Miracle-dz/UniFAR-FTUs huggingface dataset:
Utilization and Analysis of Layout Characteristics in Document Layout Automation Techniques

The flow of information is continually increasing due to the ubiquitous use of information technology. Information communication and distribution is highly automated to meet the demand for an unobtrusive information flow. Servers, systems and applications overtake the tasks of gathering, storing, distributing and selecting the diverse information requests, though the task of presenting the information in a communicatively effective manner is still a manual tasks handled by professionals. In certain contexts, such as the distribution of dynamically generated content by web servers, the manual tasks restrict the system from performing as efficiently as possible. At the moment there is a great potential for production efficacy gain by automating the workflow to some extent. The system utilization of a document layout generator may cover some designer functions and thereby reducing task redundancy related to the presentation of information. Document layout automation algorithms are typically implemented with weighting metrics for the purpose of quantifying layout characteristics, also called layout attributes, of generated layout in the perspective of visual quality. Several different weighting metrics and algorithms have been studied and implemented in the past years, but still they fail to produce layouts matching the general performance of a designer in practice. Literature suggests that many of the weighting metrics, despite their advanced mathematical implementation, lack the implementation of a persistent set of preference attributes. Weighting metrics based on an extended set of preference attributes related to designer preferences may further improve the performance of a document layout automation algorithm. The scope of this thesis is to establish knowledge about the utilization of document layout attribute operators in document layout automation. How do document layout automation system with an extended attribute operator set perform related to layout quality? The study presented in this thesis reveals that implementing operators for the layout characteristics alignment and equilibrium in layout generators doesn’t automatically enhance the visually perceived quality of the layout generated. A second scope of this thesis is to generalize the modeling paradigms derived from existing literature related to document layout automation systems. Several systems have been proposed for solving layout automation related problems, but still there is a lack of literature related to the generalization of layout automation system models. Is it possible to recognize modeling patterns can be generalized an utilized in a wide range of layout automation systems, applications and / or components? We propose a layout automation system modeling framework based on a grounded theory study of related literature. The presented proof of concept system LaG is modeled based on this modeling framework and provides an affirmation of the modeling framework flexibility regarding layout automation technology and architectural modeling patterns.
A Review on Software Defect Prediction Techniques Using Product Metrics

Presently, complexity and volume of software systems are increasing with a rapid rate. In some cases it improves performance and brings efficient outcome, but unfortunately in several situations it leads to elevated cost for testing, meaningless outcome and inferior quality, even there is no trustworthiness of the products. Fault prediction in software plays a vital role in enhancing the software excellence as well as it helps in software testing to decrease the price and time. Conventionally, to describe the difficulty and calculate the duration of the programming, software metrics can be utilized. To forecast the amount of faults in module and utilizing software metrics, an extensive investigation is performed. With the purpose of recognizing the causes which importantly enhances the fault prediction models related to product metrics, this empirical research is made. This paper visits various software metrics and suggested procedures through which software defect prediction is enhanced and also summarizes those techniques.
Semi-Automatic Forensic Speaker Identification

CEPEDA, LUIS. Semi-Automatic Forensic Speaker Identification. (Under the direction of Robert D.Rodman, David F. McAllister, Donald D. Bitzer, and Pam Arroway). With the world now facing the threat of global terrorism, speaker identification research has become a very important topic in forensics as well as academia. Many different methods have been employed for speaker identification. This thesis presents a novel 4step text-independent method. This method uses the averaging of the spectra of a set of phonemes to classify an unknown speaker as being one of the known speakers or as being someone other than the known speakers. This thesis also discusses the results of three different experiments with the method: a closed-set experiment, an out of set experiment, and an open set experiment. SEMI-AUTOMATIC FORENSIC SPEAKER IDENTIFICATION
A Social Network based Bandwidth Sharing Model for P2P Streaming Service

The combination of social network and P2P streaming service created a new kind of peers, these peers only share their bandwidth to social-connected peers and they do not need to watch the streaming video. Because of the particularity of such peers, ordinary P2P modelsdo not apply to this type of peers. Therefore, we propose a social network-based bandwidth sharing model. By creating download and upload neighbor list, our model separates the transmission of data blocks. Peer requests data blocks from peers in download neighbor list by the data block missing degree of peers in upload neighbor list. Meanwhile we redefine the buffer of social-connected peers, make the social-connected peers better collaborate with the sharing peers. Therefore the social-connected peers will not receive duplicate data blocks. Experiment data shows our sharing model could maximize the sharing ratio of sharing peers, and improve the playback quality of social-connected peers. When the number of sharing peers reaches a certain proportion, the playback delay of P2P streaming service with sharing peers is better than the playback delay of normal P2P streaming service. Keyword: P2P streaming, social network, bandwidth share, social-connected peer
A Unequalven Clustering Routing Protocol in Wireless Sensor Networks

