Miracle-dz/UniFAR-FTUs huggingface dataset:
The myth of Holy Grail in Dan Brown's The Da Vinci Code

ENGLISH: This thesis uses a novel The Da Vinci Code as a data source. Because in this novel tells about the Holy Grail that containing interesting myths about the Priory of Sion, the relationship between Mary Magdalene and Jesus Christ and the descent of Jesus were still alive and protected by a secret organization formed by the Priory of Sion until today. This novel written by famed novelist Dan Brown, it tells about the quest of the true Holy Grail. This novel packed like a detective novel and inside it there are a lot of codes that must be solved to find the Holy Grail. In this thesis, the researcher uses semiotic theory of Roland Barthes as a tool to analyze the meaning of the Holy Grail in denotative and connotative. After that, the researcher analyzed the myth behind the Holy Grail. Researcher also analyzed the characters perceive of the Holy Grail to determine the response of each character of the Holy Grail. All the data is getting from texts that exist in the novel The Da Vinci Code relating to the statements of the problem that has been determined by the researcher. After analysis, researcher made conclusions about the denotative and connotative meaning of the Holy Grail, the myth of the Holy Grail and the characters perceive of the Holy Grail that is contained in the novel The Da Vinci Code. INDONESIA: Penelitian ini menggunakan novel The Da Vinci Code sebagai sumber data. Karena dalam novel ini menceritakan tentang mitos Cawan Suci (Holy Grail) yang berkaitan dengan misteri tentang mitos Biarawan Sion, hubungan antara Maria Magdalena dan Yesus, dan keturunan Yesus yang masih hidup hingga saat ini yang dijaga oleh organisasi rahasia yang dibentuk para Biarawan Sion. Novel ini di tulis oleh novelis terkenal yang bernama Dan Brown. Novel ini menceritakan tentang perjalanan untuk menemukan rahasia mitos Holy Grail yang sesungguhnya. Dikemas dengan gaya penulisan novel detektif dan didalamnya terdapat banyak misteri tentang kode-kode yang harus dipecahkan untuk menemukan mitos Holy Grail yang sesungguhnya. Dalam penelitian ini, peneliti menggunakan teori semiotic Roland Barthes untuk menganalisa makna Holy Grail secara denotatif dan konotatif. Setelah itu, peneliti menganalisa mitos dibalik Holy Grail tersebut. Peneliti juga menganalisa persepsi para karakter terhadap Holy Grail untuk menentukan respon mereka terhadap mitos Holy Grail berdasarkan persepsi masing-masing karakter. Seluruh data diperoleh peneliti dari teks-teks yang terdapat pada novel The Da Vinci Code yang berhubungan dengan rumusan masalah yang telah ditentukan oleh peneliti. Setelah menganalisa, peneliti membuat kesimpulan tentang makna Holy Grail secara denotatif dan konotatif, mitos dibalik misteri Holy Grail dan persepsi masing-masing karakter terhadap Holy Grail yang terdapat dalam novel The Da Vinci Code.
Considerations for Planning a State Virtual School: Providing Web-Based Courses for K-12 Students.

592 10th St. N.W. Atlanta, GA 30318 (404) 875-9211 www.sreb. org William R. Thomas Courses delivered over the Web can help a state meet the academic needs of all students. SREB states are creating state virtual schools to support and manage the efficient, effective use of Web-based courses. These state virtual schools vary greatly in goals, staffing and funding. The Florida Virtual School, the nation’s largest state virtual school, offers more than 60 high school academic courses and expects to serve nearly 8,000 students this year. The Kentucky Virtual High School coordinates the services and courses that schools offer to students. Other state departments of education — including those in Maryland and West Virginia — have staff who work closely with schools and school districts to identify needs, evaluate courses and coordinate student access. Before determining whether to build a state virtual school, the Texas Legislature in 2001 directed the commissioner of education to establish a program to examine state policies and requirements or restrictions affecting districts that offer electronic courses to local students. The Texas Education Agency is scheduled to submit a report in December 2002.
Detecting session boundaries from Web user logs

Detecting session boundaries on the Web is important for several reasons. Firstly, it is important to establish a common context for various statistics relating to user sessions and frequency of user activities. More specifically, it is important to detect some boundaries in order to group related information together for other applications, such as learning techniques for adaptive search engines. To date, however, the notion of a session on the Web has not been consistently defined, if it at all. The tendency has been to group the log data that has been made available from one user or IP address under the umbrella of one session regardless of the length of time covered by the logs. This tendency lacks a more user oriented view. Our argument is that a session on the Web can be defined as a group of user activities that are related to each other not only through an evolving information need but also through close proximity in time. Thus, we describe and discuss the investigation based on two Web transaction logs (Excite and Altavista) with a view to structuring the activities into sessions or units for subsequent use in user-oriented learning techniques. The paper describes the methodology and the experiments performed followed by results and discussions. The results point to a 10-15 minute threshold between user activities for an appropriate session interval. The implications and limitations of the results as well as differences with traditional IR systems are also discussed.
Teaching connected speech rules to Japanese speakers of English so as to avoid a staccato speech rhythm

