Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical application of matching algorithms in case of a task allocation problem

Conflicts between individuals or even groups of people are part of everyday social life. However, when handling conflict situations successfully, conflicts are actually solved. In order to achieve such resolution, parties should separate the conflict from the involved people and try to create a cooperative, nonzero-sum mind set concentrating on interests and not on positions - agreeing on principles like using a fair standard and a fair procedure. In present paper such impartial standards and procedures - namely matching theory algorithms - that concentrate on factual controversies are introduced.
Region-based guaranteed image quality in JPEG2000

This paper describes a spatially variant method that optimises the compression rate within a given image dynamically depending on the application specific requirements and the actual image content. The concept utilises the JPEG2000 standard, however, a generalised region-of-interest (ROI) map is used in this paper together with a different post-compression rate distortion optimisation. The generalised ROI map comprises a multi-level priority scheme as well as continuously adjustable qualities for each individual region to reflect the application specific requirements for a particular image. The key point is that these pre-defined quality constraints are always met for each individual region, thus making the approach suitable for data with inherent reliability requirements. The implementation of the proposed system is transparent and concerns only the encoder side while any standard JPEG2000 decoder can be used for decompression. Results have shown that for the utilised imagery, i.e. satellite and medical images, compression rate improvements of up to 32% in comparison to the JPEG2000 compressor fulfilling the same quality needs are achievable.
Automatic target identification using neural networks

Neural network theories are applied to attain human-like performance in areas such as speech recognition, statistical mapping, and target recognition or identification. In target identification, one of the difficult tasks has been the extraction of features to be used to train the neural network which is subsequently used for the target's identification. The purpose of this paper is to describe the development of an automatic target identification system using features extracted from a specific class of targets. The extracted features were the graphical representations of the silhouettes of the targets. Image processing techniques and some Fast Fourier Transform (FFT) properties were implemented to extract the features. The FFT eliminates variations in the extracted features due to rotation or scaling. A Neural Network was trained with the extracted features using the Learning Vector Quantization paradigm. An identification system was set up to test the algorithm. The image processing software was interfaced with MATLAB Neural Network Toolbox via a computer program written in C language to automate the target identification process. The system performed well as at classified the objects used to train it irrespective of rotation, scaling, and translation. This automatic target identification system had a classification success rate of about 95%.
Let -imperatives in English

This paper reports the findings of a corpus-based study oflet-imperatives in English. Unlike the ordinary lexical verbletmeaning "allow", theletoflet-imperatives serves merely to mark illocutionary meaning. In "first person inclusives", the variant with us-contraction is found to have increased in popularity over recent decades. Furthermore the occurrence of cases wherelet'scan not be interpreted as a contraction oflet ussuggests that syntactic reanalysis has reached an advanced stage amongst some speakers. "Open"let-imperatives, which despite their distinctively optative or deontic-assertive force are grammatically closer to ordinary imperatives, are found to have decreased in popularity in recent decades.
Functional Decomposition Based Effort Estimation Model for Software-Intensive Systems

: An effort estimation model is needed for software-intensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.
Automated Versus Human Essay Scoring: A Comparative Study

This study investigated the effects of automated essay scoring (AES) system on writing improvement of Iranian L2 learners. About 60 Iranian intermediate EFL learners were selected on a Standard English proficiency test (Allen 2004). Afterwards, they were randomly assigned to two groups of 30, experimental and control group. Participants in experimental group received the AES scoring, and control group, received the human scoring. Statistical analyses of the results reveal that 1) AES tool results in significant improvement of L2 learners writing achievement, 2) Results from questionnaire show that Students ware favor about using AES tool, 3) The results from the current study support the conclusion that the AES tool does not seem to correlate well with human raters in scoring essays. Hence, the findings of this study indicate that using AES tools can help teachers ease their big teaching students to improve their writing and it can be used as an educational tool on classrooms.
Convergence properties of iterative soft onion peeling

