Construction progress monitoring plays a crucial role in ensuring the timely and efficient completion of infrastructure projects within smart cities. This paper proposes a novel approach utilizing the Deep AlexNet arc...
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In recent years, there has been a swift progression in employing novel methods in classrooms to enhance students’ academic achievements, especially in line with the growing digitization of education. Such methods oft...
In recent years, there has been a swift progression in employing novel methods in classrooms to enhance students’ academic achievements, especially in line with the growing digitization of education. Such methods often encompass systems like facial recognition to monitor various aspects of students, including attendance, emotional states, and attention. These tools are capable of evaluating students’ presence and engagement in class, offering quantifiable metrics regarding their concentration and emotions. However, a prominent challenge has been the translation of this data into an accessible form that enables educators to assess and enhance their teaching techniques swiftly. Our suggested solution tackles this issue by offering a real-time visual depiction of students’ classroom status through different visualization techniques. These visual aids allow teachers to promptly recognize trends in student focus, thus aiding in the strategic alteration of teaching styles. Furthermore, these visual representations can be tailored to display various metrics and applied to tasks beyond monitoring attention, like overseeing attendance or assessing student progress. By integrating these advanced visualizations into the educational process, both teaching efficacy and the learning experience for students and teachers alike can be substantially elevated.
The Sunway family supercomputers have achieved a series of remarkable achievements. However, the toolchains provided by them are not perfect, which has brought great challenges to the development of high-performance a...
The Sunway family supercomputers have achieved a series of remarkable achievements. However, the toolchains provided by them are not perfect, which has brought great challenges to the development of high-performance application software. In this paper, a profiling and optimizing tool is proposed to assist people to analyze and optimize the performance of their programs. SWPFOPLD is independent of the application program and gathers the runtime performance data through the PMUs, an automatically hot functions rearrange optimization based on the performance data is furtherly accomplished. The evaluation shows that SWPFOPLD can be easily and effectively used to analyze and optimize the performance of the application programs.
A set of orthogonal multipartite quantum states are called (distinguishability-based) genuinely nonlocal if they are locally indistinguishable across any bipartition of the subsystems. In this work, we consider the pr...
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DNA storage has become an alternative to silicon-based storage of media. However, when used to store multimodal data such as images, it fails to take full advantage of the characteristics of high correlation and varia...
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DNA storage has become an alternative to silicon-based storage of media. However, when used to store multimodal data such as images, it fails to take full advantage of the characteristics of high correlation and variability present in such data, and currently remains inferior in terms of encoding density and time complexity. It also has the shortcoming of weak performance in terms of error correction methods to address insertion and deletion errors caused by error crosstalk. Therefore, we proposed an invertible neural network-based DNA image storage self-correction encoding method (INNSE) that uses the invertibility of network to perform up-down sampling processing on image and video data, thereby greatly reducing the number of DNA sequences required for data storage. A codebook generator was then designed to encode low-dimensional vectors into DNA sequences that meet various constraints. Finally, a self-correction method was constructed to achieve DNA sequence error correction at the base level without adding any redundant information. Our experimental results showed that, compared to the Yin-Yang algorithm, the encoding density of INNSE was increased by 3×, encoding time complexity was reduced by 95.26%. Under a simulated error rate of 2%, PSNR and SSIM were raised by 80.88% and 63.82%, respectively, proving that INNSE has significant advantages in encoding performance and error correction ability.
Wood planers are high speed sophisticated lumber finishing machines that are difficult to operate and for which the available data shows complex, non-linear patterns. We present a machine learning approach to build a ...
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Wood planers are high speed sophisticated lumber finishing machines that are difficult to operate and for which the available data shows complex, non-linear patterns. We present a machine learning approach to build a control loop for an industrial wood planer. In order to predict the thickness of the outgoing boards with better accuracy than the industry standard whilst allowing dynamic planer adjustments, we use an ensemble of Gaussian Processes with a specialized weighting scheme we call Automatic State Matching. It reduces the prediction error by 39% compared to current industrial practice.
It is often the case that in the development of a system-on-a-chip(SoC)design,a family of SystemC transaction level models(TLM)is *** in the same family often share common functionalities but differ in their timing,im...
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It is often the case that in the development of a system-on-a-chip(SoC)design,a family of SystemC transaction level models(TLM)is *** in the same family often share common functionalities but differ in their timing,implementation,configuration and performance in various SoC developing *** most cases,all the TLMs in a family must be verified for the follow-up design *** our previous work,we proposed to call such family TLM product line(TPL),and proposed feature-oriented(FO)design methodology for efficient TPL ***,developers can only verify TLM in a family one by one,which causes large portion of duplicated verification ***,in our proposed methodology,functional verification of TPL has become a *** this paper,we proposed a novel TPL verification method for FO *** our method,for the given property,we can exponentially reduce the number of TLMs to be verified by identifying mutefeature-modules(MFM),which will avoid duplicated *** proposed method is presented in informal and formal way,and the correctness of it is *** theoretical analysis and experimental results on a real design show the correctness and efficiency of the proposed method.
When the scheduling is established in a semiconductor packaging factory, frequent machine-related changes can pose a serious problem because of the large number of products processed using different machines with auxi...
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We investigate the carrier transport characteristics of perforated graphene layer (PGL) composed of arrays of interdigital coplanar graphene microribbons (GMRs) connected by graphene nanoribbon (GNR) bridges. We analy...
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作者：
Ismail, LeilaBuyya, RajkumarLab
School of Computing and Information Systems The University of Melbourne Australia Lab
Department of Computer Science and Software Engineering National Water and Energy Center United Arab Emirates University United Arab Emirates
With the emergence of Cloud computing, Internet of Things-enabled Human-computer Interfaces, Generative Artificial Intelligence, and high-accurate Machine and Deep-learning recognition and predictive models, along wit...
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