Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer Learning for SAR Image Classification Via Deep Joint Distribution Adaptation Networks

The problem of different characters of heterogeneous synthetic aperture radar (SAR) images leads to poor performances for transfer learning of SAR image classification. To address this issue, a semisupervised model named as deep joint distribution adaptation networks (DJDANs) is proposed for transfer learning from a source SAR image to a different but similar target SAR image, which aims to match the joint probability distributions between the source domain and target domain. In the proposed DJDAN, a marginal distribution adaptation network is developed to map features across the domains into an augmented common feature subspace, which aims to match the marginal probability distributions and unify the dimensions. Then, a conditional distribution adaptation network is proposed to transfer knowledge across the domains, which aims to reduce the discrepancies of the conditional probability distributions and enhance the effectiveness of feature representation. Moreover, one-versus-rest classification is utilized in the proposed framework, which aims to improve the discrimination between the inside and outside class. Experimental results demonstrate the effectiveness of the proposed deep networks.
Child Development in Integrative Psychotherapy: Erik Erikson’s First Three Stages

Child development concepts and research provide the basis for therapeutic inquiry in a developmentally based, relationally focused integrative psychotherapy. This article focuses on the developmental ideas of Erik Erikson and relates them to the concepts of Bowlby, Fraiberg, Piaget, and Winnicott. The various developmental concepts provide the basis for developmental attunement, forming developmental images, phenomenological inquiry, and therapeutic inference that allow implicit and procedural memory to be expressed in a therapeutic narrative.
Two‐stage 3D model‐based UAV pose estimation: A comparison of methods for optimization

Particle Filters (PFs) have been successfully used in three‐dimensional (3D) model‐based pose estimation. Typically, these filters depend on the computation of importance weights that use similarity metrics as a proxy to approximate the likelihood function. In this paper, we explore the use of a two‐stage 3D model‐based approach based on a PF for single‐frame pose estimation. First, we use a classifier trained in a synthetic data set for Unmanned Aerial Vehicle (UAV) detection and a pretrained database indexed by bounding boxes properties to obtain an initial rough pose estimate. Second, we employ optimization algorithms to optimize the used similarity metrics and decrease the obtained error. We have tested four different algorithms: (a) Particle Filter Optimization (PFO), (b) Particle Swarm Optimization (PSO), (c) modified PSO, and (d) an approach based on the evolution strategies present in the genetic algorithms named Genetic Algorithm‐based Framework (GAbF). To check the quality of the estimate on each iteration, we have tested several similarity metrics (color, edge, and mask‐based) based on the UAV Computer‐Aided Design (CAD) model. The framework is applied to the outdoor pose estimation of a fixed‐wing UAV for autonomous landing in a Fast Patrol Boat (FPB). We extend our previous approach by adopting a better problem formulation, using Deep Neural Networks (DNNs) for UAV detection, making the comparison between the used similarity metrics, comparing pose optimization schemes, and showing new results. The future work will focus on the inclusion of this scheme in a tracking architecture to increase the accuracy of the result between observations.
Target Detection Based on Spectral Derivation in HSI Shadow Region Classified by Convolutional Neural Networks

Abstract Because of the low reflection value of the shadow regions in hyperspectral image (HSI), these regions were deleted directly or ignored in target detection or classification. There are some studies on improving the reflectivity of shadow regions, but it is still difficult to determine the actual substances contained in shadow regions. In this paper, an improved target detection method in shadow regions in HSI is proposed by combining the convolution neural network (CNN) and the adaptive cosine consistency estimation (ACE) of the spectral derivative image. Firstly, the derivative image could be obtained by deriving the original HSI in the spectral dimension. The following steps would be performed simultaneously on the original HSI and the derivative image. Next, the shadow regions in HSI could be determined through two-dimensional (2D) CNN model whose main parameters have been adjusted to optimize the network performance. Finally, the substances contained in the shadow regions would be detected by ACE algorithm. The performance of the proposed method was evaluated and analyzed on the real-world HSIs. The experiments show that the spectral derivation can help to improve the target detection and it is worth taking into account the shadow regions for processing HSI data.
An Intelligent Optimization Algorithm for Blocking Flow-Shop Scheduling Based on Differential Evolution

Owing to its large scale, the blocking flow-shop scheduling problem (BFSP) cannot be solved effectively by traditional optimization methods. To solve the problem, this paper develops a novel intelligent optimization algorithm based on differential evolution (DE) for the BFSP with a single objective: minimizing the total flow time (TFT). On the one hand, a new heuristic method was introduced to balance the quality and diversity of the initial population. On the other hand, a new operator was adopted to update the acceleration, velocity and position of each particle. In this way, the population will not converge prematurely to local optimums, and the local and global search abilities are perfectly balanced. Simulation on standard test set proves that our algorithm outperformed most commonly used methods in solving the BFSP. (
Shifting environmental attitudes and influencing pro-environmental behaviour through the process of managing how, when and in what way we communicate

