• International Journal of High-Rise Buildings
• /
• v.11 no.1
• /
• pp.61-68
• /
• 2022

The Address Jumeirah Resort is a mixed-use 77-story tower reaching a height of 301 meters with a slenderness ratio of 13.5:1. The development is situated in the Jumeirah Beach District and accommodates 217 key five-star hotel suites, 478 residential apartments, 444 serviced-branded apartments, retail shops, ballrooms and entertainment facilities around the premises. The building has over 242,000 m2 of usable area. The project is an award-winning development that broke multiple Guinness records. The focus of the paper is to present the challenges faced in the structural design and construction of the super tall tower and the highest occupiable skybridge in the world.

• International journal of advanced smart convergence
• /
• v.12 no.4
• /
• pp.88-97
• /
• 2023

Traffic flow prediction is of great significance in urban planning and traffic management. As the complexity of urban traffic increases, existing prediction methods still face challenges, especially for the fusion of spatiotemporal information and the capture of long-term dependencies. This study aims to use the fusion model of graph neural network to solve the spatio-temporal information fusion problem in traffic flow prediction. We propose a new deep learning model Spatio-Temporal Information Fusion using Graph Neural Networks (STFGNN). We use GCN module, TCN module and LSTM module alternately to carry out spatiotemporal information fusion. GCN and multi-core TCN capture the temporal and spatial dependencies of traffic flow respectively, and LSTM connects multiple fusion modules to carry out spatiotemporal information fusion. In the experimental evaluation of real traffic flow data, STFGNN showed better performance than other models.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.12
• /
• pp.3345-3363
• /
• 2023

Developers often use cross-platform frameworks to create mobile apps that can run on multiple platforms with minimal code changes. However, these frameworks may not suit all the needs of a specific app, so developers may also use native APIs to add platform-specific features. This method eventually dilutes the advantages of cross-platform development methodology that aims to reduce development costs and time, and often leads to a decision to return back to the original native mobile development methodology. In this study, we explore a different approach: combining different cross-platform tools to develop a storybook mobile app that meets various requirements. We have demonstrated that integrating two cross-platform solutions can be used reliably to develop complex mobile applications. However, we also report that this approach can introduce unforeseen issues such as sandbox redundancy, unexpected functional burdens, and redundant permission requests. Despite these challenges, we believe that combining two cross-platform solutions can be applied to a variety of functional and performance requirements, enabling the development of more sophisticated mobile applications at lower costs and with shorter development timelines than traditional mobile app development methodologies.

• Journal of Ginseng Research
• /
• v.48 no.3
• /
• pp.276-285
• /
• 2024

Diabetes mellitus (DM) is a systemic disorder of energy metabolism characterized by a sustained elevation of blood glucose in conjunction with impaired insulin action in multiple peripheral tissues (i.e., insulin resistance). Although extensive research has been conducted to identify therapeutic targets for the treatment of DM, its global prevalence and associated mortailty rates are still increasing, possibly because of challenges related to long-term adherence, limited efficacy, and undesirable side effects of currently available medications, implying an urgent need to develop effective and safe pharmacotherapies for DM. Phytochemicals have recently drawn attention as novel pharmacotherapies for DM based on their clinical relevance, therapeutic efficacy, and safety. Ginsenosides, pharmacologically active ingredients primarily found in ginseng, have long been used as adjuvants to traditional medications in Asian countries and have been reported to exert promising therapeutic efficacy in various metabolic diseases, including hyperglycemia and diabetes. This review summarizes the current pharmacological effects of ginsenosides and their mechanistic insights for the treatment of insulin resistance and DM, providing comprehensive perspectives for the development of novel strategies to treat DM and related metabolic complications.

• Journal of Advanced Navigation Technology
• /
• v.28 no.1
• /
• pp.155-158
• /
• 2024

Multipath, a major error source in urban GNSS positioning (global navigation satellite system), pose a challenge due to its site-dependent nature, varying with the user's signal reception environment. In our previous study, we introduced a technique generating GNSS multipath map in urban canyon. However, due to uncertainty in initial GNSS positions, applying multipath maps required generating multiple candidate positions. In this study, we present an efficient method for applying multipath maps by projecting the multipath correction in position domain. This approach effectively applies multipath maps, addressing the challenges posed by urban user position uncertainties.

• ETRI Journal
• /
• v.46 no.1
• /
• pp.137-153
• /
• 2024

This study introduces a new approach in Korean morphological analysis combining dictionary-based techniques with Transformer-based deep learning models. The key innovation is the use of a BERT-based reranking system, significantly enhancing the accuracy of traditional morphological analysis. The method generates multiple suboptimal paths, then employs BERT models for reranking, leveraging their advanced language comprehension. Results show remarkable performance improvements, with the first-stage reranking achieving over 20% improvement in error reduction rate compared with existing models. The second stage, using another BERT variant, further increases this improvement to over 30%. This indicates a significant leap in accuracy, validating the effectiveness of merging dictionary-based analysis with contemporary deep learning. The study suggests future exploration in refined integrations of dictionary and deep learning methods as well as using probabilistic models for enhanced morphological analysis. This hybrid approach sets a new benchmark in the field and offers insights for similar challenges in language processing applications.

