Miracle-dz/UniFAR-FTUs huggingface dataset:
Using neural networks and Dyna algorithm for integrated planning, reacting and learning in systems

The traditional AI answer to the decision making problem for a robot is planning. However, planning is usually CPU-time consuming, depending on the availability and accuracy of a world model. The Dyna system generally described in earlier work, uses trial and error to learn a world model which is simultaneously used to plan reactions resulting in optimal action sequences. It is an attempt to integrate planning, reactive, and learning systems. The architecture of Dyna is presented. The different blocks are described. There are three main components of the system. The first is the world model used by the robot for internal world representation. The input of the world model is the current state and the action taken in the current state. The output is the corresponding reward and resulting state. The second module in the system is the policy. The policy observes the current state and outputs the action to be executed by the robot. At the beginning of program execution, the policy is stochastic and through learning progressively becomes deterministic. The policy decides upon an action according to the output of an evaluation function, which is the third module of the system. The evaluation function takes the following as input: the current state of the system, the action taken in that state, the resulting state, and a reward generated by the world which is proportional to the current distance from the goal state. Originally, the work proposed was as follows: (1) to implement a simple 2-D world where a 'robot' is navigating around obstacles, to learn the path to a goal, by using lookup tables; (2) to substitute the world model and Q estimate function Q by neural networks; and (3) to apply the algorithm to a more complex world where the use of a neural network would be fully justified. In this paper, the system design and achieved results will be described. First we implement the world model with a neural network and leave Q implemented as a look up table. Next, we use a lookup table for the world model and implement the Q function with a neural net. Time limitations prevented the combination of these two approaches. The final section discusses the results and gives clues for future work.
Random e ects structure in mixed-e ects models: Keep it maximal UNDER REVIEW: Please do not cite

Linear mixed e ects models (LMEMs) are rapidly advancing as a candidate to replace ANOVA as a standard for inferential analyses in psycholinguistics and associated fields. However, because of the relative novelty of this approach, there are few clear standards regarding its correct use, as well as much uncertainty about whether it truly o ers an advantage over traditional approaches. In this paper, we argue that many of the traditional standards in accounting for observational dependencies in the design also apply to the correct use of LMEMs. We argue that valid statistical inferences using LMEMs require maximal random-e ects structures wherever possible—that is, including condition-specific random e ects by subjects/items for every fixed e ect of theoretical interest that is measured in more
Path Following Control of Autonomous Ground Vehicle Based on Nonsingular Terminal Sliding Mode and Active Disturbance Rejection Control

Due to the strong nonlinearity, coupling characteristics, external disturbance, and complex driving conditions, it is difficult to establish an accurate mathematical model for the autonomous ground vehicle (AGV). This requires the AGV path following controller to have strong robustness. In this paper, a robust AGV path following control strategy that is based on nonsingular terminal sliding mode (NTSM) and active disturbance rejection control (ADRC) is presented. First, the complex path following problem is simplified to a simple yaw angle tracking problem by constructing a desired yaw angle function that satisfies that the displacement deviation of AGV converges to zero when the actual yaw angle approaches the desired yaw angle. Second, an NTSM-ADRC controller is designed for the system, which uses the extended state observer to estimate and compensate the unmodeled dynamics and unknown external perturbations of the system in real time. In order to improve response characteristics of the controller, the nonlinear error feedback control law is designed by combining the NTSM and exponential approximation law. In contrast to the existing work, the improved controller can use the simple two-degree-of-freedom linear vehicle dynamic model to provide good performance in a range of driving conditions. Finally, the CarSim–Simulink simulation results of typical conditions show that the proposed control strategy can make the AGV follow the reference path quickly and accurately while ensuring the stability of the vehicle and has strong robustness.
Avaliação das condições de conforto térmico nas salas de aula do campus morro do cruzeiro da UFOP.

The interior environmental quality of a building is directly linked to a climate conditioning of a venue where the building is in. The comfort conditions and also asthetics of a certain built environment can influence the way the activities performed by people in it are developed. Considering educational areas, those relations of the user with the environment have a more important role, once they can directly reflect in the learning process. In this work, the classrooms’ thermal environment of the Federal University of Ouro Preto are assessed more specifically in the Minas School, in the Institute of Exact Sciences and Biological and in the Block of Rooms where the perception of the users are investigated. The investigation is realized through questionaries and alongside measurement of the environment’s variables in site during the months of June, July and September, 2011. The obtained results are statistically treated, using the calculation of the Standard Deviation from the operative and humidity averages, getting the comfort limits for the studying populations. In the studied period in which the temperature range of the outer air was approximately between 16 C and 24 C, it is obtained a percentage of approximately 75% of satisfied people with the thermal environment. In the premises of the Minas School and the Institute of Exact Science and Biological, part of the problems related to the thermal environment was solved with the installation of brises, skin insulfilm in the windows and curtains in the facades with more insolation. In the case of the Block of Rooms, for which no solution was thought, it was proposed a retrofit , encompassing the installation of mobile brisesoleil and the expansion of the medium vegetation of the immediate surroundings, avoiding direct insolation in the glazed facade, among other strategies.
Modeled MABL Responses to the Winter Kuroshio SST Front in the East China Sea and Yellow Sea

