Leveraging Uncertainty for Depth-Aware Hierarchical Text Classification

Hierarchical Text Classification(HTC)aims to match text to hierarchical labels.Existing methods overlook two critical issues:first,some texts cannot be fully matched to leaf node labels and need to be classified to the correct parent node instead of treating leaf nodes as the final classification target.Second,error propagation occurs when a misclassification at a parent node propagates down the hierarchy,ultimately leading to inaccurate predictions at the leaf nodes.To address these limitations,we propose an uncertainty-guided HTC depth-aware model called DepthMatch.Specifically,we design an early stopping strategy with uncertainty to identify incomplete matching between text and labels,classifying them into the corresponding parent node labels.This approach allows us to dynamically determine the classification depth by leveraging evidence to quantify and accumulate uncertainty.Experimental results show that the proposed DepthMatch outperforms recent strong baselines on four commonly used public datasets:WOS(Web of Science),RCV1-V2(Reuters Corpus Volume I),AAPD(Arxiv Academic Paper Dataset),and BGC.Notably,on the BGC dataset,it improvesMicro-F1 andMacro-F1 scores by at least 1.09%and 1.74%,respectively.

New Solution Generation Strategy to Improve Brain Storm Optimization Algorithm for Classification

As a new intelligent optimization method,brain storm optimization(BSO)algorithm has been widely concerned for its advantages in solving classical optimization problems.Recently,an evolutionary classification optimization model based on BSO algorithm has been proposed,which proves its effectiveness in solving the classification problem.However,BSO algorithm also has defects.For example,large-scale datasets make the structure of the model complex,which affects its classification performance.In addition,in the process of optimization,the information of the dominant solution cannot be well preserved in BSO,which leads to its limitations in classification performance.Moreover,its generation strategy is inefficient in solving a variety of complex practical problems.Therefore,we briefly introduce the optimization model structure by feature selection.Besides,this paper retains the brainstorming process of BSO algorithm,and embeds the new generation strategy into BSO algorithm.Through the three generation methods of global optimal,local optimal and nearest neighbor,we can better retain the information of the dominant solution and improve the search efficiency.To verify the performance of the proposed generation strategy in solving the classification problem,twelve datasets are used in experiment.Experimental results show that the new generation strategy can improve the performance of BSO algorithm in solving classification problems.

Hybrid Support Vector Machines-Based Multi-fault Classification

Support Vector Machines （SVM） is a new general machine-learning tool based on structural risk minimization principle. This characteristic is very signific ant for the fault diagnostics when the number of fault samples is limited. Considering that SVM theory is originally designed for a two-class classification, a hybrid SVM scheme is proposed for multi-fault classification of rotating machinery in our paper. Two SVM strategies, 1-v-1 （one versus one） and 1-v-r （one versus rest）, are respectively adopted at different classification levels. At the parallel classification level, using l-v-1 strategy, the fault features extracted by various signal analysis methods are transferred into the multiple parallel SVM and the local classification results are obtained. At the serial classification level, these local results values are fused by one serial SVM based on 1-v-r strategy. The hybrid SVM scheme introduced in our paper not only generalizes the performance of signal binary SVMs but improves the precision and reliability of the fault classification results. The actually testing results show the availability suitability of this new method.

Balance between education and game-play— A case study of design and optimization of the mini-game book classification

