• Journal of Microbiology and Biotechnology
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• v.9 no.6
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• pp.773-777
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• 1999

Scale-up experiments for hydrolysis of beef tallow, fat, and palm kernel with lipase derived from Candida cylindracea were carried out in 1-1, 100-1, and 10,000-1 reactors. The optimum agitation speed for the hydrolysis of the 1-1 reactor was investigated and found to be 350rpm, and this was a basis for the scale-up of agitation speed. The hydrolysis system in this work was the oil-water system in which the hydrolysis seems to process a heterogeneous reaction. An emulsion condition was the most important factor for determining the reaction rate of hydrolysis. Therefore, the scale-up of agitation speed was performed by using the power n = 1/3 in an equation of the rules of thumb method. The geometrical similarity for scaling-up turned out to be unsatisfactory in this study. Thus, the working volume per one agitator was used for the scale-up. In the case of scale-up from a 1-1 reactor to a 100-1 reactor, the hydrolysis of palm kernel was very much scaled-up by initiating the rules of thumb method. However, the hydrolysis of fat and beef tallow in a 100-1 reactor was a little higher than that of the 1-1 reactor because of the difference of geometrical similarity. The scale-up of hydrolysis from the 100-1 reactor to the 10,000-1 reactor was improved compared to that of the 1-1 to 100-1 reactor. The present results indicated that the scale-up of hydrolysis in the oil-water system by the rules of thumb method was more satisfactory under the condition of geometrical similarity. Even in the case where geometrical similarity was not satisfactory, the working volume per one agitator could be used for the scale-up of a heterogeneous enzyme reaction.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.253-257
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• 2000

the objective of this study is to design and evaluate a methodology for diagnosing the appendicitis in a fuzzy neural network that integrates the partition of input space by fuzzy entropy and the generation of fuzzy control rules and learning algorithm. In particular the diagnosis of appendicitis depends on the rule of thumb of the experts such that it associates with the region, the characteristics, the degree of the ache and the potential symptoms. In this scheme the basic idea is to realize the fuzzy rle base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by back propagation learning rule. To eliminate the number of the parameters of the rules, the output of the consequences of the control rules is expressed by the network's connection weights. As a result we obtain a method for reducing the system's complexities. Through computer simulations the effectiveness of the proposed strategy is verified for the diagnosis of appendicitis.

• Journal of the Korean Institute of Gas
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• v.24 no.2
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• pp.50-55
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• 2020

The heuristics accumulated in the field activities of firefighters were reviewed through big data analysis of fire occurrences in Gyeonggi-do and researched to be utilized for proper fire prevention activities according to time, day, and target through quantitative modeling. Empirical rules with high sympathy were collected through direct interviews with firefighters. Among them, the rule of thumb that "Friday is the most fire-prone" is considered to be the most important in terms of fire monitoring and prediction. A big data comparison analysis was conducted, including the number of fires and damages that occurred in Gyeonggi-do in 2018. Furthermore, fire occurrence patterns by region, day of the week, time of day, and building type were derived. Regarding empirical rules that have been validated through research, relatively inexperienced firefighters also can make decisions by relying on refined quantitative predictive modeling and empirical rules including local government and time-based factors that reflect big fire occurrence data.

• Explosives and Blasting
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• v.19 no.4
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• pp.31-36
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• 2001

This article was presented by the author at the ISEE\`s 27th Annual Conference on Explosives and Blasting Technique in January, 2001 in Orlando, Florida. This article has been updated from tits original version. The opinions and ideas expressed are not necessarily those of the International Society of Explosives Engineers or the editorial/publishing staff of the Journal of Explosives Engineering. Your esponse in form of letters to editor is encouraged.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2806-2825
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• 2018

Unsupervised learning has shown good performance on image, video and audio classification tasks, and much progress has been made so far. It studies how systems can learn to represent particular input patterns in a way that reflects the statistical structure of the overall collection of input patterns. Many promising deep learning systems are commonly trained by the greedy layerwise unsupervised learning manner. The performance of these deep learning architectures benefits from the unsupervised learning ability to disentangling the abstractions and picking out the useful features. However, the existing unsupervised learning algorithms are often difficult to train partly because of the requirement of extensive hyperparameters. The tuning of these hyperparameters is a laborious task that requires expert knowledge, rules of thumb or extensive search. In this paper, we propose a simple and effective unsupervised feature learning algorithm for image classification, which exploits an explicit optimizing way for population and lifetime sparsity. Firstly, a sparse target matrix is built by the competitive rules. Then, the sparse features are optimized by means of minimizing the Euclidean norm ($L_2$) error between the sparse target and the competitive layer outputs. Finally, a classifier is trained using the obtained sparse features. Experimental results show that the proposed method achieves good performance for image classification, and provides discriminative features that generalize well.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.631-639
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• 2010