Communication has immense power to create dialogue, evoke engagement, shift attitudes, influence decision-making and change behaviour through managing how, when and in what way companies communicate. Organisations are under pressure to adopt environmentally responsible practices and to communicate this environmental responsibility and compliance to their stakeholders, as a result of the upsurge of environmental concern among stakeholders, in international agreements and in increasingly stringent environmental legislation. This has led to an explosion of ‘’green claims’’ regarding the environmental practices of companies, or the environmental benefits of products or services, many of which cannot be substantiated or verified. Called “greenwashing”, this is unethical and can lead to irreparable brand damage, negative publicity, loss of stakeholder trust and investor confidence, and a reduction in pro-environmental behaviour, which in turn impairs efforts to improve the environment. The research objective of the study seeks to understand the role of communication as an effective and practical tool to educate, inform, influence decision-making and evoke values, beliefs and norms in order to prove the hypothesis that “through the process of managing how, when and in what way we communicate, public relations consultants and communication professionals are in a unique position to shift environmental attitudes and influence pro-environmental behaviour so that a change takes place whereby being environmentally responsible will become the ‘norm’ and not just ‘compliance driven’ because of a policy, code or law or for a competitive edge”. Conducted with members of the professional body of the Public Relations Institute of Southern Africa (PRISA) via an online questionnaire, the study looks at understanding the current state of environmental communication in South Africa. It examines how and in what way organisations communicate environmental impacts and practices; the characteristics of public relations practitioners and communication professionals communicating these “green” messages; and practitioner environmental attitudes, using the New Ecological Paradigm (NEP) Scale. The study also aims to identify the driving factors and barriers to engaging in pro-environmental behaviour. iii Stellenbosch University https://scholar.sun.ac.za
The Effect of Learning Media on Progress Quality in Office Administration Program in Vocational School Negeri 1 Watampone Bone Regency

This study aims to describe the use of learning media and the quality of learning in the Office Administration Expertise program of Vocational School Negeri 1 Watampone as well as the influence of learning media on the quality of the teaching-learning process in there. This study uses quantitative research with a population of all students in there totaling 208 students, with a sample of 68 students at a level of error of 10 percent. Data collection is done by using observations and questionnaires. The data analysis technique used is descriptive statistics and inferential statistics. The results of this study indicate that the use of learning media in there is classified as good, in terms of aspects of print media, electronic media, and media reality. The quality of the teaching-learning process in there is considered good in terms of active, innovative, creative, effective and enjoyable learning. There is a significant positive influence on the use of instructional media on the quality of learning in the office administration expertise program of Vocational School Negeri 1 Watampone which is 17.9 percent.
Can the Finger-Nose-Finger Task Be Used to Identify School-aged Children with Probable Developmental Coordination Disorder?

ABSTRACT This study aimed to investigate whether the Finger-Nose-Finger (FNF) task could be a potential test to identify school-aged children with probable Developmental Coordination Disorder (pDCD) from a large population. This study recruited 1365 nine to twelve years old children, 362 of whom were identified as pDCD using the Movement Assessment Battery for Children (MABC) test. An instrument was designed to conduct the FNF task. The times performed by the dominant hand (DH) and the non-dominant hand (NDH) in 30 seconds were recorded, as well as the Sum of both hands. The results showed that school-aged children with pDCD had significantly poor performance on DH, NDH, and Sum of the FNF task compared to typically developing children (all p’s <.001). However, the FNF task showed low sensitivity (24.9%) and low diagnostic rate (65.7%) against the MABC test, even though there was a significant moderate correlation between both tests (r = −.300, p < .001). Taken together, even though school-aged children with pDCD perform worse on the FNF task, this task may not be sensitive enough to identify children with pDCD. Other testing items assessing other motor aspects, specifically balance, should be included and validated.
The Coupling of NSSL Warn-on-Forecast and FLASH Systems for Probabilistic Flash Flood Prediction

