• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.38-48
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• 2020

The domestic AI speaker market is growing into a full-fledged early audience market beyond the innovative consumer market with 3 million domestic supply units at the end of 2018, but the reality is that for various reasons, we are not satisfied with the use. There are many previous papers on AI Speaker, but the majority of research so far tends to be biased towards the acceptance of the device's own performance. Many changes are being made, such as OTT providers trying to secure the market through collaboration with AI speaker providers. This study tried to identify the priorities for content services, which can be another major selection factor for AI speakers, excluding the factors of unsatisfactory technology. First, this study identified the priorities among AI speaker selection factors using AHP (Analytic Hierarchy Process), based on the AI speaker selection factors derived through literature research. The most important hierarchical factor are Concierge Service, Education Service, and Entertainment Service order in AI speaker selection, and the primary content among the individual factors was the one that ranked weather/temperature/fine dust (11.6%) and child caring content was in the second place (10.8%), and then music service was in the third place (9.8%). The three top priorities were derived from the items in the top tier 1, 2 and 3 priorities. Of the total 15 individual services, 6 sub-layers of Concierge Service (weather/temperature/fine dust, news, voice schedule notification) and Education Service (foreign language, toddler, reading books) were in the top 8, and two of the Entertainment Service Music service and movie service ranked third and sixth.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.9-20
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• 2011

Future warfare paradigm is changing to network-centric warfare and effects-based operations. In order to find first and strike the enemy in the battlefield, friendly unit requires real-time target acquisition, intelligence collection, accurate situation assessment, and timely decision. The rapid development in advanced sensor technology and wireless networks requires a significant change in operational concepts of the battlefield surveillance. In particular, the introduction of a battlefield surveillance sensor network system is a big challenge to the ground forces which have lack of automated information collection assets. Therefore this paper proposes an ontology-based context-aware framework for the battlefield surveillance sensor network system which is needed for early finding the enemy and visualizing the battlefield in the ground force operations. Compared with the performance of existing systems, the one of the proposed framework has shown highly positive results by applying the context systems evaluation method. The framework has also proven to be satisfactory by the structured evaluation method using device collaboration. Since the proposed ontology-based context-aware framework has a lot of advantages in terms of scalability and reusability, the ground force's reconnaissance and surveillance system can be widely applied to expand in the future. And, ontology-based model has some weak points such as ontology data size, processing time, and limitation of network bandwidth. However, these problems can be resolved by customizing properly to fit the mission and characteristics of the unit. Moreover, development of the next-generation communication infrastructure can expedite the intelligent surveillance and reconnaissance service and may be expected to contribute greatly to expanding the information capacity.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.11
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• pp.15-19
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• 2007

This paper reports the effects of Ar ion beam surface treatment on a $SiO_2$ dielectric layer in organic thin film transistors. We compared the electrical properties of pentacene-based OTFTs, treated by $O_2$ plasma or Ar ion beam treatments and characterized the states of the surface of the dielectric by using atomic force microscopy and X-ray photoelectron spectroscopy. For the sample which received $O_2$ plasma treatment, the mobility increased significantly but the on/off current ratio was found very low. The Ar ion beam-treated sample showed a very high on/off current ratio as well as a moderately improved mobility. XPS data taken from the dielectric surfaces after each of treatments exhibit that the ratio of between Si-O bonds and O-Si-O bonds was much higher in the $O_2$ plasma treated surface than in the Ar ion beam treated surface. We believe that our surface treatment using an inert gas, Ar, carried out an effective surface cleaning while keeping surface damage very low, and also the improved device performances was achieved as a consequence of improved surface condition.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.6
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• pp.26-37
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• 2019

This paper aims to investigate the seismic characteristics of strip-type damping devices possessing optimized shapes for the moment-resisting mechanism throughout analytical and experimental studies. Predicting equations for initial stiffness and yielding strength were introduced and compared with analytical results obtained from finite element analyses (FEAs) using commercial FEA program ABAQUS. In order for establishing predicting equations, two idealized processes were considered and both predicting equations showed that they could provide enough approximations for seismic applications in building structures. Throughout experimental studies, it was noted that structural uncertainties on mild steels, connection details and structural types linking damping devices with building structures could interrupt predicting structural behavior of the devices. Also, it was observed that shear stress concentrations should be considered if shear yielding type devices are applied into building structures. Nevertheless, it was shown that structural conservatism can be established using the predicting equations and seismic applications of the damping devices can enhance the seismic performance of building structures efficiently in the viewpoint that they have high resistance to low-cycle fatigue failures.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.35-41
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• 2017

