BACKGROUND Eyelid reconstruction is an intricate process,addressing both aesthetic and functional aspects post-trauma or oncological surgery.Aesthetic concerns and oncological radicality guide personalized approaches....BACKGROUND Eyelid reconstruction is an intricate process,addressing both aesthetic and functional aspects post-trauma or oncological surgery.Aesthetic concerns and oncological radicality guide personalized approaches.The complex anatomy,involving anterior and posterior lamellae,requires tailored reconstruction for optimal functionality.AIM To formulate an eyelid reconstruction algorithm through an extensive literature review and to validate it by juxtaposing surgical outcomes from Cattinara Hos-in dry eye and tears,which may lead to long-term consequences such as chronic conjunctivitis,discomfort,or photo-phobia.To prevent this issue,scars should be oriented vertically or perpendicularly to the free eyelid margin when the size of the tumor allows.In employing a malar flap to repair a lower eyelid defect,the malar incision must ascend diagonally;this facilitates enhanced flap advancement and mitigates ectropion by restricting vertical traction.Conse-quently,it is imperative to maintain that the generated tension remains consistently horizontal and never vertical[9].Lagophthalmos is a disorder characterized by the inability to completely close the eyelids,leading to corneal exposure and an increased risk of keratitis or ulceration;it may arise following upper eyelid surgery.To avert this issue,it is essential to preserve a minimum of 1 cm of skin between the superior edge of the excision and the inferior boundary of the eyebrow.Epiphora may occur in cancers involving the lacrimal puncta,requiring their removal.As previously stated,when employing a glabellar flap to rectify medial canthal abnormalities,it is essential to prevent a trapdoor effect or thickening of the flap relative to the eyelid skin to which it is affixed.Constraints about our proposed algorithm enco-mpass limited sample sizes and possible publication biases in existing studies.Subsequent investigations ought to examine long-term results to further refine the algorithm.Future research should evaluate the algorithm across varied populations and examine the impact of novel graft materials on enhancing reconstructive outcomes.CONCLUSION Eyelid reconstruction remains one of the most intriguing challenges for a plastic surgeon today.The most fascinating aspect of this discipline is the need to restore the functionality of such an essential structure while maintaining its aesthetics.In our opinion,creating decision-making algorithms can facilitate reaching this goal by allowing for the individualization of the reconstructive path while minimizing the incidence of complications.The fact that we have decreased the incidence of severe complications is a sign that the work is moving in the right direction.The fact that there has been no need for reintervention,neither for reconstructive issues nor for inadequate oncological radicality,overall signifies greater patient satisfaction as they do not have to undergo the stress of new surgeries.Even the minor complic-ations recorded are in line with those reported in the literature,and,even more importantly for patients,they are of limited duration.In our experience,after a year of application,we can say that the objective has been achieved,but much more can still be done.Behind every work,a scientific basis must be continually renewed and refreshed to maintain high-quality standards.Therefore,searching for possible alternative solutions to be included in one’s surgical armamentarium is fundamental to providing the patient with a fully personalized option.展开更多
For the dense macro-femto coexistence networks scenario, a long-term-based handover（LTBH） algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover（AHO） and the time-tos...For the dense macro-femto coexistence networks scenario, a long-term-based handover（LTBH） algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover（AHO） and the time-tostay（TTS） to reduce the unnecessary handover numbers.First, the proposed AHO parameter is used to decrease the computation complexity in multiple candidate base stations（CBSs） scenario. Then, two types of TTS parameters are given for the fixed base stations and mobile base stations to make handover decisions among multiple CBSs. The simulation results show that the proposed LTBH algorithm can not only maintain the required transmission rate of users, but also effectively reduce the unnecessary numbers of handover in the dense macro-femto networks with the coexisting mobile BSs.展开更多
Under the modern education system of China, the annual scholarship evaluation is a vital thing for many of the collegestudents. This paper adopts the classification algorithm of decision tree C4.5 based on the betteri...Under the modern education system of China, the annual scholarship evaluation is a vital thing for many of the collegestudents. This paper adopts the classification algorithm of decision tree C4.5 based on the bettering of ID3 algorithm and constructa data set of the scholarship evaluation system through the analysis of the related attributes in scholarship evaluation information.And also having found some factors that plays a significant role in the growing up of the college students through analysis and re-search of moral education, intellectural education and culture&PE.展开更多
