• Journal of Information Technology Applications and Management
• /
• v.27 no.3
• /
• pp.19-36
• /
• 2020

The Internet of things (IoT) is a system of interrelated computed devices, digital machines and any physical objects which are provided with unique identifiers and the potential to transmit data to people or machine (M2M) without requiring human interaction. IoT devices can be used to monitor and control the electrical and electronic systems used in different fields like smart home, smart city, smart healthcare and etc. In this study we introduce four imaginary IoT devices as a learning support assistants according to students' dominant learning styles measured by Honey and Mumford Learning Styles: Activists, Reflectors, Theorists and Pragmatists. This research emphasizes the association between students' strong learning styles and a preference to appropriate IoT devices with specific characteristics. Moreover, different levels of IoT devices' architecture are clearly explained in this study where all the artificial devices are designed based on this structure. Data analysis of experiment were measured by the use of chi square test for association and research results showed the statistical significance of the estimated model and the impacts of each category over the model where we finally got accurate estimates for our research variables. This study revealed the importance of considering the students' dominant learning styles before inventing a new IoT device.

• Steel and Composite Structures
• /
• v.27 no.4
• /
• pp.465-477
• /
• 2018

In this research, vibration and smart control analysis of a concrete foundation reinforced by $SiO_2$ nanoparticles and covered by piezoelectric layer on soil medium is investigated. The soil medium is simulated with spring constants and the Mori-Tanaka low is used for obtaining the material properties of nano-composite structure and considering agglomeration effects. With considering first order shear deformation theory, the total potential energy of system is calculated and by means of Hamilton's principle in three displacement directions and electric potential, the six coupled equilibrium equations are obtained. Also, based an analytical method, the frequency of system is calculated. The effects of applied voltage, volume percent and agglomeration of $SiO_2$ nanoparticles, soil medium and geometrical parameters of structure are shown on the frequency of system. Results show that with applying negative voltage, the frequency of structure is increased.

• Smart Structures and Systems
• /
• v.7 no.3
• /
• pp.229-240
• /
• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• Journal of Satellite, Information and Communications
• /
• v.11 no.2
• /
• pp.23-28
• /
• 2016

In this paper, we proposed the novel algorithm which controls the resolution of the HDMI(High Definition Multimedia Interface) by the channel estimation from WiFi-AP(Access Point) in the ISM(Industry-Science-Medical) band. The 2.4 and 5 GHz channel models are widely used since they have identical RF property as RSSI(Received Signal Strength Indication). Especially, the performance degradation of signal-transmission and streaming of WiFi will be occurred by the co-channel interference between AP(Access Point) and increased number of smart devices. Therefore, the optimization scheme of video format timing was designed by HDMI-CEC(Consumer Electronics Control) which considers the transmission speed of radio channel. The HDMI resolution, video quality of home-gateway and digital TV and the decision of PIP position can be maintained by the protocols between smart devices and DLNA(Digital Living Network Alliance) via proposed technique.

• Journal of Microbiology and Biotechnology
• /
• v.31 no.9
• /
• pp.1241-1255
• /
• 2021

This study was carried out to explore a non-chemical strategy for enhancing productivity by employing some antagonistic rhizobacteria. One hundred eighteen bacterial isolates were obtained from the rhizospheric zone of various crop fields of Gangwon-do, Korea, and screened for antifungal activity against Fusarium wilt (Fusarium oxysporum f. sp. lactucae) in lettuce crop under in vitro and in vivo conditions. In broth-based dual culture assay, fourteen bacterial isolates showed significant inhibition of mycelial growth of F. oxysporium f. sp. lactucae. All of the antagonistic isolates were further characterized for the antagonistic traits under in vitro conditions. The isolates were identified on the basis of biochemical characteristics and confirmed at their species level by 16S rRNA gene sequencing analysis. Arthrobacter sulfonivorans, Bacillus siamensis, Bacillus amyloliquefaciens, Pseudomonas proteolytica, four Paenibacillus peoriae strains, and Bacillus subtilis were identified from the biochemical characterization and 16S rRNA gene sequencing analysis. The isolates EN21 and EN23 showed significant decrease in disease severity on lettuce compared to infected control and other bacterial treatments under greenhouse conditions. Two bacterial isolates, EN4 and EN21, were evaluated to assess their disease reduction and growth promotion in lettuce in field conditions. The consortium of EN4 and EN21 showed significant enhancement of growth on lettuce by suppressing disease caused by F. oxysporum f. sp. lactucae respectively. This study clearly indicates that the promising isolates, EN4 (P. proteolytica) and EN21 (Bacillus siamensis), can be commercialized and used as biofertilizer and/or biopesticide for sustainable crop production.

