• Journal of Families and Better Life
• /
• v.10 no.2
• /
• pp.99-112
• /
• 1992

This research was designed to illuminate that work domains and family domains are not separated but interacting spheres and to suggest efficient coping strategies than alleviate work/family role conflicts. The subjects of this study were 395 employed professional wives living in Seoul. Korea. Survey methods were questionnaires. Data analysis strategies were percentile, frequency, one-way-anova and multiple classification analysis. The results were as follows; 1)Employed wives experienced time-based conflicts and strain-based role conflicts. This finding supports the scarcity approach that multiple roles inevitably create strain. 2) Individual, family and work-related variables were predictors of work/family role conflicts. This findings indicate that work domains and family domains cannot be regraded as separated spheres. 3) Employed wives tried to meet all the given roles demands not by reducing role responsibilities, but by increasing the efficiency of role performance. This finding reflects the characteristics of employed wives who try to perform successfully all the responsibilities. 4)The negative correlation of coping strategies and work/family role conflicts suggests that strategies can function effectively in alleviating the work/family role conflicts.

• Journal of Communications and Networks
• /
• v.18 no.4
• /
• pp.658-669
• /
• 2016

The tremendous increase in mobile data traffic coupled with fierce competition in wireless industry brings about spectrum scarcity and bandwidth fragmentation. This inevitably results in asymmetric-valued long term evolution (LTE) spectrum allocation that stems from different timing for twice improvement in capacity between competing operators, given spectrum allocations today. This motivates us to study the economic effects of asymmetric-valued LTE spectrum allocation. In this paper, we formulate the interactions between operators and users as a hierarchical dynamic game framework, where two spiteful operators simultaneously make spectrum acquisition decisions in the upper-level first-price sealed-bid auction game, and dynamic pricing decisions in the lower-level differential game, taking into account user subscription dynamics. Using backward induction, we derive the equilibrium of the entire game under mild conditions. Through analytical and numerical results, we verify our studies by comparing the latest result of LTE spectrum auction in South Korea, which serves as the benchmark of asymmetric-valued LTE spectrum auction designs.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.32 no.2
• /
• pp.235-246
• /
• 2008

The aims of this study were to identify benefits sought for herbal cosmetics and its significance in influencing consumers' attitude and brand choice. A questionnaire was distributed to 900 women between 20 and 50 years old who had purchased herbal cosmetics from Nov. 6, 2006 to Dec. 15, 2006. SPSS 12.0 package was used for data analysis. Factor analysis, $X^2$-test, frequency, percentage, multiple regression analysis were utilized. The results were as follows: 1. The benefits that consumer was seeking from herbal cosmetics could be classified into 9 dimensions; special function, brand, nutritional reinforcement, economy, scarcity, feeling, fragrance, fashion and skin fitness. 2. All of the above benefits sought except economy and fashion had positive impact on consumers' attitude of herbal cosmetics. 3. There was a correlation between types of benefits sought by consumers and their brand selection.

• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1929-1934
• /
• 2022

Besides recent progresses in the physics-based modelling of fission gas and helium behaviour, the scarcity of experimental data concerning their combined behaviour (i.e., cocktail) hinders further model developments. For this reason, in this work, we propose a modelling methodology aimed at providing recommendations for accelerated experimental investigations. By exploring a wide range of annealing temperatures and cocktail compositions with a physics-based modelling approach we identify the most interesting conditions to be targeted by future experiments. To corroborate the recommendations arising from the proposed methodology, we include a sensitivity analysis quantifying the impact of the model parameters on fission gas and helium release, in conditions representative of high and low burnup.

• Journal of Digestive Cancer Research
• /
• v.11 no.3
• /
• pp.130-140
• /
• 2023

Gastric cancer (GC) is one of the most common malignant tumors worldwide, with a 5-year survival rate of < 40%. The diagnosis and treatment decisions of GC rely on human experts' judgments on medical images; therefore, the accuracy can be hindered by image condition, objective criterion, limited experience, and interobserver discrepancy. In recent years, several applications of artificial intelligence (AI) have emerged in the GC field based on improvement of computational power and deep learning algorithms. AI can support various clinical practices in endoscopic examination, pathologic confirmation, radiologic staging, and prognosis prediction. This review has systematically summarized the current status of AI applications after a comprehensive literature search. Although the current approaches are challenged by data scarcity and poor interpretability, future directions of this field are likely to overcome the risk and enhance their accuracy and applicability in clinical practice.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.1-8
• /
• 2022

