• Journal of Communications and Networks
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• v.13 no.6
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• pp.567-582
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• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.27-35
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• 2001

This paper presents the assignment motion algorithm unrestricted for code optimization computationally. So, this algorithm is suppressed the unnecessary code motion in order to avoid the superfluous register pressure, we propose the assignment motion algorithm added to the final optimization phase. This paper improves an ambiguous meaning of the predicated. For mixing the basic block level analysis with the instruction level analysis, an ambiguity occurred in knoop’s algorithm. Also, we eliminate an ambiguity of it. Our proposal algorithm improves the runtime efficiency of a program by avoiding the unnecessary recomputations and reexecutions of expressions and assignment statements.

• International Journal of Railway
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• v.2 no.3
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• pp.99-106
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• 2009

Checks and tests before putting safety facilities into service as well as the results of these tests are essential, time consuming and may show great variations between each other. Economic constraints and the increasing complexity associated with the development of computerized tools tend to limit the capacity of the classic approval process (manual or automatic). A reduction of the validation cover rate could result in practice. This is not compatible with the French national plan to renew the interlocking systems of the national network. The method and the tool presented in this paper makes it possible to formally validate new computerized systems or evolutions of existing French interlocking systems with real-time functional interpreted Petri nets. The aim of our project is to provide SNCF with a method for the formal validation of French interlocking systems. A formal proof method by assertion, which is applicable to industrial automation equipment such as interlocking systems, and which covers equally the specification and its real software implementation, is presented in this paper. With the proposed method we completely verify that the system follows all safety properties at all times and does not show superfluous conditions: it replaces all the indoor checks (not the outdoor checks). The advantages expected are a significant reduction of testing time and of the related costs, an increase of the test coverage rate, an answer to the new demand of railway infrastructure maintenance engineering to modify and validate computerized interlocking systems. Formal methods mastery by infrastructure engineers are surely a key to prove that more safety is not necessarily more expensive.

• Nuclear Engineering and Technology
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• v.40 no.1
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• pp.93-98
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• 2008

Several adhesive tapes have been studied in terms of their suitability for securing gold wires into positions for neutron flux measurements in the reactor core and irradiation facilities surrounding the core of the Open Pool Australian Light water (OPAL) reactor. Gamma ray spectrometry has been performed on each irradiated tape in order to identify and quantify activated components. Numerous metallic impurities have been identified in all tapes. Calculations relating to both the effective neutron shielding properties of the tapes and the error in measurement of the $^{198}Au$ activity caused by superfluous activity due to residual tape have been made. The most important identified effects were the prolonged cooling times required before safe enough levels of radioactivity to allow handling were reached, and extra activity caused by residual tape when measured with an ionisation chamber. Knowledge of the most suitable tape can allow a minimal contribution due to these effects, and the use of gamma spectrometry in preference to ionisation chamber measurements of the flux wires is shown to make all systematic errors due to the tape completely negligible.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.223-224
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• 2021

Recently, k-farthest neighbor (kFN) queries have not as much attention as k-nearest neighbor (kNN) queries. Therefore, this study considers moving k-farthest neighbor (MkFN) queries for spatial network databases. Given a positive integer k, a moving query point q, and a set of data points P, MkFN queries can constantly retrieve k data points that are farthest from the query point q. The challenge with processing MkFN queries in spatial networks is to avoid unnecessary or superfluous distance calculations between the query and associated data points. This study proposes a batch processing algorithm, called MOFA, to enable efficient processing of MkFN queries in spatial networks. MOFA aims to avoid dispensable distance computations based on the clustering of both query and data points. Moreover, a time complexity analysis is presented to clarify the effect of the clustering method on the query processing time. Extensive experiments using real-world roadmaps demonstrated the efficiency and scalability of the MOFA when compared with a conventional solution.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.497-508
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• 2023

Manual estimation of rebar quantities by contractors often yields discrepancies between projected and actual amounts used in the construction phase, leading to cost inaccuracies and potential logistical challenges. To address these issues, there is a clear need for a method that allows precise estimation of rebar quantities during the design phase. Such a method would enhance contractor competitiveness during project bids, promote accurate cost calculations, and avert superfluous rebar purchases on-site. Given that columns are the primary structural components in reinforced concrete(RC) buildings and necessitate considerable amounts of rebar, this study focuses on creating an automated algorithm for estimating column rebar quantities. An analysis of the accurate quantities obtained via the study and those derived from manual estimation reveals a discrepancy of 0.346 tons or 2.056%. This comparison affirms the proposed algorithm's efficacy in eliminating errors from overestimation or underestimation of rebar quantities. The practical implications of this study are significant for construction companies as it fosters efficient and precise estimation of rebar quantities, ensuring compliance with related specifications and governing regulations.

