Lee, Yeong Jin;Huh, Keun Young;Kim, Inhea;Bui, Hai Dang
Journal of People, Plants, and Environment
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v.22
no.6
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pp.629-639
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2019
This study was conducted to analyze the characteristics of visitors to Hadong Bukcheon Iceland Poppy (BIP) Festival in order to sustain and enhance local flower festivals as a garden tourism. A questionnaire was distributed to BIP Festival visitors from May 18 to 27, 2018. A total of 167 responses were subject to be analyzed. Descriptive statistics analysis was mainly used and focused on describing the results in direct to explain the BIP Festival as a garden tourism. The number of female visitors and those in their 40s and 50s was high. Most of the visitors were found to live in other cities or counties near the area where BIP Festival was held and to prefer festivals held on the theme of nature and local features. The revisit rate and awareness of BIP Festival were 52.1% and 72.5% respectively. They mainly obtained the information on BIP Festival from people around them including family members, friends and colleagues, or from the Internet. Most answered that BIP festival was the most important destination on their trip. The major motives of BIP Festival visit included "spending quality time with family or friends (34.1%)", "appreciating Iceland poppy and gardens (25.6%)", and "enjoying oneself (tranquility, mental rest, etc.; 21.3%). As a companion, family and friends/colleagues accounted for 62.3% and 26.3% respectively. Most were found to spend 1-2 hours on visiting BIP festival and stay in Hadong county for a quarter of a day. In satisfaction of BIP Festival itself, "display and maintenance of Iceland poppy (3.76)" and "easiness of viewing (places arrangement, path, etc.) (3.57)" were high. In satisfaction of public relation and information, "service and hospitality of guides and desk clerks (3.66)" was high. The intention to revisit BIP Festival was nearly affirmative (3.73-3.80).
Hyun-Joong Kim;Hee-Won Yoon;Min-A Lee;Young-Hoon Kim;Chang Joo Lee
Journal of Microbiology and Biotechnology
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v.33
no.1
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pp.106-113
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2023
The supply of microbiological risk-free water is essential to keep food safety and public hygiene. And removal, inactivation, and destruction of microorganisms in drinking water are key for ensuring safety in the food industry. Ultraviolet-C (UV-C) irradiation is an attractive method for efficient disinfection of water without generating toxicity and adversely affecting human health. In this study, the disinfection efficiencies of UV-C irradiation on Shigella flexneri (Gram negative) and Listeria monocytogenes (Gram positive) at various concentrations in drinking water were evaluated using a water purifier. Their morphological and physiological characteristics after UV-C irradiation were observed using fluorescence microscopy and flow cytometry combined with live/dead staining. UV-C irradiation (254 nm wavelength, irradiation dose: 40 mJ/cm2) at a water flow velocity of 3.4 L/min showed disinfection ability on both bacteria up to 108 CFU/4 L. And flow cytometric analysis showed different physiological shift between S. flexneri and L. monocytogenes after UV-C irradiation, but no significant shift of morphology in both bacteria. In addition, each bacterium revealed different characteristics with time-course observation after UV-C irradiation: L. monocytogenes dramatically changed its physiological feature and seemed to reach maximum damage at 4 h and then recovered, whereas S. flexneri seemed to gradually die over time. This study revealed that UV-C irradiation of water purifiers is effective in disinfecting microbial contaminants in drinking water and provides basic information on bacterial features/responses after UV-C irradiation.
International Journal of Computer Science & Network Security
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v.23
no.3
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pp.67-80
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2023
Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.
