Application of Multimedia and Internet Technology in Learning Mould Design

With the use of multimedia which combines the use o f text, sound, images, motion video and animation, it is more efficient for studen ts to learn mould design interactively. A program is created using several multi media software to simulate the mechanism of moulding processes in order to let s tudents understand the concept of mould design. In addition, students can even access the program through the Internet. Therefore, the software is defined as Multimedia and Internet Technology (MIT) program. The MIT program consists of four sections: (i) simulation of mould mechanisms, ( ii) cooling system, (iii) material information and (iv) games for tutorials. Sec tion One covers the basic operations of different types of moulds such as two-p late mould, three-plate mould, split mould, side-core mould and mould with und ercuts. Section Two introduces different types of cooling systems such as bubble r, baffle, cooling circuits, etc. Section Three provides some useful material in formation for mould design. Section Four contains games of matching mould compon ents, mould design problem finding and multiple choice questions to test student s how much they understand mould design concept. Multimedia is highly effective particularly in teaching and learning. It changes the nature of learning itself. It makes reading dynamic by giving words an impo rtant new dimension. It allows students to see, hear and do simultaneously, thus significantly reducing average learning time. Furthermore, through cooperative learning on Internet, students can access the program, share data or search info rmation anytime anywhere. Therefore, Multimedia and Internet Technology is one o f the vital aspects to speed up the realization of information age in society.

Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images

Mobile technology is developing significantly.Mobile phone technologies have been integrated into the healthcare industry to help medical practitioners.Typically,computer vision models focus on image detection and classification issues.MobileNetV2 is a computer vision model that performs well on mobile devices,but it requires cloud services to process biometric image information and provide predictions to users.This leads to increased latency.Processing biometrics image datasets on mobile devices will make the prediction faster,but mobiles are resource-restricted devices in terms of storage,power,and computational speed.Hence,a model that is small in size,efficient,and has good prediction quality for biometrics image classification problems is required.Quantizing pre-trained CNN(PCNN)MobileNetV2 architecture combined with a Support Vector Machine(SVM)compacts the model representation and reduces the computational cost and memory requirement.This proposed novel approach combines quantized pre-trained CNN(PCNN)MobileNetV2 architecture with a Support Vector Machine(SVM)to represent models efficiently with low computational cost and memory.Our contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches,showing the superiority of deep features from MobileNetV2 and SVM classification models,comparing traditional methods,exploring six ocular diseases and normal classification with 20,111 images postdata augmentation,and reducing the number of trainable models.The model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration(AMD),one of the most common eye illnesses,Cataract,Diabetes,Glaucoma,Hypertension,andMyopia with one class Normal.From the experiment outcomes,it is observed that the suggested MobileNetV2-SVM model size is compressed.The testing accuracy for MobileNetV2-SVM,InceptionV3,and MobileNetV2 is 90.11%,86.88%,and 89.76%respectively while MobileNetV2-SVM,InceptionV3,and MobileNetV2 accuracy are observed to be 92.59%,83.38%,and 90.16%,respectively.The proposed novel technique can be used to classify all biometric medical image datasets on mobile devices.

Design of Quantification Model for Ransom Ware Prevent

The growth of ICT within the society has become increasingly digitized, thus, the overall activity has amounted to various researches for protecting any data from malicious threats. Recently, ransomware has been a rapidly propagated subject for social engineering techniques especially the ransomware. Users can delete a ransomeware code using an antivirus software code. However, the encrypted data would be impossible to recover. Therefore, ransomware must be prevented and must have early detection before it infects any data. In this paper, we are proposing a quantification model to prevent and detect any cryptographic operations in the local drive.

Numerical Simulation of the Motion of A Floating Body with Partially Filled Tanks by A Pressure-Convection Particle Method

The moving particle semi-implicit（MPS）method has demonstrated its usefulness in practical engineering applications.Although it has wide applicability,it is still hard to predict the pressure precisely using the MPS method.A pressure-convection particle method based on the MPS method is proposed to overcome this problem.The improved performance of this new method is validated with computational and measured results.The approach is also applied to compute the problem of sloshing associated with floating body motion in waves.The pressure-convection MPS method demonstrated its capability to improve the prediction of pressure.