This study explores the effectiveness of teaching Japanese speakers of English how to connect speech so as to avoid a robotic speech rhythm. A control and an experimental group were each given three one-hour classes in English. The control group read poetry aloud without any explicit instructions. The experimental group were instructed in how to link words with three different sound boundaries: (1) consonant to vowel, (2) vowel to vowel, and, (3) consonant to consonant. The ability to link word pairs was rated for both the control and experimental groups in pre- and post-treatment situations, and this was compared to a native-speaker baseline of connected word pairs. This research focussed on whether instruction in connected speech rules would assist in reducing the syncopated rhythm which often characterises the speech of Japanese speakers of English. Although this study was an exploratory one, with a very small sample size, the results were heartening: directly teaching these rules seemed to heighten the awareness of the need to link word pairs. However, the results indicate several problem areas on which researchers and teachers need to focus in order to optimise time spent in pronunciation training. That is, a longer period of instruction with practice may enable a more successful output. Furthermore, it would be necessary to control experimental variables more carefully and use a larger sample size in order to obtain more definitive support for the claim that teaching connected speech rules would, indeed, generally improve the speech rhythm of Japanese learners of English.
Segmentation and validation of anatomical structures in t1-weighted normal brain mr images by calculating area of the segmented regions

This paper focuses on the segmentation of noise free T1-Weighted normal brain MRIs. The skull tissues from these MRIs were removed by employing Active Contour Model (ACM) [14]. Where as, the segmentation of an image is achieved with the help of Artificial Neural Network (ANN). The results produced are validated by comparing the area of the ground truth segments with the area of the segments produced by ANN. The ANN training accuracy was found to be 99.5%. The average segmentation accuracy was found to be 97.15% with an error rate of 2.85%
The Roles of Grammar Instruction in English Writing Class

The present study evaluated whether grammar instruction can produce a positive effect on the grammatical accuracy of college students’ English writing. The methods of selective correction and comprehensive correction were compared among two groups of students (total 82 students) attending a weekly writing class, and the former was found to be a more effective teaching strategy in helping students to improve their accuracy rate, although the degree of improvement was somewhat subtle. The study also analyzed data concerning the students’ grammatical errors. In addition to the error patterns pointed out in earlier research, some additional noticeable error patterns were evident. Certain basic grammatical structures were incorrectly used by the students and some were found to be “difficult” for over 70% of the students, indicating the need to review grammar in college-level lessons. An understanding of the typical error patterns made by students will help English teachers to provide narrowly focused grammar instruction to students in efforts to improve their accuracy of English writing.
The Effects of Hypertext on Reader Knowledge Representation

The goal of this research was to evaluate the effects of hypertext as an intra-document text format. Subjects read two articles on a color VDT, one in linear and one in hypertext format. Half of the subjects read general interest articles with instructions for casual reading and the other half read technical articles with instructions to learn the material. Afterward, subjects were given free recall tests, question probe tests, and a preference questionnaire. Results indicated that for both types of article, the linear format resulted in greater memory for the basic ideas contained in the articles. Also, for the general interest articles, subjects reading in linear format assimilated more of the macro-structure than subjects reading in the hypertext format. Consistent with these findings, a majority of the subjects expressed a preference for the linear format and perceived it as requiring less mental effort than reading hypertext. These results suggest that, at least under some circumstances, hypertext can interfere with normal cognitive processes.
Operations Research in Experimental Psychology

This chapter reviews some of the uses of operations research methods in experimental psychology. We begin by describing some basic methodological issues that arise in the study of human decision making. Next, we describe in more detail research in exper- imental psychology that has used methods common to operations research|such as dynamic programming|to understand sequential observation and selection behavior. We then suggest some ways in which experimental psychology and operations research can each provide the other with new research questions.
Observations on the Development of the Human Suprarenal Gland.

