Miracle-dz/UniFAR-FTUs huggingface dataset:
EXPLORATION OF AN AUTOMATED EDITING TASK AS A GRE® WRITING MEASURE1

Two editing tasks were developed and programmed for the computer to explore the possibility that such tasks might be useful as measures of writing skill. An informal data collection was then conducted with 52 prospective graduate students. These students completed the editing tasks with no time limit, as well as a writing experience questionnaire. Scores obtained on the two editing tasks were correlated with variables developed from the questionnaire. The total score for the two editing tasks correlated . 52 with student self-assessments of their writing ability, . 46 with grade-point average (GPA) based on courses requiring at least some writing, and . 30 with writing accomplishments. The correlation with GPA, however, was only . 14. The reliability of the total editing score was estimated at . 84.
Evaluation of the usefulness of a computerbased learning program to support student learning in pharmacology

The use of computers in undergraduate education is now widespread and computer-based learning (CBL) has made a significant impact in teaching, particularly over the last decade. This is likely to increase substantially as some £100 million has been made available to stimulate software development in the UK through various initiatives, such as the EEC COMETT program and the UK Higher Education Funding Councils' Teaching and Learning Technology Programme (TLTP). DOI: 10.1080/0968776990070205
10-Hydroxy-9-methoxy-5,6,13,13a-tetrahydro[1,3]dioxolo[4,5-g]isoquino[3, 2-a]-isoquinolin-8-one

In the title compound, 8-oxotetra­hydro­thalifendine, C19H17NO5, the di­hydro­pyrido and pyrido moieties adopt the intermediate conformations of envelope–screw-boat and envelope–twist, respectively. The dihedral angle between the two benzene rings is 37.16 (8)°. In the crystal structure, the mol­ecules translated by a unit along the c axis are linked by three weak C—H⋯O intermolecular interactions to form a molecular chain. Along the a axis, the adjacent chains related by screw symmetry are connected by a strong O—H⋯O and a weak C—H⋯O intermolecular interaction to form layers parallel to the bc plane.
Promoting Effective Learning Strategy Use in CALL

Abstract This paper presents research in the area of language learning strategies, focusing on both general research and the treatment of learning strategies in CALL. Despite a recent interest in the subject of learning strategies in language learning, few CALL programs include a treatment of this issue. A small number which do consider this aspect are described, and although some are useful in this regard, most include only a limited view of learning strategies. The learning strategies component of Mr. Collins, a system aimed at promoting learners' awareness of their knowledge and approaches to learning, is presented. Research on language learning strategies demonstrates that this is an important issue; the implementation of Mr. Collins shows that detailed consideration of learning strategies in CALL is feasible.
A Monitoring System for Integrated Management of IoT-based Home Network

Recently, the society is rapidly becoming highly integrated with the convergence of smart devices, SNS, big data, cloud, and IoT. This phenomenon is being spread more swiftly based on the wired and wireless communication infrastructure provided to most homes, as terminal devices for communication have more various functions and are being supplied to homes through a multi-vendor system and as several terminal devices are installed in each home to provide services. Particularly, various IoT terminal devices and services are being introduced to facilitate functions such as home crime prevention, gas valve control, control of electric apparatus and temperature-humidity sensors, and door control based on facial recognition, and integrated IoT-based management monitoring is required for TVs, washing machines, refrigerators, etc. Hence, in this study, a monitoring system for integrated home network management and data collection management, which solves problems of existing home network systems by connecting API Adaptor connection technology, message technology for integrated management of universal communications terminal devices and IoT devices, and data modelling technology to individual network platforms, was proposed.
Hardware-software timing coverification of concurrent embedded real-time systems

The results of hardware-software codesign of concurrent embedded real-time systems are often not verified or not easily verifiable. This has serious consequences when high-assurance systems are codesigned. The main difficulty lies in the different time-scales of the embedded hardware, of the embedded software, and of the environment. This difference makes hardware-software timing coverification not only a difficult task for most systems, but has also restricted coverification to the initial system specifications. Currently, most codesign tools or methodologies only support validation in the form of cosimulation and testing of design alternatives. Here, a new formal coverification approach is proposed based on linear hybrid automata. The basic timing problems found in most coverification tasks are presented and solved. For complex systems, a simplification strategy is proposed to attack the state-space explosion occurring in formal coverification. Experimental results show the feasibility of the approach and the increase in verification scalability through the application of the proposed method.
Refinements of machine translation by automatic editorial operations