Because the uniform clustering algorithm has the problems of unbalanced and large energy consumption in long distance communication between clusters in Wireless Sensor Networks, we propose an Improved Unequalven Clustering Routing Protocol (IUCRP). To optimize the clustering mechanism, IUCRP takes residual energy, distance to the Sink node and density of surrounding nodes of the candidate cluster heads into consideration when calculates the competition radius of the node. Meanwhile, we employ the method of multi-hop routing between clusters and choose the next-hop by considering residual energy, distance and link cost factors to mitigate the “energy hole” problem. Simulations show that IUCRP can balance the network energy consumption and extend the network lifetime.
Study on Smart Home Network Technology Based on Wireless Sensor Network

The research of smart home based on the wireless sensor network is done in view of the speciality of intelligent home and the actuality of intelligent home network.Making use of the speciality and technology of wireless sensor network,the model of smart home based on wireless sensor network is made.The wireless chips based on the technology of IEEE802.15. 4 are used to reduce the power-cost in wireless sensor node.The smart home network based on wireless sensor network can control our home timely and availability,which makes our life convenient,comfortable and highly efficient.
Pattern Recognition Based on the Fuzzy Kernel Matching Pursuit

Kernel Matching Pursuit(KMP),a novel method of the pattern recognition,presents excellent performance in solving the problems with small sample,nonlinear and local minima.KMP has been proposed to provide a good generalization performance for both classes,yet the classification precision of some important data can't be classified precisely.Because the decision function found by KMP is the synthetic consideration results of all the data,it has greatly limited its use in many practical problems,such as time series identification and unbalanced data classification.In this paper,an fuzzy kernel matching pursuit machine is(FKMP)proposed,which can classify the appointed important samples much more precisely according to the predefined importance of the data.Lots of experiments have been given in the paper to prove the feasibility and validation of the fuzzy kernel matching pursuit machine.
High-Frequency QPOs and Overstable Oscillations of Black-Hole Accretion Disks

Abstract The physical origin of high-frequency QPOs (HFQPOs) in black-hole X-ray binaries remains an enigma despite many years of detailed observational studies. Although there exists a number of models for HFQPOs, many of these are simply “notions” or “concepts” without actual calculation derived from fluid or disk physics. Future progress requires a combination of numerical simulations and semi-analytic studies to extract physical insights. We review recent works on global oscillation modes in black-hole accretion disks, and explain how, with the help of general relativistic effects, the energy stored in the disk differential rotation can be pumped into global spiral density modes in the disk, making these modes grow to large amplitudes under certain conditions (“corotational instability”). These modes are robust in the presence of disk magnetic fields and turbulence. The computed oscillation mode frequencies are largely consistent with the observed values for HFQPOs in BH X-ray binaries. The approximate 2:3 frequency ratio is also expected from this model. The connection of HFQPOs with other disk properties (such as production of episodic jets) is also discussed.
SQL EXTENSION FOR RELATIONAL DATABASE MANAGEMENT SYSTEMS

Summary: In the presented paper method for extension of database management system on the MSSQL Server, which give opportunity for complete operation with fuzzy sets in a relational database is offered and shown. The method modify of a base operation in Transact-SQL. The method modifies base operation in a Transact-SQL. As well, interpretates of the modified code in Transact-SQL code, with the purpose to formation on fuzzy result set. Extension and improvement of an opportunity of a database management system with an offered method give completed and detailed result of the data processing in a database.
An Improved Design for Association Rule Discovery System for Decision Support System

- The challenge of associating rules to data set of items has been an important area in data mining research. Recent challenges is how to improve the algorithms that have been used in discovering associations that seem complex but are more useful in decision making and analysis. This paper presents a design for association rule discovery for decision support systems using an improved C4.5 Algorithm. This research work provides an efficient discretization method for the data which aids the discretization of continuous data and improves the rule discovery process from the different data sets and data attributes.
Phase-transfer-catalyzed reactions between polysulfide anions and .alpha.,.beta.-unsaturated carbonyl compounds