Due to the existing“island”state of psychological and behavioral data,there is no way for anyone to access students’psychological and behavioral histories.This limits the comprehensive understanding and effective i...Due to the existing“island”state of psychological and behavioral data,there is no way for anyone to access students’psychological and behavioral histories.This limits the comprehensive understanding and effective intervention of college students’mental health status.Therefore,this article constructs an artificial intelligence-based psychological health and intervention system for college students.Firstly,this article obtains psychological health testing data of college students through online platforms or on-campus system design,distribution of questionnaires,feedback from close contacts of students,and internal campus resources.Then,the architecture of a mental health monitoring system is designed.Its overall architecture includes a data collection layer,a data processing layer,a decision tree algorithm layer,and an evaluation display layer.The system uses the C4.5 decision tree algorithm to calculate the information gain of the processed sample data,selects the attribute with the maximum value,and constructs a decision tree structure model to evaluate students’mental health.Finally,this article studies the evaluation of students’mental health status by combining multidimensional information such as the SCL-90 scale,self-assessment scale,and student behavior data.Experimental data shows that the system can effectively identify students’mental health problems and provide precise intervention measures based on their situation,with high accuracy and practicality.展开更多
Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in ...Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in different database repositories every day. Most of the review data are useful to new customers for theier further purchases as well as existing companies to view customers feedback about various products. Data Mining and Machine Leaning techniques are familiar to analyse such kind of data to visualise and know the potential use of the purchased items through online. The customers are making quality of products through their sentiments about the purchased items from different online companies. In this research work, it is analysed sentiments of Headphone review data, which is collected from online repositories. For the analysis of Headphone review data, some of the Machine Learning techniques like Support Vector Machines, Naive Bayes, Decision Trees and Random Forest Algorithms and a Hybrid method are applied to find the quality via the customers’ sentiments. The accuracy and performance of the taken algorithms are also analysed based on the three types of sentiments such as positive, negative and neutral.展开更多
The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools.This research incorporates condition monitoring of a non-carbide tool insert using vibrat...The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools.This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach.A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe,where the condition of tool is monitored using vibration characteristics.The vibration signals for conditions such as heathy,damaged,thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system.The descriptive statistical features were extracted from the acquired vibration signal using the feature extraction techniques.The extracted statistical features were selected using a feature selection process through J48 decision tree algorithm.The selected features were classified using J48 decision tree and fuzzy to develop the fault diagnosis model for the improved predictive analysis.The decision tree model produced the classification accuracy as 94.78%with five selected features.The developed fuzzy model produced the classification accuracy as 94.02%with five membership functions.Hence,the decision tree has been proposed as a suitable fault diagnosis model for predicting the tool insert health condition under different fault conditions.展开更多
Due to continuous cutting tool usage,tool supervision is essential for improving the metal cutting industry.In the metal removal process tool,supervision is carried out either by an operator or online tool supervision...Due to continuous cutting tool usage,tool supervision is essential for improving the metal cutting industry.In the metal removal process tool,supervision is carried out either by an operator or online tool supervision.Tool super-vision helps to understand tool condition,dimensional accuracy,and surface superiority.For downtime in the metal cutting industry,the main reasons are tool breakage and excessive wear,so it is necessary to supervise tool which gives better tool life and enhance productivity.This paper presents different conventional and artificial intelligence techniques for tool supervision in the processing procedures that have been depicted in writing.展开更多
