Miracle-dz/UniFAR-FTUs huggingface dataset:
Oil Spill Detection Based on CBD-Net Using Marine SAR Image

Oil spill is one of the most widespread, frequent and harmful marine pollution. Oil spill detection based on synthetic aperture radar (SAR) images detects the oil film by identifying dark spots in the images. Dark spots detection can be achieved using image segmentation techniques. However, natural phenomena such as waves and currents can also cause dark spots, resulting in consistently uneven intensity, high noise and blurred boundaries in oil spill images. In addition, existing oil spill detection models often perform well for large targets, but have poor detection accuracy for small targets, causing part of the oil spill to be ignored. To solve the above problems, oil contextual and boundary-supervised detection network (CBD-Net) is proposed to extract refined oil spill regions by fusing multiscale features, where the scSE attention block is used to model the global context to improve the internal consistency of oil spill regions. In CBD-Net, boundary details are enhanced with optimized edge supervision. In addition, a manually labeled dataset is proposed, Deep-SAR Oil Spill (SOS) dataset, aiming to solve the problem of insufficient existing oil spill detection dataset. Experimental results demonstrate that the proposed model outperforms other comparative models, and is able to extract robust and accurate oil spill regions from complex SAR images.
Intelligent Deep Brain Stimulation Systems: A General Review

Brain Stimulation is now becoming the preferred approach where pharmacological treatment is ineffective in neurological conditions such as Parkinson’s Disease (PD), Tourette Syndrome, Addiction disorder, Depression, and Anxiety. The brain can be stimulated by electrical current, light, and sound energy, invasively or non-invasively. The article comprises of pathophysiology in Parkinson’s, current pharmacological modalities used for the treatment (along with limitations), and deep brain stimulation as the last resort. The article also provides a comprehensive analysis of intelligent Deep Brain Stimulation methods (procedure, architecture, and type) from the studies and research conducted in the last five years. In the end, research gaps and associated challenges are discussed.
Time-Series Soil Moisture Retrieval Using S-Band Backscatter Measurements from the SMEX02 Campaign

S-band observations from NASA's Passive/Active L/S Band (PALS) radar from the SMEX02 campaign were used to estimate soil moisture. The “alpha” method is applied for this process, in which a time series of ratios of normalized radar cross section values at successive measurements is used to infer the corresponding soil moisture time series given ancillary information on the minimum and maximum soil moisture values expected over the time series. Results are examined as a function of the polarization and crop type. The results show reasonable retrieval performance, indicating the potential of using S-band observations from the future NASA/ISRO SAR (NISAR) mission.
Estimating the Effect of Infrastructure on Vegetation Degradation in Eastern Mongolia Steppe Using Machine Learning and Remote Sensing

In the Eastern Mongolian Steppe Ecosystem, one of the major driving factors of human-induced land degradation is the expansion of road networks mainly due to intensifications of oil exploration and exploitation. Modern remote sensing data and machine learning techniques provide the possibility to detect and monitor long-term changes of land use such as dirt road and linear infrastructure in oil exploitation area. This study determined changes of land use/cover in the period 2005–2018 and estimated effects of dirt roads on surrounding grasslands ecosystems using multi-temporal satellite data with medium to high spatial resolution covering 20,000 km2 in eastern Mongolia. The ecological impacts of dirt roads and oil extraction sites were investigated using field vegetation photo-monitoring data, existing land use/cover maps and additional NDVI analysis. As a result, this paper describes current and historical land disturbance and its impact on grasslands ecosystem in Eastern Mongolia Steppe.
Mathematics Teachers’ Perspectives on Emergent Issues in Teaching and Learning Mathematics in Nepal

Researchers and scholars of mathematics education have discussed several issues in teaching and learning mathematics in general. However, there is minimal discussion of such issues in the Nepalese context. This study aimed to explore teaching-learning issues in mathematics in Nepal. A researcher-constructed questionnaire with 37 items had been administered to 101 mathematics teachers in Kathmandu valley. An exploratory factor analysis revealed six key components to highlight the significant issues in mathematics teaching-learning: Social and Cultural Issues, Issues with Equity and Justice, Technological and Pedagogical Issues, Professional Issues, Political and Social Issues, and Theoretical Issues. A one-sample t-test was applied to each of these components to analyze the issues from the perspectives of the research participants to emphasize their critical concerns in teaching and learning mathematics in Nepal.
DMSO_A_198154 519..526

