• 제목/요약/키워드: Scarcity

검색결과 542건 처리시간 0.024초

News-Finds-Me Perception in Digital Era: A Systematic Review from Retail Marketing Perspective

  • Doan Viet Phuong NGUYEN;Thanh-Binh PHUNG
    • 유통과학연구
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    • 제22권5호
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    • pp.11-26
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    • 2024
  • Purpose: The concept of News-finds-me Perception (NFMP) is gaining increasing scholarly interest due to its wide-ranging findings and implications in digital communications and marketing. From the retail marketing and communication approaches, social media is an effective tool to effectively communicate and persuade customers and stakeholders. Nevertheless, a scarcity of systematic review studies that systematically assemble prior research in the field is recognized. Consequently, this research investigated the Scopus database for articles pertaining to NFMP. Research design, data and methodology: The search was conducted on August 24, 2023, retrieving 46 documents. Following a data-cleaning process, 31 documents remained, providing evidence of the subject area's five-year development. The data was refined with OpenRefine and analyzed with VosViewer. Results: An overview of the subject's expansion is presented, which comprises the most cited documents, authors, organizations, journals, and countries. Furthermore, the investigation examines the influential studies that furnished scientists with essential knowledge and identify the current research trend of the research subject. Conclusions: Based on the results, the study proposes theoretical and practical implications, encouraging academics to further integrate the concept with various communication and marketing theories, as well as the retail marketing context, to gain a better understanding of its complex impacts.

Digital Twin based Household Water Consumption Forecasting using Agent Based Modeling

  • Sultan Alamri;Muhammad Saad Qaisar Alvi;Imran Usman;Adnan Idris
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.147-154
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    • 2024
  • The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

Design and Implementation of Fully Automated Solar Powered Irrigation System

  • Mohammad Fawzi Al Ajlouni;Essam Ali Al-Nuaimy;Salman Abdul-Rassak Sultan;Ali Hammod AbdulHussein Twaij;Al Smadi Takialddin
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.197-205
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    • 2024
  • This paper presents a fully automated stand-alone irrigation system with GSM (Global System for Mobile Communication) module. Solar energy is utilized to power the system and it is aimed to conserve water by reducing water losses. The system is based on a DC water pump that draws energy from solar panels along with automated water flow control using a moisture sensor. It is also fitted with alert and protection system that consists of an ultrasonic sensor and GSM messages sender that transmits signals showing the levels of the water in the reservoir and the battery charge. The control system is designed to stop the water pump from pumping water either when the battery level drops to equal or less than 10% of its full charge, or when the water level becomes less than 10 cm high in the reservoir. The experimental results revealed that the system is appropriate to use in remote areas with water scarcity and away from the national grid.

The status of clinical trials regarding root canal sealers

  • Ahmad AL Malak;Yasmina EL Masri; Mira Al Ziab;Nancy Zrara;Tarek Baroud;Pascale Salameh
    • Restorative Dentistry and Endodontics
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    • 제49권1호
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    • pp.5.1-5.11
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    • 2024
  • Objectives: This study aimed to present the results and analyses of clinical trials, including updates on the different functions of root canal sealers. Materials and Methods: In June 2023, we performed a comprehensive search of ClinicalTrials.gov to identify interventional clinical trials pertaining to root canal sealers. In total, 23 clinical trials conducted up to June 2023 were included in this study. Results: Approximately half of the trials (11 out of 23) were completed, while none were terminated or withdrawn. Each included trial had a minimum of 10 participants, with 11 trials having more than 100 participants. None of the assessed trials provided outcomes, and the majority (17 out of 23) lacked associated publications. In terms of geographic distribution, the USA and Canada did not contribute to any root canal sealer trials. Conclusions: This study highlights the lack of diversity in trial locations, the absence of reported results, and a scarcity of clinical trials examining the physicochemical properties of different sealers. Most published trials primarily focused on assessing the post-operative pain effect of these sealers, but no significant difference was found regarding post-operative pain control.

Predictive Model for Evaluating Startup Technology Efficiency: A Data Envelopment Analysis (DEA) Approach Focusing on Companies Selected by TIPS, a Private-led Technology Startup Support Program

  • Jeongho Kim;Hyunmin Park;JooHee Oh
    • International Journal of Advanced Culture Technology
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    • 제12권2호
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    • pp.167-179
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    • 2024
  • This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

Solution to promote the Circular Economy in Agriculture in Vietnam for Sustainable Development

  • Thi Huyen Tran;Hoang Tuan Nguyen;Quoc Cuong Nguyen
    • International journal of advanced smart convergence
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    • 제13권2호
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    • pp.276-283
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    • 2024
  • Currently, the overall tendency for green and sustainable economic development is creating a circular economy. In actuality, agricultural output is currently benefiting greatly from the growth of the circular economy. The creation of a circular economy helps address resource scarcity, save the environment, combat climate change, and increase economic efficiency. Vietnam's economy can grow quickly and sustainably by shifting to a circular economy production model. Comparing prior growth techniques to the digital age and implementing circular economic development connected with high technology will be a fantastic opportunity to boost growth efficiency. In actuality, Vietnam currently has a large number of agricultural circular economy models. These are models: Creating and using gas from waste and wastewater in livestock and farming; model combining cultivation, livestock, and aquaculture; agro-forestry model; garden-forest model; Circular model using agricultural by-products as a catalyst or creating other valuable products; model of moderation, linked to reducing the use of growth hormones, veterinary medications, pesticides, and artificial fertilizers in agriculture and animal husbandry. Unfortunately, there have been few studies and applications of the aforementioned models, which has made it difficult to build the agricultural sector sustainably. In this paper, we outline the current situation and propose solutions to develop a circular economy model in agriculture in Vietnam for sustainable development.