Powered by the Internet and the ever-increasing level of informatization, the cyberspace has become increasingly complex and its security situation has become increasingly grim, which requires new adaptive and collabo...Powered by the Internet and the ever-increasing level of informatization, the cyberspace has become increasingly complex and its security situation has become increasingly grim, which requires new adaptive and collaborative defense technologies. In this paper, we introduced an extended interactive multi-agent decision model for decentralized cyber defense. Based on the significant advantages of the cooperative multi-agent decision-making, the decentralized interactive decision model DI-MDPs and the corresponding interaction and retrieval algorithms are proposed. Then, we analyzed the interactive decision by the calculation and update processes of three matrices, the stability and evolutionary equilibrium of the proposed model are also analyzed. Finally, we evaluated the performance of the proposed algorithms based on open data sets and standard test environments, the experimental results shown that the proposed work will be more applicable in cyber defense.展开更多
Some techniques and methods for deriving water information from SPOT-4(XI) image were investigated and discussed in this paper. An algorithm of decision tree (DT) classification which includes several classifiers base...Some techniques and methods for deriving water information from SPOT-4(XI) image were investigated and discussed in this paper. An algorithm of decision tree (DT) classification which includes several classifiers based on the spectral responding characteristics of water bodies and other objects, was developed and put forward to delineate water bodies. Another algorithm of decision tree classification based on both spectral characteristics and auxiliary information of DEM and slope (DTDS) was also designed for water bodies extraction. In addition, supervised classification method of maximum likelyhood classification (MLC), and unsupervised method of interactive self organizing dada analysis technique (ISODATA) were used to extract waterbodies for comparison purpose. An index was designed and used to assess the accuracy of different methods adopted in the research. Results have shown that water extraction accuracy was variable with respect to the various techniques applied. It was low using ISODATA, very high using DT algorithm and much higher using both DTDS and MLC.展开更多
Most of the machineries in small or large-scale industry have rotating elementsupported by bearings for rigid support and accurate movement. For proper functioning ofmachinery, condition monitoring of the bearing is v...Most of the machineries in small or large-scale industry have rotating elementsupported by bearings for rigid support and accurate movement. For proper functioning ofmachinery, condition monitoring of the bearing is very important. In present study soundsignal is used to continuously monitor bearing health as sound signals of rotatingmachineries carry dynamic information of components. There are numerous studies inliterature that are reporting superiority of vibration signal of bearing fault diagnosis.However, there are very few studies done using sound signal. The cost associated withcondition monitoring using sound signal (Microphone) is less than the cost of transducerused to acquire vibration signal (Accelerometer). This paper employs sound signal forcondition monitoring of roller bearing by K-star classifier and k-nearest neighborhoodclassifier. The statistical feature extraction is performed from acquired sound signals. Thentwo-layer feature selection is done using J48 decision tree algorithm and random treealgorithm. These selected features were classified using K-star classifier and k-nearestneighborhood classifier and parametric optimization is performed to achieve the maximumclassification accuracy. The classification results for both K-star classifier and k-nearestneighborhood classifier for condition monitoring of roller bearing using sound signals werecompared.展开更多
The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a ...The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size（ VSS） modified constant modulus algorithms（ MC-MA） and modified decision directed modulus algorithms（ MD DMA） is proposed to ameliorate the convergence speed and mean square error（ MSE） performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.展开更多
Computational Social Choice is an interdisciplinary research area involving Economics, Political Science,and Social Science on the one side, and Mathematics and Computer Science（including Artificial Intelligence and ...Computational Social Choice is an interdisciplinary research area involving Economics, Political Science,and Social Science on the one side, and Mathematics and Computer Science（including Artificial Intelligence and Multiagent Systems） on the other side. Typical computational problems studied in this field include the vulnerability of voting procedures against attacks, or preference aggregation in multi-agent systems. Parameterized Algorithmics is a subfield of Theoretical Computer Science seeking to exploit meaningful problem-specific parameters in order to identify tractable special cases of in general computationally hard problems. In this paper, we propose nine of our favorite research challenges concerning the parameterized complexity of problems appearing in this context. This work is dedicated to Jianer Chen, one of the strongest problem solvers in the history of parameterized algorithmics,on the occasion of his 60 th birthday.展开更多