Jing Xie Ning Li Xiaoyan Jiang Liyin Chai Jian-Jun Chen Wuquan Deng 1Department of Endocrinology and Nephrology, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing 400014, People’s Republic of China; 2Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, People’s Republic of China Background: Consistent evidence is still lacking on which one, glimepiride plus metformin or repaglinide plus metformin, is better in treating type 2 diabetes mellitus (T2DM). Therefore, this study was conducted to compare the short-term efficacy and safety of these two methods in treating T2DM. Methods: The literature research dating up to August 2018 was conducted in the electronic databases. The randomized controlled trials (RCTs) comparing the short-term (treatment period ≤12 weeks) efficacy and safety of these two methods in treating patients with T2DM were included. No language limitation was used in this study. The decreased hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), and 2h plasma glucose (2hPG) levels were used as the primary outcome to assess the efficacy, and the adverse events and hypoglycemia were used as the secondary outcome to assess the safety. Results: In total, 11 RCTs composed of 844 T2DM patients were included. The results showed that there were no significant differences in decreasing HbA1c and FPG levels between the two methods, but the estimated standardized mean differences favored the repaglinide plus metformin. Meanwhile, the repaglinide plus metformin was significantly more effective in decreasing 2hPG levels than glimepiride plus metformin. In addition, fewer patients reported adverse events and experienced hypoglycemia in the repaglinide plus metformin group. Conclusion: These results indicated that the repaglinide plus metformin might have some advantages over glimepiride plus metformin in the short-term treatment of patients with T2DM, and should be further explored.
Analyzing Architectures for Neural Machine Translation Using Low Computational Resources

With the recent developments in the field of Natural Language Processing, there has been a rise in the use of different architectures for Neural Machine Translation. Transformer architectures are used to achieve state-of-the-art accuracy, but they are very computationally expensive to train. Everyone cannot have such setups consisting of high-end GPUs and other resources. We train our models on low computational resources and investigate the results. As expected, transformers outperformed other architectures, but there were some surprising results. Transformers consisting of more encoders and decoders took more time to train but had fewer BLEU scores. LSTM performed well in the experiment and took comparatively less time to train than transformers, making it suitable to use in situations having time constraints.
Individual Mobility Prediction in Mass Transit Systems Using Smart Card Data: An Interpretable Activity-Based Hidden Markov Approach

Individual mobility is driven by demand for activities with diverse spatiotemporal patterns, but existing methods for mobility prediction often overlook the underlying activity patterns. Knowledge of activity patterns can improve the performance and interpretability of existing individual mobility models, leading to more informed policy design and better user experience in intelligent transportation systems. This study develops an activity-based modeling framework for individual mobility prediction in mass transit systems. Specifically, an input-output hidden Markov model (IOHMM) approach is proposed to simultaneously predict the (continuous) time and (discrete) location of an individual’s next trip using transit smart card data. The prediction task can be transformed into predicting the hidden activity duration and end location. Based on a case study of Hong Kong’s metro system, we show that the proposed model can achieve similar prediction performance as the state-of-the-art long short-term memory (LSTM) model. Unlike LSTM, the proposed IOHMM approach can also be used to analyze hidden activity patterns, which provides meaningful behavioral interpretation for why an individual makes a certain trip. Therefore, the activity-based prediction framework offers a way to preserve the predictive power of advanced machine learning methods while enhancing our ability to generate insightful behavioral explanations, which is useful for user-centric policy design and intelligent transportation applications such as personalized traveler information.
Robot Modeling And Control 1st Edition

Geometric Algebra Applications Vol. IIReliability Models of Complex Systems for Robots and AutomationSpringer Handbook of RoboticsRoboticsFundamentals in Modeling and Control of Mobile ManipulatorsTethered Space RobotMulti-View Geometry Based Visual Perception and Control of Robotic SystemsHuman Modeling for Bio-Inspired RoboticsData-Driven Science and EngineeringRobotics, Vision and ControlNonlinear Control of Vehicles and RobotsIntroduction to Mobile Robot ControlLegged Robots that BalanceSoft Robotics: Trends, Applications and ChallengesIntelligent Robotic SystemsAutonomous RobotsTheory of Robot ControlHuman and Robot HandsNonlinear Control of Robots and Unmanned Aerial VehiclesRobotics and Automation HandbookModeling and Control for Micro/Nano Devices and SystemsIntelligent Control of Robotic SystemsProbabilistic RoboticsIntroduction to RoboticsBipedal RobotsHumanoid RobotsModeling, Identification and Control of RobotsDynamic Analysis of Robot ManipulatorsRobot Analysis and ControlA Mathematical Introduction to Robotic ManipulationWheeled Mobile RoboticsModern RoboticsModelling and Control of Robot ManipulatorsRobot Dynamics And ControlRobot Manipulator ControlProduction Planning, Modeling and Control of Food Industry ProcessesModeling and Control of Complex SystemsFeedback Control of Dynamic Bipedal Robot LocomotionControl in Robotics and AutomationFuzzy Modeling and Control
MP3804_04_Tan 386..405