Refinement of Enhanced Speech Using Hybrid-Median Filter and Harmonic Regeneration Approach

This study proposes a post-processor to improve the harmonic structure of a vowel in an enhanced speech, enabling the speech quality to be improved. Initially, a speech enhancement algorithm is employed to reduce the background noise for a noisy speech. Hence the enhanced speech is post-processed by a hybrid-median filter to reduce the musical effect of residual noise. Since the harmonic spectra are impacted by background noise and a speech enhancement process, the quality of a vowel is deteriorated. A harmonic regenerated method is developed to improve the quality of post-processed speech. Experimental results show that the proposed method can improve the quality of post-processed speech by adequately regenerating harmonic spectra.

Painlevé Integrability of Nonlinear Schrdinger Equations with both Space-and Time-Dependent Coefficients

We investigate the Painleve integrabiiity of nonautonomous nonlinear Schr6dinger （NLS） equations with both space-and time-dependent dispersion, nonlinearity, and external potentials. The Painleve analysis is carried out without using the Kruskal＇s simplification, which results in more generalized form of inhomogeneous equations. The obtained equations are shown to be reducible to the standard NLS equation by using a point transformation. We also construct the corresponding Lax pair and carry out its Kundu-type reduction to the standard Lax pair. Special cases of equations from choosing limited form of coefficients coincide with the equations from the previous Painleve analyses and/or become unknown new equations.

Improving Computation Efficiency of Source Authentication by Elliptic Curve Cryptosystem

The overload of traditional cryptosystems is too high for real-time applications so there is a need to design a new encryption and signature scheme for the multicast applications. In this paper, we use the elliptic curve cryptosystem to design a source authentication scheme for real-time applications. The proposed scheme uses the message recovery signature to reduce the computation cost. Thus, the proposed source authentication scheme is more suitable for real-time applications, such as online meeting, online movie, and online music.

Qualitative Properties of Solutions of a Doubly Nonlinear Reaction-Diffusion System with a Source

In this paper, we study properties of solutions to doubly nonlinear reaction-diffusion systems with variable density and source. We demonstrate the possibilities of the self-similar approach to studying the qualitative properties of solutions of such reaction-diffusion systems. We also study the finite speed of propagation (FSP) properties of solutions, an asymptotic behavior of the compactly supported solutions and free boundary asymptotic solutions in quick diffusive and critical cases.

Comprehensive Analysis of Caching Performance under Probabilistic Traffic Patterns for Content Centric Networking

The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology.

The Implementation and Evaluation of Training Course for Chinese as Second Language E-Teacher

In this study, we made references to past literatures and developed an e-learning training program for CSL （Chinese as a Second Language） teachers. The class was held from July to August, 2010, in Chinese Culture University （Taiwan）, and we designed a performance-evaluation questionnaire with the Delphi method. Three months after the training program was completed, the questionnaire was given to the 30 students of the class, and they were asked to answer questions regarding their use of e-learning in the actual practice. We also asked 5 teachers to conduct experimental e-learning for us to video-record and observe. This effort allows us to discuss the use of e-learning among CSL teachers in Taiwan, come up with a conclusion and suggestions, and use the findings as references for course-planning and policies or research regarding the digital learning of Chinese.

On the Characteristic of Orthogonality for Multi-Carrier-Based Systems

The dominate factors caused by reasons of losing the orthogonality in fading channel including FBC (fading branch correlation), CFO (carrier frequency offset), and even the CPN (carrier phase noise) are novel discussion in this letter. The first one factor causes the ISI (inter-symbol interference), and, however, the latter two will lead to the phenomenon of CPE (common phase error) and ICI (inter-carrier interference). On the other hand, they will lead to the loss of orthogonality for the radio system with multi-carrier modulating schemes, i.e., both them mainly deteriorate a wireless communication system. Eventually, in this letter not only the analytical expressions are derived, but a three dimension numerical results from the analysis involve the three parameters also illustrated is.

The Immutability of Online Course in Art Education

The signifier and signified of symbol representation in art works can generate and reflect reality.However,it can never produce the absolute truth.This paper mainly discusses the relationship between immutability with arbitrariness,sociality,and continuity in art education,both online and in outline.Overall,it is recommended that practical art teaching should be guided by artistic achievements.In addition,we clarify immutability of network teaching mode in art education,and recommend exploration of conscious,independent and self-discipline modes.

