Miracle-dz/UniFAR-FTUs huggingface dataset:
The Distribution Pattern of Machining Errors on Woodworking Machine Tools

The article aims to develop a methodology for calculating and predicting the distribution patterns of wood machining errors to assess the operating conditions of the machine tool according to the technological accuracy criterion. It was analytically proven and experimentally confirmed that Weibull’s law accurately describes the distribution pattern of machining errors on woodworking machines. Based on the results of experimental studies of the accuracy of machining on machines for lengthwise sawing and plano-milling of wood, it was found that the primary indicator of the Weibull distribution law is a shape parameter that takes values within 1.89–3.11. The computational algorithm was developed for statistical modeling of the pattern of the distribution of machining errors according to the Weibull distribution law. It allows for determining the main parameters of the error distribution law and evaluating the operating conditions for the machine tool according to the technological accuracy criterion. The statistical modeling results for the distribution pattern of machining errors are correlated with the experimental data with an accuracy of up to 5 %, which confirms the reliability of the obtained simulation results. The developed approach also minimizes the restoration cost for the machine’s operability.
Evaluation of resistance spot weldability and weld performance of zinc-coated martensitic steels

This paper explores the resistance spot weldability of three martensitic (MS) steels of 1500 MPa tensile strength. A weld diameter versus current plot was developed for the three MS steels to investigate their weldable current range and expulsion characteristics. The mechanical performance of the welds was investigated using cross-tension, tensile-shear and hardness tests. It was found that the differences in electrical resistivity during the nugget growth period influenced the expulsion limit and, consequently, the weldable current range. The three MS steels failed in pullout failure mode but exhibited different plug ratios. Finally, the mechanical strength of the three MS steels was observed to be better than the other advanced high-strength steels (AHSS) such as DP600, TRIP1000 and PHS1500 steels.
Effective Traffic Model for Intelligent Traffic Monitoring Enabled Deep RNN Algorithm for Autonomous Vehicles Surveillance Systems

Regardless of the terrain, weather, visibility, or road surface conditions, improving detection and forecast accuracy is a critical priority for autonomous cars. Little shifts in the images to be collected should be understood even in low-light settings because the vehicle needs more data to make a binding judgment. As a subfield of AI and DL, Recurrent Neural Networks (RNNs) are structured with temporally aware connections between their nodes. As a result, the network can engage in sequential action driven entirely by internal incentives for an extended period. Moreover, cars require enormous computational capacity and a substantial quantity of data sets in an autonomous environment, such as unexpected events, opposing movement, lane conditions, and indestructible barriers. This study presents an effective deep recurrent neural network (Deep RNN) technique for autonomous cars to meet the need for recurrent nodes and capture sequence patterns within the acquired data. In addition, this study shows how to use deep RNN for efficient data annotation. Simulated findings show a significant drop in error when the proposed Deep RNN is utilized in autonomous cars.
AVALIAÇÃO DE BICOS DE PULVERIZAÇÃO DE AGROTÓXICOS NA CULTURA DO ALGODÃO

Avaliou-se a eficiencia de tres tipos de bico de pulverizador na aplicacao de agrotoxicos em algodao, mediante experimento de campo na estacao da Dow AgroSciences. Analisou-se o comportamento dos bicos (TXVK-8, TXVK-4 e TJ-60 8002) com relacao a deposicao, tamanho e densidade das gotas nas tres partes da planta (apical, mediana e basal). Nao foi verificada diferenca estatistica entre os mesmos com relacao a deposicao. Entretanto, a deposicao media dos tres bicos foi significativamente decrescente da regiao apical (45%) para mediana (18%) e desta para a basal (7%). O bico TJ-60 8002 VS produziu gotas relativamente grandes, resultando em baixa densidade de deposicao e, portanto, nao seria recomendado para controlar pragas que apresentem baixa mobilidade sobre as plantas. EVALUATION OF PESTICIDE PULVERIZATION NOZZLES ON COTTON CULTURE Abstract The efficiency of three pulverization nozzles in the application of pesticides on cotton were evaluated through a field experiment at Dow AgroSciences Experiment Station. The behavior of the nozzles (TXVK-8, TXVK-4, and TJ-60 8002) were tested in relation to deposition, drop size and density in three parts of the plant (apical, middle, basal). There were no statistical differences among them in relation to deposition. However, the medium deposition of the three nozzles was significantly decreasing from the apical region (45%) to the middle region (18%) and from this to the basal region (7%). The TJ- 60 8002 VS nozzle produced relatively big droplets, resulting in a low density deposition, and therefore, it would not be recommended for the control of pests that show low mobility over the plants.
Research on Intelligent Indoor Positioning Technology based on 5G