The goal of the National Oceanic and Atmospheric Administration’s (NOAA) Warn-on-Forecast (WoF) program is to provide frequently updating, probabilistic model guidance that will enable National Weather Service (NWS) forecasters to produce more continuous communication of hazardous weather threats (e.g., heavy rainfall, flash floods, damaging wind, large hail, and tornadoes) between the watch and warning temporal and spatial scales. To evaluate the application of this WoF concept for probabilistic short-term flash flood prediction, the 0–3-h rainfall forecasts from NOAA National Severe Storms Laboratory’s (NSSL) experimental WoF System (WoFS) were integrated as the forcing to the NWS operational hydrologic modeling core within the Flooded Locations and Simulated Hydrographs (FLASH) system. Initial assessment of the potential impacts of probabilistic short-term flash flood forecasts from this coupled atmosphere–hydrology (WoFS-FLASH) modeling system were evaluated in the 2018 Hydrometeorology Testbed Multi-Radar Multi-Sensor Hydrology experiment held in Norman, Oklahoma. During the 3-week experiment period, a total of nine NWS forecasters analyzed three retrospective flash flood events in archive mode. This study will describe specifically what information participants extracted from the WoFS-FLASH products during these three archived events, and how this type of information is expected to impact operational decision-making processes. Overall feedback from the testbed participants’ evaluations show promise for the coupled NSSL WoFS-FLASH system probabilistic flash flood model guidance to enable earlier assessment and detection of flash flood threats and to advance the current warning lead time for these events.
The Education of the Elementary Mathematics Specialist: A Program Evaluation

Over the past 30 years, there has been a growing need to strengthen educators’ mathematical skills through additional training. Nationwide, companies such as Exxon Mobile (1988) have created mathematics and science initiatives to improve teachers’ skills in the classroom. It is important that school systems explore ways to ensure students receive quality mathematics instruction from well trained, confident teachers who understand the content, can use instructional/assessment strategies, and to understand how students learn mathematics. The purpose of this study was to examine the confidence levels in mathematical content and pedagogy of graduates of the Elementary Mathematics Specialist (EMS) program. This study presented what benefits the program provided graduates and graduates’ perceptions of their mathematics content knowledge and pedagogy due to participation in the program. This mixedmethods study used a convergent-parallel approach to examine perceptions of graduates. This study included a researcher-developed Likert scale survey, focus group discussion, interviews, and a review of course content and course syllabi to collect both quantitative and qualitative data. Results indicated most graduates had high levels of confidence in content knowledge and pedagogy across all National Council of Teachers of Mathematics Standards after completion of this program. High levels of confidence in this intensive EMS program validated the objectives of this program to provide graduates with greater mathematics content knowledge, differentiated instruction mathematical skills, collaboration among colleagues, mathematical leadership skills, and greater autonomy in their work.
Factors influencing the intention of students at a selected TVET college in the Western Cape to complete their National Certificate (Vocational) Business Studies programme

Student dropout, also called ‘early departure’, is a significant problem in South Africa’s post-school education and training (PSET) landscape, specifically in the technical and vocational education and training (TVET) sector. The challenge of student retention and programme completion (the antithesis of dropping out) is equally significant and important to TVET institutions, the state department responsible (Department of Higher Education and Training) and the South African economy. Early departure negatively influences the success rates of educational institutions. It also influences the chances of personal employment and financial well-being of individual students, causing financial ripple effects on society and government. Students’ decisions to remain or leave college or a programme are influenced by a variety of individual and social factors, both internal and external, including people close to the students and the policies, systems and structures within which students interact. These factors also encompass the quality and friendliness of teachers, social interaction with teachers and peers, and the role played by friends in academic achievement. This article reports on a study of student perspectives on the internal and external factors that influence their retention in, and completion of, a TVET college Business Studies National Certificate (Vocational) (NC(V)) programme in the Western Cape, South Africa. An improved understanding of student experiences, intentions, and decision-making processes leading to persistence provides a foundation for improving student retention and programme completion in a TVET environment.
Numerical and analytical solutions of an Oldroyd 8‐constant MHD fluid with nonlinear slip conditions

The flow of an Oldroyd 8‐constant non‐Newtonian MHD fluid is investigated analytically and numerically. The governing equations for the flow field are derived for a steady one‐dimensional flow. The effect of constant applied magnetic field is included and its influence on the flow field is studied. The nonlinear governing equation along with nonlinear boundary conditions is solved analytically and the solution is obtained in an elegant way. Numerical solutions are also obtained using higher order Chebyshev spectral methods. The influence of various non‐Newtonian parameters and applied magnetic field is investigated. Results showing the effect of various physical parameters of the flow are presented and investigated. Copyright © 2010 John Wiley & Sons, Ltd.
Plant Leaf Disease Detection Using SVM Technique

Plant disease are most common in India. Plant diseases are normally occurring due to insects. If not predict under certain time, we may chance to lose efficiency of Crops. In this paper we are helping to farmers to know and analysis the diseases. We work on an SVM for recognition and categorizing of four-leaf diseases i.e. Alternaria Alternata, Anthracnose, Bacterial Blight, Carpospora are the diseases, we worked out and we provided effective solutions to the farmers.
Continuous, multidimensional coding of 3D complex tactile stimuli by primary sensory neurons of the vibrissal system

