• Korean journal of applied entomology
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• v.61 no.1
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• pp.129-142
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• 2022

Nutrition dictates nearly all biological processes and determines Darwinian fitness in all living organisms, including insects. Research on insect nutrition has a long history in the field of insect physiology and the importance of understanding insect nutrition has become increasingly apparent with the growing need for producing insects as food and feed. Nevertheless, it is only in recent years that we have witnessed a major breakthrough in our knowledge of insect nutrition. The multivariate, interactive, and dynamic nature of nutrition has long hampered our complete understanding of insect nutrition. However, the challenge posed by such nutritional complexity has been overcome with the advent of the Nutritional Geometry, which is an integrative and multidimensional framework that enabled us to model complex interactions between multiple nutrients. In this review, we introduce the basic concepts and principles of the Nutritional Geometry and describe how this innovative framework has revolutionized the field of insect nutrition and has placed nutrition in the centre of the interface between physiology, ecology, and evolution. We close this review by discussing potentially fertile research areas that can benefit tremendously from the application of this powerful nutritional paradigm in the future.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• Analytical Science and Technology
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• v.7 no.2
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• pp.213-224
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• 1994

Several isotopomers of cyclooctanone were prepared by selective deuterium substitution. Intrinsic isotope effects on $^{13}C$ NMR chemical shifts of these isotopomers were investigated systematically at low temperature. These istope effects were discussed in relation to the preferred boat-chair conformation of cyclooctanone. Deuterium isotope effects on NMR chemical shifts have been known for a long time. Especially in a conformationally mobile molecule, isotope perturbation could affect NMR signals through a combination of isotope effects on equilibria and intrinsic effects. The distinction between intrinsic and nonintrinsic effects is quite difficult at ambient temperature due to involvement of both equilibrium and intrinsic isotope effects. However if equilibria between possible conformers of cyclooctanone are slowed down enough on the NMR time scale by lowering temperature, it should be possible to measure intrinsic isotope shifts from the separated signals at low temperature. $^{13}C$ NMR has been successfully utilized in the study on molecular conformation in solution when one deals with stable conformers or molecules were rapid interconversion occurs at ambient temperature. The study of dynamic processes in general requires analysis of spectra at several temperature. Anet et al. did $^1H$ NMR study of cyclooctanone at low temperature to freeze out a stable conformation, but were not able initially to deduce which conformation was stable because of the complexity of alkyl region in the $^1H$ NMR spectrum. They also reported the $^1H$ and $^{13}C$ NMR spectra of the $C_9-C_{16}$ cycloalkanones with changing temperature from $-80^{\circ}C$ to $-170^{\circ}C$, but they did not report a variable temperature $^{13}C$ NMR study of cyclooctanone. For the analysis of the intrinsic isotope effect with relation to cylooctanone conformation, $^{13}C$ NMR spectra are obtained in the present work at low temperatures (up to $-150^{\circ}C$) in order to find the chemical shifts at the temperature at which the dynamic process can be "frozen-out" on the NMR time scale and cyclooctanone can be observed as a stable conformation. Both the ring inversion and pseudorotational processes must be "frozen-out" in order to see separate resonances for all eight carbons in cyclooctanone. In contrast to $^1H$ spectra, slowing down just the ring inversion process has no apparent effects on the $^{13}C$ spectra because exchange of environments within the pairs of methylene carbons can still occur by the pseudorotational process. Several isotopomers of cyclooctanone were prepared by selective deuterium substitution (fig. 1) : complete deuterium labeling at C-2 and C-8 positions gave cyclooctanone-2, 2, 8, $8-D_4$ : complete labeling at C-2 and C-7 positions afforded the 2, 2, 7, $7-D_4$ isotopomer : di-deuteration at C-3 gave the 3, $3-D_2$ isotopomer : mono-deuteration provided cyclooctanone-2-D, 4-D and 5-D isotopomers : and partial deuteration on the C-2 and C-8 position, with a chiral and difunctional case catalyst, gave the trans-2, $8-D_2$ isotopomer. These isotopomer were investigated systematically in relation with cyclooctanone conformation and intrinsic isotope effects on $^{13}C$ NMR chemical shifts at low temperature. The determination of the intrinsic effects could help in the analysis of the more complex effects at higher temperature. For quantitative analysis of intrinsic isotope effects, the $^{13}C$ NMR spectrum has been obtained for a mixture of the labeled and unlabeled compounds because the signal separations are very small.

