Development and interpretation of ISO 13205:2024,Marine technology-Seawater desalination-Vocabulary

Vocabulary is the most basic subject of standardization.Despite that individual terms related to seawater desalination have been mentioned in some standards and technical documents of ISO,WHO,and ASTM,the inconsistent expression might still induce ambiguity in communications among the participators in this area.Moreover,terms in these documents are not comprehensive.Consequently,ISO 13205:2024 is developed to eliminate the misunderstanding in both the academic and commercial communications.This paper expounds on the specific progress of the research in three aspects:background,drafting of ISO 13205:2024,and interpretation of ISO 13205:2024.The significance of the standard is also discussed.

Training Low-Achiever EFL Learners with Metacognitive Strategy Training for Effective Vocabulary Retention

There is ample research on the vocabulary learning strategies used by EFL and ESL learners.Moreover,many researchers have attempted to discern the effectiveness of teaching vocabulary learning strategies instruction.However,the impact of using metacognitive strategies along with vocabulary learning strategies on weak language learners has not been researched.The aim of this paper is to report on the effects of training low-achiever English as a foreign language learners with vocabulary learning strategies along with metacognitive strategies on vocabulary acquisition.Two B1 level groups of students were assigned as treatment and control groups at a university in Istanbul,Turkey.A Vocabulary Strategy Use Survey was given to identify the vocabulary strategy use of the subjects at the outset of the study.The treatment group was trained on vocabulary learning strategies combined with metacognitive strategy training.The control group studied the same words without any training.A vocabulary test was administered to both groups as a post-test and the results were compared.The findings of the Post-Test demonstrated that training weak language learners with vocabulary learning strategies along with metacognitive strategies has a positive impact on helping these learners increase their lexical knowledge,as the experimental group scored higher on the post-test compared to the control group.

通用学术词表Academic Vocabulary List(AVL)修订述略

学术英语词汇是学术英语教学的重点和难点,不同时代和学科曾编写过各类学术词表。加德纳和戴维斯(2014)基于学术语料容量达1.2亿的COCA语料库推出学术词表Academic Vocabulary List(AVL),该词表在学术英语教学和研究中得到广泛应用。然而实践表明,AVL词表收录的3015个词元存在词汇重复、以词元为单位排列的词表和以词族为单位排列的词表不相吻合等问题。本研究尝试以科学性原则、适切性原则、时效性原则为指导,基于AVL词表原有的比率、分布、离散度、学科指数四条选词标准,增加最低频次和经验判断两条新标准对AVL词表予以完善和修订。完善修订后的AVL词表由先前的1991个词族、3015个词元缩减至709个词族1715个词元,较修订前更具简洁性和高效性。希望依据3项原则和6项标准所做的修订为学术英语教与学以及学术英语教材编写和选用带来新的参考。

A Study of the Use and Translation of Archaic Functional Vocabulary in the Berne Convention

The archaic functional vocabulary is highly with the legal features of formality and conservativeness and still holding a place in legal English.The Berne Convention is a good example to study the use and translation of the archaic functional vocabulary.By studying what archaic functional words or phrases are used in the Berne Convention,their meanings and the different use frequencies of them between the Berne Convention and the Copy Right Law of PRC,it has been found that arhcaic adverbs are used of low frequency,while some adjectives or adjectival groups as well as some prepositions or prepositional phrases are used of high frequencies.The use frequencies of the archaic functional vocabulary is higher in the Berne Convention than those in the Copy Right law of PRC.Some suggestions can be put forward to help improve translating Chinese legal documents into English or writing English legal documents.

A Study on Effective Methods of English Vocabulary Learning

English is a key subject in high school that troubles many students,especially in the aspect of vocabulary learning.Only by laying a good vocabulary foundation can students better complete the learning tasks such as reading,writing,listening,and speaking training.This paper aims to explain the importance of improving the efficiency of English vocabulary learning and discuss the effective methods of English vocabulary learning in high school,in order to help more students find their own learning methods,improve vocabulary memory and application skills,and lay a solid foundation for follow-up learning,examination,and even work.

