The concept of biological gene is transferred to the field of command information system architecture, and the concept of command information system architecture gene is proposed. For networked and intelligent systems...
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The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome t...
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The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome the high costs of traditional fingerprint database construction and matching ***,a partial fingerprint database constructed and the accelerated proximal gradient algorithm is used to fill the partial fingerprint database to construct a full fingerprint ***,a fingerprint database division method based on the strongest received signal strength indicator is proposed,which divides the original fingerprint database into several sub-fingerprint ***,a classification weighted K-nearest neighbor fingerprint matching algorithm is *** estimated coordinates of the point to be located can be obtained by fingerprint matching in a sub-fingerprint *** simulation results show that the MC-FPL algorithm can reduce the complexity of database construction and fingerprint matching and has higher positioning accuracy compared with the traditional fingerprint algorithm.
Emotion recognition using biological brain signals needs to be reliable to attain effective signal processing and feature extraction techniques. The impact of emotions in interpretations, conversations, and decision-m...
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Emotion recognition using biological brain signals needs to be reliable to attain effective signal processing and feature extraction techniques. The impact of emotions in interpretations, conversations, and decision-making, has made automatic emotion recognition and examination of a significant feature in the field of psychiatric disease treatment and cure. The problem arises from the limited spatial resolution of EEG recorders. Predetermined quantities of electroencephalography (EEG) channels are used by existing algorithms, which combine several methods to extract significant data. The major intention of this study was to focus on enhancing the efficiency of recognizing emotions using signals from the brain through an experimental, adaptive selective channel selection approach that recognizes that brain function shows distinctive behaviors that vary from one individual to another individual and from one state of emotions to another. We apply a Bernoulli–Laplace-based Bayesian model to map each emotion from the scalp senses to brain sources to resolve this issue of emotion mapping. The standard low-resolution electromagnetic tomography (sLORETA) technique is employed to instantiate the source signals. We employed a progressive graph convolutional neural network (PG-CNN) to identify the sources of the suggested localization model and the emotional EEG as the main graph nodes. In this study, the proposed framework uses a PG-CNN adjacency matrix to express the connectivity between the EEG source signals and the matrix. Research on an EEG dataset of parents of an ASD (autism spectrum disorder) child has been utilized to investigate the ways of parenting of the child's mother and father. We engage with identifying the personality of parental behaviors when regulating the child and supervising his or her daily activities. These recorded datasets incorporated by the proposed method identify five emotions from brain source modeling, which significantly improves the accurac
The video grounding(VG) task aims to locate the queried action or event in an untrimmed video based on rich linguistic descriptions. Existing proposal-free methods are trapped in the complex interaction between video ...
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The video grounding(VG) task aims to locate the queried action or event in an untrimmed video based on rich linguistic descriptions. Existing proposal-free methods are trapped in the complex interaction between video and query, overemphasizing cross-modal feature fusion and feature correlation for VG. In this paper, we propose a novel boundary regression paradigm that performs regression token learning in a transformer. Particularly, we present a simple but effective proposal-free framework, namely video grounding transformer(ViGT), which predicts the temporal boundary using a learnable regression token rather than multi-modal or cross-modal features. In ViGT, the benefits of a learnable token are manifested as follows.(1) The token is unrelated to the video or the query and avoids data bias toward the original video and query.(2) The token simultaneously performs global context aggregation from video and query ***, we employed a sharing feature encoder to project both video and query into a joint feature space before performing cross-modal co-attention(i.e., video-to-query attention and query-to-video attention) to highlight discriminative features in each modality. Furthermore, we concatenated a learnable regression token [REG] with the video and query features as the input of a vision-language transformer. Finally, we utilized the token [REG] to predict the target moment and visual features to constrain the foreground and background probabilities at each timestamp. The proposed ViGT performed well on three public datasets:ANet-Captions, TACoS, and YouCookⅡ. Extensive ablation studies and qualitative analysis further validated the interpretability of ViGT.
With the development of deep learning in recent years, code representation learning techniques have become the foundation of many software engineering tasks such as program classification [1] and defect detection. Ear...
With the development of deep learning in recent years, code representation learning techniques have become the foundation of many software engineering tasks such as program classification [1] and defect detection. Earlier approaches treat the code as token sequences and use CNN, RNN, and the Transformer models to learn code representations.
As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordin...
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As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordination of multiple robots in a multi-cluster tool,wafer production scheduling becomes rather *** a wafer is processed,due to high-temperature chemical reactions in a chamber,the robot should be controlled to take it out of the processing chamber at the right *** order to ensure the uniformity of integrated circuits on wafers,it is highly desirable to make the differences in wafer post-processing time among the individual tools in a multicluster tool as small as *** achieve this goal,for the first time,this work aims to find an optimal schedule for a dual-arm multi-cluster tool to regulate the wafer post-processing *** do so,we propose polynomial-time algorithms to find an optimal schedule,which can achieve the highest throughput,and minimize the total post-processing time of the processing *** propose a linear program model and another algorithm to balance the differences in the post-processing time between any pair of adjacent cluster *** industrial examples are given to illustrate the application and effectiveness of the proposed method.
The accurate positioning of the specular point of the spaceborne global navigation satellite system reflectometry (GNSS-R) receiver is a key step in using GNSS-R technology for geophysical parameter retrieval. As GNSS...
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Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages,such as convenience,safety,simplicity,and avoidance of *** on many studies,...
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Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages,such as convenience,safety,simplicity,and avoidance of *** on many studies,exhaled breath analysis is a promising medical detection technology capable of diagnosing different diseases by analyzing the concentration,type and other characteristics of specific *** the existing gas analysis technology,the electronic nose(eNose)analysis method has great advantages of high sensitivity,rapid response,real-time monitoring,ease of use and ***,this review is intended to provide an overview of the application of human exhaled breath components in disease diagnosis,existing breath testing technologies and the development and research status of electronic nose *** the electronic nose technology section,the three aspects of sensors,algorithms and existing systems are summarized in ***,the related challenges and limitations involved in the abovementioned technologies are also ***,the conclusion and perspective of eNose technology are presented.
THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the developmen...
THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the development of sustainable agriculture, where a fundamental step is crop breeding to improve agronomic or economic traits, e.g., increasing yields of crops while decreasing resource usage and minimizing pollution to the environment [2].
The safety and energy-saving driven co-optimization of vehicle speed and energy management for fuel cell/battery hybrid electric vehicle (FCHEV) has become a research hotspot in automotive. However, in the existing re...
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