Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between self-regulated learning strategy and motivation of management students

Self-regulated learning approach has been of interest to researchers especially at school level education. An attempt has been made here to find how self-regulated learning strategy and motivated learning strategy impacts the learning process of a MBA student. A modified self-regulated learning strategy (SRLS) and motivated learning strategy questionnaire (MLSQ) was administered to 165 students in a top residential B-School in India. Both the scales showed very high internal consistency. Students had varying prior work experiences and educational background. It was observed that students with high intrinsic motivation and high prior academic performance had significantly higher generalised organisation and planning strategy, but, these however did not significantly impact their critical thinking ability. High task motivation was observed to induce better learning strategy, external regulation and critical thinking ability. Males were observed to score significantly higher on organisation and planning strategy and need for environmental restructuring. For management students to be effective leaders and decision makers their critical thinking ability requires to be developed which can be achieved by inducing high task motivation by clear demarcation of curriculum objectives, learning objectives of each course; blended method of learning with multiple reasoning approach, thus activating the task and intrinsic motivations of students.
Analysis of Micropile Constructed in Sandy Soil of Ismailia Area

The main object of the paper is to study the behavior of Micropile in sandy soil of Ismailia. A full scale field test result on Micropiles in USA for rocky soil are numerically verified using the finite element analysis software ABAQUS. Then, the verified numerical model of the software ABAQUS is used to curry out the analysis of Micropiles constructed in sandy soil of Ismailia area. Numerical results obtained are very close to the field results. The chosen model is suitable for initial prediction of the behavior of micropile instead of field tests which take more time and cost. Results indicated that, application of the combined load on the micropile causes a decrease in the lateral displacement and bending moments compared with application of the lateral load at Ismailia site (sandy soil). The effect increasing the diameter by 50[%] on the behavior of the micropile is reducing the axial displacement by 22[%] and increasing the axial ultimate load by 30[%]. The lateral loading results indicate that the lateral displacement is reduced by 43.5[%] and the lateral ultimate load increases by 35.1[%], whereas the maximum bending moment increases by 192.4[%]. The combined loading results show that the lateral displacement is reduced by 40.4 [%] and the lateral ultimate load increases by 41[%], but there is more change in the maximum bending moment which increases by 292[%]. The study also presents guidelines and diagrams for the similar sites for different types of load.
Evaluation of the Microsoft HoloLens for the Mapping of Indoor Building Environments

: Mobile augmented reality devices like the Microsoft HoloLens are capable of simultaneously tracking the device location and mapping its environment in real-time. Thus, they offer potential for acquiring at least coarse point clouds and meshes of single rooms or even complete building structures that can be used in the context of building information modelling (BIM) in the future instead of manually modelling existing buildings based on 2D floor plans or manual measurements with laser scanners or computationally expensive image-based 3D reconstruction techniques. For this reason, we provide an extensive quantitative evaluation of the mapping results of the Microsoft HoloLens against terrestrial laser scanning (TLS) ground truth. We show that while the geometry of single rooms can be mapped quite accurately with the HoloLens, deviations may occur in the spatial arrangement of multiple rooms relative to each other.
Multiobjective optimization using a micro-genetic algorithm

In this paper, we propose a micro genetic algorithm with three forms of elitism for multiobjective optimization. We show how this relatively simple algorithm coupled with an external file and a diversity approach based on geographical distribution can generate efficiently the Pareto fronts of several difficult test functions (both constrained and unconstrained). A metric based on the average distance to the Pareto optimal set is used to compare our results against two evolutionary multiobjective optimization techniques recently proposed in the literature.
Exploring MARS: an alternative to neural networks

