Miracle-dz/UniFAR-FTUs huggingface dataset:
Task Affect and Task Understanding in Engineering Problem Solving

Within the self-regulated learning literature, motivation is considered to be an essential feature of students’ self-regulatory processes. Additionally, task affect (i.e., personal objectives and task value) is thought to influence students’ self-regulatory processes; insufficient task affect may lead to failures to selfregulate effectively. In a school setting, task affect is a form of motivation for completing the course tasks in order to attain course-level goals that are inherently valued. In this study, motivation is operationalized as students’ personal objectives and task values, and self-regulation refers to students’ understanding of tasks (also called task interpretation skill) involved in a course. This study investigates changes in students’ task interpretation skill, personal objectives for learning, and task values, if any, while engaged in engineering problem-solving activities in a 2nd-year introductory thermodynamics course. This study also seeks to explore whether patterns exist between students’ task understanding, personal objectives for learning, and task value while engaged in problem-solving activities throughout the course. The findings suggest that, as the semester progressed, both students’ task value for the course and their focus on mastering the course material were continuously developed. Similarly, students’ explicit and implicit task interpretation skills also improved as they engaged in problem-solving activities. However, it was found that implicit task interpretation skill was not developed as fully as explicit task interpretation when solving a complex problem; students seemed to understand 64–77% of the explicit and 39–49% of the implicit information presented to them.
Safety and Efficacy of The Available Oral Anti diabetic Drugs In Treating Type II Diabetics During Ramadan Fasting In Sohag Governorate.

Objective: to assess safety and efficacy of the available oral anti diabetic Drugs during Ramadan 2016 in Sohag Governorate . Methodology: This study was conducted on 90 type II Diabetic patients attending to outpatient Endocrinology clinic in Sohag University Hospital, on oral treatment classified into 5groups,as following , 20 (22.22%)patients on Metformin(Group I),30 (33.33%)patients on Sulphonylureas with or without metformin(Group II), 18 (20%) patients on Dipeptidyl peptidase-4 inhibitors with or without metformin (Group III),12 (13.33% ) patients on Thiazolidinedoines with or without metformin (Group V),10 (10%) patients on combinations of more than two drugs (Group VI), Mean age of patients is 59.93±7.87years, (61.11%)of them were females,(38.89%) of them were male patients and Mean duration of diabetes is 4.52±2.45(range 1:10). follow up of the patient was done by Wight changes, measuring blood sugar ,asses Hba1c ,and renal function also was done before and during ramadan. Results: In this study we found a significant decrease in Hba1c after Ramadan with Group III (DPP4I) compared with other Groups also we found the number of hypoglycemic episodes of all groups about 10 (11.11%), more with Group II (SUs) about (9) patients developed hypoglycemia of whom 30, compared with other groups while lower number of hypoglycemia was found with Group III (DPP4I),about one patient developed hypoglycemia, also we found the number of non fasted days more with SUs,(range 2-10) also we found no body weight changes more with Group III (DPP4I) while body weight gain occurred with Group II (SUs) about 1-4Kgs . In conclusion, Ramadan represents one of challenging issues for health care providaers all over the world . DPP4 inhibitors may considered favorable for use during and after Ramadan due to their lower rate of hypoglycemic events and weight neutral/loss effect during and after Ramadan .
CNN-based Encoding and Decoding of Visual Object Recognition in Space and Time

Deep convolutional neural networks (CNNs) have been put forward as neurobiologically plausible models of the visual hierarchy. Using functional magnetic resonance imaging, CNN representations of visual stimuli have previously been shown to correspond to processing stages in the ventral and dorsal streams of the visual system. Whether this correspondence between models and brain signals also holds for activity acquired at high temporal resolution has been explored less exhaustively. Here, we addressed this question by combining CNN-based encoding models with magnetoencephalography (MEG). Human participants passively viewed 1000 images of objects while MEG signals were acquired. We modelled their high temporal resolution source-reconstructed cortical activity with CNNs, and observed a feedforward sweep across the visual hierarchy between 75-200 ms after stimulus onset. This spatiotemporal cascade was captured by the network layer representations, where the increasingly abstract stimulus representation in the hierarchical network model was reflected in different parts of the visual cortex, following the visual ventral stream. We further validated the accuracy of our encoding model by decoding stimulus identity in a left-out validation set of viewed objects, achieving state-of-the-art decoding accuracy.
Rerating the Movie Scores in Douban through Word Embedding