The concept of iterative multiuser detection for a multiple access adder AWGN channel is coupled with turbo code used for each user, followed by an interleaver. The iterative decoding exchanges the likelihood information both among the two constituent codes of each user and among the users. The information exchange among users is performed for each chip, using a Gaussian approximation for other user's contribution. The described iterative decoding procedure, when applied to unequal user power case, implicitly implements the "onion peeling" concept-strong users converge first, their contribution to the residual noise decreases, and then the weaker users converge. This property, in focus here, was applied in previous work to illustrate applications to multiple access communication and to broadcast channels. The difference from the classical "onion peeling" is that rather than decoding a user completely and then subtracting its contribution, the convergence here occurs over several layers simultaneously. The convergence properties of the proposed method are studied, with special emphasis on the case of equal rate users with exponentially related powers.
A Concept Based Mining Model For NLP Using Text Clustering

Most of the common techniques in text mining are based on the statistical analysis of a term, either word or phrase. Statistical analysis of a term frequency captures the importance of the term within a document only. However, two terms can have the same frequency in their documents, but one term contributes more to the meaning of its sentences than the other term. A new concept-based mining model that analyses terms on the sentence, document, and corpus levels is introduced. The concept-based mining model can effectively discriminate between nonimportant terms with respect to sentence semantics and terms which hold the concepts that represent the sentence meaning. The proposed mining model consists of sentence-based concept analysis, documentbased concept analysis, corpus-based concept-analysis, and concept-based similarity measure. The term which contributes to the sentence semantics is analysed on the sentence, document, and corpus levels rather than the traditional analysis of the document only. The proposed model can efficiently find significant matching concepts between documents, according to the semantics of their sentences. The similarity between documents is calculated based on a new concept-based similarity measure. Keywords—Concept-based mining model, sentencebased, document-based, corpus-based, concept analysis, Concept based similarity.
A Heterogeneous Multihop Wireless Access Network for Multipoint Streaming: A detailed Performance Analysis

The current 3G-Cellular radio access network cannot support many concurrent high data rate unicast or multicast flows due to limited radio resources. We have proposed a heterogeneous wireless network architecture intended for point-to-multipoint services, to improve the availability of such services to mobile users. The architecture consists of a 3G-Cellular network, supported by a number of local ad hoc networks that are established on demand. In this framework the 3G multipoint-channel range is reduced while the unicast and signalling connections are maintained. Local ad hoc networks are used to forward the multicast data onto users located outside the shortened 3G multicast-channel range. In this paper we present a performance analysis of multicast streaming on the heterogeneous network architecture. The simulation results are complemented with a sensitivity analysis identifying the impact that parameters like node mobility and traffic patterns will have. The results verify that the architecture and the routing protocol are able to provide multicast services with acceptable quality to the multicast subscribers, while conserving 3G-Cellular radio resources.
A generalised design technique for traceback survivor memory management in Viterbi decoders

There are number of algorithms available for the design of traceback survivor memory units in Viterbi (1967) decoders. Perhaps the best description of the traceback algorithms was given by Feygin et al. (1993), where four separate algorithms were presented. These four algorithms, however, can all be encapsulated in the description of two broader algorithms. In addition a new implementation technique is presented for one family of algorithms. As a result a host of new, low complexity implementations of survivor memory units become possible.
Effectuation, causation, and firm growth: a study of written business plans of micro and small firms

Entrepreneurship scholars have made significant efforts to explain how and why new firms originate, survive, and grow (Davidsson, 2004; Gartner, 1985; Schumpeter, 1934). These efforts have converged into a teleological model of entrepreneurship as a rationally planned, risk-taking and linear process of opportunity recognition and exploitation (e.g., Bhave, 1994; Bird, 1988; Jenkins & Johnson, 1997; Shane & Venkataraman, 2000). In line with Sarasvathy (2001) we label this the causation model of entrepreneurship. While this causation model became the mainstream model of entrepreneurship in the 1990s, some scholars have questioned its validity. As an alternative, several authors developed a model of entrepreneurship as a means-driven, risk-aversive, and circular process involving improvisation, bricolage, and effectuation (e.g., Baker & Nelson, 2005; Sarasvathy, 2001). Adopting again Sarasvathy’s terminology, this alternative model is labeled the effectuation model of entrepreneurship. Going beyond a straightforward choice for either of the two models, today’s academic debate is increasingly subtle. The general idea is that both models can work in practice. For instance, planning activities are widely regarded as useful under certain conditions and within given environments (Gruber, 2007; Honig & Karlsson, 2004).
User Perceptions of Uncertainty in the Selection of Information Retrieval System: Implications for System and Service Improvement