This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan （total completion time）. To solve scheduling problems, a combination of Decision Tree （DT） and Scatt...This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan （total completion time）. To solve scheduling problems, a combination of Decision Tree （DT） and Scatter Search （SS） algorithms are used. Initially, the DT is used to generate a seed solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification. The advantages of both DT and SS are used to form a hybrid approach. The proposed algorithm is tested with various benchmark datasets available for flowshop scheduling. The statistical results prove that the proposed method is competent and efficient for solving flowshop problems.展开更多
文摘BACKGROUND Eyelid reconstruction is an intricate process,addressing both aesthetic and functional aspects post-trauma or oncological surgery.Aesthetic concerns and oncological radicality guide personalized approaches.The complex anatomy,involving anterior and posterior lamellae,requires tailored reconstruction for optimal functionality.AIM To formulate an eyelid reconstruction algorithm through an extensive literature review and to validate it by juxtaposing surgical outcomes from Cattinara Hos-in dry eye and tears,which may lead to long-term consequences such as chronic conjunctivitis,discomfort,or photo-phobia.To prevent this issue,scars should be oriented vertically or perpendicularly to the free eyelid margin when the size of the tumor allows.In employing a malar flap to repair a lower eyelid defect,the malar incision must ascend diagonally;this facilitates enhanced flap advancement and mitigates ectropion by restricting vertical traction.Conse-quently,it is imperative to maintain that the generated tension remains consistently horizontal and never vertical[9].Lagophthalmos is a disorder characterized by the inability to completely close the eyelids,leading to corneal exposure and an increased risk of keratitis or ulceration;it may arise following upper eyelid surgery.To avert this issue,it is essential to preserve a minimum of 1 cm of skin between the superior edge of the excision and the inferior boundary of the eyebrow.Epiphora may occur in cancers involving the lacrimal puncta,requiring their removal.As previously stated,when employing a glabellar flap to rectify medial canthal abnormalities,it is essential to prevent a trapdoor effect or thickening of the flap relative to the eyelid skin to which it is affixed.Constraints about our proposed algorithm enco-mpass limited sample sizes and possible publication biases in existing studies.Subsequent investigations ought to examine long-term results to further refine the algorithm.Future research should evaluate the algorithm across varied populations and examine the impact of novel graft materials on enhancing reconstructive outcomes.CONCLUSION Eyelid reconstruction remains one of the most intriguing challenges for a plastic surgeon today.The most fascinating aspect of this discipline is the need to restore the functionality of such an essential structure while maintaining its aesthetics.In our opinion,creating decision-making algorithms can facilitate reaching this goal by allowing for the individualization of the reconstructive path while minimizing the incidence of complications.The fact that we have decreased the incidence of severe complications is a sign that the work is moving in the right direction.The fact that there has been no need for reintervention,neither for reconstructive issues nor for inadequate oncological radicality,overall signifies greater patient satisfaction as they do not have to undergo the stress of new surgeries.Even the minor complic-ations recorded are in line with those reported in the literature,and,even more importantly for patients,they are of limited duration.In our experience,after a year of application,we can say that the objective has been achieved,but much more can still be done.Behind every work,a scientific basis must be continually renewed and refreshed to maintain high-quality standards.Therefore,searching for possible alternative solutions to be included in one’s surgical armamentarium is fundamental to providing the patient with a fully personalized option.
基金The National Natural Science Foundation of China(No.61471164)the Fundamental Research Funds for the Central Universitiesthe Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX-0133)
文摘For the dense macro-femto coexistence networks scenario, a long-term-based handover（LTBH） algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover（AHO） and the time-tostay（TTS） to reduce the unnecessary handover numbers.First, the proposed AHO parameter is used to decrease the computation complexity in multiple candidate base stations（CBSs） scenario. Then, two types of TTS parameters are given for the fixed base stations and mobile base stations to make handover decisions among multiple CBSs. The simulation results show that the proposed LTBH algorithm can not only maintain the required transmission rate of users, but also effectively reduce the unnecessary numbers of handover in the dense macro-femto networks with the coexisting mobile BSs.