Within the discipline of International Relations (IR), the literatures on global governance (GG) and great power management (GPM) at best ignore each other, and at worst treat the other as a rival or enemy. On the one hand, the GPM literature, like both realism in all its forms, and neoliberalism, takes for granted the ongoing, disproportionate influence of the great powers in the management of the international system/society, and does not look much beyond that. On the other hand, the GG literature emphasizes the roles of smaller states, non-state actors and intergovernmental organizations (IGOs), and tends to see great powers more as part of the problem than as part of the solution. This paper argues that the rise to prominence of a non-traditional security agenda, and particularly of human security, has triggered a de facto merger of GPM and GG that the IR literature usually treated as separate and often opposed theories. We use the Ebola crisis of 2014-15 to show how an issue framed as human security brought about a multi-actor response that combined the key elements of GPM and GG. The security framing overrode many of the usual inhibitions between great powers and non-state actors in humanitarian crises, including even the involvement of great power military forces. Through examining broadly the way in which the Ebola crisis is tackled, we argue that in an age of growing human security challenges, GPM and GG are necessarily and fruitfully merging. The role of great powers in this new human security environment is moving away from the simple means and ends of traditional GPM. Now, great powers require the ability to cooperate and coordinate with multiple-level actors to make the GG/GPM nexus more effective and sustainable. In doing so they can both provide crucial resources quickly, and earn respect and status as responsible great powers. IGOs provide legitimation and coordination to the GPM/GG package, and non-state actors (NSAs) provide information, specialist knowledge and personnel, and links into public engagement. In this way, the unique features of the Ebola crisis provide a model for how the merger of GPM and GG might be taken forward on other shared-fate threats facing global international society.
In this paper, we study image clustering without labeling using machine learning techniques. We proposed an unsupervised machine learning technique to design an image clustering model that automatically categorizes images into groups. Our experiment focused on inception convolutional neural networks (inception V3) with k-mean methods to cluster images. For this, we collect the public datasets containing Food-K5, Flowers, Handwritten Digit, Cats-dogs, and our dataset Rice Germination, and the owner dataset Palm print. Our experiment can expand into three-part; First, format all the images to un-label and move to whole datasets. Second, load dataset into the inception V3 extraction image features and transferred to the k-mean cluster group hold on six classes. Lastly, evaluate modeling accuracy using the confusion matrix base on precision, recall, F1 to analyze. In this our methods, we can get the results as 1) Handwritten Digit (precision = 1.000, recall = 1.000, F1 = 1.00), 2) Food-K5 (precision = 0.975, recall = 0.945, F1 = 0.96), 3) Palm print (precision = 1.000, recall = 0.999, F1 = 1.00), 4) Cats-dogs (precision = 0.997, recall = 0.475, F1 = 0.64), 5) Flowers (precision = 0.610, recall = 0.982, F1 = 0.75), and our dataset 6) Rice Germination (precision = 0.997, recall = 0.943, F1 = 0.97). Our experiment showed that modeling could get an accuracy rate of 0.8908; the outcomes state that the proposed model is strongest enough to differentiate the different images and classify them into clusters.
Journal of Korea Entertainment Industry Association
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v.13
no.7
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pp.145-153
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2019
As a category of film types, suspense thriller is constantly introducing a new element in the endless historical development and owns new vitality. The long-standing essence is that it doesn't vulgarly cater to the public, but stimulates more creativity. In this thesis, starting from theoretical foundation of creation in American contemporary suspense thriller, the author analyzes playwriting characteristics of suspense thriller and analyzes the exquisite description of characters' mental world and external presentation in detail from multiple structure modes to multiple perspectives. Also, the author comprehensively elaborates playwriting characteristic features of American contemporary suspense thriller by combining with playwriting theme, structure and viewpoint and takes the classic work of American suspense thriller by David Fincher as an example to analyze the unique value of thriller playwriting.