S ince their inception, neural networks have commanded a significant amount of attention in the world of machine learning – yet neural networks are not the only game in town. While they have been instrumental in solving many difficult real-world problems, keep in mind the wide array of alternatives. One such alternative is Multivariate Adaptive Regression Splines (MARS), developed by statistician Jerome Friedman. MARS segments the space of possible input cases into rectangular regions that are fit with linear or cubic splines — splines being moderately complex curves. The MARS approach has proven effective at a variety of learning problems and is competitive with neural networks and Non-parametric regressions, such as knearest neighbors. After its recent incorporation into the suite of products offered by Salford Systems (www.salfordsystems.com ), MARS has been further developed into a fine commercial tool (see Figures 1 and 2). MARS is an excellent example of the powerful modeling tools developed by statisticians and is explored in this article. A standard machine learning benchmarking data set, the Boston Housing data, is used to demonstrate MARS’s operation principles. This data, available on-line at the UCI Machine Learning Repository (www.ics.uci.edu/~mlearn/MLRepository.html ) contains information on 506 examples of housing data from the Boston area consisting of 13 numeric variables and 1 binary variable. One numeric variable, the learning algorithms may be placed on a spectrum from local to global. Local models utilize a large collection of small ‘micromodels’ that handle specific, small regions of the input space. Global models employ a single, monolithic model covering the entire input space. Very often, local models are fast to train, but slow to recall, whereas global models are slower to train, but quick to recall. More importantly, local models quickly learn to solve the specific types of problems that are presented during training, but are slow to generalize to other types of problems. In contrast, global models are Exploring MARS: An Alternative to Neural Networks
Applied Animal Reproduction

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Error detection in content word combinations

Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as specified in the text. I further state that no substantial part of my dissertation has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Cambridge or any other University or similar institution except as specified in the text. It does not exceed the prescribed word limit for the relevant Degree Committee. Summary This thesis addresses the task of error detection in the choice of content words focus-ing on adjective–noun and verb–object combinations. We show that error detection in content words is an under-explored area in research on learner language since (i) most previous approaches to error detection and correction have focused on other error types, and (ii) the approaches that have previously addressed errors in content words have not performed error detection proper. We show why this task is challenging for the existing error detection algorithms and propose a novel approach to error detection in content words. We note that since content words express meaning, an error detection algorithm should take the semantic properties of the words into account. We use a compositional distribu-tional semantic framework in which we represent content words using their distributions in native English, while the meaning of the combinations is represented using models of com-positional semantics. We present a number of measures that describe different properties of the modelled representations and can reliably distinguish between the representations of the correct and incorrect content word combinations. Finally, we cast the task of error detection as a binary classification problem and implement a machine learning classifier that uses the output of the semantic measures as features. The results of our experiments confirm that an error detection algorithm that uses semantically motivated features achieves good accuracy and precision and outperforms the state-of-the-art approaches. We conclude that the features derived from the semantic representations encode important properties of the combinations that help distinguish the correct combinations from the incorrect ones. The approach presented in this work can naturally be extended to …
Study and design of interaction techniques to facilitate object selection and manipulation in virtual environments on mobile devices

The advances in the field of NUIs (Natural User Interfaces) can provide more and more guidelines for designers to develop efficient and easy-to-use techniques for 3D interaction. In this context, mobile devices attract much attention to design 3D interaction techniques for ubiquitous usage. Our research work focuses on proposing new techniques to facilitate object selection and manipulation in virtual environments on mobile devices. Indeed, the efficiency and accuracy of object selection are highly affected by the target size and the cluster density. To overcome the fingertip occlusion issue on Smartphones, we have designed two touchbased selection techniques. We have also designed one freehand hybrid technique for selection of small objects displayed at a distance. To perform constrained manipulation on Tablet-PCs, we have proposed a bimanual technique based on the asymmetrical model. Both hands can be used in collaboration, in order to specify the constraint, determine the manipulation mode, and control the transformation. We have also proposed two other single-hand manipulation techniques using identified touch inputs. The evaluations of our techniques demonstrate that they can improve the users’ interaction experience on mobile devices. Our results permit also to give some guidelines to improve the design of 3D interactions techniques on mobile devices.
Brownian approximations for queueing networks with finite buffers :modeling, heavy traffic analysis and numerical implementations

Date Approved by Chairman: iii Dedication to my parents and family iv Acknowledgment I would like to express my sincere gratitude to everyone who has made it possible for me to achieve my goals and finish my degree. First and foremost I am grateful to my advisor, Professor Jim Dai, for introducing me to reflecting Brownian motions and their applications in queueing networks, and for his many helps. Throughout my graduate studies at Georgia Tech, I benefit a great deal from Professor Richard Serfozo. He has been generous with his ideas, advice and help. Queueing network knowledge from him plays a fundamental role in this thesis. I am indebted to Professor Ian F. Akyildiz in the School of Electrical and Computer Engineering for motivating my research interests in finite buffer networks. He encouraged me and offered me opportunities to learn contemporary communication theory and technologies. Thanks go to Dr. Ernie Graves at Lucent Technologies/Bell Labs who made it possible for me to continue my research and development along this direction.
Electronic Departure Approval Requests in ATD-2 Daily Operations

