Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrit...
Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.
Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher educ...
Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education.
Agility Assessment (AA) comprises tools, assessment techniques, and frameworks that focus on indicating how a company or a team is applying agile techniques and eventually pointing out problems in adopting agile pract...
The global requirement for sustainable energy supply to enhance industrial productivity and reduce production costs has focused researchers’ attention to renewable energy in recent years. Solar energy mitigates the d...
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The global requirement for sustainable energy supply to enhance industrial productivity and reduce production costs has focused researchers’ attention to renewable energy in recent years. Solar energy mitigates the dangers connected with the use of fossil fuels in electricity generation. This work is set to evaluate the heat transmission capacities of Williamson hybrid nanofluid flow across a flat plate with viscous dissipation and heat source. The mathematical model explaining the flow interaction of Williamson hybrid nanofluid, combining viscous dissipation, heat source, and temperature-variation thermal conductivity and viscosity, is created using conservation laws. The specified system of non-linear coupled partial differential equations undergoes non-similarity transformation. The resulting non-dimensional model is solved using the bivariate spectral weighted residual method. The accuracy of the method is proven by comparing obtained results with those in the literature, and a good agreement is observed. Graphs are utilized to explain the thermophysical properties that are being considered. The results show that the fluid temperature rises when there is a source of heating and viscous dissipation. The velocity and the fluid parameter (We) have an inverse connection, whereas the temperature of the fluid has the opposite impact. Moreover, when nanoparticles are present, the thermal boundary layer rises along with the nanoparticles, thickening the velocity boundary layer and decreasing fluid velocity. Findings also show that for the Vd∈[0.1,0.5], the skin drag force and Nusselt number retard by 0.64%,14.06% for the shrinking sheet and 0.21%,6.57% for the stretching sheet respectively. In the same vein, an 100% surge in the porosity parameter escalate the skin friction coefficient by 19.13% and 26.91% and the Nusselt number by 4.92% and 2.06% respectively for both the contracting and elastic sheet. The findings in the research will provide more insight in the desig
While several content management systems (CMS) and audience analytics tools are available for digital signage in the market, they are often sold separately and can be expensive. Therefore, this project aims to design ...
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This paper introduces a logic with a class of social network models that is based on standard Linear Temporal Logic (LTL), leveraging the power of existing model checkers for the analysis of social networks. We provid...
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Computational music research plays a critical role in advancing music production, distribution, and understanding across various musical styles in the world. Despite the immense cultural and religious significance, th...
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This study aims to develop a system for extracting crucial information from tire sidewalls using Optical Character Recognition (OCR). Initially, images of tire were captured manually by smartphone cameras, including R...
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ISBN:
(数字)9798331519643
ISBN:
(纸本)9798331519650
This study aims to develop a system for extracting crucial information from tire sidewalls using Optical Character Recognition (OCR). Initially, images of tire were captured manually by smartphone cameras, including Redmi 9T, iPhone 11, and Galaxy S23 Ultra. The captured images are then transferred to a computer for storage. Subsequently, these images were cropped according to the boundaries identified by Hough Circle Transform (HCT). The cropped images were then further pre-processed. During the pre-processing phase, geometrical transformation and image sharpening techniques are applied to enhance the clarity and readability of the text images. The text is then extracted using Google Vision, with the extracted text categorized by size, DOT, brand and pattern. The results indicated that the effectiveness of image pre-processing was constrained by the accuracy of circle detection, which reached a maximum rate of 87.1%. This causes parts of the text to be cut out inaccurately, leading to a suboptimal extraction accuracy of 55.65%. It is also observed that the Redmi 9T camera produced inconsistent results compared to other devices. Specifically, the iPhone 11 and Samsung Galaxy S23 Ultra demonstrated superior extraction accuracies of 69.71% and 66.37%, respectively, whereas the Redmi 9T achieved a lower extraction accuracy of 37.76%.
In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically ind...
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In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically independent and identically distributed $(iid)$ assumptions on the aforementioned random variables overestimate the variability of high-frequency characteristics, compared with considering all fluctuation factors simultaneously. Notably, the random nanosized metal grains dominates the variations of voltage gain, cut-off frequency, and 3dB frequency because the random work functions strongly alter the channel surface potential.
In this paper, for the first time, deep learning (DL) based artificial neural network (ANN) is applied to model the effects of various random variations: work function fluctuation, random dopant fluctuation, and inter...
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