The movie scores in the social networking service website such as IMDb, Totten Tomatoes and Douban are important references to evaluate the movies. Always, it will influence the box office directly. However, the public rating has strong bias depended on the types of movies, release time, and ages and background of the audiences. To fix the bias and give a movie a fair judgement is an important problem. In the paper, we focus on the movie scores on Douban, which is one of the most famous Chinese movie network community. We decompose the movie scores into two parts. One is the basis scores based on the basic properties of movies. The other is the extra scores which represent the excess value of the movies. We use the word-embedding technique to reduce the movies in a small dense subspace. Then, in the reduced subspace, we use the k-means method to offer the similar movies a basis scores.
Experimental methodology for computational fluid dynamics code validation

Validation of Computational Fluid Dynamics (CFD) codes is an essential element of the code development process. Typically, CFD code validation is accomplished through comparison of computed results to previously published experimental data that were obtained for some other purpose, unrelated to code validation. As a result, it is a near certainty that not all of the information required by the code, particularly the boundary conditions, will be available. The common approach is therefore unsatisfactory, and a different method is required. This paper describes a methodology developed specifically for experimental validation of CFD codes. The methodology requires teamwork and cooperation between code developers and experimentalists throughout the validation process, and takes advantage of certain synergisms between CFD and experiment. The methodology employs a novel uncertainty analysis technique which helps to define the experimental plan for code validation wind tunnel experiments, and to distinguish between and quantify various types of experimental error. The methodology is demonstrated with an example of surface pressure measurements over a model of varying geometrical complexity in laminar, hypersonic, near perfect gas, 3-dimensional flow.
Contributions for the improvement of specific class mapping

The analysis of remotely sensed imagery has become a fundamental task for many environmental centred activities, not just scientific but also management related. In particular, the use of land cover maps depicting a particular study site is an integral part of many research projects, as they are not just a fundamental variable in environmental models but also base information supporting policy decisions. Land cover mapping assisted by supervised classification is today a staple tool of any analyst processing remotely sensed data, insomuch as these techniques allow users to map entire sites of interest in a comprehensive way. Many remote sensing projects are usually interested in a small number of land cover classes present in a study area and not in all classes that make-up the landscape. When focus is on a particular sub-set of classes of interest, conventional supervised classification may be sub-optimal for the discrimination of these specific target classes. The process of producing a non-exhaustive map, that is depicting only the classes of interest for the user, is called specific class mapping. This is the topic of this dissertation. Here, specific class mapping is examined to understand its origins, developments, adoption and current limitations. The main research goal is then to contribute for the understanding and improvement of this topic, while presenting its main constrains in a clear way and proposing enhanced methods at the reach of the non-expert user. In detail, this study starts by analysing the definition of specific class mapping and why the conventional multi-class supervised classification process may yield sub-optimal outcomes. Attention then is turn to the previous works that have tackled this problem. From here a synthesis is made, categorising and characterising previous methodologies. Its then learnt that the methodologies tackling specific class mapping fall under two broad categories, the binarisation approaches and the singe-class approaches, and that both types are not without problems. This is the starting point of the development component of this dissertation that branches out in three research lines. First, cost-sensitive learning is utilised to improve specific class mapping. In previous studies it was shown that it may be susceptible to data imbalance problems present in the training data set, since the classes of interest are often a small part of the training set. As a result the classification may be biased towards the largest classes and, thus, be
The Co-deployment of Visual Representations and Written Language as Resources for Meaning Making in Greek Primary School Science Textbooks

The aim of this study is to examine how certain meanings related to the nature of school science are produced by the ways the visual and the linguistic mode interact in school science textbooks. In total the linkage of 1575 visual representations with their linguistic counterparts was examined in the science textbooks of the fifth and sixth grade of the Greek primary school respectively (age level 10-12 years old). The co-deployment of the two modes is examined at two levels, distinguished only for methodological reasons. The first level is that of design which according to Kress and van Leeuwen, (2001) refers to the uses of semiotic resources, in all modes and combinations (here visual and written language) and stands midway between content (i.e. meaning) and expression. The second level is that of the semantic relationships between the visual representation and their corresponding linguistic parts. Specifically, for the first level we use a scheme developed by Kress and van Leeuwen, (1996) which attributes different informational values aacording to the relative placement of visual representations and their corresponding linguistic parts on the verical (top-down) and horizontal (left-right) axes of a textbook’s page layout. Futhermore in this level the explicitness of the way the visual representations are connected to their corresponding linguistic parts is examined. The second level of analysis is based on a classification system of seven mutually exclusive categories which desctribe the semantic relationships of the visual representations in relation to their linked linguistic parts. These categories correspond to the semantic functions of: a) expansion, b) conceptual organizationsummarizing, c) exemplification or counterexemplification, d) repetition, e) testimonial evidence, f) stimulus for science based activities (e.g. observation, classificatiom, etc) and g) decoration. In our analysis the type of the visual representations according to their modality and role (Dimopoulos, Koulaidis & Sklaveniti, 2003) as well as the different genres of the linguistic parts of the textbooks are taken into consideration. The results show that despite their heavy use, the visual representations seem to paly a subservient to the linguistic parts role in the meaning articulation. Moreover, it was found that the interaction between the two expressive modes tends to produce specific effects as far as the epistemic constitution of school science as a re-contextualized body of knowledge, is concerned. These effects are firstly the objectification of the natural world and secondly the attribution to both the everyday commonsensical knowledge, mainly articulated through the visual reperesenations and to scientific knowledge itself, mainly articulated through the linguistic mode, a mythological status.
A Design Framework for Collective Inquiry Learning Environments