Purpose： Based on our experience of designing and testing a computer-based game for teaching undergraduate students information literacy （IL） concepts and skills, this paper summarizes the basic strategies for striking a balance between education and entertainment for the designers of quality IL games. Design/methodology/approach： The project team recruited 10 college students to play the game and post-game group interviews revealed problems and optimization priorities. The optimized game was tested among 50 college students. Based on a comparison of testing results of the two versions of the game, basic strategies for designing quality 1L games were summarized. Findings： The following 5 basic strategies can effectively promote combination of education and entertainment： l） using adventure games to enhance gaming experience, 2） plotting an intriguing story to attract players, 3） motivating players to engage in game play with game components such as challenge, curiosity, fantasy and control, 4） presenting learning materials through game props, and 5） assigning players tasks to be completed with subject knowledge. Research limitations： The 5 basic strategies have been tested only in the development process of one game, and the book classification knowledge in the mini-game is limited to the 22 major categories of the Chinese Library Classification. Practical implications： University libraries may refer to our experience to design and utilize educational games to promote the IL education for college students. Originality value： Few empirical studies tested and summarized strategies for combining learning and fun in the design of IL games for university students. The 5 strategies, which are summarized in the process of design and optimization of the mini-game book classification, are valuable for other designers of IL games.

A Synthesis of the Studies on Vocabulary Learning Strategies in ESL and EFL Learning

Vocabulary is the core of language learning.The efficiency of vocabulary learning may influence language learning outcome.Vocabulary learning strategies can help the learners to learn vocabulary more efficiently,and they are very useful and beneficial for language learners.This paper synthesizes the research on vocabulary learning strategies in ESL and EFL learning,including the studies on the definitions of vocabulary learning strategies,classifications of vocabulary learning strategies and previous main research areas.The previous research areas mainly involve in the following aspects:patterns and taxonomies of vocabulary learning strategies,gender difference and vocabulary learning strategies,language proficiency and vocabulary learning strategies,major or disciplinary difference and vocabulary learning strategies,vocabulary learning strategies used frequently and effectively,vocabulary learning strategies and learning outcomes,and vocabulary learning strategy training.

Major Challenges of Language Learning Strategy Research

The research of language learning strategies(LLSs) plays a significant role in language instruction, especially in learning strategy instruction, but the challenges have been identified along with researchers' enthusiasm in the research of LLSs. The serious challenges are reviewed from the perspectives of the conceptualization, the classification systems, and the identification and measurement of LLSs in this paper.

A Study of learning Strategies in Second language Acquisition

With the concept of autonomic learning being part of the mainstream of research and practice with the field of language education,the study of learning strategies has been an "explosion of activity" in recent years.This paper discusses the issues covering the fundamental aspects identification and classification of learning strategies,and some inspirations to both teachers and students.

Surgical strategies for Mirizzi syndrome:A ten-year single center experience

BACKGROUND Mirizzi syndrome(MS)remains a challenging biliary disease,and its low rate of preoperative diagnosis should be resolved.Moreover,technological advances have not resulted in decisive improvements in the surgical treatment of MS.Complex bile duct lesions due to MS make surgery difficult,especially when the laparoscopic approach is adopted.The safety and long-term effect of MS treatment need to be guaranteed in terms of preoperative diagnosis and surgical strategy.AIM To analyze preoperative diagnostic methods and the safety,effectiveness,prognosis and related factors of surgical strategies for different types of MS.METHODS The clinical data of MS patients who received surgical treatment from January 1,2010 to December 31,2020 were retrospectively reviewed.Patients with malignancies,choledochojejunal fistula,lack of data and lost to follow-up were excluded.According to preoperative imaging examination records and documented intraoperative findings,the clinical types of MS were determined using the Csendes classification.The safety,effectiveness and long-term prognosis of surgical treatment in different types of MS,and their interactions with the clinical characteristics of patients were summarized.RESULTS Sixty-six patients with MS were included(34 males and 32 females).Magnetic resonance imaging/magnetic resonance cholangiopancreatography(MRI/MRCP)showed specific imaging features of MS in 58 cases(87.9%),which was superior to ultrasound scan(USS)in the diagnosis of MS and more sensitive to subtle biliary lesions than USS.The overall laparoscopic surgery completion rate was 53.03%(35/66),where the completion rates of MS type I,II and III were 69.05%(29/42),42.86%(6/14)and zero(0/10),respectively.Thirty-one patients(46.97%)underwent laparotomy or conversion to laparotomy including 11 cases of iatrogenic bile duct injury which occurred in type I patients,and 25 of these patients underwent bile duct exploration,repair and T-tube drainage.In addition,25 patients underwent intraoperative choledochoscopy and T-tube cholangiography.Overall,21 cases(31.8%)were repaired by simple suturing,and 14 cases(21.2%)were repaired using the remaining gallbladder wall patch in the subtotal cholecystectomy.The ascendant of the Csendes classification types led to an increase in surgical complexity reflected by increased operation time,bleeding volume and cost.Gender,acute abdominal pain and measurable stone size had no effect on Csendes type of MS or final surgical approach.Age had no effect on the classification of MS,but it influenced the final surgical approach,hospital stay and cost.A total of 66 patients obtained a relatively high preoperative diagnostic rate and underwent surgery safely without serious complications,and no mortality was observed during the follow-up period of 36.5±26.5 mo(range 13-76,median 22 mo).CONCLUSION MRI/MRCP can improve the preoperative diagnosis of MS.The Csendes classification can reflect the difficulty of treatment.The surgical strategies including laparoscopic surgery for MS should be formulated based on full evaluation and selection.

