Miracle-dz/UniFAR-FTUs huggingface dataset:
Delving Deep into Least Square Regression Model for Subspace Clustering

Subspace clustering is the problem of clustering data drawn from a union of multiple subspaces. The most popular subspace clustering framework in recent years is the spectral clustering-based approach, which performs subspace clustering by ﬁrst computing an afﬁnity matrix and then applying spectral clustering to it. One of the representative methods for computing an afﬁnity matrix is the least square regression (LSR) model, which is based on the idea of self-representation. Although its efﬁciency and effectiveness have been empirically validated, it lacks some theoritical analysis and practicality, e.g . : absense of interpretations, lack of theoretical analysis on its robustness, absense of guidelines for choosing the hyper-parameter, and the scalability. This paper aims at providing novel insights for better understanding on LSR, and also improving its practicality. For this purpose, we present four contributions: ﬁrst, we present a novel interpretation of LSR, which is based on random sampling perspective. Second, we provide novel theoretical analysis on LSR’s robustness toward outliers. Third, we theoretically and empirically demonstrate that selecting a larger value for the hyper-parameter tends to result in good clustering results. Finally, we derive another equivalent form of the LSR’s solution, which can be computed with less time complexity than the original form regarding the data size.
Alexithymia Levels and Facial Emotion Recognition Skills in Psoriasis Patients

The purpose of this study was to examine alexithymia levels and abilities to recognize facial emotions among psoriasis patients and compare with healthy controls. Sixty psoriasis patients diagnosed in dermatology clinics, and 65 age, sex and educationally matched healthy controls were assessed for this randomized controlled trial. Psoriasis Area Severity Index (PASI) was applied to patients in dermatology clinics, Structured Clinical Interview for DSM-IV Axis-1 Disorders, 20-item Toronto Alexithymia Scale (TAS-20), Facial Emotion Recognition Test (FERT) were applied to patients and controls in psychiatry clinics. Patients’ mean TAS-20 total scores were higher, while their ability to recognize negative facial emotions were lower than the control group Patients might have underestimated especially negative emotions over time, for a possible defense mechanism against depression and anxiety. Alexithymia levels were significantly related with psoriasis disease severity. Thus, alexithymia might be a predictor for severity of psoriasis.
INFLUENCE OF A TEACHİNG MATERİAL DEVELOPED WİTH REGARD TO ARCS MODEL OF MOTİVATİON TO CONCEPTUAL CHANGE

The general purpose of this study is to determine its structure in terms of its attention-relevance (A-R) and confidencesatisfaction(C-S) sub-dimensions of ARCS Model of Motivation of Locating Scientific Concepts Comic Booke (LSCCB) and explaining the relation of these sub-dimensions with conceptual change. The design of the research is pre-test-post-test without control group experimental design. The study has been actualised with the participation of 212 (105 boys; 107 girls) 7th-grade learners (age of 13-14), who continue their educations, from two different state secondary schools in İzmir province, the centre of Bornova district. The working group has been defined in accordance with an appropriate sampling method. Quantitative data of the research has been collected by using the diagnostic test of energy misconception of living things and teaching materials motivation scale , on the other hand, the qualitative data has been collected by using the semi-structured interview. In the analyses; quantitative data descriptive statistical techniques, analysis of variance and correlation and regression analysis techniques have been used. As a result of the research, it has been reached a conclusion that, the attributions of LSCCS support the conceptual change, it has a motivation structure at a level of AR and CS, in the conceptual change,a motivation at a level of AR and CS has been effective.
Hardware-inthe-Loop Simulation of Satellite Capture on a Ground-Based Robotic Testbed

The development of a ground testbed that can accurately replicate robotic operations in space is critical to realizing servicing and repair of on-orbit assets. This paper focuses on a hardware in-the-loop simulation of the initial capture of the satellite using a commercial manipulator to simulate the servicing arm and a parallel motionbased platform to replicate the client satellite. Achieving a stable grasp of the satellite is highly dependent on several factors including the satellite mass parameters, approach speed, and compliance control gains. Preliminary results and key trends will be reviewed from simulations conducted on the testbed assembled at the NASA Goddard Space Flight Center.
EUCLIDEAN PROPERTIES OF BAYESIAN UPDATING