While numerous studies have suggested the significance of uncertainty during the process of information-seeking, less research has investigated user uncertainty in the actual search process using a real system. This study investigated user perceptions of uncertainty in the process of the selection of information retrieval system in the real information-seeking process. Considering the role of commercial Web search engines as supplementary tools for traditional bibliographic databases in academic research environments, this study analyzed the selection behavior of scholarly researchers, who use such search tools for their academic study. The researchers were limited to the discipline of science in order to understand user perceptions in this field. The findings revealed various dimensions, types, and incidents of uncertainty. Variations appeared in different incidents of uncertainty relating to the unique characteristics of the subjects’ information-seeking context. The identification of three principal origins of uncertainty based on the different types of uncertainty generated implications to improve information systems and services.
Reconfigurable Address Collector and Flying Cache Simulator

Trace-driven simulation is widely used to evaluate the cache memory system. The accuracy of the trace-driven simulation depends on the accuracy and length of the trace data. To achieve an accurate and long trace, trace collection hardware is designed. The flying cache simulator is attached to the tracing system to simulate various cache systems during the execution of an application program. The tracing system designed, called the Reconfigurable Address Collector and Flying Cache Simulator (RACFCS), can generate accurate and long traces and simulate the cache system for a long execution time.
A 0.5-V 1-μW successive approximation ADC

A successive approximation analog-to-digital converter (ADC) is presented operating at ultralow supply voltages. The circuit is realized in a 0.18-/spl mu/m standard CMOS technology. Neither low-V/sub T/ devices nor voltage boosting techniques are used. All voltage levels are between supply voltage V/sub DD/ and ground V/sub SS/. A passive sample-and-hold stage and a capacitor-based digital-to-analog converter are used to avoid application of operational amplifiers, since opamp operation requires higher values for the lowest possible supply voltage. The ADC has signal-to-noise-and-distortion ratios of 51.2 and 43.3 dB for supply voltages of 1 and 0.5 V, at sampling rates of 150 and 4.1 kS/s and power consumptions of 30 and 0.85 /spl mu/W, respectively. Proper operation is achieved down to a supply voltage of 0.4 V.
Reading Thomas Jefferson with TopicViz: Towards a Thematic Method for Exploring Large Cultural Archives

0 0 1 144 823 City University of New York 6 1 966 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman";} In spite of what Ed Folsom has called the “epic transformation of archives,” referring to the shift from print to digital archival form, methods for exploring these digitized collections remain underdeveloped. One method prompted by digitization is the application of automated text mining techniques such as topic modeling -- a computational method for identifying the themes that recur across an archive of documents. We review the nascent literature on topic modeling of literary archives, and present a case study, applying a topic model to the Papers of Thomas Jefferson. The lessons from this work suggest that the way forward is to provide scholars with more holistic support for visualization and exploration of topic model output, while integrating topic models with more traditional workflows oriented around assembling and refining sets of relevant documents. We describe our ongoing effort to develop a novel software system that implements these ideas.
Learning-based web query understanding

Web search is attracting more and more attention with the exponential increase in data becoming available on the Web. Typically, a Web user submits a short Web query consisting of a few words to a Web search system and expects the system to return the desired information. How to understand Web queries precisely and thoroughly lies at the heart of Web search. In this thesis, we study the Web query understanding problem from several viewpoints. The first one is through query topic classification, which aims at interpreting queries in terms of predefined categories based on the queries' topics. We propose three solutions for different scenarios in query topic classification. The second way of understanding queries is to detect the type of a Web query, such as whether it requires locality information or information about a person, or the like. In this thesis, we focus on personal name detection in Web queries. The third way is to construct query hierarchies from query logs. These hierarchies reflect the generalization/specification relationship among Web queries. Finally, we study the contribution of query logs to Web-page classification, which can in turn help understand Web queries. Experimental results on some real-world data sets validate the effectiveness of our proposed methods.
Planning, geometry, and complexity of robot motion

Robotics has come to attract the attention of mathematicians and theoretical computer scientists to a rapidly increasing degree. Initial investigations have shown that robotics is a rich source of deep theoretical problems, which range over computational geometry, control theory, and many aspects of physics, and whose solutions draw upon methods developed in subjects as diverse as automata theory, algebraic topology, and Fourier analysis. Also presented is some of this theoretical robotics research, emphasizing work relating to the geometric aspects of robot motion planning.
XML Data Management: Native XML and XML-Enabled Database Systems

