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Academic literature on the topic 'MmW reliability'
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Journal articles on the topic "MmW reliability"
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Baybayan, Jericho Y., and Michelle R. Lacia. "An Achievement Test in Mathematics in the Modern World Course: The Standardization Process." International Journal of Multidisciplinary: Applied Business and Education Research 5, no. 7 (2024): 2459–73. http://dx.doi.org/10.11594/ijmaber.05.07.08.
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This study aimed to construct and standardize an achievement test in Mathematics in the Modern World (MMW) course. Achievement test evaluates a student’s performance after a given period of instruction. Using the instrumentation research design, the data were gathered among 273 tertiary students of Notre Dame University enrolled during the second semester of Academic Year 2020-2021. Among these, 38 pilot tested and 213 tested the reliability of the instrument. This study further utilized the following: a 4-point Likert scale for the validation of the instrument, difficulty value and discrimination index formulas for the analysis of each item, and KR20 reliability for internal consistency. Furthermore, a test manual for the MMW achievement test was also established. The preliminary total number of Items before MMW teachers’ validation was 42 items covering the topics for the first 12 hours of the MMW Syllabus. These items were validated through Aiken’s Item Validity method which resulted in the acceptance of 42 items. After rigorous processes, it resulted in the acceptance of 34 items for the MMW achievement test. The instrument’s average validity is 0.935, and the reliability is 0.701 which means that this tool has high validity and acceptable reliability.
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Goldsmith, Chuck, John Maciel, and John McKillop. "Demonstrating Reliability." IEEE Microwave Magazine 8, no. 99 (2007): x2. http://dx.doi.org/10.1109/mmw.2007.4383488.
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Magoba, Moses, and Mimonitu Opuwari. "Petrophysical interpretation and fluid substitution modelling of the upper shallow marine sandstone reservoirs in the Bredasdorp Basin, offshore South Africa." Journal of Petroleum Exploration and Production Technology 10, no. 2 (2019): 783–803. http://dx.doi.org/10.1007/s13202-019-00796-1.
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Abstract The fluid substitution method is used for predicting elastic properties of reservoir rocks and their dependence on pore fluid and porosity. This method makes it possible to predict changes in elastic response of a rock saturation with different fluids. This study focused on the Upper Shallow Marine sandstone reservoirs of five selected wells (MM1, MM2, MM3, MM4, and MM5) in the Bredasdorp Basin, offshore South Africa. The integration of petrophysics and rock physics (Gassmann fluid substitution) was applied to the upper shallow marine sandstone reservoirs for reservoir characterisation. The objective of the study was to calculate the volume of clay, porosity, water saturation, permeability, and hydrocarbon saturation, and the application of the Gassmann fluid substitution modelling to determine the effect of different pore fluids (brine, oil, and gas) on acoustic properties (compressional velocity, shear velocity, and density) using rock frame properties. The results showed average effective porosity ranging from 8.7% to 16.6%, indicating a fair to good reservoir quality. The average volume of clay, water saturation, and permeability values ranged from 8.6% to 22.3%, 18.9% to 41.6%, and 0.096–151.8 mD, respectively. The distribution of the petrophysical properties across the field was clearly defined with MM2 and MM3 revealing good porosity and MM1, MM4, and MM5 revealing fair porosity. Well MM4 revealed poor permeability, while MM3 revealed good permeability. The fluid substitution affected rock property significantly. The primary velocity, Vp, slightly decreased when brine was substituted with gas in wells MM1, MM2, MM3, and MM4. The shear velocity, Vs, remained unaffected in all the wells. This study demonstrated how integration of petrophysics and fluid substitution can help to understand the behaviour of rock properties in response to fluid saturation changes in the Bredasdorp Basin. The integration of these two disciplines increases the obtained results’ quality and reliability.
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Li, Yibing, Jie Chen, Fang Ye, and Dandan Liu. "The Improvement of DS Evidence Theory and Its Application in IR/MMW Target Recognition." Journal of Sensors 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/1903792.
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ATR system has a broad application prospect in the military field, especially in the field of modern defense technology. When paradoxes are in existence in ATR system due to adverse battlefield environment, integration cannot be effectively and reliably carried out only by traditional DS evidence theory. In this paper, a modified DS evidence theory is presented and applied in IR/MMW target recognition system. The improvement of DS evidence theory is realized by three parts: the introduction of sensor priority and evidence credibility to realize the discount processing of evidences, the modification of DS combination rule to enhance the accuracy of synthesis results, and the compound decision-making rule. The application of the modified algorithm in IR/MMW system is designed to deal with paradoxes, improve the target recognition rate, and ensure the reliability of target recognition system. Experiments are given to illustrate that the introduction of the modified DS evidence theory in IR/MMW system is better able to realize satisfactory target recognition performance through multisensor information fusion than any single-mode system.
