Asynchronous Learning-Based Output Feedback Sliding Mode Control for Semi-Markov Jump Systems: A Descriptor Approach

This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization phenomenon.The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem.Based upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions.Furthermore,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion.Finally,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.

Deep learning-based magnetic resonance imaging reconstruction for improving the image quality of reduced-field-of-view diffusionweighted imaging of the pancreas

BACKGROUND It has been reported that deep learning-based reconstruction(DLR)can reduce image noise and artifacts,thereby improving the signal-to-noise ratio and image sharpness.However,no previous studies have evaluated the efficacy of DLR in improving image quality in reduced-field-of-view(reduced-FOV)diffusionweighted imaging(DWI)[field-of-view optimized and constrained undistorted single-shot(FOCUS)]of the pancreas.We hypothesized that a combination of these techniques would improve DWI image quality without prolonging the scan time but would influence the apparent diffusion coefficient calculation.AIM To evaluate the efficacy of DLR for image quality improvement of FOCUS of the pancreas.METHODS This was a retrospective study evaluated 37 patients with pancreatic cystic lesions who underwent magnetic resonance imaging between August 2021 and October 2021.We evaluated three types of FOCUS examinations:FOCUS with DLR(FOCUS-DLR+),FOCUS without DLR(FOCUS-DLR−),and conventional FOCUS(FOCUS-conv).The three types of FOCUS and their apparent diffusion coefficient(ADC)maps were compared qualitatively and quantitatively.RESULTS FOCUS-DLR+(3.62,average score of two radiologists)showed significantly better qualitative scores for image noise than FOCUS-DLR−(2.62)and FOCUS-conv(2.88)(P<0.05).Furthermore,FOCUS-DLR+showed the highest contrast ratio and 600 s/mm^(2)(0.72±0.08 and 0.68±0.08)and FOCUS-DLR−showed the highest CR between cystic lesions and the pancreatic parenchyma for the b-values of 0 and 600 s/mm2(0.62±0.21 and 0.62±0.21)(P<0.05),respectively.FOCUS-DLR+provided significantly higher ADCs of the pancreas and lesion(1.44±0.24 and 3.00±0.66)compared to FOCUS-DLR−(1.39±0.22 and 2.86±0.61)and significantly lower ADCs compared to FOCUS-conv(1.84±0.45 and 3.32±0.70)(P<0.05),respectively.CONCLUSION This study evaluated the efficacy of DLR for image quality improvement in reduced-FOV DWI of the pancreas.DLR can significantly denoise images without prolonging the scan time or decreasing the spatial resolution.The denoising level of DWI can be controlled to make the images appear more natural to the human eye.However,this study revealed that DLR did not ameliorate pancreatic distortion.Additionally,physicians should pay attention to the interpretation of ADCs after DLR application because ADCs are significantly changed by DLR.

Machine Learning-Based Models for Magnetic Resonance Imaging(MRI)-Based Brain Tumor Classification

In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause mortality.The technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of humans.Automatic(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic applications.Various diseases that cause death need to be identified through such techniques and technologies to overcome the mortality ratio.The brain tumor is one of the most common causes of death.Researchers have already proposed various models for the classification and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classification process with improved efficiency.However,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving accuracy.On the Kaggle dataset,these strategies are tested using classification accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation technique.The results show that SVM outperforms other algorithms,with 95.3%accuracy.

“社会”与Society的中英语义差别对比分析

翻译过程中,中英文同一组词的语义不对等问题引起语义学者兴趣,而高频互译的“社会”与society这组词在译者与读者视角下语义对等性极强,由此语义差别研究较少且研究空间较大。该文研究该组词的字典释义,对比探究两者的语义不对等性,归纳语义差别背后原因。研究发现,“社会”和society存在语义不对等;“社会”一词包含“社交”和“公共”两大含义,而society一词对应其中“社交”之意,表现出一定的不对等性。

Combinations of Transportation Policies to Promote BRT Usage Using Artificial Society Model

Various transportation systems have been developed in recent years.In this study,an artificial society model is developed to examine the combination of transportation policies in urban areas.In this model,each trip maker selects the primary and terminal transportation modes.An artificial society model is applied to the southeastern region of Osaka City,Japan.The effects of introducing BRT(bus rapid transit,primary transportation)and on-demand buses(terminal transportation)are investigated.The results confirm that BRT is used by a certain number of users.An increase in the use of BRT will increase the amount of walking,thus resulting in a healthy city.However,on-demand buses are rarely used as terminal transportation.Additionally,the development of bicycle parking stations near BRT stops is shown to be effective in the northern section of the BRT route.