A Comparison Between Male and Female in Their Willingness to Communicate and Use of Socio-cognitive Strategies

Willingness to communicate illustrates anyone’s tendency and wish to commence a communication.Besides,socio-cognitive strategies are used when people want to interact with others and face some difficulties.The aim of this study was twofold.The first aim was to investigate the difference in willingness to communicate between Iranian male and female.The second aim was to distinguish the frequency of socio-cognitive strategies used by Iranian advance students based on their gender.To these ends,32 advance learners(16 males and 16 females)were given the willingness to communicate questionnaire developed by MacIntyre,Baker,Clément,and Conrod(2001)and the socio-cognitive strategy use questionnaire.The range of the participants’age was 17-23 in both males and females.To analyze the result of the socio-cognitive strategies use,frequencies were counted.The result showed that although there were some similarities and differences between males and females while using socio-cognitive strategies,the differences were more in social strategies than cognitive ones.After collecting the data from the questionnaires and calculating the means of the two groups,an independent sample T-test was run to compute the significant differences between the two groups.The result of the willingness to communicate questionnaire revealed that males had more tendency in communication than females.Also,the result of the socio-cognitive strategy questionnaire showed that both groups are similar in cognitive strategy use,but they are different in social strategy use.

Global Strategies to Combat Antimicrobial Resistance: A One Health Perspective

Background: Antimicrobial resistance (AMR) is a global health challenge that has escalated due to the inappropriate use of antimicrobials in humans, animals, and the environment. Developing and implementing strategies to reduce and combat AMR is critical. Purpose: This study aimed to highlight some global strategies that can be implemented to address AMR using a One Health approach. Methods: This study employed a narrative review design that included studies published from January 2002 to July 2023. The study searched for literature on AMR and antimicrobial stewardship (AMS) in PubMed and Google Scholar using the 2020 PRISMA guidelines. Results: This study reveals that AMR remains a significant global public health problem. Its severity has been markedly exacerbated by inappropriate use of antimicrobials in humans, animals, and the broader ecological environment. Several strategies have been developed to address AMR, including the Global Action Plan (GAP), National Action Plans (NAPs), AMS programs, and implementation of the AWaRe classification of antimicrobials. These strategies also involve strengthening surveillance of antimicrobial consumption and resistance, encouraging the development of new antimicrobials, and enhancing regulations around antimicrobial prescribing, dispensing, and usage. Additional measures include promoting global partnerships, combating substandard and falsified antimicrobials, advocating for vaccinations, sanitation, hygiene and biosecurity, as well as exploring alternatives to antimicrobials. However, the implementation of these strategies faces various challenges. These challenges include low awareness and knowledge of AMR, a shortage of human resources and capacity building for AMR and AMS, in adequate funding for AMR and AMS initiatives, limited laboratory capacities for surveillance, behavioural change issues, and ineffective leadership and multidisciplinary teams. Conclusion: In conclusion, this study established that AMR is prevalent among humans, animals, and the environment. Successfully addressing AMR calls for a collaborative, multifaceted One Health approach. Despite this, some gaps remain effectively implementing strategies currently recommended to combat AMR. As a result, it is essential to reinforce the strategies that are deployed to counter AMR across the human, animal, and environmental sectors.

