The log-sum function as a penalty has always been drawing widespread attention in the field of sparse problems. However, it brings a non-convex, non-smooth and non-Lipschitz optimization problem that is difficult to t...
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The log-sum function as a penalty has always been drawing widespread attention in the field of sparse problems. However, it brings a non-convex, non-smooth and non-Lipschitz optimization problem that is difficult to tackle. To overcome the problem, an iterative threshold algorithm for the sparse optimization problems with log-sum function is proposed in this paper. For brevity, the sparse optimization problems with log-sum function are named log-sum regularization. Firstly, by introducing an intermediate function to construct another new function, a property theorem about solution for log-sum regularization is established. Secondly, based on the above theorem, the optimal setting rules of the compromising parameters are elaborated, and an iterative log-sum threshold algorithm is proposed. Thirdly, under the situation that the compromising parameters of log-sum regularization are relatively small, it can be proven that the proposed algorithm converges to a local minimizer of log-sum regularization. Finally, a series of simulations are implemented to examine performance of the proposed algorithm, and the results exhibit that the proposed algorithm outperforms the state-of-the-art algorithms.
We report the combination of the threshold algorithm with the Density Functional-based Tight Binding method allowing for the exploration of complex potential energy surfaces and the evaluation of probability flows bet...
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We report the combination of the threshold algorithm with the Density Functional-based Tight Binding method allowing for the exploration of complex potential energy surfaces and the evaluation of probability flows between their regions, at the quantum level. This original scheme is used to explore the energy landscape of an anionic 20-atom gold cluster, Au-20(-). On the basis of the relevant structures, 19 structural groups are highlighted, all of them being variations about the pyramidal shape: (1) distorted pyramids, (2) pyramids in which the atom of one of the facets has been removed, leaving a hole, and placed at different positions on the cluster and (3) pyramids on which an atom located at a vertex has been removed and placed on an edge or on a facet. Upper limits of the energies required to connect the basins of the 19 groups on the potential energy surface are evaluated. Moreover, the attractive basins are identified on the basis of the analysis of the probability flows on the landscape. The comparison of the disconnectivity tree with the results of the flux analysis provides a consistent representation of the Au-20(-) basins' proximity. Finally, we show how the new scheme allowed for the identification of counter-intuitive transition pathways.
This paper presented a method to carry out fault diagnosis via analyzing the motion signals of a SCARA. To analyze the motion signals of the end joint of a selective compliance assembly robot arm (SCARA) and carry out...
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This paper presented a method to carry out fault diagnosis via analyzing the motion signals of a SCARA. To analyze the motion signals of the end joint of a selective compliance assembly robot arm (SCARA) and carry out fault diagnosis. A model parameter-based threshold algorithm is proposed in this study to improve the efficiency of the fault diagnosis on the end joint of a SCARA manipulator. The operation state of the robot is determined by comparing the speed curve of the end joint of the robot with the threshold using the proposed algorithm. Firstly, the threshold range of the system output is estimated using the speed observer constructed via parameter separation. Secondly, the acceleration signals of the end joint of the robot are collected at various operational angular speeds by a single acceleration sensor installed at the end joint of the manipulator. The operation state of the robot is evaluated by analyzing the trend and vibration characteristics of its acceleration. Finally, experiments are conducted at three different speeds: 2.4rad/s, 3.12rad/s and 3.6rad/s. Some robot malfunctions are detected by comparing the actual speed with the threshold. Thus, the proposed method can be used to monitor the variation signal in each robot joint through a single accelerometer mounted on the top of the manipulator.
Falls more likely happen with elderly people due to weak body. These falls may possibly cause serious injuries. Therefore, recognition of early falling for diagnosis and treatment is very important. In this paper, a f...
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ISBN:
(纸本)9783319117768;9783319117751
Falls more likely happen with elderly people due to weak body. These falls may possibly cause serious injuries. Therefore, recognition of early falling for diagnosis and treatment is very important. In this paper, a fall alert system using an accelerometer sensor for elderly people based on a threshold algorithm is applied. A triaxial accelerometer sensor worn on the waist of people is employed to collect acceleration data. A threshold is determined by analyzing the difference between the normal daily activity and the fall. Data is collected from four daily activities and two falls: sit, stand, lie, walk, fall (walk) and fall (chair). This research potentially supports an enhanced understanding on the design and implementation of high-performance fall detections.
