Thank you to the Asian Journal of Urology(AJU)for the honor of allowing me to be the vip editor for this special focus section on robotic urinary tract reconstruction.This topic has been a large focus for me in my c...Thank you to the Asian Journal of Urology(AJU)for the honor of allowing me to be the vip editor for this special focus section on robotic urinary tract reconstruction.This topic has been a large focus for me in my career;in my pursuit of knowledge in this new sub-field of urology,I have been so fortunate to have met so many talented surgeons who share a similar passion.The urinary tract spans a large anatomical region,and due to the large variety of conditions that affect it,an endless variety of functional and structural urologic problems can arise.Urologists have always been adept surgeons capable of operating in various anatomical spaces and have embraced technological innovation.Historically,the trend has moved from open surgery to endoscopic treatment;however,many patients with reconstructive needs remain untreated or sub-optimally managed.展开更多
The generalized travelling salesman problem(GTSP),a generalization of the well-known travelling salesman problem(TSP),is considered for our study.Since the GTSP is NP-hard and very complex,finding exact solutions is h...The generalized travelling salesman problem(GTSP),a generalization of the well-known travelling salesman problem(TSP),is considered for our study.Since the GTSP is NP-hard and very complex,finding exact solutions is highly expensive,we will develop genetic algorithms(GAs)to obtain heuristic solutions to the problem.In GAs,as the crossover is a very important process,the crossovermethods proposed for the traditional TSP could be adapted for the GTSP.The sequential constructive crossover(SCX)and three other operators are adapted to use in GAs to solve the GTSP.The effectiveness of GA using SCX is verified on some GTSP Library(GTSPLIB)instances first and then compared against GAs using the other crossover methods.The computational results show the success of the GA using SCX for this problem.Our proposed GA using SCX,and swap mutation could find average solutions whose average percentage of excesses fromthe best-known solutions is between 0.00 and 14.07 for our investigated instances.展开更多
The intersection of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)has garnered ever-increasing attention and research interest.Nevertheless,the dilemma between the strict resource-constrained n...The intersection of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)has garnered ever-increasing attention and research interest.Nevertheless,the dilemma between the strict resource-constrained nature of IIoT devices and the extensive resource demands of AI has not yet been fully addressed with a comprehensive solution.Taking advantage of the lightweight constructive neural network(LightGCNet)in developing fast learner models for IIoT,a convex geometric constructive neural network with a low-complexity control strategy,namely,ConGCNet,is proposed in this article via convex optimization and matrix theory,which enhances the convergence rate and reduces the computational consumption in comparison with LightGCNet.Firstly,a low-complexity control strategy is proposed to reduce the computational consumption during the hidden parameters training process.Secondly,a novel output weights evaluated method based on convex optimization is proposed to guarantee the convergence rate.Finally,the universal approximation property of ConGCNet is proved by the low-complexity control strategy and convex output weights evaluated method.Simulation results,including four benchmark datasets and the real-world ore grinding process,demonstrate that ConGCNet effectively reduces computational consumption in the modelling process and improves the model’s convergence rate.展开更多
ChatGPT,launched on November 30,2022,has been adopted by the industries and academia alike.Students have started using ChatGPT for classroom assignments.In the search for the use of this tool for constructive purposes...ChatGPT,launched on November 30,2022,has been adopted by the industries and academia alike.Students have started using ChatGPT for classroom assignments.In the search for the use of this tool for constructive purposes,the professor of a graduate class(MBA)on Supply Chain and Operations Management decided to require students to use ChatGPT to first generate some material for their term papers.Typically,ChatGPT generates one to two pages of original material for the student who is not well trained in using it,which was the case for the students in this class.Then,the students were asked to use the ChatGPT-generated material as a guide to writing a 10-page long paper with new references and citations added.A comparative study is conducted to determine the usefulness of ChatGPT on this project.The preliminary results indicate that students found ChatGPT useful in generating their own papers.Meanwhile,our analysis shows beginners of ChatGPT have limited capacity to generate high-quality content based on ChatGPT.Also,text mining is conducted to compare the readability and information density of ChatGPT-generated content and student-generated content.展开更多
文摘Thank you to the Asian Journal of Urology(AJU)for the honor of allowing me to be the vip editor for this special focus section on robotic urinary tract reconstruction.This topic has been a large focus for me in my career;in my pursuit of knowledge in this new sub-field of urology,I have been so fortunate to have met so many talented surgeons who share a similar passion.The urinary tract spans a large anatomical region,and due to the large variety of conditions that affect it,an endless variety of functional and structural urologic problems can arise.Urologists have always been adept surgeons capable of operating in various anatomical spaces and have embraced technological innovation.Historically,the trend has moved from open surgery to endoscopic treatment;however,many patients with reconstructive needs remain untreated or sub-optimally managed.