This thesis describes a design-based research study of a recent KCI implementation in a wholeclass inquiry elementary science curriculum called WallCology, focusing on the interaction design aspects of its technological support. From that, the thesis builds a framework for HCI design for the specific context of Knowledge Community and Inquiry (KCI), a CSCL model that guides the design of collective inquiry curriculum in which students work together to advance their collective progress on a set of well defined learning goals. This design framework comprises a series of conceptual design principles, guidelines for implementing a visual language for interface design, and an ontology of human-computer interactions that could emerge in a KCI enactment, with examples of GUI design solutions to support them.
Adaptive spatial-temporal resolution optical vehicular communication system using image sensor

In this article, we introduce an image sensor–based optical vehicular communication system for performing vehicular condition resolution adaptively in the spatial domain and the temporal domain. To validate the proposed system, a dual camera–based approach is presented here, where a vision camera is used to detect multiple vehicles of interest (i.e. spatial condition), a communication link is set up, and then, a high-speed camera adapts its resolution to ensure fast processing and high-rate data communication (i.e. temporal condition). We suggest an adaptive algorithm that supports the detection of and communication multiple vehicles simultaneously in spatial-temporal condition. Moreover, we propose a combination of scale-invariant feature transform and iterative closest point for detection and classification of multiple vehicles. To prove the feasibility of our proposed scheme, we present simulation results.
Analyzing the Role of Users' Interactions in Information Spread

Analyzing the role of users’ interactions in information spread Milad Eftekhar Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2015 The emergence of social platforms has provided us with a vast amount of raw data on people’s daily activities, their social connections, interactions, interests, influence, etc. This creates an opportunity to extract valuable insights, helpful in various applications including but not limited to the identification of the trending topics, community detection, health purposes, and marketing. This thesis designs a platform that analyzes users’ interactions (e.g., posts, likes, and shares) and connections (e.g., friendship and followership), and maximizes information spread in the network accordingly. There are numerous applications to this such as advertising, knowledge dissemination, encouraging the adoption of productive behavior in a society, etc. I present a 3-part platform that utilizes users’ activities to maximize information spread. It starts by analyzing users’ posts (Step 1), and proceeds with users’ interactions (Step 2), and connections (Step 3). This information is utilized to locate user communities formed based on topical cascades. Targeting these communities helps to increase the spread of information. In the first step, posts (e.g., tweets) are categorized into partitions representing topics of discussion. Part 2 identifies bursty user groups for each topic of interest. A bursty user group includes a collection of socially connected users who are active and influential with regard to a specific topic. Bursty user groups for a topic are the sources of previous activities on that topic and are of high importance in marketing
A comparison of IELTS and TOEFL as predictors of academic success

With increasing numbers of international students enrolling in universities in English speaking countries such as Australia, the question of the level of English language proficiency (ELP) necessary for academic success becomes critical. The main question for this study was the usefulness of IELTS and TOEFL (the two main measures of ELP used for selection to universities in Australia) respectively as predictors of readiness for the Australian academic context. However, earlier research suggests that ELP is only one of a number of factors impinging on academic success (Davies 1990; Criper and Davies, 1988). This study was, therefore, also concerned with additional factors which may influence academic progress, such as the effect of English language support. The research was carried out at the University of Melbourne. Data for the study included students' IELTS and/or TOEFL scores and Grade Point Average as well as questionnaire and interview data. The relationship between GPA and IELTS scores was found to be moderately strong whereas the correlation between achievement and TOEFL score was relatively weak. These results appear to be consistent with the results of previous studies. In the interview and questionnaire data students identified non-linguistic factors affecting their academic performance which may help to explain the weak correlations between ELP score and academic success.
The Development and Testing of Technology Acceptance Models for Consumers towards the Intention to Use E-Wallet

