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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

AN EMPIRICAL RESEARCH ON NETWORK-BASED TEACHING APPROACH AND ITS EFFECTS

This is an empirical research on network-based teaching approach. By adopting the theory of autonomy, we redesigned the class arrangement. After the research was carried out for three months, a questionnaire was designed to learn of the student's attitude change towards the learning of English. The results show that over 80% of the students agree with the network-based teaching approach. They especially like the teaching of listening and speaking. Students have a stronger motivation than before and are more interested in learning English. We also analyzed the students' CET4 scores, and found the experimental group made more progress than the control group. All these are of great value to our further research.

A CASE STUDY OF NETWORK-BASED LANGUAGE TEACHING IN EFL WRITING

The purpose of this paper is to survey the effectiveness of Network-based language teaching (NBLT) in EFL writing. One comparative experiment has been conducted between NBLT method of teaching writing and traditional face-to-face way of teaching writing. The post-test outcomes gathered from the two groups were analyzed using SPSS statistical software package, which demonstrated the advantages of students' writing competency in a networked teaching environment over that of students in a traditional teaching environment. These findings of the research have led the author to the conclusion that NBLT might be encouraged in future language teaching.

Network-based reconfiguration routes for a self-reconfigurable robot

This paper presents a network-based analysis approach for the reconfiguration problem of a self-reconfigurable robot. The self-reconfigurable modular robot named ＂AMOEBA-I＂ has nine kinds of non-isomorphic configurations that consist of a configuration network. Each configuration of the robot is defined to be a node in the weighted and directed configuration network. The transformation from one configuration to another is represented by a directed path with nonnegative weight. Graph theory is applied in the reconfiguration analysis, where reconfiguration route, reconfigurable matrix and route matrix are defined according to the topological information of these configurations. Algorithms in graph theory have been used in enumerating the available reconfiguration routes and deciding the best reconfiguration route. Numerical analysis and experimental simulation results prove the validity of the approach proposed in this paper. And it is potentially suitable for other self-reconfigurable robots＇ configuration control and reconfiguration planning.

COMPLEXITY ANALYSIS OF NETWORK-BASED DYNAMICAL SYSTEMS

This paper investigates the nonlinear dynamics of network-based dynamical systems where network communication channels of finite data rates are inserted into the closed loops of the control systems. The authors analyze the bifurcation and chaotic behavior of the non-smooth dynamical systems. The authors first prove that for almost all system parameters there are no periodic orbits. This result distinguishes this type of non-smooth dynamical systems from many others exhibiting border-collision bifurcations. Next, the authors show analytically that the chaotic sets are separated from the region containing the line segment of all fixed points with a finite distance. Finally, the authors employ a simple model to highlight that both the number of clients sharing a common network channel and fluctuations in the available network bandwidth have significant influence on the performance of such dynamical systems.

CAD/CAM for scalable nanomanufacturing:A network-based system for hybrid 3D printing

Micro-and nano-structuring have been highlighted over several decades in both science and engineering fields.In addition to continuous efforts in fabrication techniques,investigations in scalable nanomanufacturing have been pursued to achieve reduced feature size,fewer constraints in terms of materials and dimensional complexity,as well as improved process throughput.In this study,based on recent micro-/nanoscale fabrication processes,characteristics and key requirements for computer-aided design and manufacturing(CAD/CAM)systems for scalable nanomanufacturing were investigated.Requirements include a process knowledge database,standardized processing,active communication,adaptive interpolation,a consistent coordinate system,and management of peripheral devices.For scalable nanomanufacturing,it is important to consider the flexibility and expandability of each process,because hybrid and bridging processes represent effective ways to expand process capabilities.As an example,we describe a novel CAD/CAM system for hybrid three-dimensional(3D)printing at the nanoscale.This novel hybrid process was developed by bridging aerodynamically focused nanoparticle printing,focused ion beam milling,micromachining,and spincoating processes.The system developed can print a full 3D structure using various inorganic materials,with a minimum process scale of 50 nm.The most obvious difference versus CAD/CAM at‘conventional’scales is that our system was developed based on a network to promote communication between users and process operators.With the network-based system,it is also possible to narrow the gap among different processes/resources.We anticipate that this approach can contribute to the development of CAD/CAM for scalable nanomanufacturing and a wide range of hybrid processes.

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

Gastric cancer(GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development;therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.