• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.123-127
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• 2024

Cloud computing services has gained increasing popularity in recent years for supporting various on demand and scalable services for IT consumers where there is a need of less investment towards infrastructure. While storage architecture of cloud enjoys a more robust and fault-tolerant cloud computing network, such architecture also poses a number of security challenges especially when applied in applications related to social networks, Financial transactions, etc. First, as data are stored and maintained by individual virtual machines so Cloud resources are prone to hijacked. Such attacks allow attackers to create, modify and delete machine images, and change administrative passwords and settings successfully. hence, it is significantly harder to ensure data security. Second, Due to dynamic and shared nature of the Cloud, data may be compromised in many ways. Last but not least, Service hijacking may lead to redirect client to an illegitimate website. User accounts and service instances could in turn make a new base for attackers. To address the above challenges, we propose in this paper a distributed data access control scheme that is able to fulfil fine-grained access control over cloud data and is resilient against strong attacks such as compromise and user colluding. The proposed framework exploits a novel cryptographic primitive called attribute-based encryption (ABE), tailors, and adapts it for cloud computing with respect to security requirements

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.640-643
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• 2003

A Walsh function based associative memory is capable of storing m patterns in a single pattern storage space with Walsh encoding of each pattern. Furthermore, each stored pattern can be matched against the stored patterns extremely fast using algorithmic parallel processing. As such, this special type of memory is ideal for real-time processing of large scale information. However this incredible efficiency generates large amount of crosstalk between stored patterns that incurs mis-recognition. This crosstalk is a function of the set of different sequencies [number of zero crossings] of the Walsh function associated with each pattern to be stored. This sequency set is thus optimized in this paper to minimize mis-recognition, as well as to maximize memory saying. In this paper, this Walsh memory has been applied to the problem of face recognition, where PCA is applied to dimensionality reduction. The maximum Walsh spectral component and genetic algorithm (GA) are applied to determine the optimal Walsh function set to be associated with the data to be stored. The experimental results indicate that the proposed methods provide a novel and robust technology to achieve an error-free, real-time, and memory-saving recognition of large scale patterns.

• Journal of the Korean Ceramic Society
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• v.44 no.4 s.299
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• pp.198-201
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• 2007

Multi-walled carbon nanotube (M-CNT)/Nafion nanocomposites were prepared by solution casting to elucidate the effect of M-CNT addition, from 0 to 7 wt%, on the viscoelastic behavior of the composites. The M-CNT bundles induced by the Nafion polymer were determined to be uniformly distributed for the 1 wt% M-CNT/Nafion nanocomposites. The 1 wt% M-CNT/Nafion composite exhibited the highest blocking stress of 2.3 kPa due to its high elastic modulus of 0.485 GPa. From a dynamic mechanical analysis, the 1 wt% M-CNT had the highest storage and loss moduli compared with the other samples in all frequency and temperature ranges. From the storage modulus data, the M-CNT loaded composites had similar $T_g$ values near $120^{\circ}C$. The glass transition temperatures of the M-CNT loaded composites were $120^{\circ}C$ (1 wt%), $117^{\circ}C$ (3 wt%), $117^{\circ}C$ (5 wt%), and $135^{\circ}C$ (7 wt%), suggesting that the effect of the M-CNTs on the Nafion film begins at 1 wt%. Thus, it has been concluded that the 1 wt% M-CNT disported composite is attractive for actuator applications.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2797-2804
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• 1994

This paper analyzes the behaviors of corrugated membrane under the cryogenic liquid pressure and thermal loading using the FEM analysis program MARC. The FEM calculations were carried out on the basis of measured data of Technigaz membrane. It is very important to know the concentration levels and distributions of stress in the corrugated membrane. A quarter of the membrane sheet in place of the whole membrane was simulated because of its geometric symmetricity. The calculated results of the concentrated stress showed that the maximum stress occurs at the knot parts and at the root corner radius of the corrugations. The FEM calculated results indicated that the ring knot membrane which was developed in this study showed uniformly distributed stress and the lowest stress levels in the cross knot area in comparison with other two membranes. These results are very important to optimize the shape and improve the safety of membrane structure.