The NASA Airspace Technology Demonstration 2 project is investigating Integrated Arrival-Departure-Surface air traffic management through progressive refinement of a surface air traffic management system fielded at Charlotte-Douglas International Airport. Among the areas under study are departure release-time approval request (APREQ) traffic management initiatives. Scheduling departures at downstream points and complying with approved departure release times helps flights fit smoothly into busy traffic streams. This paper presents a review of APREQ operations and compliance data from daily electronic APREQ negotiations over fourteen months beginning in January 2018. It describes APREQcompliance improvements observed as the electronic negotiation process has matured and discusses contributing factors, including renegotiation of departure release times.
Detecting communities in complex networks-A discrete hybrid evolutionary approach

Abstract Evolving densely connected communities of nodes in the real life complex networks is a computationally extensive (NP hard) problem. Nature based evolutionary heuristic algorithms provide an effective solution to such kind of problems. However, very few evolutionary approaches have been tested on this domain with most of them applying real time operators. Incorporating discrete behaviour in the evolutionary process can further lead to improvisation in the overall efficiency of the applied algorithm. This paper proposes a discrete adaption of the TL-GSO community detection (CD) algorithm for faster convergence of the optimization function in comparison to the existing variants of Group Search Optimization (GSO) and TL-GSO. The approach mixes the exploration strategies of Teachers Learners (I-TLBO) and GSO algorithms to detect communities in complex networks. It modifies the optical search of GSO to step search and real time crossover to single point crossover. The modifications result in minimizing the parameters to be externally set. Optimized search space reduces the runtime and evolve communities in an unsupervised manner. Experimental results on real and synthetic networks show that the proposed algorithm converges faster and evolves to accurate communities with high fitness as compared to varied state of the art CD algorithms.
Undergraduate Students’ Difficulties in Reading and Constructing Phylogenetic Tree

Representation is a very important communication tool to communicate scientific concepts. Biologists produce phylogenetic representation to express their understanding of evolutionary relationships. The phylogenetic tree is visual representation depict a hypothesis about the evolutionary relationship and widely used in the biological sciences. Phylogenetic tree currently growing for many disciplines in biology. Consequently, learning about phylogenetic tree become an important part of biological education and an interesting area for biology education research. However, research showed many students often struggle with interpreting the information that phylogenetic trees depict. The purpose of this study was to investigate undergraduate students’ difficulties in reading and constructing a phylogenetic tree. The method of this study is a descriptive method. In this study, we used questionnaires, interviews, multiple choice and open-ended questions, reflective journals and observations. The findings showed students experiencing difficulties, especially in constructing a phylogenetic tree. The students’ responds indicated that main reasons for difficulties in constructing a phylogenetic tree are difficult to placing taxa in a phylogenetic tree based on the data provided so that the phylogenetic tree constructed does not describe the actual evolutionary relationship (incorrect relatedness). Students also have difficulties in determining the sister group, character synapomorphy, autapomorphy from data provided (character table) and comparing among phylogenetic tree. According to them building the phylogenetic tree is more difficult than reading the phylogenetic tree. Finding this studies provide information to undergraduate instructor and students to overcome learning difficulties of reading and constructing phylogenetic tree.
Concurrent TP53 mutations predict poor outcomes of EGFR-TKI treatments in Chinese patients with advanced NSCLC