Hungry and Angry Society: Implications for Sustainable Development in Nigeria

Hunger is a physiological need,but the production and consumption of adequate and balanced food is a function of social forces.At every point,social,political,and economic processes intervene,for better or(more common)for worse.Food is one fundamental need of human beings for survival.But in Nigeria there is widespread food shortage and hunger.Development scholars have put forward reasons why poverty,hunger persists in the country,from the platitudes about population growth,inadequate implementation of agricultural policies,and neglect of agriculture,bad leadership,corruption,and the issue of distribution.Nigeria is richly blessed with arable land and citizens eager to unlock its food potentials.Unfortunately,this is far from being realized as the country depends on foreign countries for food,a situation that is tragic and sad.She spends about$10 billion a year importing food and agricultural products,the majority of which are wheat,rice,poultry,fish,and consumer-oriented foods.The pressure on the exchange rate results in devaluation-triggered inflation and food costs that fly up beyond the grasp of people at the bottom of the ladder as it is now is one of the negative repercussions of high food importation bills.Examining the effects of hunger is one of this paper’s key concerns and goals,and anger crisis for achieving sustainable development in the country using the Frustration-Aggression Theory,The Relative Deprivation and Political Economy Approach as guide.

An Overview and Experimental Study of Learning-Based Optimization Algorithms for the Vehicle Routing Problem

The vehicle routing problem(VRP)is a typical discrete combinatorial optimization problem,and many models and algorithms have been proposed to solve the VRP and its variants.Although existing approaches have contributed significantly to the development of this field,these approaches either are limited in problem size or need manual intervention in choosing parameters.To solve these difficulties,many studies have considered learning-based optimization(LBO)algorithms to solve the VRP.This paper reviews recent advances in this field and divides relevant approaches into end-to-end approaches and step-by-step approaches.We performed a statistical analysis of the reviewed articles from various aspects and designed three experiments to evaluate the performance of four representative LBO algorithms.Finally,we conclude the applicable types of problems for different LBO algorithms and suggest directions in which researchers can improve LBO algorithms.

Multi-criteria user selection scheme for learning-based multiuser MIMO cognitive radio networks

For multiuser multiple-input-multiple-output （MIMO） cognitive radio （CR） networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information （ CSI ） between primary （PR） terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.

DLBT:Deep Learning-Based Transformer to Generate Pseudo-Code from Source Code

Understanding the content of the source code and its regular expression is very difficult when they are written in an unfamiliar language.Pseudo-code explains and describes the content of the code without using syntax or programming language technologies.However,writing Pseudo-code to each code instruction is laborious.Recently,neural machine translation is used to generate textual descriptions for the source code.In this paper,a novel deep learning-based transformer(DLBT)model is proposed for automatic Pseudo-code generation from the source code.The proposed model uses deep learning which is based on Neural Machine Translation(NMT)to work as a language translator.The DLBT is based on the transformer which is an encoder-decoder structure.There are three major components:tokenizer and embeddings,transformer,and post-processing.Each code line is tokenized to dense vector.Then transformer captures the relatedness between the source code and the matching Pseudo-code without the need of Recurrent Neural Network(RNN).At the post-processing step,the generated Pseudo-code is optimized.The proposed model is assessed using a real Python dataset,which contains more than 18,800 lines of a source code written in Python.The experiments show promising performance results compared with other machine translation methods such as Recurrent Neural Network(RNN).The proposed DLBT records 47.32,68.49 accuracy and BLEU performance measures,respectively.