• Asia pacific journal of information systems
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• v.33 no.2
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• pp.389-417
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• 2023

Social distancing required the use of doorstep delivery for nearly all purchases during the COVID-19 pandemic. Foreign users in Korea are forced to participate in superfluous tasks, leading to an increase in their anxiety and fatigue while online shopping. This study examines how digital shadow work stemming from the language barrier can affect the emotions and behaviors of foreign shoppers that use Korean shopping sites. By interviewing 37 foreign users in Korea, this draft examined their experiences, behaviors, and emotional output, classifying them into 14 codes and seven categories. Using grounded theory, we found that online shoppers' emotions, feelings, experiences, and decision making may be changed in the stages of the pre-use, use, and post-use activities. User responses regarding shadow work and related obstacles can be seen with the continue, discontinue, and optional (occasional use) of Korean online shopping sites. Pleasure and satisfaction come from high efficiency and privileges, whereas anger and disappointment come from poor self-confidence and pessimism. Furthermore, buyer behavior and product orientation are identified as intervening conditions, while the online vs. offline shopping experiences are identified as contextual conditions. In conclusion, language barriers and other factors make online shopping difficult for foreign shoppers, which negatively affects their psychological mechanisms and buying behaviors. The implications from the study findings and future research are also discussed.

• ALGAE
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• v.28 no.1
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• pp.1-29
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• 2013

The conjugating algae, an almost exclusively freshwater and extraordinarily diverse group of streptophyte green algae, are referred to a class generally known as the Conjugatophyceae in Central Europe and the Zygnematophyceae elsewhere in the world. Conjugatophyceae is widely considered to be a descriptive name and Zygnematophyceae ('Zygnemophyceae') a typified name. However, both are typified names and Conjugatophyceae Engler ('Conjugatae') is the earlier name. Additionally, Zygnemophyceae Round is currently an invalid name and is validated here as Zygnematophyceae Round ex Guiry. The names of orders, families and genera for conjugating green algae are reviewed. For many years these algae were included in the 'Conjugatae', initially used as the equivalent of an order. The earliest use of the name Zygnematales appears to be by the American phycologist Charles Edwin Bessey (1845-1915), and it was he who first formally redistributed all conjugating algae from the 'Conjugatae' to the orders Zygnematales and the Desmidiales. The family Closteriaceae Bessey, currently encompassing Closterium and Spinoclosterium, is illegitimate as it was superfluous when first proposed, and its legitimization is herein proposed by nomenclatural conservation to facilitate use of the name. The genus Debarya Wittrock, 1872 is shown to be illegitimate as it is a later homonym of Debarya Schulzer, 1866 (Ascomycota), and the substitute genus name Transeauina Guiry is proposed together with appropriate combinations for 13 species currently assigned to the genus Debarya Wittrock. The relationships between Mougeotia, Mougeotiopsis, Mougeotiella, and Transeauina require further resolution, as do many of the other genera referred to the Conjugatophyceae. Type species are designated for genera for which no types were formally selected previously. The number of currently described species of conjugating green algae in AlgaeBase is about 3,500, comprising about 10% of all algal species, with about one third of species referred to the Zygnematales and two-thirds to the Desmidiales. A corresponding 10% of all algal names at the species level and below have been applied to conjugating algae, although a large proportion of these are at the infraspecific level.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.11 s.158
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• pp.1589-1597
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• 2006

Nowadays, Korean consumers prefer drum-type washing machines to pulsator-type washers. Washing is a complex process involving the interaction of numerous physical and chemical influences. The main factors in the washing operations are the washing chemistry of the detergent along with the mechanical input, the wash temperature, and the time provided by the washing machine. Heavy-duty detergents that are used in drum-type washing machines contain different components from those used in vertical-axis washing machines. The bath ratio and the mechanical actions to which laundry is subjected are different between the drum-type and the vertical-axis washing machines. In this study we examined the effects of wash temperature, wash time, detergent concentration, and revolution speed on the removal of soils from artificially soiled cloths in a drum-type washing machine with heavy-duty commercial detergent. We used multiple regression analyses to find the relative importance of the factors and the optimum washing conditions. The results of these experiments showed that the washing temperature was the most important factor in the effective removal of most soils. This was followed by the washing time, the detergent concentration, and finally the revolution speed. In this study it was found that superfluous amounts of detergent did not sufficiently increase the soil removal rate. Koreans who are used to washing with cold water should increase the wash time to launder more efficiently.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.51-63
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• 2001

In supervised machine learning, an induction algorithm, which is able to extract rules from data with learning capability, provides a useful tool for data mining. Practical induction algorithms are known to degrade in prediction accuracy and generate complex rules unnecessarily when trained on data containing superfluous features. Thus it needs feature subset selection for better performance of them. In feature subset selection on the induction algorithm, wrapper method is repeatedly run it on the dataset using various feature subsets. But it is impractical to search the whole space exhaustively unless the features are small. This study proposes a heuristic method that uses sensitivity analysis of neural networks to the wrapper method for generating rules with higher possible accuracy. First it gives priority to all features using sensitivity analysis of neural networks. And it uses the wrapper method that searches the ordered feature space. In experiments to three datasets, we show that the suggested method is capable of selecting a feature subset that improves the performance of the induction algorithm within certain iteration.