Ammonium polysulfide reacts with α,β-unsaturated ketones and aldehydes under PTC (phase transfer catalysis) conditions in a rather different manner than it does in homogeneous systems. 1,3-Diphenyl-2-propen-1-one (chalcone, 1) and 4-phenyl-3-buten-2-one (benzylideneacetone, 3) give sulfur-linked dimers (mainly disulfides). 3-Phenyl-2-propen-1-al (cinnamaldehyde) polymerizes. 1,5-Diphenyl-1,4-pentadien-3-one (dibenzylideneacetone, 7) gives the known six-membered ring thianones and new seven-membered ring 1,2-dithiepanones 9 along with a polymer. Carvone gives a disulfide dimer that converts to a mixture of bicyclic sulfur-containing compounds. Sodium polysulfide is much less effective because of the base-induced decomposition of either the products or the intermediates
Semantic rule engine for QML. Verifying semantic rules using computational tree logic

One of the most common tools used for verifying code quality in programming languages are linter programs. However, in many cases, specifically in new languages, there is no such tool. An example of such a language is QML. In this thesis this tooling issue is addressed by designing a rule engine, together with rules defined in a dedicated language. The idea is to use the rule engine as a framework for creating lint tools for any programming language and evaluate this by creating a sample implementation of a lint tool for QML. In order to make the rule engine agnostic to which programming language that is being verified, the rules described in the rule language will describe structural restrictions of the abstract syntax tree produced from the source code. Moreover, in order to make the rule language as expressive as possible it is constructed as a dialect of Computational Tree Logic (CTL). Although CTL is a logic traditionally used to describe temporal properties of infinite trees, CTL fundamentally only describes structural properties of a tree and all its possible sub-trees which makes it a great foundation for our purposes. An additional feature of using a dedicated language to define rules is that the rule engine becomes agnostic to what rules that are defined as well. Meaning that if a user wants to change, add or delete rules only the rule file has to be changed and nothing needs to be recompiled. By using this approach, this thesis solves both the lint tool issue for QML and creates a framework for defining lint tools for any other programming language as well.
Market-Based Multi-Robot Task Allocation for Fire-Disaster Response

In order to achieve distributed task allocation dynamically and effectively in multi-robot systems,multi-robot fire-disaster response was presented.The mathematical model of multi-robot cooperative fire-disaster response had been build,and market-based multi-robot task allocation for fire-disaster response was proposed.The distance factor and the fire behavior and time factors are taken into consideration,its bidding expressions accord with request of dynamic task allocation for fire-disaster response.Simulation experiment is performed in the self-develop platform,and the simulation results are analyzed.The experimental results show that this strategy can achieve multi-robot dynamic task allocation for fire-disaster response in different situation.
An Introduction to EMG Signal Processing Using MatLab and Microsoft Excel

This chapter provides the reader with an introduction to the fundamentals of biological signal analysis and processing, using EMG signals to illustrate the process. The areas covered within the chapter include: frequency analysis using the Fast Fourier Transform, identifying noise within a signal, signal smoothing via root mean square (RMS) processing and signal filtering with both low-pass and high-pass filters. Guidelines for the application of the processes covered are included in conjunction with step by step examples using both MathWorks MatLab and Microsoft Excel software. Following the examples therefore allows the reader to practice the processes described to promote and reinforce their learning.
Legal Language: What Is It and What Can We Do About It?.

ABSTRACT Legal language is discussed in the context of concern about the comprehensibility of consumer documents and the trend toward simplification of the language used in these documents. Specific features of legal language and its functions within the legal community and society are identified. As a primary tool of the legal profession, legal language is viewed as carrying a substantial social and linguistic burden. In addition, it is seen as serving separating, unifying, and prestige functions. It is proposed that these two factors explain why attempts at simplification are likely to be resisted. Legal language appears to have some features of a changing, living dialect, and while %. raditional scholars have focused only on legal vocabulary, research has demonstrated an evolution of legal terms through litigation and appeal that is analogous to the historical development of ordinary English. Recent research suggests that there is more to legal language than lexicon. Some of the attempts to simplify legal language and some research studies on the comprehension o: non-legal language are examined for the insights they provide into linguistic barriers to comprehension of legal language. Areas of research are identified. (Author/MSE)
AIMD Dynamics and Distributed Resource Allocation