5G, as the first mobile communication system that takes positioning service as one of the design goals, introduces a variety of new technologies to improve the communication performance of the system and the accuracy and applicability of wireless positioning. However, there are still some problems in 5G indoor positioning, such as low positioning accuracy and poor switching between indoor and outdoor positioning. In order to solve these problems, further research and improvement of positioning technology is needed. In summary, 5G, as the first mobile communication system that takes positioning service as one of its design goals, introduces a variety of new technologies to improve the accuracy and applicability of positioning. However, there are still some problems to be solved, such as improving indoor positioning accuracy and achieving continuous and seamless coverage for indoor and outdoor positioning. The future development trend is positioning integration and convergence, and the introduction of collaborative positioning techniques to further improve the performance of positioning. In this paper, by analyzing the current status of 5G indoor positioning, it leads to the fact that how to improve the indoor positioning accuracy and achieve continuous and seamless coverage of indoor and outdoor positioning are urgent problems in the field of positioning, for which, firstly, we analyze the positioning techniques under the ultra-dense networking for 5G, the AOA, TDOA positioning techniques, and uplink and downlink positioning techniques. Finally, it is pointed out that positioning integration and convergence is the trend of future 5G positioning development, and then the necessity and feasibility of introducing collaborative positioning technology is pointed out.
Heavy Hitter Identification Over Large-Domain Set-Valued Data With Local Differential Privacy

Set-valued data are widely used to represent information in the real word, such as individual daily behaviors, items in shopping carts and web browsing history. By collecting set-valued data and identifying heavy hitters, service providers (i.e., the collector) can learn usage preferences of costumers (i.e., users), and improve the quality of their services by the learned information. However, the collection of raw data would bring privacy risks to users. Recently, local differential privacy (LDP) has emerged as a rigorous privacy framework for user private data collection. At the same time, many LDP schemes have been designed to achieve heavy hitters, but most of them are limited by the large data domain due to the huge computation cost. In this paper, we propose an LDP framework: PemSet, to efficiently identify heavy hitters from set-valued data with a large domain. In PemSet, users mainly focus on the prefix of each item (i.e., the first few bits of the binary expression of each item), and only perturb and report prefixes to reduce computation cost. Sometimes the prefixes of different items are the same, so the reported set-valued data could be a multiset, i.e., a set including multiple same items. As such, we design four LDP protocols MOLH, MOLH-S, MPCKV, MWheel to estimate frequencies of items in the multiset setting, and compare their performance under PemSet framework by experiments. Experimental results demonstrate that MOLH can perform the best in a high privacy region, i.e., $\epsilon < 1$ , while MWheel can obtain the highest utility when privacy budget is large, i.e., $\epsilon \geqslant 1$ .
ANTIMICROBIAL POTENTIAL OF GARLIC FRESH (Allium sativum L.) AND LAKOR ONION (Allium ascalonicum L.) ON THE GROWTH OF Staphylococcus aureus

Garlic (Allium sativum L.) and shallot Lakor (Allium ascalonicum L.) local products are plants that are used as spices for various dishes and can be used as herbal medicine. For natural use, safe and easy to consume which can be seen through its potential as herbal medicine, a study was carried out to test the antimicrobial potential of garlic (Allium sativum L.) and Lakor shallot (Allium ascalonicum L.) juice on the growth of bacteria (Staphylococcus aureus). Lakor garlic and shallots are grated, the results of grated Lakor garlic and shallots are squeezed to produce 100% pure onion bulb juice. Lakor garlic and shallot juice was diluted with concentrations of 25%, 35%, 45%, 55%, 65%, 75%, 85% and 95%, respectively. Antimicrobial activity was tested by the diffusion method using a disk to measure the diameter of the clear zone. The results showed that garlic (Allium sativum L.) was able to inhibit the growth of Staphylococcus aureus which could be demonstrated by the clear zone diameter of 16.3 mm at a concentration of 35% and at a concentration of 65% the diameter of the clear zone exceeded the clear zone of the amoxycillin antibiotic. Lakor red onion (Allium ascalonicum L.) showed antimicrobial potential but was unable to damage the bacterial cell wall as indicated by the diameter of the clear zone of 7.7 mm at a concentration of 95%. There is potential for both onion bulbs but have different antimicrobial properties against the growth of Staphylococcus aureus.
The Effect of Mindful Breathing and Mindful Sitting Practices on Nanyang Zhi Hui High School Students in Medan