This paper introduces a novel framework for analyzing Bayesian updating and nonBayesian heuristics. A learning rule consists of an arbitrary set of belief states and a set of transition functions, called arguments, from the belief set to itself. Bayesian learning rules, with beliefs in the form of probability distributions over a state and arguments in the form of Bayes’ rule, are a special case. The paper’s first main result is an axiomatic characterization of Virtual Bayesian learning rules, which can be turned into a Bayesian via a relabeling of the set of beliefs. There are three substantive axioms – that arguments are injective functions, that arguments commute, and that repeated application of an argument never produces cycles of beliefs – as well as three regularity assumptions. The axioms both identify the algebraic properties common to all Bayesians and distinguish which among familiar updating heuristics are Virtual Bayesians. The second main result establishes that any Virtual Bayesian learning rule can be embedded into Euclidean space – and therefore equipped with geometric notions of magnitude, direction, etc. – by defining the ‘agreement’ between pairs of arguments in a suitably additive manner. Applying such an embedding, an argument’s direction corresponds to the limit of the support of posterior beliefs under repeated application of the argument, and its magnitude is the extent to which a single application pushes prior beliefs towards that limit. The paper discusses how the framework of learning rules could be applied to additional contexts, including the elicitation of beliefs from laboratory subjects. JEL Classification: D83, C11, C44
Image compression and enhancement by using the LZW and BHEPL

This paper describes the lossless data compression techniques LZWand also discuses about its enhancement. In lossless data compression there is no loss in original information, means that the Pre-compressed and decompressed information is same. The BHEPL is use to short processing time for image enhancement.Bi-Histogram Equalization with a Plateau Value(BHEPL) is similar to Brightness Preserving Bi-Histogram Equalization (BBHE). BHEPL enhancement method is the combination of two methods first one is BBHE and second one is clipped histogram. In BBHE we first calculate the average intensity of input image. And in BHEPL enhancement method we divide the input image into two parts or two sub images and then decide the plateau value of each sub part of the image. This paper discus about LZW, BHEPL, original enhancement image and compressed enhancement image.
Principles of Robot Autonomy I Problem Set 3

This problem will be done in your final project groups. Each final project group will be assigned a group on Genbu. Make a private post with your group number on EdStem and the TAs will provide you the group number and password. You can TurboVNC into your group account on genbu.stanford. edu. DO NOT try to log into another group’s account and avoid working on Problems 1 and 4 during section hours (see https://stanfordasl.github.io/aa274a/pdfs/Syllabus AA274A 2021.pdf), when other students could be using your machine.
Simulating transport of 129 I and idealized tracers in the northern North Atlantic Ocean

Transport of the radioactive tracer Iodine-129 (129I, T1/2 = 15.7 Myr) in the northern North Atlantic Ocean has been investigated using a global isopycnic Ocean General Circulation Model (OGCM) and observed data. 129I originates mainly from the nuclear fuel reprocessing plants in Sellafield (UK) and La Hague (France), and is transported northwards along the Norwegian coast, and then into surface and intermediate layers in the Arctic Ocean through the Barents Sea and the Fram Strait, but also partly recirculating south along the eastern coast of Greenland. In the North Atlantic Subpolar Seas, 129I is mainly found in dense overflow waters from the Nordic Seas being exported southwards in the Deep Western Boundary Current, and to a lesser extent in surface and intermediate layers circulating cyclonically within the Subpolar Gyre. Observed concentration of 129I along a surface transect in the eastern Nordic Seas in 2001 is captured by the OGCM, while in the Nansen Basin of the Arctic Ocean the OGCM overestimates the observed values by a factor of two. The vertical profile of 129I in the Labrador Sea, repeatedly observed since 1997 to present, is fairly realistically reproduced by the OGCM. This indicates that the applied model system has potential for predicting the magnitude and depth of overflow waters from the Nordic Seas into the North Atlantic Subpolar Seas. To supplement the information obtained from the 129I distribution, we have conducted a number of idealized tracer experiments with the OGCM, including tracers mimicking pure water masses, and instantaneous pulse releases. New insight into time-scales of tracer transport in this region is obtained by utilizing a few S. Orre · M. Bentsen Nansen Environmental and Remote Sensing Center & Bjerknes Centre for Climate Research, Bergen, Norway S. Orre (B) Badger Explorer ASA, Stavanger, Norway e-mail: steinar.orre@gmail.com J. N. Smith Marine Environmental Sciences Division, Bedford Institute of Oceanography, Dartmouth, NS, Canada V. Alfimov ETH/PSI Ion Beam Physics Group, Institute of Particle Physics, Zurich, Switzerland
Optimizing Optimal Experience : Flow , integration , harmony

