• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.404-412
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• 2022

The development in the field of the internet of things (IoT) have improved the quality of the life and also strengthened different areas in the society. All cities across the world are seeking to become smarter. The creation of a smart parking system is the essential use case in smart cities. In recent couple of years, the number of vehicles has increased significantly. As a result, it is critical to make the use of technology that enables hassle-free parking in both public and private spaces. In conventional parking systems, drivers are not able to find free parking space. Conventional systems requires more human interference in a parking lots. To manage these circumstances there is an intense need of IoT enabled parking solution that includes the well defined architecture that will contain the following components such as smart sensors, communication agreement and software solution. For implementing such a smart parking system in this paper we proposed a design of smart parking system and also compare it with convetional system. The proposed design utilizes sensors based on IoT and Data Mining techniques to handle real time management of the parking system. IoT enabled smart parking solution minimizes the human interference and also saves energy, money and time.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.7 no.1
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• pp.22-32
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• 2021

Fluorine-18 is by far the most widely exploited radionuclide in PET (positron emission tomography) radiochemistry. The physical half-life of fluorine-18 allows for chemical manipulation within a restricted timeframe, and cyclotron-produced fluoride ion has been widely applied in aliphatic and aromatic nucleophilic radiofluorinations to produce a variety of established radiotracers. Radiotracers have become more structurally complicated to address diverse targets in physiobiological systems. There is therefore an unmet need to complement traditional C-¹⁸F bond-forming radiofluorination with new and efficient radiolabeling techniques to tackle the myriad of possible chemical environments. This review discusses recent advances in organometallic fluorine-18 bond creation in ¹⁸F-radiochemistry. Although not widely employed, new radiolabeling strategies for constructing boron-¹⁸F, silicon-¹⁸F, aluminum-¹⁸F, and other metal-¹⁸F bonds are described in view of their potential use in the development of novel radiopharmaceuticals.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.49-62
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• 2023

There has been a rapid increase in the creation and alteration of new malware samples which is a huge financial risk for many organizations. There is a huge demand for improvement in classification and detection mechanisms available today, as some of the old strategies like classification using mac learning algorithms were proved to be useful but cannot perform well in the scalable auto feature extraction scenario. To overcome this there must be a mechanism to automatically analyze malware based on the automatic feature extraction process. For this purpose, the dynamic analysis of real malware executable files has been done to extract useful features like API call sequence and opcode sequence. The use of different hashing techniques has been analyzed to further generate images and convert them into image representable form which will allow us to use more advanced classification approaches to classify huge amounts of images using deep learning approaches. The use of deep learning algorithms like convolutional neural networks enables the classification of malware by converting it into images. These images when fed into the CNN after being converted into the grayscale image will perform comparatively well in case of dynamic changes in malware code as image samples will be changed by few pixels when classified based on a greyscale image. In this work, we used VGG-16 architecture of CNN for experimentation.

• Journal of Powder Materials
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• v.30 no.4
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• pp.310-317
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• 2023

Small-film-type ion sensors are garnering considerable interest in the fields of wearable healthcare and home-based monitoring systems. The performance of these sensors primarily relies on electrode capacitance, often employing nanocomposite materials composed of nano- and sub-micrometer particles. Traditional techniques for enhancing capacitance involve the creation of nanoparticles on film electrodes, which require cost-intensive and complex chemical synthesis processes, followed by additional coating optimization. In this study, we introduce a simple one-step electrochemical method for fabricating gold nanoparticles on a carbon nanotube (Au NP-CNT) electrode surface through cyclic voltammetry deposition. Furthermore, we assess the improvement in capacitance by distinguishing between the electrical double-layer capacitance and diffusion-controlled capacitance, thereby clarifying the principles underpinning the material design. The Au NP-CNT electrode maintains its stability and sensitivity for up to 50 d, signifying its potential for advanced ion sensing. Additionally, integration with a mobile wireless data system highlights the versatility of the sensor for health applications.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.163-175
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• 2022

Purpose - This study introduces a methodology for finding the optimal tracking error of active stock funds. Tracking error is commonly used in risk budgeting techniques as a concept of cost for alpha creation. Design/methodology/approach - This study uses a post-optimal smart beta portfolio that maximizes alpha under the given tracking error constraint. Findings - As a result of the analysis, the smart beta strategy that maximized alpha under the constraint of 0.15% daily tracking error shows the highest IR. This means the maximum theoretically achievable efficiency. In this regard, a fixed-effect panel regression analysis is conducted to evaluate the active efficiency of domestic stock funds. In addition to control variables based on previous studies, the effect of tracking error on alpha is analyzed. The alpha used in this model is calculated using the smart beta portfolio according to the size of the constraint of the tracking error as a benchmark. Contrary to theoretical estimates, in Korea, the alpha performance is maximized under a daily tracking error of 0.1%. This indicates that the active efficiency of domestic equity funds is lower than the theoretical maximum. Research implications or Originality - Based on this study, it is expected that it can be used for active risk management of pension funds and performance evaluation of active strategies.