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Liu, Yunpeng, Kaifeng Liu, Jiang Mi, and Mingbo Luo. "Distributed Multi-MMW Radar Fusion for Target Detection and Tracking in Highway Traffic Environment." Mathematical Problems in Engineering 2023 (April 15, 2023): 1–11. http://dx.doi.org/10.1155/2023/5537122.
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High-resolution millimeter-wave (MMW) radar is viewed as a low-cost and highly reliable sensor compared to camera, lidar, etc., in moving scenarios and thus has been selected by highway stakeholders as an important roadside detector to detect the movement of traffic vehicles and monitor traffic flow in real time. However, the echo signal of MMW radar in complex highway environment contains not only the signal reflected by target but also spurious signals and other interference signals, which significantly affects the estimation of the target movement state. To solve this problem, an improved vehicle tracking method is designed to simultaneously estimate the polar angle and polar radius in coordinator of MMW radar. Moreover, considering the movement patterns of target vehicles in dynamic uncertain traffic situations, a set of state space models, such as CA, CV, and CT are combined to represent the vehicle movement. In addition, based on the enhanced detection performance of a single radar, the combination of multiple MMW radars’ information was performed to determine the sequential trajectory of the target vehicle on the continuous road sections; then, the historical trajectory of the target vehicle was correlated and fused. Real experiments in highway scenarios show that the method used in this study is effective in deriving the trajectory of the vehicle and improving the positioning accuracy and reliability when the vehicle performs heavy maneuvers.
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Hou, Wenkui, Wanyu Li, and Pengyu Li. "Fault Diagnosis of the Autonomous Driving Perception System Based on Information Fusion." Sensors 23, no. 11 (2023): 5110. http://dx.doi.org/10.3390/s23115110.
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The reliability of autonomous driving sensing systems impacts the overall safety of the driving system. However, perception system fault diagnosis is currently a weak area of research, with limited attention and solutions. In this paper, we present an information-fusion-based fault-diagnosis method for autonomous driving perception systems. To begin, we built an autonomous driving simulation scenario using PreScan software, which collects information from a single millimeter wave (MMW) radar and a single camera sensor. The photos are then identified and labeled via the convolutional neural network (CNN). Then, we fused the sensory inputs from a single MMW radar sensor and a single camera sensor in space and time and mapped the MMW radar points onto the camera image to obtain the region of interest (ROI). Lastly, we developed a method to use information from a single MMW radar to aid in diagnosing defects in a single camera sensor. As the simulation results show, for missing row/column pixel failure, the deviation typically falls between 34.11% and 99.84%, with a response time of 0.02 s to 1.6 s; for pixel shift faults, the deviation range is between 0.32% and 9.92%, with a response time of 0 s to 0.16 s; for target color loss, faults have a deviation range of 0.26% to 2.88% and a response time of 0 s to 0.05 s. These results prove the technology is effective in detecting sensor faults and issuing real-time fault alerts, providing a basis for designing and developing simpler and more user-friendly autonomous driving systems. Furthermore, this method illustrates the principles and methods of information fusion between camera and MMW radar sensors, establishing the foundation for creating more complicated autonomous driving systems.
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da Silva, Claudio Bastos, Rafael da Silva Ferraz, and Horacio Tertuliano Santos. "An Analysis of the Fading Channel Valid for Frequencies Up to the mmW Range." Journal of Computational and Theoretical Nanoscience 18, no. 6 (2021): 1754–58. http://dx.doi.org/10.1166/jctn.2021.9727.
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The fading phenomenon in mobile communications is mainly a stochastic process and plays an essential role in the reliability and stability of the systems. The frequency bands currently in use it is reasonably well characterized and described. With the use of mmW, only experimental, theoretical models are being proposed; there is no unanimity regarding a model that effectively contemplates the phenomenon in this spectrum range. Some studies suggest the traditional models applied to the frequencies in use; Rician and Rayleigh are the main ones. This study aims to advance and compare, with accepted models, a broader statistical model that overcomes the limitations of the current models. It will be analyzed and compared a model using the Nakagami-m distribution covering a greater range of possibilities, given the low spreading capacity of mmW and the need for links almost always LOS situation in which the Rician model fails.