Various theories in inside and outside positive psychology make claims as to what constitutes optimal experience or human flourishing. The present paper provides a brief review and critical discussion of flow theory, self-determination theory, and the dualistic model of passion; both as interesting in itself and as a basis for comparison with concepts of optimal experience from outside positive psychology.
Chinese Intention Recognition Based on Domain Dictionary and Hard Attention

This paper proposes a dictionary classification method that incorporates hard attention mechanism in the classification of intention domain, an important link in human-computer dialogue.Based on the common method of classification of sentences, through the establishment of intent on the classification of the data of artificial domain dictionary, and then manually collected sentence to clean, cut and remove the stop operation, then iterative matching and dictionary before joining attention mechanism, will be more important information in the sentence first match, through the test on real data sets, this article selects the traditional machine learning method and the emerging neural network as a comparison method, verified: in this paper, on the accuracy and speed is better than the other.
Draft Assessment of diet composition of free-ranging antelopes ( Addax nasomaculatus ) by the combination of microhistological procedures and n-alkanes and long-chain alcohols as faecal markers

Understanding herbivore foraging behaviour is crucial for adequate wildlife management decisions. This study assessed the diet composition of free-ranging antelope Addax (Addax nasomaculatus De Blainville, 1816). Samples collected during the spring season were analyzed using microhistological procedures along with n-alkanes and long-chain alcohols as fecal markers. Twelve animals were monitored and fresh fecal samples were collected daily during a seven-day period. Diet composition estimates obtained by both methods were similar and indicate that (Stipagrostis pungens subsp. (Desf.) De Winter) was the main diet component followed by (Fagonia glutinosa var. (Delile.) nuda Hadidi), (Helianthemum kahiricum var. libycum (Pomel.) Batt. ) and (Hamada schmittiana (Pomel.) Botsch. ). Data showed that Addax have mixed diets composed of perennial woody and herbaceous plant species depending on their availability. The four species most selected by the animals were also the most abundant species in the plant cover. By contrast, species that accounted for less than 5% of the plant cover were not present in the fecal samples. Results of this study represent a single grazing season and, for that reason, further studies are required to fully understand how the antelopes’ grazing behaviour varies with seasonal changes in vegetation cover.
Impact of Feature Selection on the Performance of Wireless Intrusion Detection Systems

In this paper, we study the impact of the optimization of the feature set of wireless intrusion detection systems on the performance and learning time of different types of classifiers based on neural networks. The optimal set of features is selected using a hybrid selection model. In this approach, the wireless frame attributes are first ranked according to a score assigned by the information gain ratio measure. K-means classifier is then used to build the optimal subset of features that maximizes the accuracy of the detectors while reducing their learning time. Experimental results with three types of neural networks architectures show clearly that the optimization of the wireless feature set has a significant impact on the efficiency and accuracy of the intrusion detection system.
Chlamydia trachomatis Infections during Pregnancy: Consequences for pregnancy outcome and infants

textabstractChlamydia trachomatis is the most common bacterial sexually transmitted infection (STI) worldwide. Chlamydia is responsible for a significant proportion of genitourinary tract infections in adult males and females, but like STIs in general, it is primarily a woman’s health care issue since the manifestations and consequences are more damaging to the reproductive health of women than of men. Acute C. trachomatis infection is easy to treat, but the majority of chlamydial infections remain asymptomatic and untreated, and may lead to serious complications such as pelvic inflammatory disease (PID), ectopic pregnancy, infertility and chronic pelvic pain in women, as well as conjunctivitis and respiratory tract infection in infants. The health-economic impact of C. trachomatis infections may therefore be enormous. Vaccines are not yet available. Hence, health gain and financial benefits can only be achieved by active case finding and treatment of C. trachomatis infection, which can be done on an individual level or nationwide in a screening program.
University of Southern Denmark ' What an Eyeopener ' a qualitative study of vulnerable citizens participating in a municipality-based intervention

Purpose: To explore how psychologically vulnerable citizens experienced performing their everyday-life activities, identify activities experienced as particularly challenging and evaluate the significance of the Acceptance and Commitment Theory-based (ACT)-based program, Well-being in Daily Life, had on the participants everyday-life activities. Methods: Semistructured interviews were conducted with eight participants from the Well-being in Daily Life program. Data were analysed using Systematic Text Condensation. Results and Conclusion: The participants experienced anxiety, fatigue, lack of structure, and chaos when performing their everyday-life activities; in addition to being uncertain about the limitations of their own resources. Furthermore, balancing between demands and resources was challenging, also leading to uncertainty and identity conflicts that contributed to the participants’ concerns about re-entering the workforce. The program enabled the participants to develop social skills and trust which contributed to providing the participants with confidence, individually-tailored-possibilities for developing new competencies and courage; thus, facilitating their recovery process. ARTICLE HISTORY Accepted 2 February 2018
Becoming a tertiary teacher in New Zealand : learning in communities of practice : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Education at Massey University, Palmerston North, New Zealand

