• Journal of Distribution Science
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• v.19 no.8
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• pp.91-100
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• 2021

Purpose: Supply chain management is a significant component of marketing strategy to achieve the overall goal of maintaining a competitive edge in the industry. To better understand and compare marketing strategies between two major distribution channels (Wholesalers and Retailers), the present study examines the various critical aspects in developing marketing strategies based on numerous prior studies. Research design, data and methodology: Qualitative research involves collecting and analyzing various non-numeric data to establish different concepts or opinions in the data. In content analysis, determining the presence of different themes, concepts, or other valuable texts and their relationships is carried out. Usually, the researchers employ three distinct methods to carry out complete content analysis. Results: Developing the appropriate marketing strategy to manage the supply chain of a business is essential. Marketing strategies should be formulated in a manner that ensures the supply chain is well organized. Applying the marketing strategy in the supply chain management, the current author utilizes the four Ps to integrate strategies for two distribution channels which are essential in ensuring proper management. Conclusions: This study concluded that utilizing the existing marketing strategies and integrating them can help in better management of the supply chain, using communication, decision making, product differentiation, and pricing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4545-4566
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• 2021

The evolution of IoT technology is having a significant impact on people's lives. Almost all areas of people's lives are benefiting from increased productivity and simplification made possible by this trending technology. On the downside, however, the application of IoT technology is posing some security challenges, among them, unauthorized access to IoT devices. This paper presents an Attribute-based Access Control Fog architecture that aims to achieve effective distribution, increase availability and decrease latency. In the proposed architecture, the main functional points of the Attribute-based Access Control are distributed to provide policy decision and policy information mechanisms in fog nodes, locating these functions near end nodes. To evaluate the proposed architecture, an access control engine based on the Attribute-based Access Control was built using the Balana library and simulated using EdgeCloudSim to compare it to the traditional cloud-based architecture. The experiments show that the fog-based architecture provides robust results in terms of reducing latency in making access decisions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.794-815
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• 2023

The rapid development of mobile communication not only has made the industry gradually diversified, but also has enhanced the service quality requirements of users. In this regard, it is imperative to consider jointly network slicing and mobile edge computing. The former mainly ensures the requirements of varied vertical services preferably, and the latter solves the conflict between the user's own energy and harsh latency. At present, the integration of the two faces many challenges and need to carry out at different levels. The main target of the paper is to minimize the energy consumption of the system, and introduce a multi-slice joint task offloading and resource allocation scheme for massive multiple input multiple output enabled heterogeneous networks. The problem is formulated by collaborative optimizing offloading ratios, user association, transmission power and resource slicing, while being limited by the dissimilar latency and rate of multi-slice. To solve it, assign the optimal problem to two sub-problems of offloading decision and resource allocation, then solve them separately by exploiting the alternative optimization technique and Karush-Kuhn-Tucker conditions. Finally, a novel slices task offloading and resource allocation algorithm is proposed to get the offloading and resource allocation strategies. Numerous simulation results manifest that the proposed scheme has certain feasibility and effectiveness, and its performance is better than the other baseline scheme.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.249-257
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• 2024

As the main driver of economic growth and employment, the agricultural sector plays an important role in Vietnam's economy. However, in recent years, the sector has faced new challenges and also presented new investment opportunities to stimulate agricultural growth. Many Vietnamese agricultural producers currently lack the modern technology and decision support tools needed to maintain and improve productivity in a rapidly changing environment. Other stakeholders in the agricultural value chain, such as input suppliers, distributors, and consumers, also face significant challenges, including disrupted value chains, transportation costs. The cost of transporting goods across the supply chain continues to increase and information exchange remains fragmented. A potential solution to address these challenges is the application of digital transformation in agricultural supply chains. Farmers and other value chain participants can improve the production of their goods and procedures by utilizing new and cutting-edge technologies that are integrated into a unified system as part of the digital transformation of agricultural supply chains. In this study, we evaluate the current status of digital transformation in the supply chain of the agriculture industry by finding and examining pertinent publications from key agencies as well as prior research. From there, in the framework of the digital economy, this study suggests a digital transformation roadmap for the agricultural supply chain.