Read more and get great! That's what the book enPDFd xml data management native xml and xml enabled database systems will give for every reader to read this book. This is an on-line book provided in this website. Even this book becomes a choice of someone to read, many in the world also loves it so much. As what we talk, when you read more every page of this xml data management native xml and xml enabled database systems, what you will obtain is something great.
Teach English : a training course for teachers

Teach English is a teacher training course that develops practical skills in the teaching of English as a second language. It can be used in a variety of situations: in-service courses for teachers working at the secondary school level or in language institutes, in pre-service training of secondary school teachers, and as part of a refresher course in practical methodology for more experienced teachers. It is especially designed to meet the needs of teachers whose first language is not English, who teach large classes in rigid classrooms with few resources, who follow a set of syllabus and textbook, who have little control over course content or material.
Mapping of User Quality-of-Experience to Application Perceived Performance for Web Application.

Web browsing posses a major share among the activities on the Internet. Heavy usage of web browsing makes the Web Quality of Experience (QoE) one of the critical factor in deciding the overall success of network services. Amongst others, Web QoE can be effected by the delays in network that can result in higher application download times. In this thesis work, an effort has been made to map applications level download times to Quality of Experience. A subjective analysis on how the user takes into account the domain of web browsing has been carried out. For this purpose a testbed was developed at Blekinge Institute of Technology on which different users were tested. Specific sequences of delays were introduced on the network which resulted in desired application download times. Regression analysis was performed and a mapping between user QoE and application download times was carried out. Based on the results conclusions were made which are presented in this thesis report.
Reflections on the Use of HCI Methods for the Design of Learning Spaces

INTRODUCTION The topic of learning spaces and their design has become increasingly popular in education. Whether it is the development of physical spaces in higher education settings [5, 9] or K-12 settings [7], more attention is being paid to the design of physical spaces in educational contexts and how those spaces can be designed to support learning and other educational activity. The issue of architecture and its impact on learning is also being discussed in educational research. For example, Shulman [13] describes the notion of signature pedagogies—teaching that organizes the fundamental ways in which future practitioners are educated to think, act, and perform in their new profession—and how these pedagogies can serve to help inform and determine the architectural design of educational spaces in ways that support those pedagogies.
XML Encryption Syntax and Processing

An exhaust gas recirculator in an internal combustion engine wherein a part of the exhaust gas is supplied to a suction manifold only at the time when the throttle valve is opened and in some time interval immediately after the time afterwards, and the supply of the exhaust gas is stopped in time interval in the steady operation of the engine at the degree of opening of the throttle valve in the above supply period.
Realistic face modeling with robust correspondences

Finding robust correspondence is an important problem in structure from motion algorithm. Because the human face contains many low texture and homogeneous areas, some algorithms such as corner matching are unstable and may fail sometimes. We used the face definition parameters and the symmetry of human face as prior knowledge to find reliable correspondences between two pictures, while most SFM algorithms use the generic model as a modulator in the post-processing steps. This work proposes a whole scheme to construct textured 3D face models from two views with a few user interactions. According to the correspondences, a multistage SFM approach is used to reconstruct the structure. Then we use the RBFCS algorithm to interpolate more 3D points according to the scattered feature points. A user with an ordinary camera can use our system to generate his face model in a personal computer.
Evaluation of page quality using simple features

A classi er to determine page quality from an Optical Character Recognition (OCR) perspective is developed. It classi es a given page image as either \good" (i.e., high OCR accuracy is expected) or \bad" (i.e., low OCR accuracy expected). The classi er is based upon measuring the amount of white speckle, the amount of broken pieces, and the overall size information in the page. Two di erent sets of test data were used to evaluate the classi er: the Sample 2 dataset containing 439 pages and the Magazines dataset containing 200 pages. The classi er recognized 85% of the pages in the Sample 2 correctly. However, approximately 40% of the low quality pages were misclassi ed as \good. " To solve this problem, the classi er was modi ed to reject pages containing tables or less than 200 connected components. The modi ed classi er rejected 41% of the pages, correctly recognized 86% of the remaining pages, and did not misclassify any low quality page as \good". Similarly, it recognized 86.5% of the pages in the Magazine dataset correctly and did not misclassify any low quality page as \good" without any rejections. iii