Data Mining - Concepts and Techniques.

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Matrix Factorization Techniques for Recommender Systems

Self-Directed Learning, A Guide for Learners and Teachers

In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching.

/pdf/a-review-on-genetic-algorithm-past-present-and-future-2o5y8ru178.pdf

A review on genetic algorithm: past, present, and future

Futures market has high leverage and the characteristics of over-performing returns. Hence, it always attracts lots of investors. However, three major kinds of institutional traders are more influential than individual investors in Taiwan. In this paper, a monthly predicting model for the weighted price index of the Taiwan Stock Exchange (TAIEX) was built based on correlation and regression analysis by using the following parameters: Dow Jones industrial index, NASDAQ index, M1A, M1B, M2 annual growth rate, US dollar exchange rate, economic monitoring indicator and global oil prices. Then, based on the prediction results, we define two trading strategies and apply them in trading MTX (mini Taiwan index futures). The evaluation result shows that both the two trading strategies have good returns.

Forecasting Monthly Average of Taiwan Stock Exchange Index.

Due to its moderate overhead and small quantization error, the time-stamping counter is currently the most precise time-measuring mechanism on Intel 80X86-based Platform. On the Pentium processors, we can simply use a conventional null benchmark to determine the time-stamping counter’s overhead accurately. Similarly, on the Pentium Pro processors, Intel also recommends the same method for measuring this overhead. However, since the influence of the measured operation is neglected, we find this method becomes inaccurate on Pentium Pro. Therefore, in this paper, we propose a new method for determining the overhead of Pentium Pro‘s time-stamping counter. Furthermore, we also provide some empirical results to confirm the feasibility of our idea.

A new approach to determining the time-stamping counter's overhead on the Pentium Pro processors

The prevalence of predatory journals has become more severe recently as this is harmful to science and technology development For scholars publish papers more effectively and avoid publishers for profits, this research used a machine learning method to identify the predatory journals The features like text content and keywords of the collected journals' websites were extracted from mainstream predatory journal websites and normal journal websites This research proposed a predatory journal classification system based on a new model The results show that our model's recall rate exceeds 90%, ensuring that the journals submitted by the researchers are not predatory

Predatory Journal Classification Using Machine Learning

Face recognition has received much attention with numerous applications in various fields. Although many face recognition algorithms have been proposed, usually they are not highly accurate enough when the poses of faces vary considerably. In order to solve this problem, some researches have proposed pose normalization algorithm to eliminate the negative effect cause by poses. However, only horizontal normalization has been considered in these researches. In this paper, the HVPN (Horizontal and Vertical Pose Normalization) system is proposed to accommodate the pose problem effectively. A pose invariant reference model is re-rendered after the horizontal and vertical pose normalization sequentially. The proposed face recognition system is evaluated based on the face database constructed by our self. The experimental results demonstrate that pose normalization can improve the recognition performance using conventional principal component analysis (PCA) and linear discriminant analysis (LDA) approaches under varying pose. Moreover, we show that the combination of horizontal and vertical pose normalization can be evaluated with higher performance than mere the horizontal pose normalization.

HVPN: The Combination of Horizontal and Vertical Pose Normalization for Face Recognition

With the evolution of the Internet and smartphone devices, Internet advertising has become one of the most important methods for delivering promotional marketing messages to customers. However, the efficiency of Internet advertising for microenterprise is not very high, since Wi-Fi advertising-which is limited by a small router coverage area-is mainly used. Moreover, because of the lack of money, microenterprises have been using low-cost methods to promote their products. Thus, enhancing the effectiveness of Wi-Fi advertising, and solving the problem of cost and the range of the views are now an essential investigation in this study. In this paper, we propose a reciprocal model with Wi-Fi union mechanism for Internet advertising based on fog computing architecture to enhance the efficiency of advertisement, reduce the cost, and increase the range of the views for microenterprise by using the Internet. In particular, the system was built in advertisers', publishers', and consumers' sides. In our system, we use contribution point (CP) as an exchange value among the participants. Advertisers and publishers can get CP by helping the others in the system to promote their advertisements, increasing their CP by one unit. Similarly, advertisers and publishers can use their CP to ask for assistance from the others, decreasing their CP by one unit. The result shows that the system in a Wi-Fi union is easy to use, and advertisements can be seen by all customers who are using free Wi-Fi from the stores of the union. This method can solve the problem of cost and fixed consumer groups.

/pdf/a-wi-fi-union-mechanism-for-internet-advertising-reciprocal-zfbhohcns5.pdf

Shyan-Ming Yuan

Papers

Forecasting Monthly Average of Taiwan Stock Exchange Index.

A new approach to determining the time-stamping counter's overhead on the Pentium Pro processors

Predatory Journal Classification Using Machine Learning

HVPN: The Combination of Horizontal and Vertical Pose Normalization for Face Recognition

A Wi-Fi union mechanism for internet advertising reciprocal platform in microenterprises