Significance An animal’s primary sensory neurons (PSNs) translate information about the environment into neural signals that allow perception and action. While much is known about visual and auditory PSN responses to complex stimuli, somatosensory neurons have been characterized with simplified and repeatable stimuli. Thus, knowledge of somatosensory PSN representational capacity remains incomplete. We used the rodent whisker system to examine how tactile mechanical information is represented in PSNs of the trigeminal ganglion (Vg) when the whiskers receive complex three-dimensional stimulation. In contrast to proposed codes in which subpopulations of Vg neurons encode select stimulus features, our results show that individual Vg neurons represent multiple stimulus features in a tiled and continuous manner, thus encoding large regions of a complex sensory space. Across all sensory modalities, first-stage sensory neurons are an information bottleneck: they must convey all information available for an animal to perceive and act in its environment. Our understanding of coding properties of primary sensory neurons in the auditory and visual systems has been aided by the use of increasingly complex, naturalistic stimulus sets. By comparison, encoding properties of primary somatosensory afferents are poorly understood. Here, we use the rodent whisker system to examine how tactile information is represented in primary sensory neurons of the trigeminal ganglion (Vg). Vg neurons have long been thought to segregate into functional classes associated with separate streams of information processing. However, this view is based on Vg responses to restricted stimulus sets which potentially underreport the coding capabilities of these neurons. In contrast, the current study records Vg responses to complex three-dimensional (3D) stimulation while quantifying the complete 3D whisker shape and mechanics, thereby beginning to reveal their full representational capabilities. The results show that individual Vg neurons simultaneously represent multiple mechanical features of a stimulus, do not preferentially encode principal components of the stimuli, and represent continuous and tiled variations of all available mechanical information. These results directly contrast with proposed codes in which subpopulations of Vg neurons encode select stimulus features. Instead, individual Vg neurons likely overcome the information bottleneck by encoding large regions of a complex sensory space. This proposed tiled and multidimensional representation at the Vg directly constrains the computations performed by more central neurons of the vibrissotrigeminal pathway.
Considerations for surgical intervention in metastatic cancer to the spine: evaluation of risk factors for pathologic fracture and spinal cord compression, and analysis of pre-operative scoring systems for the prognostication and treatment of patients with spinal metastases

xi DECLARATION . xiii ACKNOWLEDGEMENTS . xv TABLE OF CONTENTS . xvii LIST OF FIGURES AND TABLES . xix LIST OF ABBREVIATIONS . xxi 1 INTRODUCTION . 1 1.1 Spinal Metastatic Disease . 1 1.2 Study Objectives . 3 1.3 Thesis Overview . 4 2 SPINAL METASTATIC DISEASE . 6 2.1 Epidemiology . 6 2.2 Pathophysiology . 6 2.3 Morbidity and Mortality . 12 2.4 Imaging . 14 2.5 Non‐Surgical Treatment . 20 2.6 Surgery for Spinal Metastases . 23 2.7 Summary . 31 3 POTENTIAL RISK FACTORS FOR PATHOLOGICAL FRACTURE AND METASTATIC EPIDURAL SPINAL CORD COMPRESSION . 33 3.1 Size . 34 3.2 Site . 36 3.3 Primary Tumour . 41 3.4 Metastatic Disease Burden . 43 3.5 Pain . 47 3.6 Neurological Symptoms . 48 3.7 Functional Status . 51 3.8 Summary . 53
Femtosecond laser inscribed advanced calibration phantom for optical coherence tomography (OCT)

Optical coherence tomography (OCT) has developed rapidly and is widely used in different fields such as biomedicine and optometry. The characterization and calibration of OCT systems is essential when testing the system and during normal use to ensure that there is no misalignment or distortion that could affect clinical decisions. Imaging distortion is a significant challenge for OCT systems when viewing through non-planar surfaces. Here we present a new multi-purpose plano-convex OCT phantom which is designed to be used for OCT characterization and calibration as well as to validate the post-processing algorithm for the imaging distortion of the OCT systems. A femtosecond laser direct writing technique is used to fabricate this phantom which consists of a landmark layer with radial lines at a 45-degree angular spacing inscribed at 50μm in apparent depth (AD) underneath the planar surface. Below that there are a further 8 layers of a spherical inscription pattern which has a 150μm (in AD) separation between each layer. The first spherical layer is located at 150μm (in AD) underneath the planar surface. Due to the laser power loss when travelling through the deeper layer, an increased power is applied to the deeper layers. The spherical pattern overcomes orientation issues seen with existing calibration phantoms. The landmark layer is applied so that it can easily tell the exact location when scanning which will also benefit the image distortion correction process.