This is the first comprehensive book on the AIMD algorithm, the most widely used method for allocating a limited resource among competing agents without centralized control. The authors offer a new approach that is based on positive switched linear systems. It is used to develop most of the main results found in the book, and fundamental results on stochastic switched nonnegative and consensus systems are derived to obtain these results. The original and best known application of the algorithm is in the context of congestion control and resource allocation on the Internet, and readers will find details of several variants of the algorithm in order of increasing complexity, including deterministic, random, linear, and nonlinear versions. In each case, stability and convergence results are derived based on unifying principles. Basic and fundamental properties of the algorithm are described, examples are used to illustrate the richness of the resulting dynamical systems, and applications are provided to show how the algorithm can be used in the context of smart cities, intelligent transportation systems, and the smart grid. Audience: The book is suitable for advanced undergraduate and graduate students and researchers.
Evaluating Students’ Perception of Teaching Learning Computer Programming: A Study in a Bruneian Technological University

The present study is part of one of the pioneering government funded research, conducted in one of the institutions of higher learning in Brunei Darussalam. The study validates the existing instrument through survey (factor analysis) among cohort of students in a programming class. The study results not only endorse the reasons of declining the art and science of teaching/learning computer programming but also have brought an interesting finding of pedagogy. The results indicate that teaching and learning strategies are more teacher-centered (mean=3.85) rather than student-centered (mean = 2.87). This is in contrast to modern approach of teaching-learning, where problem-based or constructivist approach dominates. Further 67% of the students considered lack of motivation, 80% considered the curriculum is less practical and 50% thought it was more teacher-centered, as key reasons of this decline. Based on the findings some recommendations were made to the relevant authorities to improve the practice.
Indicadores para Avaliar o Desempenho de Prefeituras Municipais

After the adoption of New Public Management (NPG), the search for mechanisms to measure performance of public organizations, which often provide heterogeneous services and intangibles, became widespread. However, many of the tools used come from the for-profit administration domain and therefore are not completely adapted to the changing political context of public organizations, as well as the management fluctuations in public agencies. Much knowledge has been produced in the area, but there are still gaps in relation to municipal government performance management. The aim of this study is to contribute to this gap by proposing a theoretical basket of indicators suitable for small municipalities and a ‘dashboard’-like tool that allows monitoring the various functions performed by municipalities in terms of efficiency, efficacy and effectiveness.
Silicon Concentration and Expression of Silicon Transport Genes in Two Thai Rice Varieties

Silicon (Si) is a beneficial element that contributes to increasing the resistance of plants to diseases, pests and lodging, and rice productivity. The objectives of the present study were to explore the relationship between Si concentration and the expression of Si transport genes in different tissues of SPR1 and PTT1 rice varieties. The rice was grown aerobically in sand culture in pots arranged in completely randomized design with 3 independent replications. Variation in Si concentration among growth stages and plant tissues in both rice varieties were detected. The Si concentration in SPR1 was higher than PTT1 in some plant parts up to flowering, but significantly higher in all tissues by maturity, including in the husk which accounts for almost all of the Si in the grain. The consistently higher expression of the genes Lsi1 and Lsi2, detectable only in the roots, was in agreement with higher Si concentration in SPR1 than PTT1 in all tissues at maturity. SPR1 had higher expression of Lsi6 than PTT1 at booting stage, but the difference between varieties was less distinct at flowering stage. Either a varietal difference in the passive Si transport by transpiration or changes in the level of expression of the gene in the period from flowering to maturity or both are suggested by discrepancies between expression of the Lsi6 gene at flowering and the Si concentrations at maturity of the two rice varieties.
RGB Medical Video Compression Using Geometric Wavelet

The video compression is used in a wide of applications from medical domain especially in telemedicine. Compared to the classical transforms, wavelet transform has significantly better performance in horizontal, vertical and diagonal directions. Therefore, this transform introduces high discontinuities in complex geometrics. However, to detect complex geometrics is one key challenge for the high efficient compression. In order to capture anisotropic regularity along various curves a new efficient and precise transform termed by bandelet basis, based on DWT, quadtree decomposition and optical flow is proposed in this paper. To encode significant coefficients we use efficient coder SPIHT. The experimental results show that the proposed algorithm DBT-SPIHT for low bit rate (0.3Mbps) is able to reduce up to 37.19% and 28.20% of the complex geometrics detection compared to the DWT-SPIHT and DCuT-SPIHT algorithm.
Comparative Anatomy Of The Vertebrates

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Information Retrieval A Health And Biomedical Perspective

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