—Acceptance of technology for consumers is still an interesting part to be investigated to date. Although the Technology Acceptance Model (TAM) has been widely referred by researchers from various sciences, there are still weaknesses that can be investigated, including not fully answering the problems related to cognitive and affective factors in understanding consumer behavior. The purpose of this study is to develop and test an integrated model to determine the intention of consumers to use technology. The object used is the go-pay application as e-Wallet-based Electronic Money which is one of the relatively new technology products as an alternative means of payment or transaction and is part of the National Non-Cash Movement by the government of the Republic of Indonesia. Modeling in this study, integrating the TAM model by involving affective factors namely Pleasure, Arousal, and Dominance (PAD) theory, and prior experience variables as a direct effect on perceived usefulness and attitude toward usage, then its effect on adoption intention. The sample in this study is millennial age people who have known go-pay in areas of East Java with a total sample of 270 respondents. Collecting data through questionnaires using a Likert scale with analysis techniques using Partial Least Square (PLS). The results of this study indicate that Perceived Usefulness, Perceived Easy of Use, Pleasure, and Arousal have a positive effect on attitude and intention to use go-pay, while Prior Experience supports perceived usefulness, but does not support attitude, neither does Dominance support the attitude of using gopay.
Implementation of novel sensors on underwater gliders

Around a quarter of global anthropogenic carbon emissions have been absorbed by the ocean. Underwater gliders have been identified as important tools for gathering information related to climate change and ocean acidification processes. The REP14 -MED experiment involved the deployment of eleven gliders in the northwestern Mediterranean Sea; one of these had an experimental ion sensitive field effect transistor (ISFET) sensor attached. A comparison between pH observed by the glider and ship during the deployment indicated problems with the sensor accuracy and stability. Sunlight caused an apparent sensor pH decrease of up to 0.1 close to the surface around local noon. The pH corrected for drift, temperature, and pressure is presented with other ocean variables measured by the glider. The timing of the phytoplankton spring bloom in the northwestern Mediterranean Sea varies year-on-year. A glider with an ISFET pH sensor was deployed close to the BOUSSOLE mooring site. This deployment offered a second opportunity to test the ISFET sensor with improvements. Similarly to during the REP14 -MED experiment, ISFET pH measurements were corrected for drift, temperature and pressure effects. Measurements at the BOUSSOLE mooring indicated that the spring bloom started around March 19. Mean net community production (N) rates were estimated from the glider dissolved oxygen concentrations, as well as glider and buoy dissolved inorganic carbon concentrations derived using other parameters. N ranged between -82±317 mmol m-2 d-1 and 460±870 mmol m-2 d-1. Horizontal spatial scales of variability highlight physical and biogeochemical processes, and are useful for designing ocean observing systems. Spatial scales of variability were estimated from semivariograms using glider measurements. Spatial scales of variability were mostly small at depths affected by biology, and large at depths affected by largescale processes, such as weather, although this was not true in every case. Some direction-dependency was found, which may be related to ocean currents, or the density of glider meridional measurements. keywords: pH sensor; underwater gliders; biogeochemistry; net community production; spatial scales; northwestern Mediterranean Sea
Subjective survival: An assessment of accuracy according to individual social profile

Abstract The present study aims at identifying traits that relate to the underestimation or the overestimation of survival, using information from a rich dataset, the Survey of Health Ageing and Retirement in Europe (SHARE wave 6, 2015) and the Human Mortality Database. The statistical analysis is based on generalized linear regression models. Better cognitive function and higher educational attainment are linked to more accurate predictions. Female gender, smoking, poor health and memory, lower income, and depression seem associated with the underestimation of survival while older age, better quality of life, being employed and having more children are related to overestimation.
Implementasi Protokol MQTT pada Smart Building Berbasis OpenMTC

Abstrak Bangunan adalah salah satu kebutuhan pokok, sebagai ruang yang memberikan kenyamanan dan keamanan bagi penghuninya. Seiring pertumbuhan teknologi dan ilmu pengetahuan, fungsionalitas bangunan pun ditingkatkan. Bangunan yang dapat mengatur konsumsi energinya dan mengurangi dampak pada lingkungan sehingga dapat kita sebutkan sebagai smart building. Hal yang paling mendasar adalah smart building dapat memberikan layanan yang lebih seperti pengaturan pencahayaan, keamanan, pengatur suhu dan lain sebagainya. Smart building adalah hasil implementasi dari Machine-to-Machine (M2M). OpenMTC adalah salah satu platform M2M dengan protokol komunikasi yang disediakan adalah HTTP. Pada penelitian ini menerapkan protokol MQTT pada platform OpenMTC sebagai protokol komunikasi. Hasil penelitian menunjukan protokol MQTT dapat diterapkan pada platform OpenMTC sehingga mendapatkan hasil perbandingan protokol MQTT dan protokol HTTP dengan parameter uji delay, packet loss, protocol overhead. Kata Kunci: Smart Building, M2M, OpenMTC, MQTT, HTTP