The layout of haul routes within a construction site of large complex projects needs to be carefully determined as the productivity of earthwork activity heavily depends on the efficiency of the layout and the routes are not likely to change once they are settled. This paper aims to provide a construction planner with a reliable framework to create an efficient layout of haul routes within a large complex construction site. To construct the framework, five factors affecting haul route layout and the productivity of earthwork activity are described along with the associated rules of thumb recommended by design and field experts. In addition, a methodology based on spatial analysis using raster format in GIS is proposed to further increase haul route efficiency. The proposed planning framework enables a construction planner to easily find a more reliable route layout by thoroughly considering the key factors prior to setting up an earthmoving plan.

• Computers and Concrete
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• v.9 no.5
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• pp.327-340
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• 2012

The search for a design that meets both performance and safety, with minimal cost and lesser environmental impact was always the goal of structural engineers. In general, the design of conventional reinforced concrete structures is an iterative process based on rules of thumb established from the personal experience and intuition of the designer. However, such procedure makes the design process exhaustive and only occasionally leads to the best solution. In such context, this work presents the development and implementation of a mathematical formulation for obtaining optimal sections of reinforced concrete columns subjected to uniaxial flexural compression, based on the verification of strength proposed by the Brazilian standard NBR 6118 (ABNT 2007). To minimize the cost of the reinforced concrete columns, the Simulated Annealing optimization method was used, in which the amount and diameters of the reinforcement bars and the dimensions of the columns cross sections were considered as discrete variables. The results obtained were compared to those obtained from the conventional design procedure and other optimization methods, in an attempt to verify the influence of resistance class, variations in the magnitudes of bending moment and axial force, and material costs on the optimal design of reinforced concrete columns subjected to uniaxial flexural compression.

• Advances in Computational Design
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• v.1 no.3
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• pp.253-264
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• 2016

Based on the variation of strain along the cross section, any region in a structural member can be classified into two regions namely, Bernoulli's region (B-region) and Disturbed region (D-region). Since the variation of strain along the cross section for a B-region is linear, well-developed theories are available for their analysis and design. On the other hand, the design of D-region is carried out based on thumb rules and past experience due to the presence of nonlinear strain distribution. Strut-and-Tie method is a novel approach that can be used for the analysis and design of both B-region as well as D-region with equal importance. The strut efficiency factor (${\beta}_s$) is needed for the design and analysis of concrete members using Strut and Tie method. In this paper, equations for finding ${\beta}_s$ for bottle shaped struts in concrete deep beams (a D-region) with and without steel fibres are developed. The effects of transverse reinforcement on ${\beta}_s$ are also considered. Numerical studies using commercially available finite element software along with limited amount of experimental studies were used to find ${\beta}_s$.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.361-368
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• 2002

This paper presents a new data path synthesis algorithm which takes into account simultaneously three important design criteria: testability, design area, and total execution time. We define a goodness measure on the testability of a circuit based on three rules of thumb introduced in prior work on synthesis for testability. We then develop a stepwise refinement synthesis algorithm which carries out the scheduling and allocation tacks in an integrated fashion. Experimental results for benchmark and other circuit examples show that we are able to enhance the testability of circuits with very little overheads on design area and execution time.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.155-178
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• 2010

Assessment of information credibility is a ubiquitous human activity given that people constantly make decisions and selections based on the value of information in a variety of information seeking and use contexts. Today, people are increasingly engaging in diverse online activities beyond searching for and reading information, including activities such as creating, tagging and rating content, shopping, and listening to and watching multimedia content. The Web 2.0 environment presents new challenges for people because the burden of information evaluation is shifted from professional gatekeepers to individual information consumers. At the same time, however, it also provides unprecedented opportunities for people to use tools and features that help them to make informed credibility judgments by relying on other people's ratings and recommendations. This paper introduces fundamental notions and dimensions of credibility, and contends that credibility assessment can be best understood with respect to human information behavior because it encompasses both the level of effort people exert as well as the heuristics they employ to evaluate information. The paper reports on a survey study investigating people's credibility judgments with respect to online information, focusing on the constructs, heuristics, and interactions involved in people's credibility assessment processes within the context of their everyday life information activities. Using an online activity diary method, empirical data about people's online activities and their associated credibility assessments were collected at multiple points throughout the day for three days. The results indicate that distinct credibility assessment heuristics are emerging as people engage in diverse online activities involving more user-generated and multimedia content. A heuristic approach suggests that people apply mental shortcuts or rules of thumb in order to minimize the amount of cognitive effort and time required to make credibility judgments. The paper discusses why a heuristic approach is key to reaching a more comprehensive understanding of people's credibility assessments within the information-abundant online environment.