Efficient Computation Offloading of IoT-Based Workflows Using Discrete Teaching Learning-Based Optimization

As the Internet of Things(IoT)and mobile devices have rapidly proliferated,their computationally intensive applications have developed into complex,concurrent IoT-based workflows involving multiple interdependent tasks.By exploiting its low latency and high bandwidth,mobile edge computing(MEC)has emerged to achieve the high-performance computation offloading of these applications to satisfy the quality-of-service requirements of workflows and devices.In this study,we propose an offloading strategy for IoT-based workflows in a high-performance MEC environment.The proposed task-based offloading strategy consists of an optimization problem that includes task dependency,communication costs,workflow constraints,device energy consumption,and the heterogeneous characteristics of the edge environment.In addition,the optimal placement of workflow tasks is optimized using a discrete teaching learning-based optimization(DTLBO)metaheuristic.Extensive experimental evaluations demonstrate that the proposed offloading strategy is effective at minimizing the energy consumption of mobile devices and reducing the execution times of workflows compared to offloading strategies using different metaheuristics,including particle swarm optimization and ant colony optimization.

电影《Dead Poets Society》中对教育共情力的思考

共情力是个体在观察和理解他人情感的基础上,产生与观察对象相似的情感体验并表现出相应行为反应的一种能力。在教育过程中,家庭和学校对个体的教育最为直接,学生阶段是个体人生成长的重要时期,好的教育是需要共情力的。本文以美国影片《Dead Poets Society》为例,针对“共情教育”,启发家长、教师在教育过程中的共情能力对个体心理发展所具有的积极作用。提出加强教育者共情意识,家校合力,建立轻松和谐的交往氛围,促进教育者与受教育者之间关系融洽。

An Analysis of the Current State of Civil Society Participation in Ensuring the National Security of Mongolia

In this article, the researchers tried to evaluate the contribution of civil society to Mongolian democracy and the problems faced by civil society. In addition, the article aimed to determine the unique national criteria of Mongolian democracy and the need to create an organization to monitor the process of democracy. The process of identifying important documents and ideals for the development of Mongolian civil society today is still in its early stages. It can be said that the approval of the democratic constitution and the first free and fair parliamentary elections as a country that has newly and restored democracy became another impetus for the creation of a new type of citizen organization. It is characterized by trying to study the changes that have occurred since this historical period at the intersection of political science and security studies. One of the most important issues today is to find out how many non-governmental and civil society organizations exist in Mongolia today, which are Western-oriented, focused on specific issues, have their own position and opinion, are specialized, and are capable of influencing government policy. On the other hand, in this article, we emphasize whether non-governmental and civil society organizations, which aim to hold the government accountable, and carry out influence and control activities, are fully developed.

How Does the Film Raise the Red Lantern Explore the Oppression of Women by the Patriarchal Society in China

With the gradual improvement of Chinese women’s status in the 21st-century,gender studies and gender relations had become one of the hottest topics in Chinese society,which consequently prompted Chinese Women’s Cinema to attract the attention of larger audiences.Therefore,many researchers have focused their research on Chinese Women’s Cinema,but at present,it seems that there is still a research gap to discuss and analyze the changes in women’s status and identity in China in recent years.This paper will take the famous early Chinese Women’s Cinema Raise the Red Lantern as an example for discussion and analysis.The purpose of this paper is to discuss the oppression of women in Chinese feudal patriarchal society through the details in the film Raise the Red Lantern.The significance of this paper is to appeal for gender equality in China by analyzing the oppression of women by the feudal patriarchal society in the film Raise the Red Lantern.Through careful analysis and research,it is concluded that the film Raise the Red Lantern profoundly criticizes the oppression and exploitation of women and vulnerable groups by the Republic of China through shooting details.At the same time,it is in sharp contrast with the independent thought and social status of Chinese women in the 21st-century.

The Protection of the Right to Equality of the Elderly in the Digital Society

The inequality faced by the elderly in a digital society is the digital inequality caused by both public and private actions,as well as the societal inequality exacerbated by the digital inequality.The essence of this issue lies in the unequal social participation due to the expansion of digital space under digital inequality.The characteristics of the elderly,combined with their inherent human dignity,determine that the ultimate goal of protecting their right to equality in a digital society is not limited to equal digital rights alone.Instead,it aims to ensure that the elderly have equal opportunities for social participation in both digital and non-digital spaces by eliminating digital inequality and curbing the expansion of digital space.This ensures the autonomy of the elderly in the digital society.Accordingly,the State should implement two policies based on both prohibitive obligations that prevent direct infringements and protective obligations that safeguard the equal rights of the elderly against encroachments from private entities.The first policy,“Digital Integration”,empowers the elderly with digital skills and helps them actively integrate into the digital society.The second policy,“Digital Coexistence,”ensures that the elderly can equally participate in society even when they choose to abstain from digital technology.