Based on the Weather Research Forecasting (WRF) model, we designed a long‐term sea surface temperature (SST)‐forcing simulation to simulate the influences of SST front on the marine atmospheric boundary layer (MABL) over the East China Sea and the Yellow Sea during wintertime. The results revealed that SST front have significant relationship with MABL adjustment. The atmospheric modulations and the comparisons of the vector wind and the scalar wind indicate that the MABL responses to the SST front are quite different under different wind directions. When the prevailing wind blows parallel to the SST front (NE wind directions), the sea level pressure adjustment mechanism dominates the atmospheric adjustment. The variances of scalar wind and vector wind are similar. However, when prevailing wind crossing SST front from cold to warm (NW wind directions), both the sea level pressure adjustment mechanism and vertical mixing mechanism play an important role. The maximum variations of the scalar wind are just over the core of SST front, whereas maximum vector wind variations are over warm flank. When wind blowing from warm to cold (SE wind directions), the vertical mixing mechanism contributes more to the MABL responses. The maximum variations of the scalar wind are beyond the top of MABL, which occur over the core SST front. The further diagnosis analysis showed that the meridional transient eddies and mean flow interaction contribute to the scalar wind variations under cross‐front conditions.
Stela: On-demand Elasticity in Distributed Data Stream Processing Systems Table of Contents

Big data is characterized by volume and velocity [24], and recently several real-time stream processing systems have emerged to combat this challenge. These systems process streams of data in real time and computational results. However, current popular data stream processing systems lack the ability to scale out and scale in (i.e., increase or decrease the number of machines or VMs allocated to the application) efficiently and unintrusively when requested by the user on demand. In order to scale out/in, a critical problem that needs to be solved is to determine which operator(s) of the stream processing application need to be given more resources or taken resources away from, in order to maximize the application throughput. We do so by presenting a novel metric called "Expected Throughput Percentage" (ETP). ETP takes into account not only congested elements of the stream processing application but also their effect on downstream elements and on the overall application throughput. Next, we show how our new system, called Stela (STream processing ELAsticity), incorporates ETP in its scheduling strategy. Stela enables scale out and scale in operations on demand, and achieves the twin goals of optimizing post-scaling throughput and minimizing interference to throughput during the scaling out/in. We have integrated the implementation of Stela into Apache Storm [27], a popular data stream processing system. We conducted experiments on Stela using a set of micro benchmark topologies as well as two topologies from Yahoo! Inc. Our experiment results shows Stela achieves iii 45% to 120% higher post scale throughput comparing to default Storm scheduler performing scale out operations, and 40% to 500% of throughput improvement comparing to the default scheduler during scale in stage. This work is a joint project with Master student Boyang Peng [1]. iv For Mom and Dad, who give me all they have. v ACKNOWLEDGMENTS I would like to thank my advisor, Indranil Gupta, to provide invaluable support, inspirations, and guidance for my research during my study. I am also very grateful to him for his millions of suggestions and corrections to help me to improve my writing skill. I would like to thank Boyang Jerry Peng for his collaboration in this project [1]. This work will not be possible without them. I would also like to express my sincere gratitude to all former and current members of Distributed Protocols Research Group (DPRG), for their constant support like a family. Working with them has …
Patterns between crown characteristics and radial increment in trees are similar during recovery and normal growth: a long-term example from old-growth forests

Crown traits and competition attributes have an important effect on tree radial increment. Relationships among these elements are modeled using the distributions of the crown characteristics in a given calendar year, but these patterns can differ over time. The suitability of the patterns during recovery and normal growth was investigated using silver fir, Abies alba Mill. , in old-growth forests. Generalized additive models (GAMs) for silver fir in the older (OG, trees aged 136–300 years) and younger (YG, trees aged 45–135 years) generations were developed. To test the validity of these GAMs, field data sets representing silver fir recovery and normal growth were used. For silver fir in OG, crown transparency had the largest effect on tree growth, explaining more than 25% of the variance. For silver fir in YG, relative crown length had the largest effect on tree growth, explaining more than 15% of the variance. The absolute relative prediction errors, AREmin and AREmax, were less than 0.03 and 1.50 mm, respectively. The developed GAMs are suitable during recovery and normal growth, but the GAMs were fitted to a relatively small area, neglecting climatic gradients and different disturbance types. This type of investigation should be continued on a larger scale.
Toxicological Effects and Histopathological Alterations of Diazinon and Alpha Cypermethrin on Male Albino Rats