IN THIS STUDY, THE ROBUSTNESS OF AN ONLINE tool for objectively assessing singing ability was examined by: (1) determining the internal consistency and test-retest reliability of the tool; (2) comparing the task performance of web-based participants (n 1⁄4 285) with a group (n 1⁄4 52) completing the tool in a controlled laboratory setting, and then determining the convergent validity between settings, and (3) comparing participants’ task performance with previous research using similar singing tasks and populations. Results indicated that the online singing tool exhibited high internal consistency (Cronbach’s alpha 1⁄4 .92), and moderate-tohigh test-retest reliabilities (.65–.80) across an average 4.5-year-span. Task performance for weband laboratory-based participants (n 1⁄4 82) matched on age, sex, and music training were not significantly different. Moderate-to-large correlations (|r|1⁄4.31–.59) were found between self-rated singing ability and the various singing tasks, supporting convergent validity. Finally, task performance of the web-based sample was not significantly different to previously reported findings. Overall the findings support the robustness of the online tool for objectively measuring singing pitch accuracy beyond a controlled laboratory environment and its potential application in largescale investigations of singing and music ability.
Poultry Production and Research Using EM Technologies

Introduction This manual was created for people interested in using Effective Microorganisms (EM) for poultry production or research. An attempt has been made to explain what EM is and create a comprehensive evaluation of the theoretical basis for and previous scientific research of EM in poultry production. Because every region and management system is different, a basic experimental design is included in this manual as a guideline for researching the best rates, frequency and methods of application for unique circumstances. Laboratory and field trials have shown very good results when using EM for health, performance, disease control, odor control, and waste treatment in poultry production. The manual also includes general guidelines for the use of EM in poultry production as well as directions for making EM Fermented Feed. EM, like poultry, is a living thing and therefore certain conditions must be met in order to achieve positive results with EM. If you are interested in using EM in poultry production or research, please read this manual carefully in order to understand how EM is used and why it is used so that your production or research will be effective. If EM is used in accordance with the information of this manual many problems of poultry production can be reduced or eliminated.
A Computational Framework for Estimating Collision Risk against Pedestrians

In the present paper, a new framework for calculating subjective risk estimation (SRE) of an attentive human driver is proposed. First, we conduct a psychological interview of an expert driver to obtain his cognitive structure of SRE. These results suggest that SRE can be expressed as a collision probability between the ego-vehicle and other road users, and the probability can be estimated based on subjective behavior prediction (SBP) for the road users, which is the future position of each user expressed as a probability distribution (position distribution). The future position distribution is influenced by two types of subjective factors on a traffic scene: environmental factors and target factors. These factors can prompt and regulate SBP for each road user. Second, the cognitive structure of SRE is mathematically redescribed to propose the framework for SRE. Third, we propose an algorithm by which to calculate SRE, which is a collision probability, using a particle filter technique. Finally, numerical simulations for several traffic situations, in which the ego-vehicle passes a pedestrian, are conducted. The results of these simulations reveal the validity of the proposed framework.
Development of Crop Security Model for Enhancement in Agricultural Productivity using Internet of Things

: Most of the time in agriculture field, crops ravaged by local animals that leads to huge losses for the farmers. It’s very difficult for farmers to barricade entire fields and monitors continuously. Here the crop protection system model is developed for the farmers to prevent the crops from the animals. The model adopts Arduino Uno based system uses wired security that gives the shock to animals if they are approaching the field. The fire sensor is also used in the model to detect the fire issues. In such situations, the microcontroller will turn ON the motor if there is a fire that interns intimate the farmers through mobile application. The temperature sensor, humidity sensors are also used in the model to provide the details of temperature and soil moisture of the field. The experimental values obtained by the model ensure complete safety of crops from animals and from fire thus protecting the farmer’s loss. In addition, mobile application is also developed to provide the details of parameters such as temperature, moisture, water levels to farmers.
Data screening and Preliminary Analysis of the Determinants of User Acceptance of Telecentre

-The quality of an acceptable analysis is subject to the quality of initial data screening and treatment. This paper presents a preliminary analysis with regards to exploring the determinants of User acceptance of Telecentre in Nigeria. One hundred and ninety one valid questionnaires were retrieved from the respondents. Data screening and cleaning was performed in order to fulfill the requirement of performing multivariate analysis. Accordingly, assessment of missing data, outliers, multicollinearity and normality were carried out. Moreover, exploratory factor analysis (EFA) was performed through principal components analysis (PCA). The analysis was accomplished using Statistical Package for Social Science (SPSS) and Analysis of Moment Structures (AMOS) software’s. The preliminary analysis has shown that the data satisfied the requirements for conducting the subsequent multivariate analysis.
The Vitality of Employee Based Pharmaceutical Brands' Equity in Indonesia: Relationship between Environmental Management Accounting and Organization Performance