The Study of Language Learning Strategies of Non-English Majors

This paper, from the educational and psychological point of view, explores EFL college students＇ language learning strategies in the Chinese context. The subjects under study involve 106 non-English majors from Hohai University at its Changzhou Campus. The approach is used for the research through two questionnaires to investigate the learners＇ language learning strategies. In the study, it is found that students use compensation strategies most frequently, while metacognitive strategies less and social strategies the least. Findings of the present study also indicate that the different strategies are respectively emphasized for the male and female students, students of arts and science and engineering.

A comparison of mapping strategies from DDC to CLC

Purpose: This study aims to discuss the strategies for mapping from Dewey Decimal Classification(DDC) numbers to Chinese Library Classification(CLC) numbers based on co-occurrence mapping while minimizing manual intervention.Design/methodology/approach: Several statistical tables were created based on frequency counts of the mapping relations with samples of USMARC records,which contain both DDC and CLC numbers. A manual table was created through direct mapping. In order to find reasonable mapping strategies,the mapping results were compared from three aspects including the sample size,the choice between one-to-one and one-to-multiple mapping relations,and the role of a manual mapping table.Findings: Larger sample size provides more DDC numbers in the mapping table. The statistical table including one-to-multiple DDC-CLC relations provides a higher ratio of correct matches than that including only one-to-one relations. The manual mapping table cannot produce a better result than the statistical tables. Therefore,we should make full use of statistical mapping tables and avoid the time-consuming manual mapping as much as possible.Research limitations: All the sample sizes were small. We did not consider DDC editions in our study. One-to-multiple DDC-CLC relations in the records were collected in the mapping table,but how to select one appropriate CLC number in the matching process needs to be further studied.Practical implications: The ratio of correct matches based on the statistical mapping table came up to about 90% by CLC top-level classes and 76% by the second-level classes in our study. The statistical mapping table will be improved to realize the automatic classification of e-resources and shorten the cataloging cycle significantly.Originality/value: The mapping results were investigated from different aspects in order to find suitable mapping strategies from DDC to CLC while minimizing manual intervention.The findings have facilitated the establishment of DDC-CLC mapping system for practical applications.

Application of dynamic programming to structural repairing strategies

A model of dynamic programming for repairing strategies of concrete structures during a projected service period is proposed, which takes into account the degradation in strength of components and the probability of accidental load. This model takes the safety grade of a structural system as the state variable of repairing strategies, and incorporates economic factors including expected repair cost, property loss due to structure failure, goods and material loss due to structure failure, loss of production interrupt due to structure failure, and inspection cost in decision making. It is found that the optimal repairing strategies are sensitive to the probability of accidental loads as well as the failure costs. The practicality of the model is demonstrated by an example.

Treatment Strategy for Post-Hepatectomy Recurrent Hepatocellular Carcinoma: A Single Center Experience with 556 Consecutive Cases in China