• Journal of Information Technology Services
• /
• v.11 no.4
• /
• pp.309-333
• /
• 2012

Recently, emergence of smart-phones and Social Networking Service(SNS) would offer the market environment changes and the opportunities for new business. For the case analysis comprehensive survey were implemented. And those data were analyzed along the research framework. The late-comer firms offered differential services, maintained creative and opened corporate culture, shoed learning capabilities which means absorption and organization of external knowledge, innovative efforts to control the insurgents than early-mover firms. When we analyze these phenomena along the developmental stages of late-comer, we can perceive that the stage of late-comers firms were moving from the "tracing the path" stage to "jumping the path" stage which means the creating capabilities were more or less enhanced and the firms become more stable in terms of business operation. In business model, early-mover firms showed clear definition for each business element, especially the revenue structure, while late-mover firms seemed unstable or unclear revenue structure.

• Smart Structures and Systems
• /
• v.5 no.1
• /
• pp.23-42
• /
• 2009

In order to reduce vibration or to control shape of structures made of metal or composites, piezoelectric materials have been extensively used since their discovery in 1880's. A recent trend is also seen to apply piezoelectric materials to flexible structures made of rubber-like materials. In this paper a non-linear finite element model using updated Lagrangian (UL) approach has been developed for static analysis of rubber-elastic material with surface-bonded piezoelectric patches. A compressible stain energy function has been used for modeling the rubber as hyperelastic material. For formulation of the nonlinear finite element model a twenty-node brick element is used. Four degrees of freedom u, v and w and electrical potential ${\varphi}$ per node are considered as the field variables. PVDF (polyvinylidene fluoride) patches are applied as sensors/actuators or sensors and actuators. The present model has been applied to bimorph PVDF cantilever beam to validate the formulation. It is then applied to study the smart rubber components under different boundary and loading conditions. The results predicted by the present formulation are compared with the analytical solutions as well as the available published results. Some results are given as new ones as no published solutions available in the literatures to the best of the authors' knowledge.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.2
• /
• pp.249-253
• /
• 2013

This study analyzed that technological competition, variety and simility of Green IT fields using patents data. To achieve this, we limited range of Green IT that reduction of energy, eco-friendly technology. Therefore we conducted analysis of patents that power saving systems, light control system, smart system, cloud computing and green house/eco systems. As the result of that, power saving field was the most developed. The simililarty of power saving and cloud computing systems are very high and similiarities of light control system, green house/eco systems and smart system were very high.

• Journal of Bio-Environment Control
• /
• v.30 no.1
• /
• pp.19-26
• /
• 2021

In this study, analysis was performed to identify three greenhouses located in the same area using principal component analysis (PCA) and linear discrimination analysis (LDA). The environmental data in the greenhouse were from 3 farms in the same area, and the values collected at 1 hour intervals for a total of 4 weeks from April 1 to April 28 were used. Before analyzing the data, it was pre-processed to normalize the data, and the analysis was performed by dividing it into 80% of the training data and 20% of the test data. As a result of PCA and LDA analysis, it was found that PCA classification accuracy was 57.51% and LDA classification was 67.06%, indicating that it can be classified by greenhouse. Based on the farmhouse data classified in advance, the data of the new environment can be classified into specific groups to determine the tendency of the data. Such data is judged to be a way to increase the utilization of data by facilitating identification.

• Journal of Information Processing Systems
• /
• v.15 no.5
• /
• pp.1156-1170
• /
• 2019

In recent years, the problem of data drifted of the smart grid due to manual operation has been widely studied by researchers in the related domain areas. It has become an important research topic to effectively and reliably find the reasonable data needed in the Supervisory Control and Data Acquisition (SCADA) system has become an important research topic. This paper analyzes the data composition of the smart grid, and explains the power model in two smart grid applications, followed by an analysis on the application of each parameter in density-based spatial clustering of applications with noise (DBSCAN) algorithm. Then a comparison is carried out for the processing effects of the boxplot method, probability weight analysis method and DBSCAN clustering algorithm on the big data driven power grid. According to the comparison results, the performance of the DBSCAN algorithm outperforming other methods in processing effect. The experimental verification shows that the DBSCAN clustering algorithm can effectively screen the power grid data, thereby significantly improving the accuracy and reliability of the calculation result of the main grid's theoretical line loss.