The cooking process significantly influences consumer perception and preference for meat. This study systematically compares the sensory and neurophysiological responses elicited by beef processed via five cooking met...
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Motion planning for many unmanned aircraft is challenging because they have a larger configuration space than self-driving automobile development (Automated guided vehicles). Additionally, there are more significant u...
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Motion planning for many unmanned aircraft is challenging because they have a larger configuration space than self-driving automobile development (Automated guided vehicles). Additionally, there are more significant uncertainties and disruptions in UAV environments, which makes inter automatic navigation more difficult. In this letter, I proposed a 2 recurrent neural networks (RL) oriented multi-UAV collision avoidance technique by modeling the unpredictability or noise in the environment. Our objective is to create a strategy that can construct a path without clashing with anything using local noisy data. But unlike supervised algorithms, RL lacks a steady training data set with floor labels, thus its collision avoidance strategies often show significant fluctuation and are difficult to reproduce. To solve these issues, we created a two-stage training method for RL-based collision avoidance. We first optimize the policy, and then we utilize a supervised learning methodology with a loss function that encourages the agents to adopt the well-known reciprocity obstacle detection mechanism. In the second step, we use transmission to fine-tune the policy. The complete computer simulation findings demonstrate that this approach can handle noisy local views with erratic sound levels and can design moment & accident paths under inadequate sensing. We review the impact of our policies in a variety of ways.
This study aims to design the movement of the hexapod robot so that it can move straight forward, turn 90 degrees forward, and move forward 180 degrees by applying the tripod gait method to produce a maximum movement ...
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Higher education is an education unit that organizes higher education. College students are called students, while college educators are called lecturers. Higher education as a place of learning and self-development S...
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Big data refers to big data, fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods. Big data technology is used in various industrial sect...
Big data refers to big data, fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods. Big data technology is used in various industrial sectors. Big data technology is the whole technology that can handle Big Data. Some of the uses of big data are based on the largest significant data traffic sources such as social media, financial transactions, public data, sensor data, and corporate data. The same is the case with the status of so many villages in Indonesia, so it is better to use big data for the classification of village status based on the village index build by involving an algorithm process. This research aims to produce a description of the role of big data in supporting activities in a grouping. The method used is a qualitative approach related to data collection based on scientific work with the source of data information needed to study literature techniques from various studies that have been published in national and international journals. A decision is made that big data has been widely used in different circles to facilitate performance and speed up the decision-making process.
Big data technology is the overall technology that can handle the processing associated with analyzing the data to explore the potential that is in it. Some of the uses of big data are based on the biggest data traffi...
Big data technology is the overall technology that can handle the processing associated with analyzing the data to explore the potential that is in it. Some of the uses of big data are based on the biggest data traffic sources, such as social media, financial transactions, public data, censorship data, and company data. The problem found in the accumulation of village status data that has not been utilized in the decision-making process to determine the status of the next village and the absence of an application to process the data stored in the data database so that a tool is developed to analyze the buildup. The results of this study are to produce a prototype design that is Unified Modeling Language (UML) design, Form Design, and Database Design that will be used to develop Big Data Technology in determining the classification of village status based on the Village Build index.
Nowadays, The roads have increased the number of streetlights for the roads vehicles/pedestrians, which raises investment and energy. Observations made to obtain most of the road lights are always active at night, eve...
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ISBN:
(数字)9780738125176
ISBN:
(纸本)9781665418614
Nowadays, The roads have increased the number of streetlights for the roads vehicles/pedestrians, which raises investment and energy. Observations made to obtain most of the road lights are always active at night, even when there are no vehicles or pedestrians on the road. The problems that occur are the waste of energy sources that are used in streetlights. This research designs the concept of intelligent traffic flow based (LED) for energy optimization, maximum efficiency. This concept uses intelligent light architecture using the LoRaWAN Mesh network. The application of this concept offers system reliability, reduces costs, and makes user satisfaction. The results of this study are demonstrated by experimenting with comparing conventional LED lights. The proposed system, resulting in 33% to 62% energy savings depending on when the usage process in streetlights. Smart lighting LEDs with LoRaWAN provide a remote-control mechanism that can be dynamically adjusted based on environmental conditions, distance, and automatic motion.