Background: Treatment strategy for recurrent hepatocellular carcinoma (HCC) remains scantily defined. This study was aimed to establish a treatment strategy to manage post-hepatectomy recurrent HCC and report the clinical outcomes. Methods: From January 2006 to December 2016, 556 consecutive patients who developed post-hepatectomy HCC recurrence were enrolled in the study. The patients were clinically stratified and treated according to a strategy established by a multi-disciplinary team. Clinical data and survival times were collected prospectively and analyzed retrospectively. Results: According to the strategy, there were 298 (53.6%), 214 (38.5%), 32 (5.7%) and 12 (2.2%) patients stratified into Early, Intermediate, Advanced and Terminal stages, respectively. In Early stage patients, 164 (55.0%) received curative treatment in the form of repeat resection or local ablation, 134 (45.0%) received transarterial chemoembolization (TACE), and the 1-, 3-, and 5-year overall survival (OS) rates were 82.0%, 46.8% and 37.3%, respectively. In Intermediate stage patients, 207 (96.7%) received TACE, 7 (3.3%) radiotherapy, and the 1-, 3-, and 5-year OS rates were 73.2%, 31.8% and 15.9%, respectively. In Advanced stage patients, 22 patients received sorafenib, 10 radiotherapy, and the mean survival time (MST) was 25.1 ± 3.1 months. All the 12 patients in Terminal stage received the best supportive treatment, and the MST was 6.5 ± 3.4 months. Clinical stages and duration of disease-free interval were independent factors relating to overall survival. Conclusions: A treatment strategy derived from the Barcelona Clinic Liver Cancer staging system, with some modifications, has been successfully established to manage post-hepatectomy recurrent HCC, and the clinical outcomes were commendable.

多区域注意力的细粒度图像分类网络

目前细粒度图像分类的难点在于如何精准定位图像中高度可辨的局部区域以及其他辅助判别特征。提出一种多区域注意力的细粒度图像分类网络来解决这个问题。首先使用Inception-V3对图像特征进行提取,通过重复使用注意力擦除的方法使模型关注次要特征;然后通过背景去除以及上采样的方法获取图像更精准的局部图像,对提取到的局部特征进行位置统计,并以矩形框的方式获取图像整体,减少细节信息丢失;最后对局部与整体图像进行更加细致的学习。此外,设计联合损失函数,通过动态平衡难易样本和缩小类内差距的方法改善模型的识别效果。实验结果表明,该方法在公开的细粒度图像数据集CUB-200-2011、Stanford-Cars和FGVC-Aircraft上的准确率分别达到89.2%、94.8%、94.0%,相较于对比方法性能更优。

Surgical strategies for peripheral nerve schwannoma based on the intraoperative neurophysiological monitoring

Objective:To present our classification for peripheral nerve schwannomas as well as explore the surgical strategies and operative management of peripheral nerve schwannomas based on the intraoperative neurophysiological monitoring(INM)technique and to decrease the risk of postoperative neurological deficits in the management of these schwannomas.Materials and methods:A retrospective study was conducted on 92 cases of peripheral nerve microsurgery performed,using the INM technique.We also made the classification for peripheral nerve schwannomas into two types according to operative findings and proceeded corresponding surgical strategies.Results:All tumors were removed completely under microscopy and INM.Three patients developed residual neurological deficits at final follow-up.There were different results about temporary(18/92,19.6%)and permanent(3/92,3.3%)neurological deficits.The incidence of temporary and permanent neurological deficits in type II group was significantly higher than that in type I group(p<0.01).The incidence of permanent neurological deficits in larger size tumors was significantly higher than that of smaller size(p<0.01).Conclusions:We made the classification for peripheral nerve schwannomas according to operative findings based on INM that is helpful to our surgical strategies.Intracapsular enucleation was the preferred strategy with satisfactory results and low risk of nerve injury.The size and location of tumors seem to be related to the risk of fascicular injury.