Background: In Egypt, risk assessment of pesticides usage and pesticides misuse to protect plants and increase productivity connected with health hazards and pollution problems have been of public interest. Around the world three million acute poisoning cases from pesticide exposure annually report. Aim of study was to investigate the histopathological alterations, biochemical and genotoxicity adverse effects of synthetic insecticides Diazinon (organophosphorus) and alpha cypermethrin (pyrethroid) which are using for agricultural and public health applications on male albino rats. Methods: Twenty one albino rats were detached into control and two experimental groups. The experimental groups were treated with Diazinon (DIZ) and Alpha-cypermethrin (α-CYP) at sub-lethal dose (1/10 LD50 36.51 and 1.4 mg/kg body weight, respectively) by oral treatment for consecutively 28-days. The male albino rats in control treatment were put in similar surrounding conditions and treated with 5 ml /Kg tap water. Albino rats were killed after completing exposure of 28-days, liver and brain samples were dissected out for processing and sectioning examinations. Results: The obtained results revealed that both tested insecticides induced oxidative damage as appearance by a significant raise in malondialdehyde (MDA) indicating lipid peroxidation and deoxyribonucleic acid (DNA) damage indicating genotoxicity in the liver and brain. Besides, increase in GSH level and decline in enzymatic antioxidants (GST, CAT, SOD) activities were observed in liver. Marked increase was noticed in GSH levels and GST activity in brain whereas CAT and SOD antioxidant enzymes activity were significantly reduced. Histopathological studies in brain and liver revealed multiplied focal hepatic necrosis, hydropic degeneration of the hepatocytes and portal infiltration inflammatory cells in the liver. Necrosis of neurons, neuronophagia, focal gliosis and cellular oedema, congestion of cerebral blood vessel were noticed in the brain of exposed rats. Conclusion: The histopathological examination of brain and liver tissues and oxidative damage biomarkers showed adverse effects of DIZ or α-CYP insecticides at the tested dose (1/10 LD50).
Maximising production of prebiotic sugar (Cellobiose) from sago frond

Numerous fronds are discarded as waste upon harvesting of sago logs for starch production. Currently, these fronds are left to degrade in sago estates which potentially pose fire hazard in the dry season, concomitantly accommodating various pests that endanger the livelihood of the sago farmers. The objective of this study is to utilize the frond for the production of cellobiose, a non-table sugar known to harbour various prebiotic properties. Enzymatic hydrolysis was performed on treated sago frond fibre utilizing the cellulolytic enzyme Celluclast 1.5L. Characterization of the lignocellulosic component revealed that adolescent sago fronds have the highest cellulose content (41.43%) which is beneficial for high yield of cellobiose. Pruned sago fronds have the highest lignin (40.63%) which hinders the hydrolysis process. Nevertheless the hemicellulose content was found to be approximately similar (between 15 to18%) which promotes the production of cellobiose. Optimum enzymatic hydrolysis was achieved at 6% (w/v) sago frond powder coupled with 10% (v/v) enzyme and incubated for 48 hours, producing a maximum recovery of cellobiose at 25.5%.
Offset Power-law Dependence of the Sun’s Radial Electron Density Profile: Evidence and Implications

The radial electron density profile ne(r) of the Sun’s corona and solar wind contains information on the sources, heating, and acceleration of the coronal and solar wind plasma. Currently, several empirically derived density models are used to describe the corona, with varying degrees of success and little physical justification or predictive power. The offset power-law (OPL) profile , with radial offset r0 and power-law index α, models radial outflow from r0 that conserves total electron number and may be accelerated and heated (affecting α), thus having physical significance and predictive power. We fit the OPL model to multiple sets of published radial density profiles obtained from spectroscopic, white light, and radio data from different regions on the Sun and during different periods of solar activity. The spectroscopic and white light data yield r0 = (1.02 ± 0.06) RS, where the uncertainties are standard errors of the mean, and , consistent with plasma originating near the chromosphere and acceleration similar to the nominal Parker solar wind model. Comparisons with time-lapse coronagraph and spectroscopic observations are favorable and show evidence for significant variations with position and time. These are expected given the corona’s well-known asymmetries, three-dimensional structures, and time variability. Radio burst data yield flatter profiles α < 2, suggesting that pre-flare activity alters the density profile by increasing the coronal density at large heights. We discuss the possible interpretations and implications for coronal physics and solar radio bursts.
AUTONOMOUS UAV-BASED 3D-RECONSTRUCTION OF STRUCTURES FOR AERIAL PHYSICAL INTERACTION