This study analyzes six threshold approaches for measuring swirling flame properties including flame length, lift-off height, maximum width, area, and flame pulsating displacements in terms of flame center of gravity,...
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This study analyzes six threshold approaches for measuring swirling flame properties including flame length, lift-off height, maximum width, area, and flame pulsating displacements in terms of flame center of gravity, length, and width under three operating conditions. Flame video images are captured with the use of a high-speed camera for this objective. The image processing of frames obtained from a high-speed video was fulfilled by utilizing the intermittency distribution approach in order to compare the flame properties quantitatively. The findings show that the Huang technique binarizes the experimental images of the swirling flames the best of the six threshold methods, whereas the Minimum approach produces a large error in flame morphology prediction. After the Huang algorithm, the Yen and Renyi's Entropy-based algorithms do well in forecasting flame morphology, respectively. When compared to the Huang algorithm, the Minimum technique reduces the flame length, maximum width, and area by approximately 34, 26, and 56% for fuel and airflow rates of 0.200 and 3 slpm, respectively. The two approaches of Otsu and Intermodes, on the other hand, yield almost identical flame characteristics. In addition, flame pulsating displacements in terms of center of gravity, length, and width exhibit linear dependency on the fuel flow rate (positive slope), and at a fixed fuel flow rate, pulsating displacement in terms of flame length is larger than pulsating displacement in terms of flame width. In addition, flame pulsating displacement in terms of center of gravity shows the least sensitivity to the fuel flow rate.
Climate change and associated weather variability across the Australian landscape has lent themselves to an increased incidence of cattle heat stress. Water consumption can have a sizeable, sustained impact on reticul...
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Climate change and associated weather variability across the Australian landscape has lent themselves to an increased incidence of cattle heat stress. Water consumption can have a sizeable, sustained impact on reticulorumen temperature readings, thereby impacting our interpretation of an individual's underlying physiological response to changing environmental conditions. To distinguish drinking events, we developed a drinking event detection model based on observed drinking events (video recording) from 28 dairy heifers, alongside sensorderived reticulorumen temperature (smaXtec Animal Care GmbH) profiles. The optimised model identified drinking events with high accuracy (F-score = 0.99), as predicted when the average reticulorumen temperature declined by at least 0.5 degrees C per 10-minutes, over a 10-, 20-, or 30-minute period. To account for differences in rapidity of decline, smaller reductions of 0.25 degrees C per 10 min were considered valid indicators of a drinking event, provided the 0.5 degrees C per 10-minute threshold was also met in a consecutive observation period. The temporal variability in drinking behaviour for 1,429 lactating dairy cattle across three dairy farms was then determined. Daily drinking events were greater in summer (mean 4.1) than winter (mean 3.3), while the change in reticulorumen temperature with each drinking event was smaller in summer (mean 3.7 degrees C) than winter (mean 4.9 degrees C). Drinking-recovery duration averaged 97.8 min/event. By revealing temporal differences in drinking behaviour for pasture-based dairy cattle, this work provides the basis for an improved understanding of core body temperature diversity.
This study aims to peak power shaving and reduce the cost of energy by using improved energy management system (EMS) in a microgrid. This study has three scenarios. In the first scenario, the EV charging station and t...
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This study aims to peak power shaving and reduce the cost of energy by using improved energy management system (EMS) in a microgrid. This study has three scenarios. In the first scenario, the EV charging station and the wind turbine operate standalone. In the second scenario, a microgrid structure including an energy storage system (ESS) and an EMS is established. The threshold algorithm has been used for the energy management. In the last scenario, fuzzy logic-based EMS is used for energy management. The impact of EV charge station and wind turbine on the grid and the cost of energy are analyzed for three scenarios. The results show that the use of microgrid-connected ESS significantly reduces the cost of energy and creates a more balanced load for the grid side. It is also proved that the EMS affects the energy losses. It is revealed that when the proposed fuzzy logic-based EMS is used, the energy cost is reduced by 78% and the peak power is reduced by 70%. Thus, it is seen that the proposed EMS successfully reduces both the cost of energy and the negative impact of EVs on the grid by balancing grid side load.