This work provides a reliable and classified stocks dataset merged with Saudi stock news. This dataset allows researchers to analyze and better understand the realities, impacts, and relationships between stock news and stock fluctuations. The data were collected from the Saudi stock market via the Corporate News (CN) and Historical Data Stocks (HDS) datasets. As their names suggest, CN contains news, and HDS provides information concerning how stock values change over time. Both datasets cover the period from 2011 to 2019, have 30,098 rows, and have 16 variables-four of which they share and 12 of which differ. Therefore, the combined dataset presented here includes 30,098 published news pieces and information about stock fluctuations across nine years. Stock news polarity has been interpreted in various ways by native Arabic speakers associated with the stock domain. Therefore, this polarity was categorized manually based on Arabic semantics. As the Saudi stock market massively contributes to the international economy, this dataset is essential for stock investors and analyzers. The dataset has been prepared for educational and scientific purposes, motivated by the scarcity of data describing the impact of Saudi stock news on stock activities. It will, therefore, be useful across many sectors, including stock market analytics, data mining, statistics, machine learning, and deep learning. The data evaluation is applied by testing the data distribution of the categories and the sentiment prediction-the data distribution over classes and sentiment prediction accuracy. The results show that the data distribution of the polarity over sectors is considered a balanced distribution. The NB model is developed to evaluate the data quality based on sentiment classification, proving the data reliability by achieving 68% accuracy. So, the data evaluation results ensure dataset reliability, readiness, and high quality for any usage.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.7
• /
• pp.2304-2320
• /
• 2021

Intelligently detecting anomalies in health sensor data streams (e.g., Electrocardiogram, ECG) can improve the development of E-health industry. The physiological signals of patients are collected through sensors. Timely diagnosis and treatment save medical resources, promote physical health, and reduce complications. However, it is difficult to automatically classify the ECG data, as the features of ECGs are difficult to extract. And the volume of labeled ECG data is limited, which affects the classification performance. In this paper, we propose a Generative Adversarial Network (GAN)-based deep learning framework (called CAB) for heart arrhythmia classification. CAB focuses on improving the detection accuracy based on a small number of labeled samples. It is trained based on the class-imbalance ECG data. Augmenting ECG data by a GAN model eliminates the impact of data scarcity. After data augmentation, CAB classifies the ECG data by using a Bidirectional Long Short Term Memory Recurrent Neural Network (Bi-LSTM). Experiment results show a better performance of CAB compared with state-of-the-art methods. The overall classification accuracy of CAB is 99.71%. The F1-scores of classifying Normal beats (N), Supraventricular ectopic beats (S), Ventricular ectopic beats (V), Fusion beats (F) and Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively. Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.6
• /
• pp.110-120
• /
• 2008

Cognitive Radio (CR) technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problems. Spectrum sensing technology is one of the key challenge issues in cognitive radio technologies, which enables unlicensed users to identify and utilize vacant spectrum resource allocated to primary users. In this paper, the cooperative spectrum sensing technologies apply the ITS(Intelligent Transport System) and performance of signal detection analyzes. Then, we utilize the OR-rule and AND-rule for the cooperative signal detection. These data fusion rules improve the performance and reliability of the signal detection.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.2
• /
• pp.371-388
• /
• 2014

Cognitive Radio (CR) has been recently proposed as a promising technology to remedy the problems of spectrum scarcity and spectrum underutilization by enabling unlicensed users to opportunistically utilize temporally unused licensed spectrums in a cautious manner. In Cognitive Radio Ad Hoc Networks (CRAHNs), data routing is one of the most challenging tasks since the channel availability and node mobility are unpredictable. Moreover, the network performance is severely degraded due to large numbers of path failures. In this paper, we propose the Fault-Tolerant Cognitive Ad-hoc Routing Protocol (FTCARP) to provide fast and efficient route recovery in presence of path failures during data delivery in CRAHNs. The protocol exploits the joint path and spectrum diversity to offer reliable communication and efficient spectrum usage over the networks. In the proposed protocol, a backup path is utilized in case a failure occurs over a primary transmission route. Different cause of a path failure will be handled by different route recovery mechanism. The protocol performance is compared with that of the Dual Diversity Cognitive Ad-hoc Routing Protocol (D2CARP). The simulation results obviously prove that FTCARP outperforms D2CARP in terms of throughput, packet loss, end-to-end delay and jitter in the high path-failure rate CRAHNs.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.6
• /
• pp.2429-2435
• /
• 2012

Methyl isocyanate may have a role in cancer etiology, although the link is unclear. There is evidence in the literature that it can induce cancer in animals but the carcinogenic potency is weak. Pheochromocytoma of adrenal medulla and acinar cell tumors of pancreas have been observed in methyl isocyanate exposed animals. Conversely, emerging data from population-based epidemiological studies are contradictory since there is no evidence of such cancers in methyl isocyanate exposed humans. Recently, we reported a high prevalence of breast and lung cancers in such a population in Bhopal. In vitro findings appearing in the latest scientific literature suggest that genomic instability is caused by methyl isocyanate analogs in lung, colon, kidney, ovary epithelial cells, and that hepatocytes may undergo oncogenic transformation, have obvious implications. The conflicting information prompted us to present this update over the last three decades on methyl isocyanate-induced cancers after an extensive literature search using PubMed. While the pertinent literature remains limited, with a scarcity of strong laboratory analyses and field-epidemiological investigations, our succinct review of animal and human epidemiological data including in vitro evidences, should hopefully provide more insight to researchers, toxicologists, and public health professionals concerned with validation of the carcinogenicity of methyl isocyanate in humans.