The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques...The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.展开更多
Considering the recent developments in the digital environment,ensuring a higher level of security for networking systems is imperative.Many security approaches are being constantly developed to protect against evolvi...Considering the recent developments in the digital environment,ensuring a higher level of security for networking systems is imperative.Many security approaches are being constantly developed to protect against evolving threats.An ensemble model for the intrusion classification system yielded promising results based on the knowledge of many prior studies.This research work aimed to create a more diverse and effective ensemble model.To this end,selected six classification models,Logistic Regression(LR),Naive Bayes(NB),K-Nearest Neighbor(KNN),Decision Tree(DT),Support Vector Machine(SVM),and Random Forest(RF)from existing study to run as independent models.Once the individual models were trained,a Correlation-Based Diversity Matrix(CDM)was created by determining their closeness.The models for the ensemble were chosen by the proposed Modified Minimization Approach for Model Subset Selection(Modified-MMS)from Lower triangular-CDM(L-CDM)as input.The proposed algorithm performance was assessed using the Network Security Laboratory—Knowledge Discovery in Databases(NSL-KDD)dataset,and several performance metrics,including accuracy,precision,recall,and F1-score.By selecting a diverse set of models,the proposed system enhances the performance of an ensemble by reducing overfitting and increasing prediction accuracy.The proposed work achieved an impressive accuracy of 99.26%,using only two classification models in an ensemble,which surpasses the performance of a larger ensemble that employs six classification models.展开更多
Regression testing is a widely used approach to confirm the correct functionality of the software in incremental development.The use of test cases makes it easier to test the ripple effect of changed requirements.Rigo...Regression testing is a widely used approach to confirm the correct functionality of the software in incremental development.The use of test cases makes it easier to test the ripple effect of changed requirements.Rigorous testingmay help in meeting the quality criteria that is based on the conformance to the requirements as given by the intended stakeholders.However,a minimized and prioritized set of test cases may reduce the efforts and time required for testingwhile focusing on the timely delivery of the software application.In this research,a technique named Test Reduce has been presented to get a minimal set of test cases based on high priority to ensure that the web applicationmeets the required quality criteria.A new technique TestReduce is proposed with a blend of genetic algorithm to find an optimized and minimal set of test cases.The ultimate objective associated with this study is to provide a technique that may solve the minimization problem of regression test cases in the case of linked requirements.In this research,the 100-Dollar prioritization approach is used to define the priority of the new requirements.展开更多
As for the affine energy, Edir Junior and Ferreira Leite establish the existence of minimizers for particular restricted subcritical and critical variational issues on BV(Ω). Similar functionals exhibit deeper weak* ...As for the affine energy, Edir Junior and Ferreira Leite establish the existence of minimizers for particular restricted subcritical and critical variational issues on BV(Ω). Similar functionals exhibit deeper weak* topological traits including lower semicontinuity and affine compactness, and their geometry is non-coercive. Our work also proves the result that extremal functions exist for certain affine Poincaré-Sobolev inequalities.展开更多
