• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.183-188
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• 2023

Game object inheritance and multiple components allow for visualization of system architecture, good code reuse, and fast prototyping. On the other hand, objects are more likely to rely on high latency between game objects and components, static casts, and lots of references to things like null pointers. Therefore, It is important to design a game in such a way so that the dependency of objects on multiple classes could be reduced and existing codes could be reused. Therefore, we designed the game to make the classes more modular by applying Dependency Injection and the design patterns proposed by the Gang of Four. Since these dependencies are attributes of the game object and the injection occurs only in the initialization pass, there is little performance degradation or performance penalty in the game loop. Therefore, this paper proposed an efficient design method to effectively reuse APIs in the design and implementation of survival games.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.23-28
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• 2023

In a wireless smart utility network communication system, an asynchronous low power MAC is standardized and used according to IEEE 802.15.4e. An asynchronous MAC called RIT (Receiver Initiated Transmission) has a characteristic in which delay time and power consumption are greatly affected by a check-in interval (RIT period). By waking up from sleep every check-in interval and checking whether there is data to be received, power consumption in the receiving end can be drastically reduced, but power consumption in the transmitting end occurs due to an excessive wakeup sequence. If an excessive wake-up sequence is reduced by shortening the check interval, power consumption of the receiving end increases due to too frequent wake-up. In the RIT asynchronous MAC technique, power consumption performance according to traffic load and operation of check-in interval is analyzed and applied to Wi-SUN construction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.171-176
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• 2023

In the modern society of the 21st century, portable electronic products using secondary batteries are continuously becoming lightweight and miniaturized. And along with this trend, we are active in the era of the Fourth Industrial Revolution, where we collect and share information in our daily lives using wearable electronic devices. Therefore, the role of secondary batteries that can be recharged while using small home appliances and digital devices is increasingly important. Along with this increase, secondary battery performance tests require various test methods such as characteristics, lifespan, failure diagnosis, and recycling. In addition, the construction of a battery test system to ensure the safety and proper functioning of the battery, along with guidelines and correct basic knowledge are being considered. Therefore, in this paper, we will examine the characteristics of the secondary battery Li-ion battery according to the charging and discharging scenarios directly connected to the performance of the battery.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.223-228
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• 2023

According to the Korea Information Society Development Institute, OTT services grew at a rate of 33.4% in four yearsfrom 2017, when they were first launched.TheKorea Export-Import Bank announced in 2020 that the domestic OTT market was worth 780.1 billionKRW. This growth of the OTT market is expected to stimulate competition among OTT service platforms, and user satisfactionwithconvenience features, such as video recommendations, seems to be acting as an important factor in the competition.Currently, the OTT market uses a variety ofdata for customized recommendations, but the limitationis that it only uses datacollected within the app. Thereby we have proposed the use ofpersonal data collected outside the app for personalized recommendations, and the survey results showed that user satisfaction was 23.72% higher for recommended content based on the proposedmethod thanNetflix recommended content.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.51-56
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• 2022

With the development of industrialization, the amount of food and waste is rapidly increasing. Accordingly, the government is aware of the seriousness and is making efforts in various ways to reduce it. As a part of that, the volume-based food system was introduced, and although there were several trials and errors at the beginning of the introduction, it shows a reduction effect of 20 to 30%. These results suggest that the volume-based food system is being established. However, the waste is caused by foreign substances in the process of recycling resources by collecting them from the 1st collection to the 2nd collection process. Therefore, in this study, to solve these problems fundamentally, artificial intelligence is applied to classify foreign substances and improve them. Due to the nature of food waste, there is a limit to obtaining many images, so we compare several models based on CNNs and classify them as abnormal data, that is, CNN-based models are trained on various types of foreign substances, and then models with high accuracy are selected. We intend to prepare improvement measures for maintenance, such as manpower input to protect equipment and classify foreign substances by applying it.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.165-171
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• 2022

Human heart rate can be used to measure exercise intensity as an important indicator. If heart rate can be predicted, exercise can be performed more efficiently by regulating the intensity of exercise in advance. In this paper, a FitRec-based prediction model is proposed for estimating running heart rate for users. Endomondo data is utilized for training the proposed prediction model. The processing algorithms for time-series data, such as LSTM(long short term memory) and GRU(gated recurrent unit), are employed to compare their performance. On the basis of simulation results, it was demonstrated that the proposed model trained with running exercise performed better than the model trained with several cardiac exercises.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.107-112
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• 2022

In an embedded system such as a drone, it is difficult to store, transfer and analyze the entire hyper-spectral image to a server in real time because it takes a lot of power and time. Therefore, the hyper-spectral image data is transmitted to the server through dimension reduction or compression pre-processing. Feature selection method are used to send only the bands for analysis purpose, and these algorithms usually take a lot of processing time depending on the size of the image, even though the efficiency is high. In this paper, by improving the temporal disadvantage of the band selection algorithm, the time taken 24 hours was reduced to around 60-180 seconds based on the 40000*682 image resolution of 8GB data, and the use of 7.6GB RAM was significantly reduced to 2.3GB using 45 out of 150 bands. However, in terms of pixel classification performance, more than 98% of analysis results were derived similarly to the previous one.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.127-132
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• 2024

Recently, secondary batteries, commonly known as rechargeable batteries, find widespread applications across various industries. Particularly valued for their compact and lightweight characteristics, they play a crucial role in diverse portable electronic devices such as smartphones, laptops, and tablets, offering high energy density and efficient charge-discharge capabilities. Moreover, they serve as vital components in electric vehicles and contribute significantly to the field of renewable energy as part of Energy Storage Systems(ESS). However, despite advancements in this technology, issues such as reduced lifespan, cracking, damage, and even the risk of fire can arise due to excessive charging and discharging of secondary batteries. To address these challenges, Battery Management System(BMS) are employed to protect against overcharging and improve overall performance. Nevertheless, understanding the protective range settings of BMS using lithium-ion batteries, the most commonly used secondary batteries, and lead-acid batteries can be challenging. Therefore, this paper aims to utilize a battery charge-discharge tester and simulator to investigate the charging and discharging characteristics of lithium-ion batteries and lead-acid batteries, addressing the associated challenges of reduced lifespan, cracking, damage, and fire hazards in secondary batteries.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.69-76
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• 2024

This dissertation developed a five-story vertical livestock and fisheries farm (palm tower) model for sustainable food production in cities. It proposes to integrate marine farms, livestock raising, and pesticide-free automated crop farms to efficiently use resources and minimize environmental impact. Based on circular economy principles, the model can recycle the output of each part into resources from the other, increasing the efficiency of the system, utilizing idle space in the city, and promoting job creation and community participation. It can also contribute to reducing the carbon footprint of food production and improving food safety. In addition, the study explores how advanced agricultural technologies can be integrated into urban structures to address global food security challenges. This model presents potential solutions to the food crisis caused by climate change and population growth, and suggests a direction for the development of urban agriculture. Future research should address the technical and policy challenges for practical implementation.