• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.31-40
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• 2005

we propose an enhanced self-generation supervised algorithm that by combining an ART algorithm and the delta-bar-delta method. Form the input layer to the hidden layer, ART-1 and ART-2 are used to produce nodes, respectively. A winner-take-all method is adopted to the connection weight adaption so that a stored pattern for some pattern is updated. we test the recognition of student identification, a certificate of residence, and an identifier from container that require nodes of hidden layers in neural network. In simulation results, the proposed self-generation supervised learning algorithm reduces the possibility of local minima and improves learning speed and paralysis than conventional neural networks.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.191-198
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• 2003

Flat slab system has been adopted in many buildings constructed recently because of the advantage of reduced floor heights to meet the economical and architectural demands. Structural engineers commonly use the equivalent frame method(EFM) with equivalent beams proposed by Jacob S. Grossman in practical engineering for the analysis of flat slab structures. However, in many cases, when it is difficult to use the EFM, it is necessary to use a refined finite element model for an accurate analysis. But it would take significant amount of computational time and memory if the entire building structure were subdivided into a finer mesh. An efficient analytical method is proposed in this study to obtain accurate results in significantly reduced computational time. The proposed method employs super elements developed using the matrix condensation technique and fictitious beams are used in the development of super elements to enforce the compatibility at the interfaces of super elements. The stiffness degradation of flat slab system considered in the EFM was taken into account by reducing the elastic modulus of floor slabs in this study. Static and dynamic analyses of example structures were peformed and the efficiency and accuracy of the proposed method were verified by comparing the results with those of the refined finite element model and the EFM.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.851-861
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• 2021

This study aims to explore the specific risks in family small-medium enterprises (SMEs) and explain how they manage these risks to sustain and expand. In Indonesia, family business composes around 95 percent of all businesses and contributes about 80 percent to the country's economy. SMEs contribute approximately 57.8 percent to the nation's gross domestic product. Risk management poses challenges to the family business's survival, as family members do not take actions on risk. The assessment of risk is difficult and family businesses lack the ability to determine risk management priorities, including risk management review processes to evaluate risk, thus leading to family business failures. Applying the case study approach, in-depth semi-structured interviews were conducted in seven family SMEs comprising fifteen informants. Additionally, a focus group discussion consisting of three experts is conducted to reaffirm the findings from the interviews, observations, and field notes. The research identified the specific risks and how the family owners strategize to safeguard against these risks such as cash flow deficiency, operations dysfunction, cultural frailty, disharmony, transgenerational entrepreneurship failure, political uncertainty, and unprofessionalism. Comprehending these risks and their strategic decisions elucidated in this research could enable the family owners and key non-family professionals to work hand-in-hand to thrive over the family business risks together. Further avenues of research regarding family business risk management are also suggested in this study.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.199-206
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• 2021

This study investigated the main concerns and strategies in Indonesian large family businesses to undertake intergenerational succession effectively. The research data was obtained to shed light on the incumbents' mindsets, key preferences, and experiences during the succession process. Access to incumbents of large family businesses that are conglomerates is scant. The preceding survey research was conducted to sensitize with the intricacy of the intergenerational succession process in large family businesses before entailing interpretative phenomenology analysis of qualitative data from interviews, observations, and field notes by approaching family members in five conglomerate groups that have major impacts on the economy. The findings explicate the incumbents' preferred criteria in choosing their successors as well as their perceived concerns revolving around the appointment. Additionally, the incumbents' succession approaches such as apprentice learning by successors, adaptability to external forces by successors, nurturing the entrepreneurial spirit in successors, governance establishment in the firms, business interest stimulation in successors, role modeling by incumbents, and collaboration between family and key non-family members are elicited during the intergenerational succession process. This study concluded with noteworthy implications for incumbents and successors in large family businesses, especially providing explicit criteria and strategies to appoint suitable successors, and suggesting potential avenues for future research.

• Food Science of Animal Resources
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• v.42 no.5
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• pp.723-743
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• 2022

Beef muscles from mature cows and bulls, especially those originating from the extremities of the carcass, are considered as underutilized due to unsatisfactory palatability. However, beef from culled animals comprises a substantial proportion of the total slaughter in the US and globally. Modern consumers typically favor cuts suitable for fast, dry-heat cookery, thereby creating challenges for the industry to market inherently tough muscles. In general, cull cow beef would be categorized as having a lower extent of postmortem proteolysis compared to youthful carcasses, coupled with a high amount of background toughness. The extent of cross-linking and resulting insolubility of intramuscular connective tissues typically serves as the limiting factor for tenderness development of mature beef. Thus, numerous post-harvest strategies have been developed to improve the quality and palatability attributes, often aimed at overcoming deficiencies in tenderness through enhancing the degradation of myofibrillar and stromal proteins or physically disrupting the tissue structure. The aim of this review is to highlight existing and recent innovations in the field that have been demonstrated as effective to enhance the tenderness and palatability traits of mature beef during the chilling and postmortem aging processes, as well as the use of physical interventions and enhancement.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.25 no.2
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• pp.109-120
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• 2022