基金the Deanship of Scientific Research,Imam Mohammad Ibn Saud Islamic University(IMSIU),Saudi Arabia,for funding this research work through Grant No.(221412020).
文摘The generalized travelling salesman problem(GTSP),a generalization of the well-known travelling salesman problem(TSP),is considered for our study.Since the GTSP is NP-hard and very complex,finding exact solutions is highly expensive,we will develop genetic algorithms(GAs)to obtain heuristic solutions to the problem.In GAs,as the crossover is a very important process,the crossovermethods proposed for the traditional TSP could be adapted for the GTSP.The sequential constructive crossover(SCX)and three other operators are adapted to use in GAs to solve the GTSP.The effectiveness of GA using SCX is verified on some GTSP Library(GTSPLIB)instances first and then compared against GAs using the other crossover methods.The computational results show the success of the GA using SCX for this problem.Our proposed GA using SCX,and swap mutation could find average solutions whose average percentage of excesses fromthe best-known solutions is between 0.00 and 14.07 for our investigated instances.
文摘The intersection of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)has garnered ever-increasing attention and research interest.Nevertheless,the dilemma between the strict resource-constrained nature of IIoT devices and the extensive resource demands of AI has not yet been fully addressed with a comprehensive solution.Taking advantage of the lightweight constructive neural network(LightGCNet)in developing fast learner models for IIoT,a convex geometric constructive neural network with a low-complexity control strategy,namely,ConGCNet,is proposed in this article via convex optimization and matrix theory,which enhances the convergence rate and reduces the computational consumption in comparison with LightGCNet.Firstly,a low-complexity control strategy is proposed to reduce the computational consumption during the hidden parameters training process.Secondly,a novel output weights evaluated method based on convex optimization is proposed to guarantee the convergence rate.Finally,the universal approximation property of ConGCNet is proved by the low-complexity control strategy and convex output weights evaluated method.Simulation results,including four benchmark datasets and the real-world ore grinding process,demonstrate that ConGCNet effectively reduces computational consumption in the modelling process and improves the model’s convergence rate.
文摘ChatGPT,launched on November 30,2022,has been adopted by the industries and academia alike.Students have started using ChatGPT for classroom assignments.In the search for the use of this tool for constructive purposes,the professor of a graduate class(MBA)on Supply Chain and Operations Management decided to require students to use ChatGPT to first generate some material for their term papers.Typically,ChatGPT generates one to two pages of original material for the student who is not well trained in using it,which was the case for the students in this class.Then,the students were asked to use the ChatGPT-generated material as a guide to writing a 10-page long paper with new references and citations added.A comparative study is conducted to determine the usefulness of ChatGPT on this project.The preliminary results indicate that students found ChatGPT useful in generating their own papers.Meanwhile,our analysis shows beginners of ChatGPT have limited capacity to generate high-quality content based on ChatGPT.Also,text mining is conducted to compare the readability and information density of ChatGPT-generated content and student-generated content.
