• Journal of Bio-Environment Control
• /
• v.29 no.3
• /
• pp.277-284
• /
• 2020

To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO₂ is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO₂. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO₂. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.

• Journal of Appropriate Technology
• /
• v.5 no.2
• /
• pp.106-113
• /
• 2019

In order to respond to the global environmental issues, developed countries have been helped the developing countries as the Official Development Assistance (ODA). It is important to understand technology needs of the developing countries to provide the optimum solutions. In this study, the information of the environmental R&D dealing with appropriate technology were comprehensively collected based on the conducted R&D projects from the ministry of environment in Korea. The technology needs by UNFCCC (United Nations Framework Convention on Climate Change) and Korean government were analyzed named as TNA and CPS according to the target developing countries. In South-East Asia and Africa region, there were technology needs on water, biota, air, solid wastes, infrastructures and resources. And they were related to the issues such as environmental pollution, construction, climate change, biodiversity, energy and water management. The technology needs by UNFCCC and Korean government were also compared. Furthermore, the environmental R&D on appropriate technology should be focused on localization and maintenance to provide sustainable solutions to the developing countries.

• Journal of KIISE:Software and Applications
• /
• v.31 no.9
• /
• pp.1233-1245
• /
• 2004

Though biometrics to authenticate a person is a good tool in terms of security and convenience, typical authentication algorithms using biometrics may not be executed on resource-constrained devices such as smart cards. Thus, to execute biometric processing on resource-constrained devices, it is desirable to develop lightweight authentication algorithm that requires only small amount of memory and computation. Also, among biological features, face is one of the most acceptable biometrics, because humans use it in their visual interactions and acquiring face images is non-intrusive. We present a new face authentication algorithm in this paper. Our achievement is two-fold. One is to present a face authentication algorithm with low memory requirement, which uses support vector machines (SVM) with the feature set extracted by genetic algorithms (GA). The other contribution is to suggest a method to reduce further, if needed, the amount of memory required in the authentication at the expense of verification rate by changing a controllable system parameter for a feature set size. Given a pre-defined amount of memory, this capability is quite effective to mount our algorithm on memory-constrained devices. The experimental results on various databases show that our face authentication algorithm with SVM whose input vectors consist of discriminating features extracted by GA has much better performance than the algorithm without feature selection process by GA has, in terms of accuracy and memory requirement. Experiment also shows that the number of the feature ttl be selected is controllable by a system parameter.

• KSBB Journal
• /
• v.24 no.4
• /
• pp.410-414
• /
• 2009

Single-nucleotide polymorphisms (SNPs) are the DNA sequences difference among the same species in the level of nucleic acids and are widely applied in clinical fields such as personalized medicine. The routine and labor-intensive methods to determine SNPs are performing the sequence homology search by using BLAST and navigating the trace of chromatogram files generated by high-throughput DNA sequencing machine by using Chromas program. In this paper, we developed SNPchaser, a web-based program for detecting SNPs substitution and heterozygosity existence, to improve the labor-intensive method in determining SNPs. SNPchaser performed sequence alignment and visualized the suspected region of SNPs by using user's reference sequence, AB1 files, and positional information of SNPs. It simultaneously provided the results of sequences alignment and chromatogram of relevant area of SNPs to user. In addition, SNPchaser can easily determine existence of heterozygosity in SNPs area. SNPchaser is freely accessible via the web site http://www.bioinformatics.ac.kr/SNPchaser and the source codes are available for academic research purpose.

• Applied Microscopy
• /
• v.41 no.4
• /
• pp.229-234
• /
• 2011

The occurrence of nuclear inclusions has been reported in various plant groups from primitive ferns to higher flowering plants. Their presence within a group seems to be randomly distributed without any phylogenetic relationships among species. According to the current survey, nuclear inclusions have been widely documented in more than several hundreds of species from various families of plants. The morphology and internal structures of nuclear inclusions are diverse and at least five types of inclusions develop within plant nuclei; amorphous, crystalline, fibrous, lamellar, and tubular form. Among these types, crystalline inclusions are the ones that are the most frequently reported. The inclusions are not bound by membranes and appear to be related to the nucleoli, either spatially by a close association or by an inverse relationship in size during development. The idea that nuclear inclusions are of a proteinaceous nature has been widely accepted. Further link to nucleolar activity as a protein storing site has also been suggested based on the association between the nucleolus and nuclear inclusions. Various investigations of nuclear inclusions have revealed more information about their structural features, but characterizing their precise function and subunit complexity employing molecular analysis and 3-D reconstruction remains to be elucidated. Tilting and tomography of serial sections with appropriate image processing can provide valuable information on their subunit(s). The present review summarizes discussion about different nuclear inclusions in plants from previous works, giving special attention to their fine, ultrastructural morphology, function, and origin.

• Journal of KIISE:Databases
• /
• v.34 no.5
• /
• pp.396-408
• /
• 2007

After the Human Genome Project finished the sequencing of a human DNA sequence, the concerns on protein functions are increasing. Since the structures of proteins are conserved in divergent evolution, their functions are determined by their structures rather than by their amino acid sequences. Therefore, if similarities between two protein structures are observed, we could expect them to have common biological functions. So far, a lot of researches on protein structure alignment have been performed. However, most of them use RMSD(Root Mean Square Deviation) as a similarity measure with which it is hard to judge the similarity level of two protein structures intuitively. In addition, they retrieve only one result having the highest alignment score with which it is hard to satisfy various users of different purpose. To overcome these limitations, we propose a novel protein structure alignment algorithm based on MRPD(Maximum of Residue Pair Distance) and SG (Similarity Graph). MRPD is more intuitive similarity measure by which fast tittering of unpromising pairs of protein pairs is possible, and SG is a compact representation method for multiple alignment results with which users can choose the most plausible one among various users' needs by providing multiple alignment results without compromising the time to align protein structures.