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da Silva, Claudio Bastos, Rafael da Silva Ferraz, and Horacio Tertuliano Santos. "An Analysis of the Fading Channel Valid for Frequencies Up to the mmW Range." Journal of Computational and Theoretical Nanoscience 18, no. 6 (2021): 1754–58. http://dx.doi.org/10.1166/jctn.2021.9727.
Full textAbstract:
The fading phenomenon in mobile communications is mainly a stochastic process and plays an essential role in the reliability and stability of the systems. The frequency bands currently in use it is reasonably well characterized and described. With the use of mmW, only experimental, theoretical models are being proposed; there is no unanimity regarding a model that effectively contemplates the phenomenon in this spectrum range. Some studies suggest the traditional models applied to the frequencies in use; Rician and Rayleigh are the main ones. This study aims to advance and compare, with accepted models, a broader statistical model that overcomes the limitations of the current models. It will be analyzed and compared a model using the Nakagami-m distribution covering a greater range of possibilities, given the low spreading capacity of mmW and the need for links almost always LOS situation in which the Rician model fails.
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Jing, Rui, Zhenqi Jiang, and Xiaoying Tang. "Advances in Millimeter-Wave Treatment and Its Biological Effects Development." International Journal of Molecular Sciences 25, no. 16 (2024): 8638. http://dx.doi.org/10.3390/ijms25168638.
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This comprehensive review critically examines the current state of research on the biological effects of millimeter-wave (MMW) therapy and its potential implications for disease treatment. By investigating both the thermal and non-thermal impacts of MMWs, we elucidate cellular-level alterations, including changes in ion channels and signaling pathways. Our analysis encompasses MMW’s therapeutic prospects in oncology, such as inducing apoptosis, managing pain, and modulating immunity through cytokine regulation and immune cell activation. By employing a rigorous methodology involving an extensive database search and stringent inclusion criteria, we emphasize the need for standardized protocols to enhance the reliability of future research. Although MMWs exhibit promising therapeutic potential, our findings highlight the urgent need for further elucidation of non-thermal mechanisms and rigorous safety assessments, considering the intricate nature of MMW interactions and inconsistent study outcomes. This review underscores the importance of focused research on the biological mechanisms of MMWs and the identification of optimal frequencies to fully harness their therapeutic capabilities. However, we acknowledge the challenges of variable study quality and the necessity for advanced quality control measures to ensure the reproducibility and comparability of future investigations. In conclusion, while MMW therapy holds promise as a novel therapeutic modality, further research is imperative to unravel its complex biological effects, establish safety profiles, and optimize treatment protocols before widespread clinical application.
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Jin, Tianshi, Chenxi Zhang, Yikang Zhang, Mingliang Yang, and Weiping Ding. "A Hybrid Fault Diagnosis Method for Autonomous Driving Sensing Systems Based on Information Complexity." Electronics 13, no. 2 (2024): 354. http://dx.doi.org/10.3390/electronics13020354.
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In the context of autonomous driving, sensing systems play a crucial role, and their accuracy and reliability can significantly impact the overall safety of autonomous vehicles. Despite this, fault diagnosis for sensing systems has not received widespread attention, and existing research has limitations. This paper focuses on the unique characteristics of autonomous driving sensing systems and proposes a fault diagnosis method that combines hardware redundancy and analytical redundancy. Firstly, to ensure the authenticity of the study, we define 12 common real-world faults and inject them into the nuScenes dataset, creating an extended dataset. Then, employing heterogeneous hardware redundancy, we fuse MMW radar, LiDAR, and camera data, projecting them into pixel space. We utilize the “ground truth” obtained from the MMW radar to detect faults on the LiDAR and camera data. Finally, we use multidimensional temporal entropy to assess the information complexity fluctuations of LiDAR and the camera during faults. Simultaneously, we construct a CNN-based time-series data multi-classification model to identify fault types. Through experiments, our proposed method achieves 95.33% accuracy in detecting faults and 82.89% accuracy in fault diagnosis on real vehicles. The average response times for fault detection and diagnosis are 0.87 s and 1.36 s, respectively. The results demonstrate that the proposed method can effectively detect and diagnose faults in sensing systems and respond rapidly, providing enhanced reliability for autonomous driving systems.