), sometimes very significantly. It also outperformed the previous LEM2 implementation.
Planned Versus Ad-Hoc Deployment of Fixed Amplify-and-Forward Relays

A previous study of the last-mile cost of a hybridcellular-relaying architecture [1], used for downlink coverage, hasshown that the ad-hoc (random) deployment of fixed relays maylead to some cost gains over the purely cellular system, but thatthese gains are strongly dependent on the unit costs. This paperstudies the benefits of using planned relay deployment, modeledby a pruning algorithm. As expected, the use of planned relaysenhances the feasibility of the hybrid architecture with respectto the cellular one. However, the ad-hoc deployment may stillbe feasible, in case the planning costs exceed the savings fromthe reduced number of units. For the hypothetical unit costsconsidered in the numerical examples, the ad-hoc deployment ispreferred if the base stations are of micro-type and the planningcosts exceed 5 keuro per km2.
Object-Oriented Database Design Clearly Explained

1. Introduction 2. Introducing the Object-Oriented Paradigm 3. The Object-Oriented Data Model 4. The Proposed Object Database Standard 5. The Proposed Standards for Object Database 6. Database Design Case Study #1: Mighty-Mite Motors 7. Database Design Case Study #2: East Coast Aquarium 8. Database Design Case Study #3: International Intelligence Agency 9. Implementation Example #1: Oracle 10. Implementation Example #2: Jasmine
Visualization of literary style

Visualization techniques help organize the vast amount of data generated in computational studies of literary style. These techniques are demonstrated by showing two-dimensional representations of the style of the authors of the Federalist Papers. The techniques are used to determine the authorship of the eleven unattributed papers. The results of assigning authors to these papers are consistent with the results of other studies. <<ETX>>
CHASING THE COLOUR GLOVE: VISUAL HAND TRACKING

I present a visual hand tracking system that can recover 3D hand shape and motion from a stream of 2D input images. The hand tracker was originally intended as part of a computer interface for (American) sign language signers, but the system may also serve as a general purpose hand tracking tool. In contrast to some previous 2D-to-sign approaches, I am taking the 3-dimensional nature of the signing process into account. My main objective was to create a versatile hand model and to design an algorithm that uses this model in an effective way to recover the 3D motion of the hand and fingers from 2D clues. The 2D clues are provided by colour-coded markers on the finger joints. The system then finds the 3D shape and motion of the hand by fitting a simple skeletonlike model to the joint locations found in the image. This fitting is done using a nonlinear, continuous optimization approach that gradually adjusts the pose of the model until correspondence with the image is reached. My present implementation of the tracker does not work in real time. However, it should be possible to achieve at least slow real-time tracking with appropriate hardware (a board for real-time image-capturing and colour-marker detection) and some code optimization. Such an 'upgraded7 version of the tracker might serve as a prototype for a Lcolour glove7 package providing a cheap and comfortable-though maybe less powerful-alternative to the data glove.
Software Error Detection through Testing and Analysis

An in-depth review of key techniques in software error detection Software error detection is one of the most challenging problems in software engineering. Now, you can learn how to make the most of software testing by selecting test cases to maximize the probability of revealing latent errors. Software Error Detection through Testing and Analysis begins with a thorough discussion of test-case selection and a review of the concepts, notations, and principles used in the book. Next, it covers: Code-based test-case selection methods Specification-based test-case selection methods Additional advanced topics in testing Analysis of symbolic trace Static analysis Program instrumentation Each chapter begins with a clear introduction and ends with exercises for readers to test their understanding of the material. Plus, appendices provide a logico-mathematical background, glossary, and questions for self-assessment. Assuming a basic background in software quality assurance and an ability to write nontrivial programs, the book is free of programming languages and paradigms used to construct the program under test. Software Error Detection through Testing and Analysis is suitable as a professional reference for software testing specialists, software engineers, software developers, and software programmers. It is also appropriate as a textbook for software engineering, software testing, and software quality assurance courses at the advanced undergraduate and graduate levels.
Scheduling concurrent rpcs in the globe location service