Journal of The Geomorphological Association of Korea
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v.18
no.4
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pp.35-57
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2011
Minor erosional forms in the bedrock river, like potholes, are not just research subject for the professional geomorphologis. In addition, these features attract general public and make them understand the social contribution and importance of geomorphologic research activities. In this paper, the studies on bedrock minor forms in Korea was reviewed. For further researches, some of major erosional processes and minor forms in bedrock rivers were discussed in detail. Cavitation, plucking, hydro-wedging, and abrasion by passing sediment particles are the major processes to create the longitudinal or transverse minor forms like pothole, furrows, flutes, and runnels. Especially the definition of furrows and runnels are explained to prevent the confusion with pothole, weathering pits and grooves. To make a progress in research on bedrock minor forms the quantitative relationship between the variables should be studied. New techniques for scientific estimation of erosion rates and exposure ages of bedrock surfaces should be used in this field.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.33
no.4
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pp.439-446
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2023
Objectives: The aims of this study are to investigate how X-rays are emitted to surrounding parts during the ion implantation process, to analyze these emissions in relation to the properties of the ion implanter equipment, and to estimate the resulting exposure dose. Eight ion implanters equipped with high-voltage electrical systems were selected for this study. Methods: We monitored X-ray emissions at three locations outside of the ion implanters: the accelerator equipped with a high-voltage energy generator, the impurity ion source, and the beam line. We used a Personal Portable Dose Rate and Survey Meter to monitor real-time X-ray levels. The SX-2R probe, an X-ray Features probe designed for use with the RadiagemTM meter, was also utilized to monitor lower ranges of X-ray emissions. The counts per second (CPS) measured by the meter were estimated and then converted to a radiation dose (𝜇Sv/hr) based on a validated calibration graph between CPS and μGy/hr. Results: X-rays from seven ion implanters were consistently detected in high-voltage accelerator gaps, regardless of their proximity. X-rays specifically emanated from three ion implanters situated in the ion box gap and were also found in the beam lines of two ion implanters. The intensity of these X-rays did not show a clear pattern relative to the devices' age and electric properties, and notably, it decreased as the distance from the device increased. Conclusions: In conclusion, every gap, in which three components of the ion implanter devices were divided, was found to be insufficiently shielded against X-ray emissions, even though the exposure levels were not estimated to be higher than the threshold.
KSII Transactions on Internet and Information Systems (TIIS)
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v.17
no.10
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pp.2627-2642
/
2023
Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.
This investigation delves into the adverse repercussions stemming from the impact of arsenic on steel pipes concealed within soil designated for rice cultivation. Simultaneously, the study aims to ascertain effective techniques for detecting arsenic in the soil and to provide strategies for mitigating the corrosion of steel pipes. The realm of nanotechnology presents promising avenues for addressing the intricate intersection of renewable energy, oil, and environmental pollution from a novel perspective. Nanostructured materials, characterized by distinct chemical and physical attributes, unveil novel pathways for pioneering materials that exert a substantial impact across diverse realms of food production, storage, packaging, and quality control. Within the scope of the food industry, the scope of nanotechnology encompasses processes, storage methodologies, packaging paradigms, and safeguards to ensure the safety of consumables. Of particular note, silver nanoparticles, in addition to their commendable antibacterial efficacy, boast anti-fungal and anti-inflammatory prowess, environmental compatibility, minimal irritability and allergenicity, resilience to microbial antagonism, thermal stability, and robustness. Confronting the pressing issue of arsenic contamination within both environmental settings and the food supply is of paramount importance to preserve public health and ecological equilibrium. In response, this study introduces detection kits predicated upon silver nanoparticles, providing an expeditious and economically feasible avenue for identifying arsenic concentrations ranging from 0.5 to 3 ppm within rice. Subsequent quantification employs Hydride Atomic Absorption Spectroscopy (HG-AAS), which features a detection threshold of 0.05 ㎍/l. A salient advantage inherent in the HG-AAS methodology lies in its capacity to segregate analytes from the sample matrix, thereby significantly reducing instances of spectral interference. Importantly, the presence of arsenic in the soil beneath rice cultivation establishes a causative link to steel pipe corrosion, with potential consequences extending to food contamination-an intricate facet embedded within the broader tapestry of renewable energy, oil, and environmental pollution.
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