Synthesis,Style Editing,and Animation of 3D Cartoon Face

As a popular kind of stylized face,cartoon faces have rich application scenarios.It is challenging to create personalized 3D cartoon faces directly from 2D real photos.Besides,in order to adapt to more application scenarios,automatic style editing,and animation of cartoon faces is also a crucial problem that is urgently needed to be solved in the industry,but has not yet had a perfect solution.To solve this problem,we first propose“3D face cartoonizer”,which can generate high-quality 3D cartoon faces with texture when fed into 2D facial images.We contribute the first 3D cartoon face hybrid dataset and a new training strategy which first pretrains our network with low-quality triplets in a reconstruction-then-generation manner,and then finetunes it with high-quality triplets in an adversarial manner to fully leverage the hybrid dataset.Besides,we implement style editing for 3D cartoon faces based on k-means,which can be easily achieved without retrain the neural network.In addition,we propose a new cartoon faces'blendshape generation method,and based on this,realize the expression animation of 3D cartoon faces,enabling more practical applications.Our dataset and code will be released for future research.

Access Control Policy Analysis and Access Denial Method for Cloud Services

Personal cloud computing is an emerging trend in the computer industry. For a sustainable service, cloud computing services must control user access. The essential business characteristics of cloud computing are payment status and service level agreement. This work proposes a novel access control method for personal cloud service business. The proposed method sets metadata, policy analysis rules, and access denying rules. Metadata define the structure of access control policies and user requirements for cloud services. The policy analysis rules are used to compare conflicts and redundancies between access control policies. The access denying rules apply policies for inhibiting inappropriate access. The ontology is a theoretical foundation of this method. In this work, ontologies for payment status, access permission, service level, and the cloud provide semantic information needed to execute rules. A scenario of personal data backup cloud service is also provided in this work. This work potentially provides cloud service providers with a convenient method of controlling user access according to changeable business and marketing strategies.

ID-Based User Authentication Scheme for Cloud Computing

In cloud computing environments, user authentication is an important security mechanism because it provides the fundamentals of authentication, authorization, and accounting （AAA）. In 2009, Wang et al. proposed an identity-based （ID-based） authentication scheme to deal with the user login problem for cloud computing. However, Wang et aL＇s scheme is insecure against message alteration and impersonation attacks. Besides, their scheme has large computation costs for cloud users. Therefore, we propose a novel ID-based user authentication scheme to solve the above mentioned problems. The proposed scheme provides anonymity and security for the user who accesses different cloud servers. Compared with the related schemes, the proposed scheme has less computation cost so it is very efficient for cloud computing in practice.

Computer Assisted Language Learning Social Networks: What Are They Talking about?

There are many reasons that motivate people to build online communities. The purpose of this study was to identify the topics that learners discuss when they are part of a computer assisted language learning course in order to answer the question “What are they talking about?”. We have examined an e-community of 618 students who were learning the Modern Greek language online. We analyzed their conversation topics directly from the discussion boards of the web-based course and sorted them into the pre-defined topic categories. The results of the study showed that during the first lessons of the course the students contributed more to social discussions which were unrelated to the course material. The reason of this outcome is that the students want to introduce themselves and meet their peers. As they progressed through the course’s lessons, however, their discussion topics became more course material related. The study ends with implications of the results and future research directions.

Color Image Enhancement by an Integral Mask-filtering Approach Employing Nonlinear Transfer Function

We demonstrate a brand-new method to sharpen a color image by using an integral mask-filtering technique. The derivatives between the target pixel and its neighbors are transferred by the cubic root function instead of the traditional linear one. The obtained final image has clearer fine characteristics along with much less overshooting.

Solving Dynamic Spectrum Management Problem Based on Cloud Computing Using Genetic Algorithm

With the rapid development of wireless sensor network （WSN）, the demands of limited radio frequency spectrum rise sharply, thereby dealing with the frequency assignment of WSN scientifically and efficiently becomes a popular topic. To improve the frequency utilization rate in WSN, a spectrum management system for WSN combined with cloud computing technology should be considered. From the optimization point of view, the study of dynamic spectrum management can be divided into three kinds of methods, including Nash equilibrium, social utility maximization, and competitive economy equilibrium. In this paper, we propose a genetic algorithm based approach to allocate the power spectrum dynamically. The objective is to maximize the sum of individual Shannon utilities with the background interference and crosstalk consideration. Compared to the approach in [1], the experimental result shows better balance between efficiency and effectiveness of our approach.