THE study of the changes that occur in the minute structure of an organ during its development naturally arouses curiosity as to the nature of any concomitant acquisition of function or changes of function which may occur, and though the main object of this paper is to describe the minute structure of the developing human suprarenal gland as fully and as consecutively as the material at our disposal allows, the scope of the investigation also includes the determination of the earliest appearance of adrenin, the general distribution of lipoid, and the variations that occur in certain cases of abnormal development.
Cell Loss Clustering Prevents Avalanches in ATM Networks

ATM networks handle congestion by discarding cells that overflow switch queues, leaving the responsibility of reconstructing damaged protocol data units (PDU) to higher-level protocols. The loss of a single ATM cell from a PDU can require the retransmission of the entire PDU, which can be disastrous because the loss of a few ATM cells can cause the loss of a much larger amount of PDU data – this is the so-called “avalanche effect” [3]. The avalanche effect has caused much concern in the networking community regarding the effectiveness of ATM for transporting data network traffic because of the short cell length of ATM cells relative to the long packet lengths of typical PDUs. Our simulation results and those of others [2] [1] indicate that cell losses are highly correlated, and tend to occur in clusters. Cell losses which occur closely in time are likely to be from the same PDUs, thus alleviating the avalanche effect. Hardware support has been proposed to handle avalanche effect, including switches which are aware of the higher level protocols, and which drop cells of the same PDU subsequent to the first lost cell – this strategy is called Partial Packet Discard (PPD) [4]. We simulate PPD and conclude that because of the high degree of cell loss clustering, PPD only marginally improves performance over plain ATM switches.
Automatic Extraction of Lemma-based Bilingual Dictionaries for Morphologically Rich Languages

Thesis (M.S.)--Georgetown University, 2009. ; Includes bibliographical references. ; Text (Electronic thesis) in PDF format. The present study introduces a system designed to automatically extract a comprehensive up-to-date Arabic-English lemma-based MRD from parallel corpora. The designed system makes use of state-of-the-art techniques in both aligning parallel corpora and deciding which alignment pairs are highly probable good MRD entries. Comparing the results of the present system to Buckwalter's manually built dictionary shows that the automatic extraction of lemma-based bilingual MRD is better in terms of time, coverage, dialectal issues, and updating.
A META-ANALYSIS OF SECOND LANGUAGE CLOZE TESTING RESEARCH

INTRODUCTION Cloze procedure first appeared in 1953 when Wilson Taylor researched its effectiveness as a procedure for estimating the readability of textbooks for school children in the United States. A decade later, research began to appear on the usefulness of cloze for testing the reading proficiency of native speakers of English (e.g., Bormuth, 1965, 1967; Crawford, 1970; Gallant, 1965; or Ruddell, 1964). In the 1960s and 1970s, a number of studies focusing on second language learners emerged and the usefulness of cloze procedure as a measure of overall ESL proficiency was examined (see Alderson 1978; Oller 1979; Cohen 1980 for summaries of this early ESL research). Since then, the cloze procedure has gained popularity and is a commonly used test in many language programs. The literature on cloze testing now spans more than half a century of research and covers a diverse range of topics. Researchers have manipulated an assortment of variables including, but not limited to: deletion patterns (for example, every nth word, or rational deletion), starting point of deletions (for example, after the first sentence, or prescriptively at the nth word), scoring methods (such as exact answer or acceptable answer), text difficulty (using a readability index, or the source of text; see, Brown, 1993), and the number of items—to name just five of the many variables that have been researched. With such a myriad of research topics both within and among studies, it not surprising that the field of cloze test research has produced varying results. One noteworthy topic is that of reliability. The reliability estimates for various cloze tests, over the years, have spanned the reliability spectrum from both weak 0.31 (Brown, 1982) to very strong 0.95 (Brown 1978) estimates. Many cloze studies (e.g., Alderson, 1979a, 1979b 1980; Bachman, 1985; Brown, 1980, 1983, 1984, 1988b, 1989, 1993, 1994, 1998, 2002; Brown, Yamashiro, & Ogane, 1999, 2001; Conrad, 1970; Darnell, 1970; Hinofotis, 1980; Irvine, Atai, & Oller, 1974; Jonz, 1976; Mullen,
Adapting an argumentation framework for online discourse analysis: A knowledge building approach

The use of online tools to support teaching and learning is now commonplace within educational institutions, with many of these institutions mandating or strongly encouraging the use of a blended learning approach to teaching and learning. Consequently, these institutions generally adopt a learning management system (LMS), with a fixed set of collaborative tools, in the belief that effective teaching and learning approaches will be used, to allow students to build knowledge. While some studies into the use of an LMS’s still identify continued didactic approaches to teaching and learning, the focus of this paper is on the ability of collaborative tools such as discussion forums, to build knowledge. In the context of science education, argumentation is touted as playing an important role in this process of knowledge building. However, there is limited research into argumentation in other domains using online discussion and a blended learning approach. This paper describes a study, using design research, which adapts a framework for argumentation that can be applied to other domains. In particular it will focus on an adapted social argumentation schema to identify argument in a discussion forum of N=16 participants in a secondary High School.
Application of Likelihood Methods to Models Involving Large Numbers of Parameters