Indonesia meets the needs of 50% of the world's palm oil needs. Sources of Indonesian palm oil, 34 % are produced by independent smallholders. The lack of governance of independent smallholders leads to low produc...
Indonesia meets the needs of 50% of the world's palm oil needs. Sources of Indonesian palm oil, 34 % are produced by independent smallholders. The lack of governance of independent smallholders leads to low productivity of their crops. Global market demands for palm oil derivative sources become an obligation to compete. The development of blockchain technology that favors traceability and transparency is applied in the supply agriculture sector, and this is an opportunity for how blockchain technology can help the palm oil supply chain become transparent and can find its source. This research uses the system development life cycle (SDLC) method. And business process model and notation in business model design. The results of the design of the FFB sale and purchase transaction system with blockchain technology have succeeded in connecting farmer transactions as FFB providers with traders and PKS as FFB buyers. Every transaction sent by the farmer will be locked by a hash, as immunity makes the data sent immutable. The system can display the traceability of transactions while maintaining the integrity of member information.
In this investigation, a quantitative structure-property relationship (QSPR) model coupled with a quantum neural network (QNN) was used to explore the corrosion inhibition efficiency (CIE) of quinoxaline compounds. In...
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In this investigation, a quantitative structure-property relationship (QSPR) model coupled with a quantum neural network (QNN) was used to explore the corrosion inhibition efficiency (CIE) of quinoxaline compounds. Integrating quantum chemical properties (QCP) features reduced computational burden by strategically reducing the features from 11 to 4 while maintaining prediction accuracy. QNN models outperform traditional methods like artificial neural networks (ANN) and multilayer perceptron neural networks (MLPNN), with a coefficient of determination (R 2 ) value of 0.987, coupled with diminished root mean square error (RMSE), mean absolute error (MAE), and mean absolute deviation (MAD) values of 0.97, 0.92, and 1.10, respectively. Predictions for six newly synthesized quinoxaline derivatives: quinoxaline-6-carboxylic acid (Q1) , methyl quinoxaline-6-carboxylate (Q2) , (2 E ,3 E )-2,3-dihydrazono-1,2,3,4-tetrahydroquinoxaline (Q3) , (2 E ,3 E ) 2,3-dihydrazono-6-methyl-1,2,3,4-tetrahydroquinoxaline (Q4) , ( E )-3-(4-methoxyethyl)-7-methylquinoxalin-2(1 H)-one (Q5) , and 2-(4-methoxyphenyl)-7-methylthieno[3,2- b ] quinoxaline (Q6) , show remarkable CIE values of 95.12, 96.72, 91.02, 92.43, 89.58, and 93.63 %, respectively. This breakthrough technique simplifies testing and production procedures for new anti-corrosion materials.
The rapid development of technology, information, and communication requires students to master digital literacy. In addition, the rapid development of technology also affects environmental conditions, so it is necess...
The rapid development of technology, information, and communication requires students to master digital literacy. In addition, the rapid development of technology also affects environmental conditions, so it is necessary to master environmental literacy to understand and interpret environmental conditions, as well as build students’ awareness of environmental issues. This study aims to determine the correlation between digital literacy and student environmental literacy. The population in this research includes 11th-grade students of SMAN 1 Batu. The research sample amounted to 102 students, and the sampling technique used was purposive random sampling. Data were collected through digital literacy questionnaires, environmental literacy questionnaires, and environmental literacy tests. The data were tested for normality and homogeneity prerequisites and then analyzed using the Pearson Correlation statistical test. The results obtained show that the average digital literacy score of students is 105.1, including the high category, and the average student environmental literacy score is 279.7, included in the medium category. The high level of digital literacy will make students more critical in accessing technology and digital media. Digital literacy includes the process of finding, using multiple sources, evaluating, and using information to produce original products, with the maximum application of digital literacy, which is expected to support students’ environmental literacy in providing knowledge, understanding, and building an attitude of caring for the environment. The data obtained shows that there is a positive relationship between digital literacy and environmental literacy.
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