Procreation Anxiety in Climate Crisis:Comparative Analysis of The Smog Society and Diary of an Interesting Year

The deterioration of the environment caused by climate change has been entangled with other factors to wane people’s desire for having children.This paper takes two climate short stories,The Smog Society by the Chinese SF author Chen Qiufan and Diary of an Interesting Year by the British writer Helen Simpson as case studies,comparing the writing of the climate change induced fertility anxiety in the two stories from both the individual and community perspectives.By associating the textual analysis with the social reality about fertility rate in China and Britain,the paper explores performance and coping methods of fertility anxiety in the face of climate crisis,aimed at providing possible solutions for the sustainable development of population.

青年“低欲望躺平”:全球图景、影响因素与引导策略

在全球图景下,以“躺平”为代表的青年低欲望现象已成为世界各国共同面临的难题。文章聚焦美国、英国、日本、韩国、巴西、印度、南非等国的青年低欲望现象,展现了世界各国的差异化表现,并剖析其产生原因。研究指出,全球青年低欲望现象的形成受到外源性因素和内源性因素的影响。其中,外源性因素包括经济下行时期青年就业困难,宗教信仰和社会文化中的男权色彩,以及社会舆论对“躺平”的负面评价;内源性因素包括与青年关系紧密的初级群体的基础素养,以及青年对教育体系和社会现状的不满,而且部分青年的低欲望表现已成为他们抵御社会异化的另类方式。研究提出,面对这一全球普遍存在的社会现象,我们既要承认青年低欲望现象的合理性,营造宽松和谐的社会环境,也要通过政府、媒体、家庭和个人的多方联动,加强青年社交情感发展和能力培养,帮助青年从“躺平”中站起来。

六十载风雨同舟 四代人薪火相传——广东图书馆学会六十年之传统与精神

文章采用历史研究方法,回顾广东图书馆学会60年(1963-2023)的发展历史,以丰富详实的史料阐述杜定友先生“爱国、爱馆、爱书、爱人”的图书馆精神、广东图书馆学会“一个宗旨”“两个法宝”的学会精神和现代图书馆“自由、平等、开放、共享”的专业精神,认为这三种精神是一个不可分割的整体,是广东图书馆学会的优良传统和广东图书馆事业繁荣发展的根本。

2023年ESMO会议食管癌药物治疗进展

2023年欧洲肿瘤内科学会(European Society for Medical Oncology,ESMO)年会于2023年10月20日~24日在西班牙马德里隆重召开。本次大会报道多项食管癌领域的最新前沿研究。本文将从食管癌围手术期治疗和晚期食管癌药物治疗方面整理并解读此次会议中食管癌的重要进展。

从中国地质学会创立看青年的作为

本文简要回顾了中国地质学会成立的过程,分析了学会成立背景中青年的作用,从制度的建立、奖项设置、组织建设、学术活动上等方面梳理了学会百年历程中对青年会员工作的重视,提出传承优良传统,坚定地质文化自信,丰富并开拓新的服务方式,凝聚广大地质青年,发挥青年会员在学会服务地质科学和经济社会发展中的作用。

“研究翻译话翻译”对话录

20世纪缘起的翻译标准大讨论方兴未艾。在新的历史发展时期,由于翻译研究的多元化和有关评价体系的变化,翻译实践这一经典问题有了重新讨论和阐释的必要。翻译实践在译学界的地位和功能是什么?翻译专业学生培养如何与社会需求有效对接?为此,周领顺教授、孟祥春教授、冯全功教授、任东升教授、李正栓教授和王理行编审以“翻译实践之史”“翻译实践之理”“翻译实践之功”“翻译实践之练”“翻译实践之趣”和“翻译实践之需”为主题发表了真知灼见,以期对译学界学者的翻译研究以及现阶段翻译专业硕士和未来翻译专业博士的培养发挥积极的指导或借鉴作用。