The performance of state-of-the-art machine translation (MT) systems is still far from being perfect. In this article, we investigate the combination of on-line MT systems to produce better outputs. The basic idea is to apply editorial operations of substitution, insertion, and deletion to candidate outputs in an automatic fashion. The proposed methods are evaluated on the translation task in the travel domain from Chinese to English as defined in the International Workshop on Spoken Language Translation evaluation campaign. Outputs of three on-line MT engines are combined. The proposed method is evaluated on Chinese-to-English MT tasks in the tourism domain. An overall improvement of 1.4 in the BLEU score over the best single-system baseline has been achieved.
Speaking: From Intention to Articulation

In Speaking, Willem "Pim" Levelt, Director of the Max-Planck-Institut fur Psycholinguistik, accomplishes the formidable task of covering the entire process of speech production, from constraints on conversational appropriateness to articulation and self-monitoring of speech. Speaking is unique in its balanced coverage of all major aspects of the production of speech, in the completeness of its treatment of the entire speech process, and in its strategy of exemplifying rather than formalizing theoretical issues.
Face Processing: Models For Recognition

The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.
Implementation of Support Vector Machine Technique in Feedback Analysis System

E-commerce is very popular and interactive these days. Industries that produce new products and selling them on the Web often ask their customers to review the products which they have purchased. These reviews help both i.e. customers as well as producers. Producers get the idea from reviews about how their customers feel about the product which they have purchased and customers who want purchase the product read these reviews and take decision. As the number of responses are available very large in number, manually organizing large set of reviews/responses into required categories and analyzing them is time consuming, expensive and is often not feasible. So automated text classification is done to overcome these constraints. Various techniques can be used for automatic text classification. In this paper Support Vector Machine (SVM) which is a supervised learning technique is used in feedback analysis system which accepts the responses given by students as input preprocess it and lastly applies term weighting algorithm. After applying term weighting algorithm it displays analysis to the particular faculty. General Terms Web, E-commerce, Responses, Techniques
Implications of frequent subtree mining using hybrid support definitions

Frequent subtree mining has found many useful applications in areas where the domain knowledge is presented in a tree structured form, such as bioinformatics, web mining, scientific knowledge management etc. It involves the extraction of a set of frequent subtrees from a tree structured database, with respect to the user specified minimum support. Up to date, the commonly used support definitions are occurrence match and transaction based support. There are some application areas where using either of these support definitions would not provide the desired information automatically, but instead further querying on the extracted patterns needs to take place. This has motivated us to develop a hybrid support definition that constrains the kind of patterns to be extracted and provides additional information not provided by previous support definitions. This would simplify some of the reasoning process which commonly takes place in certain applications. In this paper we demonstrate the need for the hybrid support definition by presenting some applications of tree mining where traditional support definitions would fall short in providing the desired information. We have extended our previous tree mining algorithms to mine frequent subtrees using the hybrid support definition. Using real-world and synthetic data sets we demonstrate the effectiveness of the method, and further implications for reasoning with the extracted patterns.
Matched-filter based detection and localization of epileptic seizures from spectrographic chirps in ECoG recordings

Discusses the use of a common signal-processing tool, the spectrogram, in the detection and localization of epileptic seizures. Spectrograms are computed from electrocorticograms (ECoG) obtained by measuring electric potentials directly on the surface of the brain. Chirp-like patterns are observed in spectrograms of single-channel ECoG recordings during seizure activity which appear unique for each patient. Detection and localization of epileptic seizures are illustrated through design of a matched filter based on these patterns.
Velocity based vestibular-visual integration in active sensing system

It is necessary for most of advanced visual sensing systems to realize visual stabilization and target gazing prior to recognition process when operating in a structurally unconstrained environment. In this paper, a new method of acquiring that fundamental ability by sensor fusion technique is proposed. It is important to choose an appropriate sensor fusion basis, and it is proposed to integrate the visual system with angular velocity sensors and a gaze control system by one of those constraint conditions which govern the relation between measured and control variables. It is also proposed that such a visual sensing system is realized by integrating the systems through their (angular) velocity information. Because the velocity field in the image can be now calculated in real time and the angular velocity can be treated directly by both rate gyroscopes and gaze control motors, such an integration is expected to fit for the visual system which requires quick response. Experimental results show that proposed velocity based visual stabilization is feasible and exhibits better performance than that solely by a single sensation. The reason accounting for this improvement is also theoretically discussed. <<ETX>>
Efficient Features for Movie Recommendation Systems