• Korean Journal of Biological Psychiatry
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• v.5 no.1
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• pp.95-101
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• 1998

The changes of electroencephalogram(EEG) in patients with dementia of Alzheimer's type are most commonly studied by analyzing power or magnitude in traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to the chaos theory, irregular signals of EEG can be also resulted from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the largest Lyapunov exponent($L_1$). The authors have analyzed EEG epochs from three patients with dementia of Alzheimer's type and three matched control subjects. The largest $L_1$ is calculated from EEG epochs consisting of 16,384 data points per channel in 15 channels. The results showed that patients with dementia of Alzheimer's type had significantly lower $L_1$ than non-demented controls on 8 channels. Topographic analysis showed that the $L_1$ were significantly lower in patients with Alzheimer's disease on all the frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer's type have a decreased chaotic quality of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating the $L_1$ can be a promising tool for detecting relative changes in the complexity of brain dynamics.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Archives of design research
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• v.19 no.1 s.63
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• pp.201-214
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• 2006

Modern society is an age of vagueness and confusion. In addition, vagueness, complexity and variety are seen throughout art including modern philosophy, literature, and environmental design. A phenomenon like this shows that modern society has integrated different components as an organic relationship frequently crossing the boundary of fields. This feature can be regarded as hybrid related with accepting contradictory components and binding them into one under relationship between part and whole. As new design concept, presented are attitude to accept the two instead of attitude to select one of the alternatives, abundance instead of dearness, and ambiguity instead of simplicity. This principle has a crucial influence on creative design providing opposing contradiction and several alternative plans as non-deterministic form not completed one and, above all, useful information in mutual dependence and mutual relationship. When it comes to hybrid, therefore, a strategy is needed to consider layer of several fields getting out of standardizing space into a single space. As an event of this situation and concept, space experience means behaving freely based on experience of users' body. It can be known that this experience brings about users' more dynamic experience in comparison with the experience of seeing environmental design from a viewpoint of visual ism on the existing simplicity. Such a practical experience is subjective, synesthetic, and non-observational one. Therefore, hybrid has brought active users to the stage, which is distinguished from synesthesia felt through body's experience, not through observational attitude and visual space which achieve former balance and harmony with non-determination. That's because hybrid creatures are turning to a product resulted from creative imagination instead of from reappearance which makes text visualized. Such experience performed by user's active participation collapses the boundary between special elite-centered art and daily life and it is the present progressive form showing creation process of future events and new esthetic experience.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3159-3174
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• 1997

This paper reports a research to develop a methodology and a tool for understanding of very large and complex real-time software. The methodology and the tool mostly developed by the author are called the Architecture-based Real-time Software Understanding (ARSU) and the Software Re/reverse-engineering Environment (SRE) respectively. Due to size and complexity, it is commonly very hard to understand the software during reengineering process. However the research facilitates scalable re/reverse-engineering of such real-time software based on the architecture of the software in three-dimensional perspectives: structural, functional, and behavioral views. Firstly, the structural view reveals the overall architecture, specification (outline), and the algorithm (detail) views of the software, based on hierarchically organized parent-chi1d relationship. The basic building block of the architecture is a software Unit (SWU), generated by user-defined criteria. The architecture facilitates navigation of the software in top-down or bottom-up way. It captures the specification and algorithm views at different levels of abstraction. It also shows the functional and the behavioral information at these levels. Secondly, the functional view includes graphs of data/control flow, input/output, definition/use, variable/reference, etc. Each feature of the view contains different kind of functionality of the software. Thirdly, the behavioral view includes state diagrams, interleaved event lists, etc. This view shows the dynamic properties or the software at runtime. Beside these views, there are a number of other documents: capabilities, interfaces, comments, code, etc. One of the most powerful characteristics of this approach is the capability of abstracting and exploding these dimensional information in the architecture through navigation. These capabilities establish the foundation for scalable and modular understanding of the software. This approach allows engineers to extract reusable components from the software during reengineering process.