Satellite altimetry has enhanced the understanding of ocean dynamics through high-rate sampling and global coverage. However, land contamination and bad reflection effects limit its accuracy. We present a geometrical ...
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Satellite altimetry has enhanced the understanding of ocean dynamics through high-rate sampling and global coverage. However, land contamination and bad reflection effects limit its accuracy. We present a geometrical method for retracking altimetry waveforms in coastal areas. Our method follows a geometrical assumption related to the symmetrical reciprocal motion of the radar pulse. Based on this assumption, the altimetry waveform is modelled as a continuous and differentiable third-order spline function, and the symmetry point of this function is considered as the retracking gate. The spline retracking algorithm is validated against the tide gauges at Onsala, Halmstad, and Muscat stations in Sweden and Oman, and its performance is compared with existing retracking algorithms. Our results showed a remarkable reduction of 50-91% in the unbiased-Root-Mean-Squared-Error (ubRMSE) and an increase of at least 13% in correlation coefficients when compared with other algorithms in Swedish coast. This algorithm presented equivalent results with the threshold and improved threshold retrackings in Muscat station, based on Jason-2 measurements. However, along the Jason-3 pass, our spline method showed a considerable reduction of 80% in ubRMSE and the minimum increase of 42% in correlation coefficients than the empirical algorithms. This method also outperformed the ALES algorithm in most cases.
In order to achieve real-time monitoring and management of tool inventory, design a remote monitoring system for tool inventory based on multi terminal regulation of server network nodes. By establishing server nodes ...
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ISBN:
(纸本)9798350366105;9798350366099
In order to achieve real-time monitoring and management of tool inventory, design a remote monitoring system for tool inventory based on multi terminal regulation of server network nodes. By establishing server nodes and corresponding multi terminal control modules, the system can achieve load balancing, fault tolerance, and data storage functions. By implementing a threshold algorithm for tool inventory alarm, the inventory quantity of tools can be monitored and judged in real time, and abnormal inventory situations can be detected in a timely manner, triggering an alarm mechanism. At the same time, a hierarchical permission algorithm is adopted for user permission management to improve the data security and information confidentiality of the system. The experimental results show that the system can efficiently manage tool inventory and achieve remote monitoring and control to meet the requirements of real-time and reliability.
Given a database of vectors, a cosine threshold query returns all vectors in the database having cosine similarity to a query vector above a given threshold theta. These queries arise naturally in many applications, s...
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Given a database of vectors, a cosine threshold query returns all vectors in the database having cosine similarity to a query vector above a given threshold theta. These queries arise naturally in many applications, such as document retrieval, image search, and mass spectrometry. The paper considers the efficient evaluation of such queries, as well as of the closely related top-k cosine similarity queries. It provides novel optimality guarantees that exhibit good performance on real datasets. We take as a starting point Fagin's well-known threshold algorithm (TA), which can be used to answer cosine threshold queries as follows: an inverted index is first built from the database vectors during pre-processing;at query time, the algorithm traverses the index partially to gather a set of candidate vectors to be later verified for theta-similarity. However, directly applying TA in its raw form misses significant optimization opportunities. Indeed, we first show that one can take advantage of the fact that the vectors can be assumed to be normalized, to obtain an improved, tight stopping condition for index traversal and to efficiently compute it incrementally. Then we show that multiple real-world data sets from mass spectrometry, natural language process, and computer vision exhibit a certain form of data skewness and we exploit this property to obtain better traversal strategies. We show that under the skewness assumption, the new traversal strategy has a strong, near-optimal performance guarantee. The techniques developed in the paper are quite general since they can be applied to a large class of similarity functions beyond cosine.
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