User written movie reviews carry substantial amounts of movie relatedfeatures such as description of location, time period, genres, characters,etc. Using natural language processing and topic modeling basedtechniques, it is possible to extract features from movie reviews and findmovies with similar features. In this thesis, a feature extraction methodis presented and the use of the extracted features in finding similarmovies is investigated. We do the text pre-processing on a collection ofmovie reviews. We then extract topics from the collection using topicmodeling techniques and store the topic distribution for each movie.Similarity metrics such as Hellinger distance is then used to find movieswith similar topic distribution. Furthermore, the extracted topics areused as an explanation during subjective evaluation. Experimental resultsshow that our extracted topics represent useful movie features andthat they can be used to find similar movies efficiently.
Standing on the shoulders of the trusted web: Trust, Scholarship and Linked Data

The web of linked data is incompatible with the modern \selsh scientist". What is missing is a mechanism that supports both what scientists share, and how they share. Solutions must be informed by social, technical and cultural issues surrounding the sharing of scientic data in the web of linked data. We propose the adoption of social trust techniques to share a new emerging class of scientic digital object - Research Objects. We suggest a mechanism for introducing social trust metrics into the distributed social web to facilitate access control to aggregations of linked data resources. Through the application and analysis of two established trust metrics, we then present the grounding of the Colleague of a Colleague (Cocoa) trust metric suited to the sharing of scientic knowledge delivered as Research Objects.
The Effect of Dehydration on Metabolism and Energy Substrate Utilization

The purpose of this study was to measure hormonal and metabolic markers in humans to see if simulating dehydration would emulate measures that are seen in prediabetic humans. 60 volunteers were divided into equal categories by sex and body mass index of normal or overweight. Participants completed two oral glucose tolerance tests (OGTT) after being intravenously infused with a isotonic or hypertonic saline solution for 120 minutes in a counter balanced order. All trials began with a euhydrated subject with a urine specific gravity (USG) <1.020. Participants remained sedentary and were infused with the same amount of volume of solution in each trial, blood samples were taken every 30 minutes and respiratory exchange ratio was measured every 60 minutes. The hypertonic (HYPER) trial 120 minutes after OGTT was administered had significantly higher carbohydrate oxidation then that of the isotonic trial. Blood markers such as cortisol and aldosterone lowered significantly from baseline, but glucose was significantly elevated 60 and 90 minutes post infusion, reaching blood glucose levels of 155mg/dL. Plasma osmolality rose from baseline and remained elevated throughout the duration of the trial. Copeptin rose significantly during the HYPER trial 30 minutes into infusion and remained elevated the entire length of the trial falling slightly after infusion stopped. This may indicate that the elevated copeptin is associated with elevated glucose levels, and carbohydrates as the primary fuel source
Training Novices on Hierarchical Task Analysis

Understanding how best to provide training for task analysis remains unspecified. This study examined how different training methods affect knowledge acquisition, focusing on content learned and errors made by novices in the initial phase of learning Hierarchical Task Analysis (HTA). Participants were assigned to one of three types of declarative instructions: procedures, decision/actions, and concept map, which were representative of different types of diagrams (matrix, network, hierarchy). After instructions, participants performed task analyses of five different tasks. Questionnaire data (declarative knowledge) and task analyses (procedural knowledge) were coded on five criteria: hierarchical representation, stating high-level goal, stating plan, stating subgoals, and satisfaction criteria. Results indicated that various aspects of the task analyses were influenced more by the nature of the task than the differences in training material at this early stage of learning. Participants recognized the importance of mentioning the high-level goal, redescribing goals into subgoals, and the plan. However, the hierarchical aspect and considering satisfaction criteria were not prevalent in either recall test or the task analyses produced. Participants in the concept map condition did identify a larger number of subgoals, but further studies are needed to understand this effect. This study informs research about various types of diagrams that are useful for training and adds to the literature on training HTA itself.
Study-abroad, Language Proficiency, and Learner Beliefs about Language Learning