Abstract. We introduce a fully automated only path planning approach especially for drones. This novel method relies on usage of a stereo camera mounted at the bottom of a hexagonal drone for real-time point cloud reconstruction and localization. The real-time point cloud is analyzed in a software loop where the entropy of the point cloud and the surface normals are calculated. The low entropy positions (which indicate the 3D areas with less point density and less information) and the surface normals are used for calculating the next inspection point which can be targeted by the drone in order to enhance the point cloud best. Path planning to these automatically selected target points is done during the flight (quite real-time) and automatically. The initial experiments are performed on Gazebo simulation environment within the ROS system using realistic parameters of our real drone and real stereo camera.
An Ultrawide Band Antipodal Vivaldi Antenna for Airborne GPR Application

An ultrawide band (UWB) antipodal Vivaldi antenna is designed for airborne ground penetrating radar (GPR) system. With exponential tapered slots and slot edges, the presented antenna demonstrates a wide operating band from 300 MHz to more than 2 GHz. The fabricated prototype of this antenna with a compact size of 450 mm <inline-formula> <tex-math notation="LaTeX">$\times \,\, 600$ </tex-math></inline-formula> mm <inline-formula> <tex-math notation="LaTeX">$\times \,\, 1.5$ </tex-math></inline-formula> mm has been measured in anechoic chamber. Both simulation and experimental results show that good radiation patterns with gain 4.4–11.5 dBi in the endfire direction could be achieved in the whole working band, which indicates that the proposed antenna is suitable for airborne GPR application.
Vitamin D Status in Primary Hypothyroid Subjects Attending a Specialized Endocrine Center of Bangladesh

Background: Association between vitamin D deficiency and hypothyroidism has been reported by many authors though the study results are mixed. Objective: The study was conducted to observe vitamin D status among primary hypothyroid subjects. Materials/Methods: In this single-center cross-sectional study, 356 subjects with primary hypothyroidism (either new or previously diagnosed) were evaluated for serum thyroid stimulating hormone (TSH) and 25(OH) vitamin D levels. 25(OH)D levels were classified as normal (≥30 ng/ml), insufficient (>20 to 29.9 ng/ml), and deficient (≤20 ng/ml). Results: The mean age of the study subjects was 36.33 (±12.44) years; majority of them were female (89.9%), homemaker (79.8%), residing in urban or suburban areas (64%), and literate (85.7%); almost half (48%) of them were obese. Their median TSH was 6.17 μIU/ml and mean 25(OH)D was 25.16 (±12.18) ng/ml. The frequencies of vitamin D deficiency and insufficiency were 39.6% and 34.3% respectively. No statistical differences were observed in 25(OH)D levels between males and females, obese and non-obese, new cases and previously diagnosed cases, new cases with subclinical and overt hypothyroidism, the previously diagnosed cases with controlled and uncontrolled hypothyroidism, and among subjects living in urban, suburban and rural areas. Serum 25(OH) vitamin D level showed no correlations with age, body mass index (BMI) and TSH levels of the study subjects. Conclusion: The observed frequency of hypovitaminosis D (deficiency and insufficiency) was high (73.9%) in primary hypothyroid subjects from Bangladesh.
Surface Defect Detection Based on Deep Convolutional Siamese Networks and Defect Saliency

Compared with the general target, defect is sparse in the product surface image to be detected. There are many challenges in defect detection. Firstly, there are much fewer pixels available for small defective objects. Secondly, there is limited prior knowledge and experience in this area. The scale of defects changes considerable, and defective areas have greater visual saliency than other areas. This paper proposes a defect detection method using the deep convolutional Siamese neural network to automatically extract the features of defects and classify and identify defects based on the extracted features. Firstly, the defect image is manually labeled using Groundtruth, and a defect mask map image will be generated according to the Groundtruth annotation. The defect image and the defect mask map image will be respectively inputted into two sub-networks of the deep convolutional Siamese network to extract the saliency features and defect features. Finally, the enhanced convolution feature maps are sent to the RPN (Region Proposal Networks) for the initial assessment of the targets and background; the generated proposal boxes are sent to the detection network to be classified for specific categories; and the accurate target detection box is regressed by using the bounding box regression layer. The proposed method not only avoids the problem in traditional defect detection of manually selecting target features, but also solves the difficulty of detecting small defects. The method proposed in this paper has a high level of detection accuracy and is robust to defect types, defect sizes, defect scales and defect diversification. This paper puts forward a more efficient method for detecting defects in industrial product surface images.