• Biomolecules & Therapeutics
• /
• v.32 no.3
• /
• pp.291-300
• /
• 2024

Autosomal dominant polycystic kidney disease (ADPKD), a congenital genetic disorder, is a notable contributor to the prevalence of chronic kidney disease worldwide. Despite the absence of a complete cure, ongoing research aims for early diagnosis and treatment. Although agents such as tolvaptan and mTOR inhibitors have been utilized, their effectiveness in managing the disease during its initial phase has certain limitations. This review aimed to explore new targets for the early diagnosis and treatment of ADPKD, considering ongoing developments. We particularly focus on cell polarity, which is a key factor that influences the process and pace of cyst formation. In addition, we aimed to identify agents or treatments that can prevent or impede the progression of renal fibrosis, ultimately slowing its trajectory toward end-stage renal disease. Recent advances in slowing ADPKD progression have been examined, and potential therapeutic approaches targeting multiple pathways have been introduced. This comprehensive review discusses innovative strategies to address the challenges of ADPKD and provides valuable insights into potential avenues for its prevention and treatment.

• Communications for Statistical Applications and Methods
• /
• v.31 no.2
• /
• pp.191-202
• /
• 2024

The goal of this paper is to show how multivariate regression analysis with high-dimensional responses is facilitated by the response dimension reduction. Multivariate regression, characterized by multi-dimensional response variables, is increasingly prevalent across diverse fields such as repeated measures, longitudinal studies, and functional data analysis. One of the key challenges in analyzing such data is managing the response dimensions, which can complicate the analysis due to an exponential increase in the number of parameters. Although response dimension reduction methods are developed, there is no practically useful illustration for various types of data such as so-called large p-small n data. This paper aims to fill this gap by showcasing how response dimension reduction can enhance the analysis of high-dimensional response data, thereby providing significant assistance to statistical practitioners and contributing to advancements in multiple scientific domains.

• Journal of Microbiology and Biotechnology
• /
• v.30 no.9
• /
• pp.1335-1342
• /
• 2020

The identification of bacterial pathogens to humans is critical for environmental microbial risk assessment. However, current methods for identifying pathogens in environmental samples are limited in their ability to detect highly diverse bacterial communities and accurately differentiate pathogens from commensal bacteria. In the present study, we suggest an improved approach using a combination of identification results obtained from multiple databases, including the multilocus sequence typing (MLST) database, virulence factor database (VFDB), and pathosystems resource integration center (PATRIC) databases to resolve current challenges. By integrating the identification results from multiple databases, potential bacterial pathogens in metagenomes were identified and classified into eight different groups. Based on the distribution of genes in each group, we proposed an equation to calculate the metagenomic pathogen identification index (MPII) of each metagenome based on the weighted abundance of identified sequences in each database. We found that the accuracy of pathogen identification was improved by using combinations of multiple databases compared to that of individual databases. When the approach was applied to environmental metagenomes, metagenomes associated with activated sludge were estimated with higher MPII than other environments (i.e., drinking water, ocean water, ocean sediment, and freshwater sediment). The calculated MPII values were statistically distinguishable among different environments (p < 0.05). These results demonstrate that the suggested approach allows more for more accurate identification of the pathogens associated with metagenomes.

• Nutrition Research and Practice
• /
• v.13 no.3
• /
• pp.222-229
• /
• 2019

BACKGROUND/OBJECTIVES: Aging is an imperative problem for many countries in this century, and presents several challenges for the maintenance of good nutritional status. This study aims to assess the impact of socio-demographic factors, lifestyle and health status on the nutritional status among the elderly in Taiwan. SUBJECTS/METHODS: A cross-sectional study was carried out in Taiwan. Data were obtained from the Mei Jau Health Management Institution, which is a private health evaluation provider with multiple health screening centers in Taiwan and Asia. This study included 7947 adults aged 65 years or above. The data were extracted between 2001 to 2010. Nutritional status was assessed using anthropometric data, biochemical data and dietary intake information. RESULTS: Among the 7947 participants with mean age of 70.1 (SD = 4.5) years, 20.2%, 6.6%, 10.5% and 52.5% experienced underweight, protein malnutrition, anemia and inadequate dietary intake in the past month, respectively. Age was negatively correlated with body weight (r = -0.19, P = 0.02), body mass index (r = -0.41, P < 0.001), albumin level (r = -0.93, P < 0.001) and hemoglobin level (r = -0.30, P = 0.008). Age above 70 years, gender, unmarried status, retirement, lack of education, low family income, smoking, alcohol drinking, sleep duration of 6-8 hours, vegetarian diet, multiple medications, comorbidity and dysphagia were positively associated with malnutrition in older adults. CONCLUSIONS: Underweight and inadequate dietary intake are prevalent among the elderly in Taiwan. Vegetarian diet, multiple medications, comorbidity, dysphagia and lifestyle factors such as smoking, alcohol drinking and sleep duration of 6-8 hours are risk factors for undernutrition in older adults.