To achieve robust communication in high mobility scenarios,an iterative equalization algorithm based on alternating minimization(AM)is proposed for the orthogonal time frequency space(OTFS)system.The algorithm approxi...To achieve robust communication in high mobility scenarios,an iterative equalization algorithm based on alternating minimization(AM)is proposed for the orthogonal time frequency space(OTFS)system.The algorithm approximates the equalization problem to a convex function optimization problem in the real-valued domain and solves the problem iteratively using the AM algorithm.In the iterative process,the complexity of the proposed algorithm is reduced further based on the study of the cyclic structure and sparse property of the OTFS channel matrix in the delay-Doppler(DD)domain.The new method for OTFS is simulated and verified in a high-speed mobile scenario and the results show that the proposed equalization algorithm has excellent bit error rate performance with low complexity.展开更多
The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations ar...The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations are used for self-consumption with excess energy injected into centralized grids (CGs). However, the improper sizing of renewable energy systems (RESs) exposes the entire system to power losses. This work presents an optimization of a system consisting of distributed generations. Firstly, PSO algorithms evaluate the size of the entire system on the IEEE bus 14 test standard. Secondly, the size of the system is allocated using improved Particles Swarm Optimization (IPSO). The convergence speed of the objective function enables a conjecture to be made about the robustness of the proposed system. The power and voltage profile on the IEEE 14-bus standard displays a decrease in power losses and an appropriate response to energy demands (EDs), validating the proposed method.展开更多
目的:探讨免疫球蛋白重链(IgH)基因重排在多发性骨髓瘤(MM)自体造血干细胞移植(auto-HSCT)后微小残留病监测中的价值。方法:收集2018年-2022年于武汉市第一医院血液内科接受auto-HSCT的26例MM患者的临床资料,通过多重PCR联合毛细管电泳...目的:探讨免疫球蛋白重链(IgH)基因重排在多发性骨髓瘤(MM)自体造血干细胞移植(auto-HSCT)后微小残留病监测中的价值。方法:收集2018年-2022年于武汉市第一医院血液内科接受auto-HSCT的26例MM患者的临床资料,通过多重PCR联合毛细管电泳片段分析法检测IgH重排来评价微小残留病(MRD),对疾病的转归进行相关统计学分析。结果:全部26例MM患者中,男性18例,女性8例,中位年龄59(41-70)岁,移植后中位随访时间33(7-52)个月。与骨髓IgH重排阴性组(17例)比较,移植前骨髓IgH重排阳性(9例)患者移植后3个月达到CR和sCR疗效的比例更低(1/9 vs 14/17),移植后缓解持续的时间(DOR)更短(10.78±4.35 vs 15.88±5.22个月),两组DOR差异有统计学意义(P<0.05);与外周血干细胞采集物IgH重排阴性组(21例)比较,外周血干细胞采集物IgH重排阳性(5例)患者移植后3个月达到CR和sCR的比例更低(0/5 vs 15/21),移植后缓解持续的时间(DOR)更短(9.60±4.83 vs 15.19±5.11个月),两组DOR差异有统计学意义(P<0.05)。在随访期内,移植前骨髓IgH重排阳性的患者有5例(5/9)死亡,IgH重排阴性患者均存活;外周血干细胞采集物IgH重排阳性患者有4例(4/5)死亡,IgH重排阴性患者有1例死亡(1/21)。无论是骨髓还是外周血干细胞采集物标本,IgH重排阳性患者移植后生存时间较IgH重排阴性患者更短(P<0.05)。Logistic回归分析结果显示,性别、疾病分期、初诊时骨髓涂片浆细胞比例、干细胞动员方案、移植前疗效评价(≥CR和<CR)、CD34+细胞计数对移植前骨髓及干细胞采集物IgH重排均无影响(P>0.05)。结论:通过检测接受auto-HSCT的MM患者IgH重排,可以进一步评价MRD的深度,对疾病的疗效及预后判断有一定的指导意义。展开更多
文摘The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.
基金The APC was funded by the Vellore Institute of Technology(VIT)。
文摘Considering the recent developments in the digital environment,ensuring a higher level of security for networking systems is imperative.Many security approaches are being constantly developed to protect against evolving threats.An ensemble model for the intrusion classification system yielded promising results based on the knowledge of many prior studies.This research work aimed to create a more diverse and effective ensemble model.To this end,selected six classification models,Logistic Regression(LR),Naive Bayes(NB),K-Nearest Neighbor(KNN),Decision Tree(DT),Support Vector Machine(SVM),and Random Forest(RF)from existing study to run as independent models.Once the individual models were trained,a Correlation-Based Diversity Matrix(CDM)was created by determining their closeness.The models for the ensemble were chosen by the proposed Modified Minimization Approach for Model Subset Selection(Modified-MMS)from Lower triangular-CDM(L-CDM)as input.The proposed algorithm performance was assessed using the Network Security Laboratory—Knowledge Discovery in Databases(NSL-KDD)dataset,and several performance metrics,including accuracy,precision,recall,and F1-score.By selecting a diverse set of models,the proposed system enhances the performance of an ensemble by reducing overfitting and increasing prediction accuracy.The proposed work achieved an impressive accuracy of 99.26%,using only two classification models in an ensemble,which surpasses the performance of a larger ensemble that employs six classification models.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups,Project under grant number RGP.2/49/43.
