• Journal of Information Technology Applications and Management
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• v.22 no.4
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• pp.95-103
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• 2015

In this paper, we designed a platform-based $ERP^+$ system, which integrates ERP system and SCM system. With platform-based technology we can connect online and offline platforms, enterprise management systems, and government systems. In our research, first we examined the problems of the existing ERP systems, and second we discussed all basic tasks of our $ERP^+$ system. We also designed several modules for this platform-based system and system network. Our results showed that a platform-based $ERP^+$ system can effectively manage the information and the human/material resources, by using O2O (online to offline) technic. Even different systems can be integrated effectively. It can reduce the costs of enterprise management activities, enhance the enterprise competitiveness.

• Journal of Multimedia Information System
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• v.3 no.3
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• pp.85-90
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• 2016

We firstly tried to understand consumers' purchasing tendencies and mainly focused on designing a platform model that offers integrated support. C2B (Customer to Business) orders integrate with a consumption platform of a B2C (Business to Customer) model, and integrated support aims at design, supply, processing, and distribution of a fashion business. All the information such as orders, sales, production, supply, and settlement of accounts is synchronized under the C2B, B2C, and O2O (Online to Offline) environment so that accurate information can be shared in real time. Our platform automatically handles with a net income of a product designer, manufacturer, and shipping company once shipping is confirmed.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.59-66
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• 2023

Text mining (TM) is most widely used to find patterns from various text documents. Cyber-bullying is the term that is used to abuse a person online or offline platform. Nowadays cyber-bullying becomes more dangerous to people who are using social networking sites (SNS). Cyber-bullying is of many types such as text messaging, morphed images, morphed videos, etc. It is a very difficult task to prevent this type of abuse of the person in online SNS. Finding accurate text mining patterns gives better results in detecting cyber-bullying on any platform. Cyber-bullying is developed with the online SNS to send defamatory statements or orally bully other persons or by using the online platform to abuse in front of SNS users. Deep Learning (DL) is one of the significant domains which are used to extract and learn the quality features dynamically from the low-level text inclusions. In this scenario, Convolutional neural networks (CNN) are used for training the text data, images, and videos. CNN is a very powerful approach to training on these types of data and achieved better text classification. In this paper, an Ensemble model is introduced with the integration of Term Frequency (TF)-Inverse document frequency (IDF) and Deep Neural Network (DNN) with advanced feature-extracting techniques to classify the bullying text, images, and videos. The proposed approach also focused on reducing the training time and memory usage which helps the classification improvement.

• Journal of Korea Game Society
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• v.6 no.2
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• pp.33-44
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• 2006

This article examines cultural content distribution system, particularly of game industry based on the development of digital technology. In this period of convergence and fusion, some phenomenon leads the cultural content distribution system change like value transfer from platform to content. In relation to it, especially in the game industry, three types of distribution is categorized by the industrial structure (offline, online, mobile game) through the case studies and it is expected to be evolve into a base for development of distribution integration model in the future. In conclusion, the article suggest the policy subject for the promotion of cultural content that hold so much competitiveness for long-lasting development by the improvement of distribution structure, blowing off the conflict between companies and publishers, and global business, etc.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1306-1315
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• 2016

Modern power systems driven by high-power converters have become inevitable in view of the ever increasing demand for electric power. The total power loss can be reduced by limiting the switching losses in such power converters; increased power efficiency can thus be achieved. A reduced switching frequency that is less than a few hundreds of hertz is applied to power converters that produce output waveforms with high distortion. Selective harmonic elimination pulse width modulation (SHEPWM) is an optimized low switching frequency pulse width modulation method that is based on offline estimation. This method can pre-program the harmonic profile of the output waveform over a range of modulation indices to eliminate low-order harmonics. In this paper, a SHEPWM scheme for three-phase three-leg neutral point clamped inverter is proposed. Aside from eliminating the selected harmonics, the DC capacitor voltages at the DC bus are also balanced because of the symmetrical pulse pattern over a quarter cycle of the period. The technique utilized in the estimation of switching angles involves the firefly algorithm (FA). Compared with other techniques, FA is more robust and entails less computation time. Simulation in the MATLAB/SIMULINK environment and experimental verification in the very large scale integration platform with Spartan 6A DSP are performed to prove the validity of the proposed technique.