• Korean Journal of Breeding Science
• /
• v.50 no.4
• /
• pp.364-377
• /
• 2018

Hexaploid wheat (common wheat/bread wheat) is one of the most important cereal crops in the world and a model for research of an allopolyploid plant with a large, highly repetitive genome. In the heritability of agronomic traits, variation in gene presence/absence plays an important role. However, there have been relatively few studies on the variation in gene presence/absence in crop species, including common wheat. Recently, a reference genome sequence of common wheat has been fully annotated and published. In addition, advanced next-generation sequencing (NGS) technology provides high quality genome sequences with continually decreasing NGS prices, thereby dawning full-scale wheat functional genomic studies in other crops as well as common wheat, in spite of their large and complex genomes. In this review, we provide information about the available tools and methodologies for wheat functional genomics research supported by NGS technology. The use of the NGS and functional genomics technology is expected to be a powerful strategy to select elite lines for a number of germplasms.

• Korean Journal of Cognitive Science
• /
• v.23 no.2
• /
• pp.133-164
• /
• 2012

Paul Churchland(1989) suggests the theory of representation from the results of cognitive biology and connectionist AI studies. According to the theory, our representations of the diverse phenomena in the world can be represented as the positions of phase state spaces with the actions of the neurons or of the assembly of neurons. He insists connectionist AI neural networks can have the semantical category systems to recognize the world. But Fodor and Lepore(1996) don't look the perspective bright. From their points of view, the Churchland's theory of representation stands on the base of Quine's holism, and the network semantics cannot explain how the criteria of semantical content similarity could be possible, and so cannot the theory. This thesis aims to excavate which one is the better between the perspective of the theory and the one of Fodor and Lepore's. From my understandings of state space theory of representation, artificial nets can coordinates the criteria of contents similarity by the learning algorithm. On the basis of these, I can see that Fodor and Lepore's points cannot penetrate the Churchlands' theory. From the view point of the theory, we can see how the future's artificial systems can have the conceptual systems recognizing the world. Therefore we can have the perspectives what cognitive scientists have to focus on.

• Journal of Korean Society of Forest Science
• /
• v.109 no.4
• /
• pp.371-381
• /
• 2020

The Ministry of Environment (ME) is planning to adopt in 2020 the IUCN regional Red List for "Guidelines for listing and delisting rare & endangered species and management of endangered Species System". The ME designated 377 species of vascular plants on the regional Red List. In a previous study it had been suggested that 103 species from this list are candidates for the regional Red List. With respect to a possible Red List, we assessed 59 species (after excluding 34 additional NA species and ten endemic species). These assessments indicated that 16 species are at the "threatened" level. Of those, one species is Critically Endangered, ten are Endangered, and five are Vulnerable. A further four species are classified as Near Threatened, 30 as Of Least Concern, and nine as Data Deficient. We found that most of the assessments proposed by the Ministry of Environment were not supported by scientific data, including quantitative geographic data (over 70%) in Criteria B. In order to determine the endangered species belonging to the orchid family, it is necessary to obtain records of illegal activities or data on overcollection. The current problem with the Ministry of Environment Red List has been the lack of management of scientific data on species showing a trend in decreasing population in the mid- to long-term; thus, there is a lack of critical resources for policy-makers. The ME legally designated categories and assessment, and the lack of expertise in failing to comply with the legal law by itself. The key to presenting an accurate overview of the state of Korean flora is to fill the information gaps with respect to significant geographical and taxonomical biases in the quality and quantity of data. By regularly updating the qualified data, we will be able to track the changes in the conservation status of the flora and inform the necessary conservation policies.

• Journal of Biosystems Engineering
• /
• v.28 no.6
• /
• pp.511-516
• /
• 2003

Computer vision technology has been utilized as one of the most powerful tools to automate various agricultural operations. Though it has demonstrated successful results in various applications, the current status of technology is still for behind the human's capability typically for the unstructured and variable task environment. In this paper, a man-machine interactive hybrid decision-making system which utilized a concept of tole-operation was proposed to overcome limitations of computer image processing and cognitive capability. Tasks of greenhouse watermelon cultivation such as pruning, watering, pesticide application, and harvest require identification of target object. Identifying water-melons including position data from the field image is very difficult because of the ambiguity among stems, leaves, shades. and fruits, especially when watermelon is covered partly by leaves or stems. Watermelon identification from the cultivation field image transmitted by wireless was selected to realize the proposed concept. The system was designed such that operator(farmer), computer, and machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. And the developed system was composed of the image monitoring and task control module, wireless remote image acquisition and data transmission module, and man-machine interface module. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. Operator communicated with computer through touch screen interface. And then a sequence of algorithms to identify the location and size of the watermelon was performed based on the local image processing. And the system showed practical and feasible way of automation for the volatile bio-production process.