• Archives of design research
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• v.13
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• pp.45-53
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• 1996

After the callapse of the 80's bubble economy. consumers tend to consider the fundamental values of a product such as price, usage, and quality more significantly than ever before. Due to this change in attitude. the most important factor in a consumer's decision for choosing a product becomes the quality of a product that safisfies consumer's practical values whith convincing features and logical differentiations devoted to fundamental values. Under the circumstances. Factor Oriented Process and Multi-Sequential Process are proposede not just as merely defining concept through study of consumers' needs. but as methods of gaining competitive edge and eatablishing corporate identity in market, competition by bringing out consumers' various wants and needs to lead them to a specific product. Factor Oriented Process emphasizes the analysis of factors within the process itself, especially the synthesis of factors which would bring about new solutions as its special feature and acts as a logical element for further design development. Thus, the synthesis process consists of re-organizing analyzed factors, andduring this process, analyzing correlation between the restrictions of factors would lead to discovery of 'dominant factors'. Afterward, design basis may be formed with design concepts proposed by several concept codes made up of one dominant factor and other associate factors. Multi-Sequential Process is an extensive approach to discover differentiated design proposals through careful examination of dominant factors within the product, and furthermor, to discount 'anterior factor' (directional factors that decide design directions based on multi-value criteria) for self-determined decision of design directions.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.88-95
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• 2011

An embedded mobile device mostly has lower computation power than a general purpose computer because of its relatively lower system specifications. Consequently, conventional face tracking and face detection methods, requiring complex algorithms for higher recognition rates, are unsuitable in a mobile environment aiming for real time detection. On the other hand, by applying a real-time tracking and detecting algorithm, we would be able to provide a two-way interactive multimedia service between an user and a mobile device thus providing a far better quality of service in comparison to a one-way service. Therefore it is necessary to develop a real-time face and eye tracking technique optimized to a mobile environment. For this reason, in this paper, we proposes a method of tracking horizontal face position of a user on a T-DMB device for enhancing the quality of 3D DMB content. The proposed method uses the orientation of edges to estimate the left and right boundary of the face, and by the color edge information, the horizontal position and size of face is determined finally to decide the horizontal face. The sobel gradient vector is projected vertically and candidates of face boundaries are selected, and we proposed a smoothing method and a peak-detection method for the precise decision. Because general face detection algorithms use multi-scale feature vectors, the detection time is too long on a mobile environment. However the proposed algorithm which uses the single-scale detection method can detect the face more faster than conventional face detection methods.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.38-47
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• 2013

An image coding based on MRC model, a kind of multi-layer image model, first segments a screen image into foreground, mask, and background layers, and then compresses each layer using a codec that is suitable to the layer. The mask layer defines the position of foreground regions such as textual and graphical contents. The colour signal of the foreground (background) region is saved in the foreground (background) layer. The mask layer which contains the segmentation result of foreground and background regions is of importance since its accuracy directly affects the overall coding performance of the codec. This paper proposes a new layer segmentation algorithm for the MRC based image coding. The proposed method extracts text pixels from the background using morphological top hat filtering. The application of white or black top hat transformation to local blocks is controlled by the information of relative brightness of text compared to the background. In the proposed method, the boundary information of text that is extracted from the edge map of the block is used for the robust decision on the relative brightness of text. Simulation results show that the proposed method is superior to the conventional methods.

• Geophysics and Geophysical Exploration
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• v.20 no.2
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• pp.61-71
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• 2017

Recently, ground-penetrating radar (GPR) surveys have been actively carried out for precise subsurface void investigation because of the rapid increase of subsidence in urban areas. However, since the interpretation of GPR data was conducted based on the interpreter's subjective decision after applying only the basic data processing, it can result in reliability problems. In this research, to solve these problems, we analyzed the difference between the events generated from subsurface voids and those of strong diffraction sources such as the buried pipeline by applying the edge detection technique, which is one of image processing technologies. For the analysis, we applied the image processing technology to the GRP field data containing events generated from the cavity or buried pipeline. As a result, the main events by the subsurface void or diffraction source were effectively separated using the edge detection technique. In addition, since subsurface voids associated with the subsidence has a relatively wide scale, it is recorded as a gentle slope event unlike the event caused by the strong diffraction source recorded with a sharp slope. Therefore, the directional analysis of amplitude variation in the image enabled us to effectively separate the events by the subsurface void from those by the diffraction source. Interpretation based on these kinds of objective analysis can improve the reliability. Moreover, if suggested techniques are verified to various GPR field data sets, these approaches can contribute to semiautomatic interpretation of large amount of GPR data.