文摘Under the modern education system of China, the annual scholarship evaluation is a vital thing for many of the collegestudents. This paper adopts the classification algorithm of decision tree C4.5 based on the bettering of ID3 algorithm and constructa data set of the scholarship evaluation system through the analysis of the related attributes in scholarship evaluation information.And also having found some factors that plays a significant role in the growing up of the college students through analysis and re-search of moral education, intellectural education and culture&PE.
文摘Due to the existing“island”state of psychological and behavioral data,there is no way for anyone to access students’psychological and behavioral histories.This limits the comprehensive understanding and effective intervention of college students’mental health status.Therefore,this article constructs an artificial intelligence-based psychological health and intervention system for college students.Firstly,this article obtains psychological health testing data of college students through online platforms or on-campus system design,distribution of questionnaires,feedback from close contacts of students,and internal campus resources.Then,the architecture of a mental health monitoring system is designed.Its overall architecture includes a data collection layer,a data processing layer,a decision tree algorithm layer,and an evaluation display layer.The system uses the C4.5 decision tree algorithm to calculate the information gain of the processed sample data,selects the attribute with the maximum value,and constructs a decision tree structure model to evaluate students’mental health.Finally,this article studies the evaluation of students’mental health status by combining multidimensional information such as the SCL-90 scale,self-assessment scale,and student behavior data.Experimental data shows that the system can effectively identify students’mental health problems and provide precise intervention measures based on their situation,with high accuracy and practicality.
文摘Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in different database repositories every day. Most of the review data are useful to new customers for theier further purchases as well as existing companies to view customers feedback about various products. Data Mining and Machine Leaning techniques are familiar to analyse such kind of data to visualise and know the potential use of the purchased items through online. The customers are making quality of products through their sentiments about the purchased items from different online companies. In this research work, it is analysed sentiments of Headphone review data, which is collected from online repositories. For the analysis of Headphone review data, some of the Machine Learning techniques like Support Vector Machines, Naive Bayes, Decision Trees and Random Forest Algorithms and a Hybrid method are applied to find the quality via the customers’ sentiments. The accuracy and performance of the taken algorithms are also analysed based on the three types of sentiments such as positive, negative and neutral.
文摘The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools.This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach.A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe,where the condition of tool is monitored using vibration characteristics.The vibration signals for conditions such as heathy,damaged,thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system.The descriptive statistical features were extracted from the acquired vibration signal using the feature extraction techniques.The extracted statistical features were selected using a feature selection process through J48 decision tree algorithm.The selected features were classified using J48 decision tree and fuzzy to develop the fault diagnosis model for the improved predictive analysis.The decision tree model produced the classification accuracy as 94.78%with five selected features.The developed fuzzy model produced the classification accuracy as 94.02%with five membership functions.Hence,the decision tree has been proposed as a suitable fault diagnosis model for predicting the tool insert health condition under different fault conditions.
文摘Due to continuous cutting tool usage,tool supervision is essential for improving the metal cutting industry.In the metal removal process tool,supervision is carried out either by an operator or online tool supervision.Tool super-vision helps to understand tool condition,dimensional accuracy,and surface superiority.For downtime in the metal cutting industry,the main reasons are tool breakage and excessive wear,so it is necessary to supervise tool which gives better tool life and enhance productivity.This paper presents different conventional and artificial intelligence techniques for tool supervision in the processing procedures that have been depicted in writing.
基金financially supported by the National Natural Science Foundation of China (No. 62106060)in part by the Beijing Natural Science Foundation (No. 4214061)
文摘Powered by the Internet and the ever-increasing level of informatization, the cyberspace has become increasingly complex and its security situation has become increasingly grim, which requires new adaptive and collaborative defense technologies. In this paper, we introduced an extended interactive multi-agent decision model for decentralized cyber defense. Based on the significant advantages of the cooperative multi-agent decision-making, the decentralized interactive decision model DI-MDPs and the corresponding interaction and retrieval algorithms are proposed. Then, we analyzed the interactive decision by the calculation and update processes of three matrices, the stability and evolutionary equilibrium of the proposed model are also analyzed. Finally, we evaluated the performance of the proposed algorithms based on open data sets and standard test environments, the experimental results shown that the proposed work will be more applicable in cyber defense.