文摘Regression testing is a widely used approach to confirm the correct functionality of the software in incremental development.The use of test cases makes it easier to test the ripple effect of changed requirements.Rigorous testingmay help in meeting the quality criteria that is based on the conformance to the requirements as given by the intended stakeholders.However,a minimized and prioritized set of test cases may reduce the efforts and time required for testingwhile focusing on the timely delivery of the software application.In this research,a technique named Test Reduce has been presented to get a minimal set of test cases based on high priority to ensure that the web applicationmeets the required quality criteria.A new technique TestReduce is proposed with a blend of genetic algorithm to find an optimized and minimal set of test cases.The ultimate objective associated with this study is to provide a technique that may solve the minimization problem of regression test cases in the case of linked requirements.In this research,the 100-Dollar prioritization approach is used to define the priority of the new requirements.
文摘As for the affine energy, Edir Junior and Ferreira Leite establish the existence of minimizers for particular restricted subcritical and critical variational issues on BV(Ω). Similar functionals exhibit deeper weak* topological traits including lower semicontinuity and affine compactness, and their geometry is non-coercive. Our work also proves the result that extremal functions exist for certain affine Poincaré-Sobolev inequalities.
基金supported by the 54th Research Institute of China E lectronics Technology Group Corporation(SKX212010007)。
文摘To achieve robust communication in high mobility scenarios,an iterative equalization algorithm based on alternating minimization(AM)is proposed for the orthogonal time frequency space(OTFS)system.The algorithm approximates the equalization problem to a convex function optimization problem in the real-valued domain and solves the problem iteratively using the AM algorithm.In the iterative process,the complexity of the proposed algorithm is reduced further based on the study of the cyclic structure and sparse property of the OTFS channel matrix in the delay-Doppler(DD)domain.The new method for OTFS is simulated and verified in a high-speed mobile scenario and the results show that the proposed equalization algorithm has excellent bit error rate performance with low complexity.
文摘The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations are used for self-consumption with excess energy injected into centralized grids (CGs). However, the improper sizing of renewable energy systems (RESs) exposes the entire system to power losses. This work presents an optimization of a system consisting of distributed generations. Firstly, PSO algorithms evaluate the size of the entire system on the IEEE bus 14 test standard. Secondly, the size of the system is allocated using improved Particles Swarm Optimization (IPSO). The convergence speed of the objective function enables a conjecture to be made about the robustness of the proposed system. The power and voltage profile on the IEEE 14-bus standard displays a decrease in power losses and an appropriate response to energy demands (EDs), validating the proposed method.
文摘目的:探讨免疫球蛋白重链(IgH)基因重排在多发性骨髓瘤(MM)自体造血干细胞移植(auto-HSCT)后微小残留病监测中的价值。方法:收集2018年-2022年于武汉市第一医院血液内科接受auto-HSCT的26例MM患者的临床资料,通过多重PCR联合毛细管电泳片段分析法检测IgH重排来评价微小残留病(MRD),对疾病的转归进行相关统计学分析。结果:全部26例MM患者中,男性18例,女性8例,中位年龄59(41-70)岁,移植后中位随访时间33(7-52)个月。与骨髓IgH重排阴性组(17例)比较,移植前骨髓IgH重排阳性(9例)患者移植后3个月达到CR和sCR疗效的比例更低(1/9 vs 14/17),移植后缓解持续的时间(DOR)更短(10.78±4.35 vs 15.88±5.22个月),两组DOR差异有统计学意义(P<0.05);与外周血干细胞采集物IgH重排阴性组(21例)比较,外周血干细胞采集物IgH重排阳性(5例)患者移植后3个月达到CR和sCR的比例更低(0/5 vs 15/21),移植后缓解持续的时间(DOR)更短(9.60±4.83 vs 15.19±5.11个月),两组DOR差异有统计学意义(P<0.05)。在随访期内,移植前骨髓IgH重排阳性的患者有5例(5/9)死亡,IgH重排阴性患者均存活;外周血干细胞采集物IgH重排阳性患者有4例(4/5)死亡,IgH重排阴性患者有1例死亡(1/21)。无论是骨髓还是外周血干细胞采集物标本,IgH重排阳性患者移植后生存时间较IgH重排阴性患者更短(P<0.05)。Logistic回归分析结果显示,性别、疾病分期、初诊时骨髓涂片浆细胞比例、干细胞动员方案、移植前疗效评价(≥CR和<CR)、CD34+细胞计数对移植前骨髓及干细胞采集物IgH重排均无影响(P>0.05)。结论:通过检测接受auto-HSCT的MM患者IgH重排,可以进一步评价MRD的深度,对疾病的疗效及预后判断有一定的指导意义。
