This paper investigates the content placement problem to maximize the cache hit ratio in device-to-device(D2D)communications overlaying cellular networks.We consider offloading contents by users themselves,D2D communi...This paper investigates the content placement problem to maximize the cache hit ratio in device-to-device(D2D)communications overlaying cellular networks.We consider offloading contents by users themselves,D2D communications and multicast,and we analyze the relationship between these offloading methods and the cache hit ratio.Based on this relationship,we formulate the content placement optimization as a cache hit ratio maximization problem,and propose a heuristic algorithm to solve it.Numerical results demonstrate that the proposed scheme can outperform existing schemes in terms of the cache hit ratio.展开更多
The hit ratio of the yield strength of HRB400 D reinforced bar(Tangshan Iron and Steel Co.) is low. In this study, the effects of [C], [Mn], [Si], and [V] on the yield strength and mechanism were investigated. The HRB...The hit ratio of the yield strength of HRB400 D reinforced bar(Tangshan Iron and Steel Co.) is low. In this study, the effects of [C], [Mn], [Si], and [V] on the yield strength and mechanism were investigated. The HRB400 D reinforced bar with a specification of 22 spiral was chosen. A narrow composition control was achieved by reducing the lower limit of the Mn content and the amount of the alloying elements; moreover, the hit ratio of the reinforced bar yield strength increased from 65.54% to 96.27%, enhancing product stability. The cost of the steel alloy reduced by 8.86 RMB/ton, improving the market competitiveness of the product.展开更多
A collaborative filtering-based recommendation system has been an integral part of e-commerce and e-servicing.To keep the recommendation systems reliable,authentic,and superior,the security of these systems is very cr...A collaborative filtering-based recommendation system has been an integral part of e-commerce and e-servicing.To keep the recommendation systems reliable,authentic,and superior,the security of these systems is very crucial.Though the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks,in this paper,we prove that they fail to detect a new or unknown attack.We develop a new attack model,named Obscure attack,with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as intended.The Obscure attack is able to push target items to the top-N list as well as remove the actual rated items from the list.Our proposed attack is more effective at a smaller number of k in top-k similar user as compared to other existing attacks.The effectivity of the proposed attack model is tested on the MovieLens dataset,where various classifiers like SVM,J48,random forest,and naïve Bayes are utilized.展开更多
In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation...In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation results show that the performance of our presented mechanism in this paper is greatly improved, much better than that of the other three mechanisms： earliest deadline first （EDF）, highest value first （HVF） and highest density first （HDF）, under the same conditions of all nominal loads and task type proportions.展开更多
This study investigates the role of generative large language models(GLLMs)in supporting complex selection and evaluation tasks within the academic paper review process.Using empirical data from management journal sub...This study investigates the role of generative large language models(GLLMs)in supporting complex selection and evaluation tasks within the academic paper review process.Using empirical data from management journal submissions,we compared the performance of six leading GLLMs(Claude 3.5,GPT-4O,Gemini 2.5,Deepseek-R3,Moonshot-V1(kimi),and Qwen-Long)against human editors and reviewers.The results show that,at the editorial screening stage,GLLMs can help editors identify manuscripts with low publication potential,with aggregated model scores closely matching human editorial decisions.At the review stage,comments generated by the union of any three GLLMs from six GLLMs can cover over 61%of issues raised by human reviewers and are rated as superior by management professors.These findings demonstrate that GLLMs can complement human judgment in multi-stage,knowledge-intensive decision processes,improving both the efficiency and quality of academic paper reviews.The study expands the application boundaries of generative Al in management research evaluation and offers practical insights for integrating GLLMs into scholarly review workflows.展开更多
基金partly supported by the Na-tional Natural Science Foundation of China (No.61601334,61601509)
文摘This paper investigates the content placement problem to maximize the cache hit ratio in device-to-device(D2D)communications overlaying cellular networks.We consider offloading contents by users themselves,D2D communications and multicast,and we analyze the relationship between these offloading methods and the cache hit ratio.Based on this relationship,we formulate the content placement optimization as a cache hit ratio maximization problem,and propose a heuristic algorithm to solve it.Numerical results demonstrate that the proposed scheme can outperform existing schemes in terms of the cache hit ratio.
文摘The hit ratio of the yield strength of HRB400 D reinforced bar(Tangshan Iron and Steel Co.) is low. In this study, the effects of [C], [Mn], [Si], and [V] on the yield strength and mechanism were investigated. The HRB400 D reinforced bar with a specification of 22 spiral was chosen. A narrow composition control was achieved by reducing the lower limit of the Mn content and the amount of the alloying elements; moreover, the hit ratio of the reinforced bar yield strength increased from 65.54% to 96.27%, enhancing product stability. The cost of the steel alloy reduced by 8.86 RMB/ton, improving the market competitiveness of the product.
基金Funding is provided by Taif University Researchers Supporting Project number(TURSP-2020/10),Taif University,Taif,Saudi Arabia.
文摘A collaborative filtering-based recommendation system has been an integral part of e-commerce and e-servicing.To keep the recommendation systems reliable,authentic,and superior,the security of these systems is very crucial.Though the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks,in this paper,we prove that they fail to detect a new or unknown attack.We develop a new attack model,named Obscure attack,with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as intended.The Obscure attack is able to push target items to the top-N list as well as remove the actual rated items from the list.Our proposed attack is more effective at a smaller number of k in top-k similar user as compared to other existing attacks.The effectivity of the proposed attack model is tested on the MovieLens dataset,where various classifiers like SVM,J48,random forest,and naïve Bayes are utilized.
基金supported by the Shanghai Applied Materials Foundation (Grant No.06SA18)
文摘In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation results show that the performance of our presented mechanism in this paper is greatly improved, much better than that of the other three mechanisms： earliest deadline first （EDF）, highest value first （HVF） and highest density first （HDF）, under the same conditions of all nominal loads and task type proportions.
基金supported by the National Natural Science Foundation of China[grant number 72372102]for the project'Research on the coordination mechanism of digital transformation strategies between leading firms and follower firms in business ecosystem'.
文摘This study investigates the role of generative large language models(GLLMs)in supporting complex selection and evaluation tasks within the academic paper review process.Using empirical data from management journal submissions,we compared the performance of six leading GLLMs(Claude 3.5,GPT-4O,Gemini 2.5,Deepseek-R3,Moonshot-V1(kimi),and Qwen-Long)against human editors and reviewers.The results show that,at the editorial screening stage,GLLMs can help editors identify manuscripts with low publication potential,with aggregated model scores closely matching human editorial decisions.At the review stage,comments generated by the union of any three GLLMs from six GLLMs can cover over 61%of issues raised by human reviewers and are rated as superior by management professors.These findings demonstrate that GLLMs can complement human judgment in multi-stage,knowledge-intensive decision processes,improving both the efficiency and quality of academic paper reviews.The study expands the application boundaries of generative Al in management research evaluation and offers practical insights for integrating GLLMs into scholarly review workflows.