An Experimental Study of Network-based Language Learning in Less-developed Areas

The advent of the Age of Information brings about bright prospects to Network-based Language Learning(NBLL).The thesis adopts the Engagement Theory as guided principles.The purpose is to use the novel NBLL model effectively with the help of modern technology especially in less-developed areas.This thesis focuses on network-based experimental study.The research shows that the students under NBLL environment have cultivated the capabilities in information collection,computer operation,and information evaluation,as well as the abilities in problem solving,reasoning with criticism,and cooperating with others.

A Network-Based VPN Architecture Using Virtual Routing

A network-based Virtual Private Network (VPN) architecture by using fundamental routing mechanism is proposed. This network is a virtual overlay network based on the relay of IP-in-IP tunneling of virtual routing modules. The packet format employs the encapsulation of IPSec ESP(Encapsulating Security Payload), an impact path code and an extended DS(Differentiated Services) code to support multi-path routing and QoS. Comparing with other models of VPN, this network system can be deployed in the current network with little investment, and it is easy to implement. The simulation result shows its performance is better than the traditional VPN system of black box mode.

A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model

An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.

Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

Predictive Tracking Control of Network-Based Agents With Communication Delays

This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network. Furthermore, the problem of consecutive data loss in the feedback channel is solved using aforementioned controller, where lateral movement perturbations are introduced.Simulations and experiments are provided for several cases,which verify the realizability and effectiveness of the proposed controller.

Parallel Neural Network-Based Motion Controller for Autonomous Underwater Vehicles

A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.

Probe on Network-based Collaborative Maintenance Model for After-sales Equipment

In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.

Design and implementation of self-protection agent for network-based intrusion detection system

Static secure techniques, such as firewall, hierarchy filtering, distributed disposing,layer management, autonomy agent, secure communication, were introduced in distributed intrusion detection. The self-protection agents were designed, which have the distributed architecture,cooperate with the agents in intrusion detection in a loose-coupled manner, protect the security of intrusion detection system, and respond to the intrusion actively. A prototype self-protection agent was implemented by using the packet filter in operation system kernel. The results show that all the hosts with the part of network-based intrusion detection system and the whole intrusion detection system are invisible from the outside and network scanning, and cannot apperceive the existence of network-based intrusion detection system. The communication between every part is secure. In the low layer, the packet streams are controlled to avoid the buffer leaks exist ing in some system service process and back-door programs, so as to prevent users from misusing and vicious attack like Trojan Horse effectively.

Where Have Network-based Self-learning Classes Gone?——Reflections & Expectations on the Employment of Network-based Self-learning Classes

To respond to the further development of college English reforms,many universities employed network-based selflearning classes to aid the traditional classroom teaching,especially in teaching listening,but as time went by,some universities gradually gave them up.The paper intends to reflect on the employment of network-based self-learning listening classes,analyz ing the learning with and without its aid,and meanwhile introduce the need to re-employ it,and discuss how we can improve the network-based self-learning classes to help with students' listening.

State feedback control of network-based systems with packet disordering

A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network-based systems with packet disordering, is constructed. Different from the existing models of network-based systems, the number of delay items is time-varying in the model proposed. Further, this model is converted into a parameter-uncertain discrete-time system with time-varying delay item numbers in terms of matrix theory. Moreover, the less conservative stability condition is obtained by avoiding utilisation of Moon et al.’ inequality and bounding inequalities for quadratic functional terms. By solving a minization problem based on linear matrix inequalities, the state feedback controller is presented. A numerical example is given to illustrate the effectiveness of the proposed method.

Error code analysis and selection principle of M-ary modulation in network-based control systems

Error codes induced by M-ary modulation and modulation selection in network-based control systems are studied.It is the first time the issue of error codes induced by M-ary modulation is addressed in control field.In network-based control systems,error codes induced by noisy channel can significantly decrease the quality of control.To solve this problem,the network-based control system with delay and noisy channel is firstly modeled as an asynchronous dynamic system(ADS).Secondly,conditions of packet with error codes(PEC)loss rate by using M-ary modulation are obtained based on dynamic output feedback scheme.Thirdly,more importantly,the selection principle of M-ary modulation is proposed according to the measured signal-to-noise ratio(SNR)and conditions of PEC loss rate.Finally,system stability is analyzed and controller is designed through Lyapunov function and linear matrix inequality(LMI)scheme,and numerical simulations are made to demonstrate the effectiveness of the proposed scheme.