Multi-Purpose Hybrid Recommendation System on Artificial Intelligence to Improve Telemarketing Performance

  • Hyung Su Kim;Sangwon Lee
    • Asia pacific journal of information systems
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    • 제29권4호
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    • pp.752-770
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    • 2019
  • The purpose of this study is to incorporate telemarketing processes to improve telemarketing performance. For this application, we have attempted to mix the model of machine learning to extract potential customers with personalisation techniques to derive recommended products from actual contact. Most of traditional recommendation systems were mainly in ways such as collaborative filtering, which predicts items with a high likelihood of future purchase, based on existing purchase transactions or preferences for products. But, under these systems, new users or items added to the system do not have sufficient information, and generally cause problems such as a cold start that can not obtain satisfactory recommendation items. Also, indiscriminate telemarketing attempts can backfire as they increase the dissatisfaction and fatigue of customers who do not want to be contacted. To this purpose, this study presented a multi-purpose hybrid recommendation algorithm to achieve two goals: to select customers with high possibility of contact, and to recommend products to selected customers. In addition, we used subscription data from telemarketing agency that handles insurance products to derive realistic applicability of the proposed recommendation system. Our proposed recommendation system would certainly solve the cold start and scarcity problem of existing recommendation algorithm by using contents information such as customer master information and telemarketing history. Also. the model could show excellent performance not only in terms of overall performance but also in terms of the recommendation success rate of the unpopular product.

Mushroom consumption and cardiometabolic health outcomes in the general population: a systematic review

  • Jee Yeon Hong;Mi Kyung Kim;Narae Yang
    • Nutrition Research and Practice
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    • 제18권2호
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    • pp.165-179
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    • 2024
  • BACKGROUND/OBJECTIVES: Mushroom consumption, rich in diverse nutrients and bioactive compounds, is suggested as a potential significant contributor to preventing cardiometabolic diseases (CMDs). This systematic review aimed to explore the association between mushrooms and cardiometabolic health outcomes, utilizing data from prospective cohort studies and clinical trials focusing on the general population, with mushrooms themselves as a major exposure. SUBJECTS/METHODS: All original articles, published in English until July 2023, were identified through searches on PubMed, Ovid-Embase, and google scholar. Of 1,328 studies, we finally selected 5 prospective cohort studies and 4 clinical trials. RESULTS: Existing research is limited, typically consisting of 1 to 2 studies for each CMD and cardiometabolic condition. Examination of articles revealed suggestive associations in some cardiometabolic conditions including blood glucose (both fasting and postprandial), high-density lipoprotein cholesterol related indices, high-sensitivity C-reactive protein, and obesity indices (body weight, body mass index, and waist circumference). However, mushroom consumption showed no association with the mortality and morbidity of cardiovascular diseases, stroke, and type 2 diabetes, although there was a potentially beneficial connection with all cause-mortality, hyperuricemia, and metabolic syndrome. CONCLUSION: Due to the scarcity of available studies, drawing definitive conclusions is premature. Further comprehensive investigations are needed to clarify the precise nature and extent of this relationship before making conclusive recommendations for the general population.

Development of a link extrapolation-based food web model adapted to Korean stream ecosystems

  • Minyoung Lee;Yongeun Kim;Kijong Cho
    • 환경생물
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    • 제42권2호
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    • pp.207-218
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    • 2024
  • Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

Using No-Code/Low-Code Solutions to Promote Artificial Intelligence Adoption in Vietnamese Businesses

  • Quoc Cuong Nguyen;Hoang Tuan Nguyen;Jaesang Cha
    • International Journal of Internet, Broadcasting and Communication
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    • 제16권3호
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    • pp.370-378
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    • 2024
  • Recently, Artificial Intelligence (AI) has been emerging as a technology that has transformed and revolutionized various industries around the world. In recent years, businesses in Vietnam have also started to embrace AI applications to enhance their operations and gain a competitive edge in the market. As AI technologies continue to evolve rapidly, their impact on Vietnamese businesses is becoming increasingly profound. As artificial intelligence continues to progress across various fields, the need to democratize AI technology becomes increasingly clear. In a rapidly growing market like Vietnam, leveraging AI offers significant opportunities for businesses to improve operational efficiency, customer engagement, and overall competitiveness. However, significant barriers to AI adoption in Vietnam are the scarcity of skilled developers and the high cost of implementing traditional AI. No-code/low-code platforms offer an innovative solution that can accelerate AI adoption by making these technologies accessible to a wider audience. This article analyzes and understands the benefits of no-code/low-code solutions and proposes a roadmap for implementing no-code/low-code solutions in promoting AI applications in Vietnamese businesses.