[Read before the ROYAL STATISTICAL SOCIETY at a meeting organized by the RESEARCH SECTION on Wednesday, March 11th, 1970, Professor J. DURBIN in the Chair] SUMMARY Likelihood methods of dealing with some multiparameter problems are introduced and exemplified. Specifically, methods of eliminating nuisance parameters from the likelihood function so that inferences can be made about the parameters of interest are considered. In this regard integrated likelihoods, maximum relative likelihoods, conditional likelihoods, marginal likelihoods and second-order likelihoods are introduced and their uses illustrated in examples. Marginal and conditional likelihoods are dependent upon factorings of the likelihood function. They are applied to the linear functional relationship and to related models and are found to give intuitively appealing results. These methods indicate that in many situations commonly encountered objective methods of eliminating unwanted parameters from the likelihood function can be adopted. This gives an alternative method of interpreting multiparameter likelihoods to that offered by the Bayesian approach.
Machine learning and high-performance computing: Infrastructure and algorithms for the genome-scale study of genetic and epigenetic regulatory mechanisms with applications in neuroscience

The advent of next-generation sequencing (NGS) has fundamentally changed modern genomics research. These sequencers generate terabytes of data and necessitate the use, not only of highperformance compute (HPC) clusters for data processing and storage, but also of intelligent, scalable algorithms for pattern discovery and data mining. This thesis details the development of infrastructure and algorithms which automate much of this data analysis process allowing bench biologists to remain focused on the scientific questions that drive them, rather than the informatics challenges associated with these new platforms. We describe WASP, one of the first end-to-end systems to handle all aspects of NGS data generation, including sample submission, laboratory information management system (LIMS) functionality, and assay-specific processing pipelines. Furthermore, we present two machine learning algorithms for the secondary analysis of ChIP-seq data, the first, based on the use of self-organising maps (SOMs) for improved de novo motif discovery, and the second, which uses genetic algorithms (GAs) to automatically cluster transcription factor binding motifs. Finally, we present an application of this infrastructure and these techniques to the study of the role of the TBX1 transcription factor in 22q11.2 Deletion Syndrome, examining its putative role in neural development, adult neurogenesis, autism spectrum disorder (ASD), and schizophrenia.
A repository for the management of artifacts in system engineering

The research took place at Chess BV in Haarlem. Software design at Chess (and other companies) is done in MS Word documents in which the systems decomposition is stated. MS Word documents are very simple in use but lack analysis checking features. Chess identifies this as a problem and that is why this research was started. The problem for this research was defined as: ? How to manage software design artifacts within Chess? Design artifacts are parts of information about the system, like the structure or requirements of the system. The answer to this question led to a repository that supports the management of design artifacts, numerous of analysis checks on these artifacts, and the generation of documentation. To reach this goal, an explorative research in the literature was performed to provide a theoretical base. This theory is then used for analyzing the current situation and designing a new repository where the design artifacts are stored and managed in. Nowadays, development projects are getting bigger and more complex. This means that large amounts of design artifacts are created and these artifacts need to be stored somewhere. This also means that when changes occur (and they do) these design artifacts need to be changed. All these problems demand facilities for storing and managing the design artifacts in a repository.
Recognizing complex faces and gaits via novel probabilistic models

In the field of computer vision, developing automated systems to recognize people under unconstrained scenarios is a partially solved problem. In unconstrained scenarios a number of common variations and complexities such as occlusion, illumination, cluttered background and so on impose vast uncertainty to the recognition process. Among the various biometrics that have been emerging recently, this dissertation focus on two of them namely face and gait recognition. Firstly we address the problem of recognizing faces with major occlusions amidst other variations such as pose, scale, expression and illumination using a novel PRObabilistic Component based Interpretation Model (PROCIM) inspired by key psychophysical principles that are closely related to reasoning under uncertainty. The model basically employs Bayesian Networks to establish, learn, interpret and exploit intrinsic similarity mappings from the face domain. Then, by incorporating efficient inference strategies, robust decisions are made for successfully recognizing faces under uncertainty. PROCIM reports improved recognition rates over recent approaches. Secondly we address the newly upcoming gait recognition problem and show that PROCIM can be easily adapted to the gait domain as well. We scientifically define and formulate sub-gaits and propose a novel modular training scheme to efficiently learn subtle sub-gait characteristics from the gait domain. Our results show that the proposed model is robust to several uncertainties and yields significant recognition performance. Apart from PROCIM, finally we show how a simple component based gait reasoning can be coherently modeled using the recently prominent Markov Logic Networks (MLNs) by intuitively fusing imaging, logic and graphs. We have discovered that face and gait domains exhibit interesting similarity mappings between object entities and their components. We have proposed intuitive probabilistic methods to model these mappings to perform recognition under various uncertainty elements. Extensive experimental validations justifies the robustness of the proposed methods over the state-of-the-art techniques. i