With the advances in Internet over Things, the demand in diverse electronic devices such as mobile phones and sensors has been rapidly increasing and boosting up the researches on those products. Semiconductor materials, devices, and fabrication processes are becoming more diverse and complicated, which accompanies finding parameters for an optimal fabrication process. In order to find the parameters, a process simulation before fabrication or a real-time process control system during fabrication can be used, but they lack incorporating the feedback from post-fabrication data and compatibility with older equipment. In this research, we have developed an artificial intelligence based simulator, which finds parameters for an optimal process and controls process equipment. In order to apply the control concept to all the equipment in a fabrication sequence, we have developed a prototype for a manipulator which can be installed over an existing buttons and knobs in the equipment and controls the equipment communicating with the AI over the Internet. The AI is based on the deep learning to find process parameters that will produce a device having target electrical characteristics. The proposed simulator can control existing equipment via the Internet to fabricate devices with desired performance and, therefore, it will help engineers to develop new devices efficiently and effectively.

• Journal of Acupuncture Research
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• v.19 no.3
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• pp.64-76
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• 2002

Objective : The purpose of this study is to investigate the mechanism and effect of moxibustion objectively and to be used as the quantitative data for developing the new thermal stimulating treatment by observing the combustion characteristics of commercial moxaes. Methods : We have selected two types(large-size moxa A(LMA), large-size moxa B(LMB)) among large moxaes used widely in the clinic. We examined combustion times, temperatures, temperature gradients in each period during a combustion of moxa. Results : 1. The ascending temperature gradient measured in the central point of non-contacted surface was fastest, the average ascending temperature gradient of both moxaes was $0.0384^{\circ}C/sec$, $0.0123^{\circ}C/sec$ respectively, 3.1 times faster in LMA. The maximum ascending temperature gradient was also about 2.9 times faster in LMA. The time required for the maximum ascending temperature gradient from ignition was 254sec, 411sec respectively. 2. The minimum descending temperature gradient in the retaining period was $-0.0250^{\circ}C/sec$, $-0.0090^{\circ}C/sec$ respectively and the average descending temperature gradient was $-0.0160^{\circ}C/sec$, $-0.0037^{\circ}C/sec$ respectively on the non-contact surface. 3. On the basis of the non-contact surface($A_I$), the time at which the effective stimulus period began to occur was about 264sec, 796sec respectively after an ignition, the time at which the maximum temperature began to occur was about 373sec, 1323sec respectively after an ignition, and the maximum temperature was $0.9^{\circ}C$ higher in LMA. The maximum ascending temperature gradient was also about 4.2 times faster in LMA. Conclusion : It was thought that not only the figure of moxicombustion device, but also the form and size of moxa had influence on the combustion characteristics deciding the performance of stimulus seriously.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.25-31
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• 2016

With the development of IOT technology and the expansion of ICT services recently, a variety of home network services have been advanced based on wired and wireless high speed telecommunication. Domestic and global companies have been studying on the innovative technology for the users using IOT based technology and the environment for the smart home services has been gradually developed. The users live their lives with more convenience due to the expansions and developments of smart phones. However, the threatening on the security of the smart home network had occurred by various attacks with the connection to the smart environment telecommunication, lack of applications on low powered and light weight telecommunication, and the problems of security guideline. In addition, the solutions are required for the new and variant attacking cases such as data forgery and alteration of the device for disguising approach with ill will. In this article, the safe communication protocol was designed using certification management technique based on AKI which supplemented the weakness of PKI, the existing certification system in the smart environment. Utilizing the signature technique based on ECDSA, the efficiency on the communication performance was improved, and the security and the safety were analyzed on the security threat under the smart home environment.