Environmental management accounting and employee-based brand equity are experienced by every organizations’ front-line employees. This study has a vital aim to analyze the relationship between environmental management accounting and organizational performance, while the employee-based brand equity and its aspects such as brand endorsement, brand consistent behavior, band allegiance have played an important mediating role between them. The data has been collected from 399 individuals, consisting of frontline employees of pharmaceutical sectors. The data has been analyzed by applying various software such as AMOS and SPSS. The data analysis techniques that have been used are SEM and CFA. The discussion has shown that all the hypotheses have been accepted. The results have indicated that employee-based brand equity and its aspects such as brand endorsement, brand consistent behavior, brand allegiance have played an important mediating role between environment management accounting and organizational performance. The study is also effective in terms of theoretical, managerial, and practical implications. The study has aided employees, companies, and managers to understand the role of environmental management accounting, employee-based brands’ equity in maintaining the performance of an organization.
A Review on Automatic Generation of Architectural Space Layouts with Energy Performance Optimization

The space layout design is one of the most important phases of the architectural design, and the automatic generation of space layout has shown great potential as a design aid. Research has shown that space layouts can have a significant impact on the improvement of energy performance. The combination of the automatic generation of space layout and the optimization of energy performance is expected to be greatly helpful for the development of an energy efficient design in the early design phase. This paper presents a literature review of the current research about the automatic generation of space layout related to the energy performance.
Airbus' Electrically Powered Aircraft as an Answer to the European Union's Low-Carbon Policy

Air transport is currently the fastest developing branch of transport, and airlines get to carry more and more passengers and cargo every year. At the same time, societies are more aware of environmental damage caused by transport, which is why the European Parliament developed a document titled An Aviation Strategy for Europe, which points out actions that should be taken inorder to make air transport more environmentally-friendly. One of the assumptions is to reduce the greenhouse gas’ emission. The European Parliament suggests the use of biofuels as one of pos-sible solutions to reduce the negative impact that air transport has on the natural environment. However, airplane manufacturers come up with different ideas how to reduce emission. Airbus in cooperation with Siemens and Rolls-Royce are working on an electrically powered aircraft. The project they are working on is called E-Fan X and it involves replacing one of airplane’s four turbine engines with an electric motor with a capacity of 2 MW. The first tests are to be performed next year. The paper describes the idea developed by Airbus, points out its advantages and disadvantages, and forecasts what impact the appearance of electrically powered aircraft will have on the environment and airline industry. The paper will be based on author’s own knowledge and gathered materials, and also on literature analysis, deduction and empirical research using non-experimental methods.
Water Volume and Deposition Effects on Harvest-Aid Efficacy

Harvest aids provide cotton farmers with the ability to harvest in an efficient and timely manner. Harvest aids also assistant in preserving overall fiber quality by reducing fiber degradation and discoloration from exposure to weather and by the reduction of foreign matter. Many harvest-aid active ingredients do not translocate within the plant, thus adequate spray coverage is recommended to improve efficacy of these products. The widespread and rapid adoption of auxin-tolerant cotton varieties has increased the use of larger droplet size nozzles that are required for use with auxin herbicides. Subsequently, the use of larger droplet size nozzles for harvest-aid applications will likely increase. The objective of this study was to determine the impact of droplet size and carrier volume on defoliation, desiccation, boll opening, terminal and basal regrowth, and cotton leaf grade. Varying water volumes of 47, 93, 140, and 187 L ha-1, and nozzles that produced fine, medium, and ultra-coarse droplets were evaluated at 14 site years across the Cotton Belt in 2016 and 2017. Numeric trends indicate higher carrier volumes are more successful at defoliating and opening bolls than lower carrier volumes. Water volumes of 47 L ha-1 should be avoided when making cotton harvest-aid applications, as all defoliation, open boll, and regrowth values were consistently reduced at the lowest carrier volume. Treatments of various nozzle types had less impact on harvest-aid efficacy than carrier volume. Site interactions with harvest aids had a greater effect than nozzle type or water volume.
Orbital Dynamics in a Triaxial Barred Galaxy Model. I. The 2D System

We present the planar orbital dynamics of a realistic barred galaxy model, containing a nucleus (bulge), a triaxial bar, and a disk. After conducting a systematic and exhaustive orbit classification, we manage to determine how the dynamical parameters associated with the bar (mass, semiaxes, and angular velocity) affect the nature of the trajectories of the test particle. In our analysis, we distinguish not only between ordered, chaotic, and escaping motions but also between different types of regular orbits. More specifically, we reveal how the main types of regular orbits are influenced by the changes in the parameters of the galactic bar. Of particular interest is the phenomenon of trapped chaos that occurs in this galaxy model.