Purpose: While regurgitation is a common and often benign phenomenon in infants and younger children, it can also be a presenting symptom of gastroesophageal reflux disease (GERD). If untreated, GERD can lead to dangerous or lifelong complications. Clinical practice guidelines (CPGs) have been published to inform clinical diagnosis and management of pediatric GERD, but to date there has been no comprehensive review of guideline quality or methodological rigor. Methods: A systematic literature search was performed, and a total of eight CPGs pertaining to pediatric GERD were identified. These CPGs were evaluated using the Appraisal of Guidelines for Research and Evaluation instrument. Results: Three CPGs were found to be "high" quality, with 5 of 6 domains scoring >60%, one "average" quality, with 4 of 6 domains meeting that threshold, and the remaining four "low" quality. Conclusion: Areas of strength among the CPGs included "Scope and Purpose" and "Clarity and Presentation," as they tended to be well-written and easily understood. Areas in need of improvement were "Stakeholder Involvement," "Rigor of Development," and "Applicability," suggesting these CPGs may not be appropriate for all patients or providers. This analysis found that while strong CPGs pertaining to the diagnosis and treatment of pediatric GERD exist, many published guidelines lack methodological rigor and broad applicability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4456-4475
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• 2021

The system for re-identifying persons is used to find and verify the persons crossing through different spots using various cameras. Much research has been done to re-identify the person by utilising features with deep-learned or hand-crafted information. Deep learning techniques segregate and analyse the features of their layers in various forms, and the output is complex feature vectors. This paper proposes a distinctive framework called Integrated Level Feature Pattern (ILFP) framework, which integrates local and global features. A new deep learning architecture named modified XceptionNet (m-XceptionNet) is also proposed in this work, which extracts the global features effectively with lesser complexity. The proposed framework gives better performance in Rank1 metric for Market1501 (96.15%), CUHK03 (82.29%) and the newly created NEC01 (96.66%) datasets than the existing works. The mean Average Precision (mAP) calculated using the proposed framework gives 92%, 85% and 98%, respectively, for the same datasets.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.814-822
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• 2022

The deployment of sensors for Structural Health Monitoring requires a complicated network arrangement, ground truthing, and calibration for validating sensor performance periodically. Any conventional sensor on a structural element is also subjected to static and dynamic vertical loadings in conjunction with other environmental factors, such as brightness, noise, temperature, and humidity. A structural model with strain gauges was built and tested to get realistic sensory information. This paper investigates different deep learning architectures and algorithms, including unsupervised, autoencoder, and supervised methods, to benchmark blind drift calibration methods using deep learning. It involves a fully connected neural network (FCNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU) to address the blind drift calibration problem (i.e., performing calibrations of installed sensors when ground truth is not available). The results show that the supervised methods perform much better than unsupervised methods, such as an autoencoder, when ground truths are available. Furthermore, taking advantage of time-series information, the GRU model generates the most precise predictions to remove the drift overall.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.382-388
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• 2011

Being aware of the risk in advance necessitates intricate processes but is feasible. Although previous studies have demonstrated high accuracy, their performance still leaves room for improvement. A self-organizing feature map (SOM) based neurofuzzy model is developed in this study to provide another alternative for forecasting corporate financial distress. The model is designed to yield high prediction accuracy, as well as reference rules for evaluating corporate financial status. As a database, the study collects all financial reports from listed construction companies during the latest decade, resulting in over 1000 effective samples. The proportion of "failed" and "non-failed" companies is approximately 1:2. Each financial report is comprised of 25 ratios which are set as the input variable s. The proposed model integrates the concepts of pattern classification, fuzzy modeling and SOM-based optimization to predict corporate financial distress. The results exhibit a high accuracy rate at 85.1%. This model outperforms previous tools. A total of 97 rules are extracted from the proposed model which can be also used as reference for construction practitioners. Users may easily identify their corporate financial status by using these rules.

• Anatomy and Cell Biology
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• v.56 no.2
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• pp.288-292
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• 2023

In the foot, the lumbricals flex the metatarsophalangeal joints and extend the interphalangeal joints. The lumbricals are known to be affected in neuropathies. It is not known whether they may degenerate in normal individuals. Here, we report our findings of isolated degenerated lumbricals in seemingly normal feet of two cadavers. We explored lumbricals in 20 male and 8 female cadavers that were 60-80 years of age at the time of death. As part of routine dissection, we exposed the tendons of the flexor digitorum longus and the lumbricals. From the degenerated lumbricals, we took some tissue for paraffin-embedding, sectioning, and staining by hematoxylin and eosin, and Masson's trichrome technique. Of the 224 lumbricals studied, we found four apparently degenerated lumbricals in two male cadavers. In the first, the 2nd and 4th lumbricals in the left foot and the 2nd in the right foot were degenerated. In the second, the right 4th lumbrical was degenerated. Microscopically, the degenerated tissue was made of bundles of collagen. The lumbricals may have degenerated due to compression of their nerve supply. We cannot comment on whether the functionality of the feet were affected by these isolated degeneration of the lumbricals.