This article reports an empirical study of a 1 -week study-abroad program for Japanese university students, examining changes in the students’ beliefs about language learning (measured by means of a questionnaire) and in their English proficiency (measured by means of the TOEFL). The results showed statistically significant changes in the students’ beliefs relating to analytic language learning, experiential language learning and self-efficacy/confidence during the study-abroad period. Statistically significant gains in proficiency are also reported. However, Pearson product moment correlations between the students’ responses to the Belief Questionnaire and their TOEFL scores both before and after the study-abroad period were weak and generally statistically non-significant. The results are discussed in relation to study-abroad programs and also to the role of learner beliefs in second language learning. 本稿は、15週間の海外留学プログラムに参加した日本人大学生の言語学習に関する確信 (beliefs)と英語能力の変化を、質問紙とTOEFLを用いて測定した調査の報告である。 分 析の結果、留学経験後、分析的言語学習、経験的言語学習、そして自己能力・自信に関す る学生達の確信に、統計的に有意な変化が見られた。 また英語能力に関しても、統計的に 有意な変化が見られた。 しかし、質問紙への回答に表れた学生達の言語学習に関する確信 とTOEFLスコアの相関は、留学前も留学後も弱く、統計的に有意なものではなかった。 こうした結果を、海外留学プログラムや第二言語習得における学習者の確信の役割と関連 付けて論じる。
Recursive Autoencoder with HowNet Lexicon for Sentence-Level Sentiment Analysis

Semantic word representations have been very useful but usually ignore the syntactic relationship. In the task of sentiment analysis, compositional vector representations require more structure information from natural language text and richer supervised training for more accuracy predictions. However, labeled data are generally expensive to acquire in reality. To remedy this, we propose a new method that train our model based on fully labeled parse tree using supervised learning without manual annotation. Our method not only significantly reduces the burden of manual labeling, but also allows the compositionality to capture syntactic and semantic information jointly. We show the effectiveness of this model on the task of sentence-level sentiment classification and conduct preliminary experiments to investigate its performance. Lastly, it can accurately predict the sentiment distribution and outperforms other approaches.
Online software applications for learning: observations from an elementary school

This exploratory case study research describes the integration of Information Communication Technology (ICT) into the teaching and learning of English, mathematics and science in an elementary school in Singapore. The school in this case study research is one of the first primary-level future schools that was set up under the FutureSchools@Singapore program in 2008. The school has implemented a successful one-to-one program (i.e. one-to-one computer to student ratio) for all its students. The use of blogs, communication applications (e.g. online chats and email), online educational games, online learning management systems, online searches for information and educational related videos were commonly used to integrate ICT into the teaching and learning of the various subjects mentioned above. A total of 221 (Primary 3 and 4) and 466 (Primary 3, 4 and 5) students participated in an ICT usage survey conducted in 2011 and 2012, respectively. Three interesting phenomena were observed through the descriptive statistics. First, it was observed that the ICT usage rates for the various subjects (i.e. English, mathematics and science) peaked at the primary 4 level when the computer ownership program was introduced and declined in primary 5. Second, descriptive statistical analysis suggested the use of blogs, communication applications, online educational games and Internet searches, were more frequently used, as compared to the learning management systems and the use of videos, in the students’ learning of English, mathematics and science. Thirdly, ICT usage rates were also different for the different classes of Primary 5. Follow-up interviews with teachers and student open-ended survey responses were also analysed. The triangulated findings seemed to suggest that blogs were frequently used and acted as gateways to other online software applications. The findings also once again pointed to the importance of the sociocultural context – school leadership, curriculum planning and assessment, technological infrastructure and teachers’ practices – in ICT usage and integration in schools.
A scalability Study of SGI Clustered XFS Using HDF Based AMR Application

Many large-scale parallel scientific and engineering applications, especially climate modeling, often run for lengthy periods and require data checkpointing periodically to save the state of the computation for a program restart. In addition, such applications need to write data to disks for post-processing, e.g., visualization. Both these scenarios involve a write-only pattern using Hierarchal Data Format (HDF) files. In this paper, we study the scalability of CXFS by HDF based Structured Adaptive Mesh Refinement (AMR) appli- cation for three different block sizes. The code used is a block-structured AMR hydrodynamics code that solves compressible, reactive hydrodynamic equations and characterizes physics and mathematical algorithms used in studying nuclear flashes on neutron stars and white dwarfs. The computational domain is divided into blocks distributed across the processors. Typically, a block contains 8 zones in each coordinate direction (x, y, and z) and a perimeter of guard cells (in this case, 4 zones deep) to hold information from the neighbors. We used three different block sizes of 8 × 8 × 8, 16 × 16 × 16, and 32 × 32 × 32. Results of parallel I/O bandwidths (checkpoint file and two plot files) are presented for all three-block sizes on a wide range of processor counts, ranging from 1 to 508 processors of the Co- lumbia system.