The research objective was to determine the effect of mindful breathing and mindful sitting practices on the academic stress of Nanyang Zhi Hui High School students in Medan. The population in this study was 82 high school students who had known and participated in the practice of mindful breathing and mindful sitting for 5 years. Data collection methods are questionnaires and documentation as support. Methods of data analysis using inferential statistics with a quantitative approach and multiple linear regression. The data that has been collected is tested for validity and reliability, which is then analyzed using inferential statistical methods. The results showed that the practice of mindful breathing had an effect on the academic stress of Nanyang Zhi Hui Medan High School students by 6.6%, the practice of mindful sitting had an effect on the academic stress of Nanyang Zhi Hui Medan High School students by 5.8% and the practice of mindful breathing and mindful sitting together (simultaneously) had an effect on the academic stress of Nanyang Zhi Hui High School students by 13.6%, with the variable of mindful breathing practice providing an effective contribution of 7.17% while the variable of mindful sitting practice providing an effective contribution of 6.41%. Based on the results of the study, it can be concluded that the practice of mindful breathing and mindful sitting has a significant effect on the academic stress of Nanyang Zhi Hui High School students.
Flared natural gas-based onsite atmospheric water harvesting (AWH) for oilfield operations

Natural gas worth tens of billions of dollars is flared annually, which leads to resource waste and environmental issues. This work introduces and analyzes a novel concept for flared gas utilization, wherein the gas that would have been flared is instead used to condense atmospheric moisture. Natural gas, which is currently being flared, can alternatively power refrigeration systems to generate the cooling capacity for large scale atmospheric water harvesting (AWH). This approach solves two pressing issues faced by the oil–gas industry, namely gas flaring, and sourcing water for oilfield operations like hydraulic fracturing, drilling and water flooding. Multiple technical pathways to harvest atmospheric moisture by using the energy of natural gas are analyzed. A modeling framework is developed to quantify the dependence of water harvest rates on flared gas volumes and ambient weather. Flaring patterns in the Eagle Ford Shale in Texas and the Bakken Shale in North Dakota are analyzed to quantify the benefits of AWH. Overall, the gas currently flared annually in Texas and North Dakota can harvest enough water to meet 11% and 65% of the water consumption in the Eagle Ford and the Bakken, respectively. Daily harvests of upto 30 000 and 18 000 gallons water can be achieved using the gas currently flared per well in Texas and North Dakota, respectively. In fifty Bakken sites, the water required for fracturing or drilling a new well can be met via onsite flared gas-based AWH in only 3 weeks, and 3 days, respectively. The benefits of this concept are quantified for the Eagle Ford and Bakken Shales. Assessments of the global potential of this concept are presented using data from countries with high flaring activity. It is seen that this waste-to-value conversion concept offers significant economic benefits while addressing critical environmental issues pertaining to oil–gas production.
Stability Analysis of Tendon Driven Continuum Robots and Application to Active Softening

Tendon driven continuum robots are often considered to navigate through and operate in cluttered environments. While their compliance allows them to conform safely to obstacles, it leads them also to buckle under tendon actuation. In this article, we perform for the first time an extensive elastic stability analysis of these robots for arbitrary planar designs. The buckling phenomena are investigated and analyzed using bifurcation diagrams, complementing the current state of the art and adding new knowledge about robots composed of $n$ spacer disks. We show the existence of multiple robot configurations with different shapes, achievable with the same actuation inputs. A global stability criterion is also established, which links the critical tendon force, until which the robot is stable to the design parameters. Finally, the buckling phenomena are used to actively soften the robot for a better compromise between compliance and payload. An open loop control strategy is proposed, which can theoretically decrease the stiffness to zero, while maintaining the same robot shape. Experimentally, the robot is made four times more compliant than it is nominally using tendon actuation only.
Collaborative Online Learning Based on The Inter-University Learning Management System

This research aims to describe the implementation of online learning between PGRI Banyuwangi University and PGRI Mahadewa University Indonesia during the Covid-19 pandemic. So that the learning process continues to run well and keeps the quality of education high, universities collaborate in organizing a flexible learning system. The method used in this research was descriptive qualitative. Data was collected using literature study, document analysis, observation, and interviews. The informants in this research were 30 students from both universities who took Cultural History courses. The research results showed that this collaborative learning focused on online learning design to create social interaction and a humanist side of learning. It leads to effective learning, namely social interaction in the online learning process and performance between students. Collaboration-based online learning design was managed in the following way: (1) collaboration-based online learning planning begins with needs analysis; (2) the implementation of collaboration-based online learning is carried out by providing teaching materials in the LMS and then accessing them independently. Furthermore, the effectiveness of collaboration-based online learning was obtained through involvement in completing assignments through integrated online worksheets and group work.
Review of satellite image segmentation for an optimal fusion system based on the edge and region approaches