• Journal of Distribution Science
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• v.22 no.1
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• pp.25-36
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• 2024

Purpose: The study attempts to explore the operational performance of the existing Malaysian logistics companies and the extent of their adoption of digitalization. The role of digitalization in enhancing the performance of companies in the logistics industry in Malaysia, for value creation, is the topic of study. Research design, data and methodology: A qualitative research method with a semi-structured interview approach was applied and judgmental sampling was used as the sampling technique to collect data. The research has chosen nine companies in the logistics industry in Peninsular Malaysia, with the interviews aimed at eleven members of top and middle-level management. Data analysis was performed using logical system techniques to examine and evaluate data, reorganizing feedback, comparing it with literature, and transforming it into structured, valuable information after interviews. Results: The study revealed mixed opinions on digitalization in logistics, despite its potential benefits such as improved operational efficiency, real-time information, and customer service. However, high costs may hinder financial performance and require revisions due to stakeholder involvement. Conclusions: The Malaysian logistics industry's adoption of digitalization is gaining traction, with most companies satisfied with their status. However, challenges like cost and inefficiency persist, prompting calls for government support to improve efficiency and reduce costs while ensuring sustainable transportation.

• International journal of advanced smart convergence
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• v.13 no.2
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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.

• Journal of Distribution Science
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• v.22 no.6
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• pp.83-93
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• 2024

Purpose: The present study is developed with the aim of mapping the trends in scientific production related to the implementation of artificial intelligence systems for agro-food supply chains. Research design, data and methodology: The methodological approach of the research shows a descriptive documentary process based on bibliometric techniques for mapping the main indicators of the area of knowledge through the establishment of a search equation in Scopus. Results: The research results show a total of 633 documents published between 2019 and 2023, with a great annual growth rate of 61.68%; In addition to a notable participation of countries such as India, China, the United Kingdom and the United States in the generation of new knowledge related to artificial intelligence applied to food distribution systems. Conclusions: It is concluded that the rise of new artificial intelligence technologies has shown extremely important results in the development of industries worldwide, with increasingly accelerated steps; which certainly translates into the creation of spaces and incentives in the production of research aimed at understanding these dynamics and in turn to propose new alternatives and proposals for the reduction of the large technological gaps that are present within the agro-food sector.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1687-1697
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• 2024

This study presents the Supporting platform for reactor fine flow characteristics calculation and analysis (Cilian platform), a user-friendly tool that supports the analysis and optimization of pressurized water reactor (PWR) cores with mixing vanes using computational fluid dynamics (CFD) computing. The Cilian platform allows for easy creation and optimization of PWR's main CFD calculation schemes and autonomously manages CFD calculation and analysis of PWR cores, reducing the need for human and computational resources. The platform's key features enable efficient simulation, rapid solution design, automatic calculation of core scheme options, and streamlined data extraction and processing techniques. The Cilian platform's capability to call external CFD software reduces the development time and cost while improving the accuracy and reliability of the results. In conclusion, the Cilian platform exemplifies an innovative solution for efficient computational fluid dynamics analysis of pressurized water reactor (PWR) cores. It holds great promise for driving advancements in nuclear power technology, enhancing the safety, efficiency, and cost-effectiveness of nuclear reactors. The platform adopts a modular design methodology, enabling the swift and accurate computation and analysis of diverse flow regions within core components. This design approach facilitates the seamless integration of multiple computational modules across various reactor types, providing a high degree of flexibility and reusability.

• Cartoon and Animation Studies
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• s.10
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• pp.1-16
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• 2006

This thesis aims to recall the importance of language in comics by studying comic strips in Korean daily newspapers: the comic strips are analyzed for rhetorical puns in its language text as they representatively show the value and role of language in comics. Moreover, Korean comic strips, as they developed into current affairs comics, acquired a stronger media characteristic of communicating information compared to other genres of cartoons. As a result, comics strips have become a genre where language plays an important role and the words needing to be able to convey the meaning quickly and implicitly. Due to tight control of national authority, the language technique developed into an indirect expression rather than a stronger direct imaging technique. The political oppression of the comic strip paradoxically brought on the rhetorical development in the creative techniques. Based on this analysis, the writer studied the rhetorical puns of the texts Korean comic strips by implementing the classification techniques of rhetoric expressions. As a result, through quotes and analysis of actual comic strips, the writer confirmed that Korean comic strips do actually show tremendously vast rhetorical puns in its language application techniques. The writer was also able to conclude that the rhetorical puns in comics were the force entertaining and impressing the readers, and also acting as the creative principle. Concluding this study, the writer emphasizes that language, not only in comic strips, is a combination of words and images and is also an important factor in all cartoons in general. Thus the thesis proposes that the training of humanistic thoughts and linguistic sensitivity are as important as learning to draw in the creation of cartoons.