Purpose: The study investigated the impact of TP53 mutations on the clinical efficacy of first-generation EGFR-tyrosine kinase inhibitors (TKIs) in Chinese patients with advanced or recurrent non-small-cell lung cancer (NSCLC). Patients and methods: Tissues from 163 NSCLC patients at the Affiliated Hospital of Qingdao University were analyzed by next-generation sequencing (NGS) to determine the mutational status of EGFR and concurrent genetic alterations. TP53 mutations were evaluated in relation to baseline patient characteristics and treatment outcomes (progression-free survival [PFS], overall survival [OS], objective response rate [ORR] and disease control rate [DCR]). Results: Among 163 patients with advanced NSCLC, 77 were identified as EGFR-mutant (47.2%). Six patients who did not receive TKI treatment were excluded. Among the remaining 71 patients with EGFR genetic alterations, the frequency of pathogenic TP53 mutations was 60.6% (43/71), while other concurrent mutations were rare events. Markedly shorter median PFS (mPFS) (6.5 versus 14.0 months, P=0.025) and median OS (mOS) (28.0 versus 52.0 months, P=0.023) were observed in TP53-mut patients than in TP53-wt controls. The overall DCR and ORR of TP53-mutant patients were both lower than those of the TP53-wt cases (DCR: 76.7% versus 89.3%, P=0.160; ORR: 25% versus 28%, P=0.374). Differences in prognosis were significant, especially in the subgroup of patients with TP53 non-missense mutations, non-disruptive mutations, mutations in exon 6, mutations in exon 7 and mutations in the non-DBD region among all TP53 mutations. Conclusion: TP53 mutations reduce responsiveness to TKIs and worsen the prognosis of EGFR-mutant NSCLC patients, especially for those with non-missense mutations and non-disruptive mutations, as well as mutations in exon 6, exon 7 and non-DBD region, thus acting as an independent predictor of poor outcome in advanced NSCLC patients treated with first-generation TKI therapy. Our study also suggests that TP53 mutation might be involved in primary resistance to EGFR-TKIs in Chinese NSCLC patients.
Scale of Stereotypes about the Mentally Ill: Construction and Preliminary Psychometric Evidence

Developing awareness of stereotypes regarding people with mental disorders has great relevance, as it implies understanding the characteristics of the shared conceptualization society has toward this social group. Such understanding identifi es elements for action aiming to favor the social inclusion of these individuals. This research aimed to develop the Scale of Stereotypes about the Mentally Ill (SSMI) by gathering psychometric data. Two studies were performed. In Study 1, 210 university students with a mean age of 24.07 (SD = 5.77) participated. In Study 2, 206 university students with a mean age of 24.35 (SD = 6.51) were included. In the fi rst study, principal component analysis indicated the existence of two components (Threat Stereotypes, α = 0.81; Disability stereotypes, α = 0.80) with 10 items in total. In the second study, a confi rmatory factor analysis indicated that the two-factor model proposed for the scale was adequate: χ2/df = 2.31, GFI = 0.93, CFI = 0.94, and RMSEA = 0.08 (90% CI = 0.057 – 0.103). It was concluded that this measure exhibits apparent factor validity and internal consistency and can be used to measure stereotypes about individuals with mental illness adequately.
Radio background and IGM heating due to Pop III supernova explosions

We consider the synchrotron emission from high energy electrons accelerated in supernova explosions of massive Population III stars in high redshift minihaloes of mass $10^{5\hbox {--}7} \rm M_\odot$. We show the resulting intensity of radio background from this process can be substantial, which could potentially explain the recently reported EDGES result, if not for the associated heating of the IGM by CR protons which are also produced at the same time. The trade-off between the radio background and heating is such that the 21 cm brightness temperature cannot be larger than $\vert \Delta T_{21}\vert \sim 0.25$ K. The radio background and heating are both produced by energetic particles, although one by energetic electrons and the other by energetic protons. The two competing processes, production of radio background and heating of IGM by Pop III supernovae, determine the depth of the trough in the 21 cm brightness temperature which can be observed in future experiments and used as a test of this scenario.
The representation of spatial mental models in long-term memory

This thesis is concerned with how people understand and remember spatial information derived from verbal descriptions. The thesis distinguishes between three different ways of representing spatial information in working memory. The first way is to represent the surface form of the source from which the spatial information is derived (the language of a description). The second is to represent the structure of the situation derived from that source (a spatial mental model). The third is to represent the perceptual characteristics of the situation from a particular perspective (a visual image). Considerable evidence exists that people construct and manipulate spatial mental models in working memory. The purpose of this thesis is to investigate the claim that mental models are represented in long-term memory. An outline of the spatial mental modeling processes required to understand a simple spatial description is proposed. It is proposed that spatial mental modeling is comprised of three processing stages. Firstly, comprehension processes are required to access the linguistic meaning of information presented in spatial description. Secondly, construction processes are required to build up a representation of the spatial structure of the situation derived from the language of the description. Thirdly, consultation processes are required to monitor construction and to access information from the spatial mental model. Nine experiments are reported which investigate evidence for and against the view that people remember the construction and consultation of a spatial mental model. In the final chapter this evidence is reviewed and a 'sketch' of a processing theory of memory for spatial descriptions is proposed. It is argued that memory for a spatial mental model is a product of the interaction between construction and consultation processes over a period of time rather than a simple 'copy' of a completed working memory spatial mental model.