Language Learning Strategies in a Network-based Environment

With the swift development of network technology, research on how to integrate network technology into language learning has become a trend. This paper examines whether the application of language learning strategy(LLS) in the networkbased environment has incomparable superiority. Beginning with the literature review, it presents an analysis on similarities and differences between network-based language learning strategy(NBLLS) and non-NBLLS, and then expounds the characteristics,the influencing factors and teachers' role of NBLLS. Taking 25 participants in the group of non-NBLL and 34 in the NBLL group as the comparative survey study, the empirical result shows the new evidence that there is a little difference between the two groups in the use of LLS. The findings of this study have implications for the application of NBLLS.

College English Teachers’ Beliefs on Network-based Language Learning

The advantages and disadvantages for learning English in the Network-based environment attract most researchers’concern nowadays.This study profiles college English teachers’beliefs about the networkbased language learning.The main finding is that teachers’beliefs about network-based language learning are heterogeneous and thus reflect a wide range in terms of the evolution of approaches and technology use.

Re-Exploring Biomarkers and Therapeutic Targets in Primary Melanoma Patients: Insights from Network-Based Analysis of Microarray Data

Objective To identify novel biomarkers and therapeutic targets for primary melanoma using network-based microarray data analysis.Methods Eligible microarray datasets from the Gene Expression Omnibus(GEO)database were used to identify differentially expressed genes(DEGs).The protein-protein interaction(PPI)network,Gene Ontology(GO),and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed to identify hub genes and pathways that might affect the survival of melanoma patients.Immunohistochemistry results obtained from the Human Protein Atlas(HPA)database confirmed the protein expression levels of hub genes.The Cancer Genome Atlas(TCGA)database was used to further verify the gene expression levels and conduct survival analysis.Results Three microarray datasets(GSE3189,GSE15605,and GSE46517)containing 122 melanoma and 30 normal skin tissue samples were included.A total of 262 common differentially expressed genes(cDEGs)were identified based on three statistical approaches(Fisher’s method,the random effects model(REM),and vote counting)with strict criteria.Of these,two upregulated genes,centromere protein F(CENPF)and pituitary tumortransforming gene 1(PTTG1),were selected as hub genes.HPA and TCGA database analyses confirmed that CENPF and PTTG1 were overexpressed in melanoma.Survival analysis showed that high expression levels of CENPF were significantly correlated with decreased overall survival(OS)(P=0.028).Conclusion The expression level of CENPF was significantly upregulated in melanoma and correlated with decreased OS.Thus,CENPF may represent a novel biomarker and therapeutic target for melanoma patients.

A Quasi-Experimental Study of English Vocabulary Teaching Based on Incidental Acquisition

Recent years have witnessed a phenomenon that major English teachers in China have adopted the traditional teaching pattern, mechanically linking English pronunciations directly with the meaning of Chinese, which gradually dampens learners’ enthusiasm. The chief purpose of this paper was to design one English vocabulary teaching lesson based on incidental acquisition. More specifically, the questions raised are, on the one hand, whether incidental vocabulary teaching imprints differences on the learning outcomes for middle school students, and, on the other hand, whether incidental acquisition results in positive feedback between teachers and students. The technique we applied was referred to as questionnaires and interviews addressed to a sample of 68 students. Focusing on the effect of incidental vocabulary acquisition, the analysis demonstrated that it could enhance students’ vocabulary capacity. In addition, it was interesting to note that excellent students and average students tended to embrace the new teaching style while underachievers were on the opposite side. On this basis, it is recommended for English teachers to design English vocabulary lessons, adopting visual, auditory, oral, reading or writing training. More precisely, they should use phonics rules and patterns, holistic learning, classified vocabulary teaching, visual illustration or multimedia teaching to give lessons effectively and expand learners’ vocabulary.