Single-cell sequencing technologies allow for a high-resolution examination of various biological activities, such as the genome, transcriptome, and epigenetic modifications, across thousands of cells. In contrast, si...
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Augmented reality superimposes digital information onto objects in the physical world and enables multi-user *** that previous proxemic interaction research has explored many applications of user-object distance and u...
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Augmented reality superimposes digital information onto objects in the physical world and enables multi-user *** that previous proxemic interaction research has explored many applications of user-object distance and user-user distance in an augmented reality context,respectively,and combining both types of distance can improve the efficiency of users’perception and interaction with task objects and collaborators by providing userswith insight into spatial relations of user-task object and user-user,less is concerned about howthe two types of distances can be simultaneously adopted to assist collaboration tasks *** fulfill the gap,we present UOUU,the user-object distance and user-user distance combined method for dynamically assigning tasks across *** conducted empirical studies to investigate how the method affected user collaboration tasks in terms of collaboration occurrence and overall task *** results show that the method significantly improves the speed and accuracy of the collaboration tasks as well as the frequencies of collaboration *** study also confirms the method’s effects on stimulating collaboration activities,as the UOUU method has effectively reduced the participants’perceived workload and the overall moving distances during the *** for generalising the use of the method are discussed.
Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the ***,the abundance of reviews and the risk of encounte...
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Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the ***,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic *** study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie *** allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language *** adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better *** distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for *** proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and *** SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both *** indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English *** study helps deepen the understanding of sentiments across various linguistic *** many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.
The rapid growth of service-oriented and cloud computing has created large-scale data centres *** data centres’operating costs mostly come from back-end cloud infrastructure and energy *** cloud computing,extensive c...
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The rapid growth of service-oriented and cloud computing has created large-scale data centres *** data centres’operating costs mostly come from back-end cloud infrastructure and energy *** cloud computing,extensive communication resources are ***,cloud applications require more bandwidth to transfer large amounts of data to satisfy end-user *** is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching *** paper proposes a novel Energy and Communication(EC)aware scheduling(EC-scheduler)algorithm for green cloud computing,which optimizes data centre energy consumption and traffic *** primary goal of the proposed EC-scheduler is to assign user applications to cloud data centre resources with minimal utilization of data *** first introduce a Multi-Objective Leader Salp Swarm(MLSS)algorithm for task sorting,which ensures traffic load balancing,and then an Emotional Artificial Neural Network(EANN)for efficient resource ***-scheduler schedules cloud user requirements to the cloud server by optimizing both energy and communication delay,which supports the lower emission of carbon dioxide by the cloud server system,enabling a green,unalloyed *** tested the proposed plan and existing cloud scheduling methods using the GreenCloud simulator to analyze the efficiency of optimizing data centre energy and other scheduler *** EC-scheduler parameters Power Usage Effectiveness(PUE),Data Centre Energy Productivity(DCEP),Throughput,Average Execution Time(AET),Energy Consumption,and Makespan showed up to 26.738%,37.59%,50%,4.34%,34.2%,and 33.54%higher efficiency,respectively,than existing state of the art schedulers concerning number of user applications and number of user requests.
There an area. In this paper, we consider the site selection problem under two base station coverage modes. If the base station coverage area is a prototype, we plan to build 16 macro base stations and 2,763 micro bas...
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In recent times, the system's mathematical expression and operation have gained greater reach in engineering and mathematics. It is vital to solving more complex expressions and equations in a short time. The most...
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In the realm of deep learning, Generative Adversarial Networks (GANs) have emerged as a topic of significant interest for their potential to enhance model performance and enable effective data augmentation. This paper...
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Medical image segmentation has an important application value in the modern medical field, it can help doctors accurately locate and analyze the tissue structure, lesion areas, and organ boundaries in the image, which...
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The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power *** complexity necessitates t...
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The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power *** complexity necessitates the employment of distributed solution methodologies,which are not only essential but also highly *** the realm of computational modelling,the multi-area economic dispatch problem(MAED)can be formulated as a linearly constrained separable convex optimization *** proximal point algorithm(PPA)is particularly adept at addressing such mathematical constructs *** study introduces parallel(PPPA)and serial(SPPA)variants of the PPA as distributed algorithms,specifically designed for the computational modelling of the *** PPA introduces a quadratic term into the objective function,which,while potentially complicating the iterative updates of the algorithm,serves to dampen oscillations near the optimal solution,thereby enhancing the convergence ***,the convergence efficiency of the PPA is significantly influenced by the parameter *** address this parameter sensitivity,this research draws on trend theory from stock market analysis to propose trend theory-driven distributed PPPA and SPPA,thereby enhancing the robustness of the computational *** computational models proposed in this study are anticipated to exhibit superior performance in terms of convergence behaviour,stability,and robustness with respect to parameter selection,potentially outperforming existing methods such as the alternating direction method of multipliers(ADMM)and Auxiliary Problem Principle(APP)in the computational simulation of power system dispatch *** simulation results demonstrate that the trend theory-based PPPA,SPPA,ADMM and APP exhibit significant robustness to the initial value of parameter c,and show superior convergence characteristics compared to the residual balancing ADMM.
Current emergency response systems are facing several challenges, including complex emergency network structure definition and inefficient emergency scheduling. For these problems, the paper analyzes the characteristi...
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Current emergency response systems are facing several challenges, including complex emergency network structure definition and inefficient emergency scheduling. For these problems, the paper analyzes the characteristics of emergency networks, and abstracts them into multiple interconnected, interdependent and interactive networks according to the characteristics of hierarchy, attribute and function, and then proposes a hypernetwork based model and its constraint conditions. Furthermore, the paper proposes an emergency scheduling method. This method fully considers the psychological factors of people and the rescue cost factors in disasters in order to balance the interests among different levels of network during rescue. The experiment results show that the model and the method proposed in this paper can not only better reveal the composition and structure of emergency response system, but also effectively balance the cost and the satisfaction in rescue.
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