This study is related to a system that enables elderly people to communicate interactively with young people who use existing message exchange services by simply speaking to an avatar on a tablet PC, without having to...
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Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among th...
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One way to save time and resources in the human recruitment and hiring process is to post open job positions on the Internet, but the overload of applications creates challenges for hiring managers and companies to se...
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A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches...
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The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict su...
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The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict sugar content by considering uncertainty factors. A hybrid model combining fuzzy subtractive clustering, and a fuzzy inference system is proposed to predict sugar content. The clustering results using silhouette and fuzzy subtractive clustering successfully identified 6 cluster centres from 2225 datasets collected in a sugar industry in East Java Province. The hybrid inference engine model is designed with fuzzy rules derived from the clustered data. Two inference models are developed: triangular and Gaussian fuzzy numbers. The testing results indicate that the hybrid model with triangular fuzzy numbers shows the smallest error with an R2 value of 0.95. This model is possible to applied in the sugar industry for decision makers in improving productivity with taking attention into uncertain factors influencing sugar content.
This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square wa...
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In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest ***,effective design and ...
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In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest ***,effective design and planning for estimating heating load(HL)and cooling load(CL)for energy saving have become *** this vein,efforts have been made to predict the HL and CL using a univariate ***,this approach necessitates two models for learning HL and CL,requiring more computational ***,the one-dimensional(1D)convolutional neural network(CNN)has gained popularity due to its nominal computa-tional complexity,high performance,and low-cost hardware *** this paper,we formulate the prediction as a multivariate regression problem in which the HL and CL are simultaneously predicted using the 1D *** the building shape characteristics,one kernel size is adopted to create the receptive fields of the 1D CNN to extract the feature maps,a dense layer to interpret the maps,and an output layer with two neurons to predict the two real-valued responses,HL and *** the 1D data are not affected by excessive parameters,the pooling layer is not applied in this ***,the use of pooling has been questioned by recent *** performance of the proposed model displays a comparative advantage over existing models in terms of the mean squared error(MSE).Thus,the proposed model is effective for EPB prediction because it reduces computational time and significantly lowers the MSE.
This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, sta...
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Unmanned aerial vehicles (UAVs) are a valuable source of data for a wide range of real-time applications, due to their functionality, availability, adaptability, and maneuverability. Working as mobile sensors, they ca...
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LoRa's biggest advantage is its flexibility, which is the ability to increase or decrease data rate and range while decreasing or increasing sensitivity. Whenever propagation conditions change frequently, this fun...
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