This thesis reports a research project studying how people become tertiary teachers in New Zealand. While studies of many aspects of tertiary teaching, teacher professional development and workplace learning have been published, no comparative study of tertiary teacher development across different types of institutions had been carried out. Few previous studies had linked the concept of learning in a community of practice with teachers ' workplace learning. A qualitative, interpretive research framework was adopted, using three case studies. Data were gathered from institutional documents, educational developers and experienced teaching staff of three representative institutions, a polytechnic, a wananga and a university, from mid-2000 to mid-200l . Data gathering strategies included semi­ structured interviews with teachers and educational developers, examination of documents, a teacher questionnaire and some class observations. Interview transcripts and other data were analysed to identify common themes, and findings were reported as three individual cases before integration. It was found that most tertiary teachers' learning about teaching and how to teach was in-service, mainly informal and experiential, and the knowledge gained was mainly tacit and process-oriented. Although that was complemented by varying amounts of formal learning, gained through courses or professional development activities, few tertiary teachers have sought or gained teaching qualifications. While institutions have central policies and procedures to support in-service teacher development, their implementation is often uneven, with little integration or balancing of the parts. Differences of practice were observed both between institutions, and between departments within institutions, indicating the importance of context for tertiary teachers ' development. It was concluded that non-formal workplace learning is likely to continue to be the mainstay of tertiary teacher development, and that it needs to be refocussed and approached from a fresh angle. The perspective of learning in a community of teaching practice provides a conceptual framework for integrating different levels and forms of support for tertiary teachers. Recommendations for strengthening tertiary teacher development are addressed at three levels: institutions (as social learning systems); communities of practice within those institutions (such as departments, discipline groups, programme teams, or campus whanau); and individual teachers (whose teaching identities develop within those communities).
Positioning Self in SQuAD

Current state of the art NLP models for reading comprehension tasks entail extremely large and complex neural architectures to achieve optimal performance. Many of these models capitalize on the sequential nature of language by employing RNNs to encode and capture meaning in the input space. However, these models have been shown to be relatively slow, limiting both training and performance speeds. More specifically, much of contemporary research has focused on abandoning recurrent models in favor of ones that scale more efficiently as the training data or input size grows [6]. Our paper focuses on building a question answering system that is both accurate and efficient so that its knowledge can grow unimpeded by computational costs. We build on the already proofed BiDAF architecture while building towards swapping out the usage of RNN-based encoding layers with other types of encoding blocks. We take inspiration from QANET and BERT that primarily make use of convolutional and attention based frameworks. Our aim is to significantly improve both the efficiency and accuracy of the baseline BiDAF model. We found that replacing encoding blocks with GRU’s instead of LSTM’s not only improved performance speed but also improved accuracy. Incorporating self-attention into the BiDAF framework in addition to positional encodings significantly improved F1 and EM scores on the dev and test sets as well. We conclude by analyzing both the quantitative results and the qualitative implications with respect to our final model architecture.
Impacts of microeconomic uncertainty shocks on the aggregate economy : an analysis for Brazil

This work aims to estimate a dynamic stochastic general equilibrium model (DSGE) to evaluate the impact of microeconomic uncertainty shocks in the Brazilian economy. The microeconomic shocks emerge from the interaction with a continuum of entrepreneur agents and the financial sector. Calibrating the model using quarterly data from 2003 to 2017, we find that agency costs in the entrepreneurial and financial sector impact economic growth, capital accumulation and household’s welfare.
Growth , Nutrient Uptake and Seed Cotton Yield of Summer Cotton as Influenced by Drip , Surface Irrigation Methods and Mulching Practices

An experiment was carried out at Agricultural College and Research Institute, Madurai during summer season of 2002 to study the effect of drip and surface irrigation methods with rice straw mulching on nutrient uptake and growth of cotton. The treatments consisted of six methods of irrigation as main plot and two mulching practices as subplot. The highest plant height, more LAI, DMP AND seed cotton yield (2,430 kg ha) were recorded with drip irrigation. Rice straw mulch @ 5 t ha also significantly increased the cotton growth in terms of plant height, LAI, DMP and seed cotton yield (2,013 kg ha ) over no mulching.