文摘Some techniques and methods for deriving water information from SPOT-4(XI) image were investigated and discussed in this paper. An algorithm of decision tree (DT) classification which includes several classifiers based on the spectral responding characteristics of water bodies and other objects, was developed and put forward to delineate water bodies. Another algorithm of decision tree classification based on both spectral characteristics and auxiliary information of DEM and slope (DTDS) was also designed for water bodies extraction. In addition, supervised classification method of maximum likelyhood classification (MLC), and unsupervised method of interactive self organizing dada analysis technique (ISODATA) were used to extract waterbodies for comparison purpose. An index was designed and used to assess the accuracy of different methods adopted in the research. Results have shown that water extraction accuracy was variable with respect to the various techniques applied. It was low using ISODATA, very high using DT algorithm and much higher using both DTDS and MLC.
文摘Most of the machineries in small or large-scale industry have rotating elementsupported by bearings for rigid support and accurate movement. For proper functioning ofmachinery, condition monitoring of the bearing is very important. In present study soundsignal is used to continuously monitor bearing health as sound signals of rotatingmachineries carry dynamic information of components. There are numerous studies inliterature that are reporting superiority of vibration signal of bearing fault diagnosis.However, there are very few studies done using sound signal. The cost associated withcondition monitoring using sound signal (Microphone) is less than the cost of transducerused to acquire vibration signal (Accelerometer). This paper employs sound signal forcondition monitoring of roller bearing by K-star classifier and k-nearest neighborhoodclassifier. The statistical feature extraction is performed from acquired sound signals. Thentwo-layer feature selection is done using J48 decision tree algorithm and random treealgorithm. These selected features were classified using K-star classifier and k-nearestneighborhood classifier and parametric optimization is performed to achieve the maximumclassification accuracy. The classification results for both K-star classifier and k-nearestneighborhood classifier for condition monitoring of roller bearing using sound signals werecompared.
基金Supported by the National Natural Science Foundation of China(6100201461101129+1 种基金6122700161072050)
文摘The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size（ VSS） modified constant modulus algorithms（ MC-MA） and modified decision directed modulus algorithms（ MD DMA） is proposed to ameliorate the convergence speed and mean square error（ MSE） performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.
基金supported by the Deutsche Forschungsgemeinschaft, project PAWS (NI 369/10)supported by the Studienstiftung des Deutschen Volkes+2 种基金supported by DFG "Cluster of Excellence Multimodal Computing and Interaction"supported by DIAMANT (a mathematics cluster of the Netherlands Organization for Scientific Research NWO)the Alexander von Humboldt Foundation, Bonn, Germany
文摘Computational Social Choice is an interdisciplinary research area involving Economics, Political Science,and Social Science on the one side, and Mathematics and Computer Science（including Artificial Intelligence and Multiagent Systems） on the other side. Typical computational problems studied in this field include the vulnerability of voting procedures against attacks, or preference aggregation in multi-agent systems. Parameterized Algorithmics is a subfield of Theoretical Computer Science seeking to exploit meaningful problem-specific parameters in order to identify tractable special cases of in general computationally hard problems. In this paper, we propose nine of our favorite research challenges concerning the parameterized complexity of problems appearing in this context. This work is dedicated to Jianer Chen, one of the strongest problem solvers in the history of parameterized algorithmics,on the occasion of his 60 th birthday.
文摘This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan （total completion time）. To solve scheduling problems, a combination of Decision Tree （DT） and Scatter Search （SS） algorithms are used. Initially, the DT is used to generate a seed solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification. The advantages of both DT and SS are used to form a hybrid approach. The proposed algorithm is tested with various benchmark datasets available for flowshop scheduling. The statistical results prove that the proposed method is competent and efficient for solving flowshop problems.