风险动物园(Ⅶ):灰犀牛风险分类体系、演化机制与管控策略

作为风险管理领域的新兴概念和隐喻理论的重要组成部分,风险动物园中灰犀牛的本质属性和风险特征被广泛研究和应用。为防范化解新时代的风险挑战,加强灰犀牛相关研究的系统梳理和内涵挖掘,通过融合现有理论模型和借鉴风险分类方法,开展灰犀牛风险的类型体系构建、演化机制探析与管控策略研究。结果表明:灰犀牛风险作为客观环境因素和主观认知影响交互作用下的产物,按照特征维、认知维和状态维以及时间视角、空间视角和主体视角,把灰犀牛风险划分为隐藏灰犀牛、静止灰犀牛和冲撞灰犀牛;根据风险感知、风险距离和风险框架影响因素的作用机制,评估每类灰犀牛风险的发展态势;进而构建复杂系统内“累积—波动—突变”的演化框架,提出风险管控策略,提高认知能力察觉不易感知的隐藏灰犀牛;强化创新思维化解常态共存的静止灰犀牛;打造敏捷模式应对突然爆发的冲撞灰犀牛。

基于承载力—内生力—潜力的湖北省乡镇分类及规划策略研究

因地施策是乡镇级国土空间规划的要求,也是乡镇高质量发展的必然选择。以湖北省为例,以乡镇为基本单元,基于承载力—内生力—潜力分析乡镇发展情况,从区位条件、自然资源、社会经济、设施配套、地方特色5个维度34项指标构建乡镇分类指标体系,利用主客观叠加组合分析法赋值,通过自然间断点分级法进行乡镇发展类型划分。根据乡镇的综合优势和特色优势,将其分为“五型四类”,即城郊服务类、重点发展类、优化提升类、保留改善类以及生态资源型、旅游带动型、现代农业型、工业主导型、均衡发展型,并对各类乡镇的发展特点和空间格局进行对比分析。最后,针对综合分类和特色分类形成组合分类,提出相应的规划策略,为乡镇的分类评价和发展规划提供科学依据。

基于多节点策略的雷达智能干扰调制类型识别技术研究

采用认知雷达架构有助于实现雷达抗干扰技术的智能化程度提升。针对认知抗干扰技术领域中雷达对电磁干扰环境的感知问题,文中提出了一种基于深度学习的多节点干扰调制类型识别方法。该方法针对雷达信号处理的不同节点,如数字波束形成、自适应副瓣对消、脉冲压缩前后以及动目标检测之后,采用多个节点的时频平面和距离多普勒平面作为干扰信号的联合特征提取对象,建立了基于深度学习的多节点干扰识别策略模型,以提高多种干扰场景下的干扰识别正确率。为了提升干扰特征的提取能力和网络的训练效率,将用于干扰识别的深度学习算法在卷积神经网络的基础上引入了注意力机制和残差网络,建立了针对多节点策略下的干扰类型识别网络结构,实现了对多种不同干扰场景下的干扰类型识别。仿真结果表明:在单一干扰场景下,当干噪比为14 dB时,所提算法的干扰识别准确率可达92%;在多干扰场景下,所提算法在不同节点策略的加持下,识别准确率可达90%。

基于加速骨干二元粒子群优化的样本规约方法

样本规约方法是统计机器学习中的杰出数据预处理范式,能从有标记训练集中移除冗余样本和噪声,从而提升分类统计算法的性能。虽然学者们提出了大量基于进化算法的样本规约方法,并证明了其有效性,但是现有基于进化算法的样本规约方法依赖太多参数。而且随着有标记训练集中的样本数量增加,现有基于进化算法的样本规约方法的搜索效率较低且时间成本较高。为了克服上述问题,文章提出一种基于加速骨干二元粒子群优化的样本规约方法(SRM-HBPSO)。在SRM-HBPSO中,首先,设计了一种结合搜索空间约简策略的加速骨干二元粒子群优化算法(HBPSO);其次,用HBPSO优化有标记训练集,从而得到一个被优化的约简子集;最后,SRM-HBPSO在被优化的约简子集上训练给定的分类统计算法,从而改进其性能。经仿真实验证明,就改进随机森林分类统计算法的平均分类正确率和提升平均样本约简率而言,在来自金融、医疗、图像等领域的10个真实基准数据集上,SRM-HBPSO优于5个先进的样本规约算法。