Summary Image analysis, usually, refers to a process of images provided by a computer in order to find the objects within the image. Image segmentation is one of the most critical tasks in automatic image analysis. It consists of subdividing an image into its constituent parts as well as extracting them. A great variety of segmentation algorithms have been developed in the last few decades; but more of these algorithms can be really applied to all images. Some of them are not suitable for some particular situations, especially in satellite images which, often, contain different textured regions or varying background, and are often subjected to illumination changes or environmental effects. Searching for more precision, we propose, in this work a fusion of the edge approach with the region approach for satellite image segmentation. Indeed, this paper presents an overview on image fusion techniques applied to satellite image segmentation. The aim is to exploit the advantages of the two approaches in order to know closed contours and homogeneous areas for optimal image segmentation.
Seasonal probabilistic forecasting of tropical cyclone activity in the North Indian Ocean

Coastal flooding due to tropical cyclones (TCs) is a major concern in low‐lying areas of the North Indian Ocean. In the past few years, there have been devastating TCs (e.g. Nargis and Layla in the Bay of Bengal and Gonu in the Arabian Sea) that have galvanised efforts to better understand and forecast such events. Here, we focus on the role of sea‐surface temperature (SST) as a predictor of TC intensification. We develop a statistical downscaling model that identifies patterns of large‐scale SST associated with TC activity in terms of occurrence rate and expected tracks. Finally, we use the Climate Forecast System v2 to construct a probabilistic forecast of TC activity for the coming months/season. We demonstrate that this approach is an integral component of a very early TC warning system.
Initialization of LSTM Networks for Data-Driven Modeling Based on Real-Driving Data

Modeling transient systems is challenging regardless of the conceptual approach and requires the use of case-specific adaptations for a successful implementation. The conventional representation in the form of a white-box approach using physical simulation models can determine labels very well for short prediction periods. Unfortunately, this capability cannot be extended to longer prediction periods, so an alternative approach is essential. With the increasingly improving prediction capabilities of neural networks due to better databases and more powerful computing systems, transient systems can be predicted remarkably well for extended periods. However, previously used methods show comparatively high deviations in the initial phases. This paper introduces an initialization method for recurrent neural networks that counteracts this problem. This method has been developed independently of the initialization methods already discussed in the literature. Consequently, the resulting advantages are briefly explained. The proposed initialization method is validated with the sub-models of the digital twin of a power-split hybrid vehicle powertrain.
UN Infects Science with Cancer of Global Warming

century was extremely high. Atmospheric CO2 levels rose as the sea surface warmed. Henry’s Solubility Law, coupled with mass balances of carbon and its isotopes, prove the total increase in atmospheric CO2 from pre-industrial times is less than 4%. Burning all our remaining fossil fuels, cannot double the CO2, but only increase it by 20%. Beck (2007 cataloged 90,000 chemical measurements of CO2 in the 1800s, some as high as 470 ppm. (Greater than the current Mauna Loa value of 385 ppm). These data exposed as false, the UN IPCC’s 280 ppm ice core values, supposedly measured during the 1800s. IPCC’s ice core measurements of CO2 were incorrect due to their inability to correct for problems with gas solubility and the extreme pressures in glaciers. Not man, but nature rules the climate.
Impact of the number of players on the emergence of creative movements in small-sided soccer games: a systematic review emphasizing deliberate practice

Introduction Creativity is a recognized quality in various areas, including sports. Within the training processes, various modifications to objectives, game configurations, rules, among other factors, can be considered to favor creative solutions to the tactical problems inherent to soccer. This systematic review aimed to identify the impact of the number of players on the emergence of creative movements in small-sided soccer games, emphasizing deliberate practice. Methods A systematic review of Scopus, PubMed, Scielo, PsycInfo, SportDiscus and Lilacs databases was performed according to PRISMA guidelines. Eligibility criteria were defined based on the elements of population, context and concept. Only full articles published in scientific journals written in English were included. No period restriction was applied. Results Five papers were included and the results of studies indicate greater number of actions, variability, and creativity in small-sided games compared to formal soccer matches. When comparing different small-sided game formats, 5 v 5 showed higher values in terms of total number of actions compared to 7 v 7, and the absolute number of original and creative actions tended to decrease as the game format increased. Imbalanced small-sided games format can promote increased exploratory behavior. Structural manipulation in goal positioning in 5 v 5 games may also influence the originality of tactical behaviors, while the use of different ball types in 4 v 4 games appears to decrease fluency values. In 6 v 6 games, fluency and versatility are negatively impacted. Conclusion Reduced game formats with fewer players and in smaller field dimensions provide more suggestive environment for exploratory behavior, variability and original and creative actions. The protocol was registered on the Open Science Framework (OSF) on 2 December 2022 (DOI: 10.17605/OSF.IO/VN6YZ). Systematic review registration [https://osf.io/jmf4k/].