• Journal of the korean society of oceanography
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• v.32 no.3
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• pp.120-127
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• 1997

Depositional environment off the Shihwa Dam has been studied to investigate the change of sedimentation process and the pollution. In order to understand how the sediments are distributed, polluted and modified, depositional factors have been analyzed and compared with the previous data. Study area, located off the Shihwa Dam, was surveyed to collect 25 bottom samples and 2 cores in 1996 and echo-sounding in 1997. These sediments were analyzed for the study of the global characteristics of sediment such as grain size and organic matter. Among these samples, the selected twenty surface sediments were analyzed for the comparison with their contents of metallic elements (Al, Mn, Fe, V, Cr, Co, Ni, Cu, Zn, Cd, Pb, As). According to field and lab analysis of sediments, three sedimentological zones have been generally identified around study area; near the dam (sandy Silt), near the dike (Sand) and offshore (silty Sand) zones. Textural parameters show that the content of silt and clay is dominant near the dam excepting the dike zone of LNG Storage Base and offshore (Palmido). The total concentration of Mn, Ni, Fe, Zn and Cd in bulk sediments was increased after the construction of the dam, while the content of Mn and Cr were higher near tidal channel than in the offshore area. Meanwhile, the annual increasing pattern of some heavy metal has appeared in this area. Based on this primary study, modification of the depositional environment may be caused by the construction of the dam and LNG Storage Base. Additionally, environmental evaluation on organic/inorganic factors has been suggested for interpreting environmental changes caused by coastal development in the nearshore such as the Shihwa coastal area.

• Journal of Fisheries and Marine Sciences Education
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• v.22 no.2
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• pp.180-194
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• 2010

Coastal sand dunes are dynamic and fragile buffer zones of sand and vegetation where the following three characteristics can be found: large quantities of sand, persistent wind capable of moving sand, and suitable locations for sand to accumulate. The functional properties of coastal sand dunes include the roles in sand storage, underground freshwater storage, coastal defense, and ecological environment space, among others. Recently, however, the integrity of coastal dune systems has been threatened by development, including sand extraction for the construction industry, military usage, conversion to golf courses, the building of seawalls and breakwaters, and recreational facility development. In this paper, we examined the development mechanisms and structural/format types of coastal sand dunes, as well as their functions and value from the perspective of coastal engineering based on reviews of previous researches and a case study of a small coastal sand dune in the Nakdong river estuary. Existing data indicate that there are a total of 133 coastal sand dunes in South Korea, 43 distributed on the East Sea coast (32 in the Gangwon area, and 11 in Gyeongsangbuk-do), 60 on the West Sea coast (4 in Incheon and Gyeonggi-do, 42 in Ghungcheongnam-do, 9 in Jellabuk-do, and 5 in Jellanam-do), and 30 on the South Sea coast (16 in Jellanam-do, 2 in Gyeongsangnam-do, and 12 in Jeju).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.732-736
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• 2005

ln general, hospital information system should provide interoperability hat usually and operate independence of other HIS. This study proposes a new HIS paradigm that can be implemented within standard HL7 Interface engine and clinical data repository (CDR). We have developed an alternative architecture relying on agent solutions with distributed queries to heterogeneous databases. This architecture creates a very fine and flexible repository that can handle queries with the bases of standard HL7 messaging structure. Deploying Agent solutions to manipulate autonomy of storage management and sociality for communication with open world is another issue that keeps this system from reinventing existing wheels in medical informatics. This study the first attempt to construct CDR based private clinic. We used the information stored in the clinical patient record system of the internal medicine private hospital which is used rational database. We were searched increasing the 1,000 data entry from 1,000 to 10,000. By the result, experimental CDR showed highly efficient performance more than 6,000. In the future, the CDR can be further extended for clinical information among private hospitals estranged from EHR (Electronic Health Records).

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.117-124
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• 2003

The system implemented in this paper partitions and stores specimen data captured by a light microscope on distributed or parallel systems. Users ran observe images on computers as we use a physical microscope. Based on the client-server computing model, the system consists of client, coordinator, and data manager. Three components communicate messages. For retrieving images, we implemented the client program with necessary functions for educational applications such at image mark and text annotation, and defined the communication protocol. We performed the experiment for introducing a tape storage which stores a large volume of data. The experiment results showed performance improvement by data partitioning and indexing technique.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.89-96
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• 2023

Intrusion detection has been widely studied in both industry and academia, but cybersecurity analysts always want more accuracy and global threat analysis to secure their systems in cyberspace. Big data represent the great challenge of intrusion detection systems, making it hard to monitor and analyze this large volume of data using traditional techniques. Recently, deep learning has been emerged as a new approach which enables the use of Big Data with a low training time and high accuracy rate. In this paper, we propose an approach of an IDS based on cloud computing and the integration of big data and deep learning techniques to detect different attacks as early as possible. To demonstrate the efficacy of this system, we implement the proposed system within Microsoft Azure Cloud, as it provides both processing power and storage capabilities, using a convolutional neural network (CNN-IDS) with the distributed computing environment Apache Spark, integrated with Keras Deep Learning Library. We study the performance of the model in two categories of classification (binary and multiclass) using CSE-CIC-IDS2018 dataset. Our system showed a great performance due to the integration of deep learning technique and Apache Spark engine.