Globe is a wide-area distributed system in which an object can be located through its location-independent identifier. This is done by means of a worldwide location service. In contrast to comparable services, the approach that is followed in Globe allows objects to be highly mobile, replicated, or physically distributed. In addition, our algorithms adapt dynamically to an object’s behavior, resulting in an efficient and above all, scalable approach. The algorithms for updating and looking up an object’s location are expressed as high-level operations on a worldwide search tree. We have designed and implemented a middleware layer providing all the necessary network communication. In this paper, we show that such a layer hardly introduces any additional overhead. The important consequence is that our location service can be designed and implemented at a high level of abstraction. Compared to the design and implementation of comparable worldwide services, this approach is quite unique. 1 The Globe Location Service
A Survey on Template Based Abstractive Summarization of Twitter Topic Using Ensemble SVM with Speech Act

In this todays Internet world, social media service such as Twitter is very popular and used worldwide. In this survey paper we are going to describe various methodology and approches that are useful in twitter topic summarization. In this survey paper, we have described various approch such as analysing and summarizing of twitter tweets using SPUR (Summarization via Pattern Utility and Ranking). In Participant-based Event Summarization we are able to identify each participant that are included in event and generate summary of that event. In automatic summarization of social media we have described a search and summarization framework to extract relevant representative tweets from an unfiltered tweet stream. Also we have described sequential summarization technique for summary creation that uses stream-based approach and the semantic-based approach that create good quality summary. We have also described Phrase Reinforcement algorithm and PageRank algorithm that generate summary by extracting information from the tweets. Twitter topic summarization must handle various numerious, short, dissimilar and noisy nature of tweet. So all the approches that we have described here have its own advantages and limitation over the other. In this survey paper we have try to describe various implemented approches, algorithm, evalution technique and their advantages and limitations.
New Method for Micro-blog User Influence Evaluation based on TransferEntropy

Micro-blog is essentially a kind of web service platform, and it had a wide space with the development of mo- bile Internet. As an important part of social network, influences among the micro-blog users are becoming a hot spot in the research of the micro-blog. This work has a very important theoretical and practical significance for monitoring public opinion. Through the analysis of user's behavior patterns using the transfer Entropy theory, this paper set up an improved model for better evaluating micro-blog users' influences. We processed and analyzed micro-blog users' behaviors based on time series, and focused on the users' "tweet", "retweet", "comment" and "call"(@) behavior patterns. In turn, this would allow us to gain a better understanding of the characteristics of the new web service platform, and at the same time to find its potential values for researches and applications. To validate our method, we crawled data from the Sina weibo, and these data was processed and analyzed by our method in this paper. The experiment result showed that our method performed well on evaluating users' influences.
Elderly support - android application for fall detection and tracking

The purpose of the project is to develop an Android application that is capable of detecting possible falls for the elderly. With the advancement of wireless communications, the world has become smarter and there has been increase in use of smart phones. Android, being an open source platform has made it simple for every individual to develop their own applications, which in turn can be used on Android devices. Falls among the elderly are a serious concern for both families as well as medical professionals, since falls are considered to be the eighth leading cause of death in the United States. Untreated fall injuries in adults 65 or older can result in serious risks and health complications, since 20% of falls require immediate medical attention and about one-tenth of the falls result in fractures. Thus, as mentioned, fall detection is a critical event requiring quick and accurate response, especially for elderly people living by themselves. This is the motivation behind developing an elderly support, which detects a fall and alerts the caretaker regarding the information. The elderly support is about tracking the person and notifying the caretaker if there is an occurrence. One of the main features of this Android application is that it notifies the caretaker with alert messages which contain all the necessary information . The alert messages contain useful information about the people in danger, such as his/her geo location and also corresponding directions on a map. In occasions of false alerts, the supervised person is given the ability to estimate the value of importance of a possible alert and to stop it before proceeding with further steps. This project is geared towards supporting the elderly. The mobile application is capable of detecting possible falls and through a user-friendly interface that can be used to alert relatives, doctors, and other people who take care of the elderly.
Horizontal partitioning ID3 algorithm A new approach of detecting network anomalies using decision tree

In this paper we are proposing a new approach of Detecting Network Anomalies using improved ID3 with horizontal portioning based decision tree. Here we first apply different clustering algorithms and after that we apply horizontal partioning decision tree and then check the network anomalies from the decision tree. Here in this paper we find the comparative analysis of different clustering algorithms and existing id3 based decision tree.