• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4658-4679
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• 2017

Android is now the most popular smartphone platform and remains rapid growth. There are huge number of sensitive privacy information stored in Android devices. Kinds of methods have been proposed to detect Android malicious applications and protect the privacy information. In this work, we focus on extracting the fine-grained features to maximize the information of Android malware detection, and selecting the least joint features to minimize the number of features. Firstly, permissions and APIs, not only from Android permissions and SDK APIs but also from the developer-defined permissions and third-party library APIs, are extracted as features from the decompiled source codes. Secondly, feature selection methods, including information gain (IG), regularization and particle swarm optimization (PSO) algorithms, are used to analyze and utilize the correlation between the features to eliminate the redundant data, reduce the feature dimension and mine the useful joint features. Furthermore, regularization and PSO are integrated to create a new joint feature mining method. Experiment results show that the joint feature mining method can utilize the advantages of regularization and PSO, and ensure good performance and efficiency for Android malware detection.

• Korean Journal of Veterinary Service
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• v.36 no.2
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• pp.147-150
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• 2013

This study was carried out to investigate the prevalence of honeybee (Apis mellifera) disease in cheonan and asan area. From September to November in 2012, 33 samples were collected from 33 apiculture farms in the regions and reverse transcriptase-polymerase chain reaction (RT-PCR) and polymerase chain reaction (PCR) was conducted. Among 33 samples, prevalence rate was 42% in Sac Brood Virus (SBV), 52% in Nosema, 21% in American foulbrood (AFB), 70% in European foulbrood (EFB), 97% in Stonebrood, 3% in Chalkbrood. The result indicate that stonebrood was most prevalent disease in apiculture farms in cheonan and asan area.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.173-186
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• 2011

Due to the disadvantages of signature-based computer virus detection techniques, behavior-based detection methods have developed rapidly in recent years. However, current popular behavior-based detection methods only take API call sequences as program behavior features and the difference between API calls in the detection is not taken into consideration. This paper divides virus behaviors into separate function modules by introducing DLLs into detection. APIs in different modules have different importance. DLLs and APIs are both considered program calling resources. Based on the calling relationships between DLLs and APIs, program calling resources can be pictured as a tree named program behavior resource tree. Important block structures are selected from the tree as program behavior features. Finally, a virus detection model based on behavior the resource tree is proposed and verified by experiment which provides a helpful reference to virus detection.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.808-826
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• 2017

Most of conventional DSS's(Digital Signage Systems) have been built based on LAMP framework. Recent researches have shown that MEAN or MERN stack framework is simpler, more flexible, faster and more suitable for web-based application than LAMP stack framework. In this paper, we propose a design and implementation of MEARN (ME(A+R)N) stack-based real-time digital signage system, MR-DSS, which supports handing real-time tasks like urgent/instant messaging, system status monitoring and so on, efficiently in addition to conventional digital signage CMS service tasks. MR-DSCMS, CMS of MR-DSS, is designed to provide most of its normal services by REST APIs and real-time services like urgent/instant messaging by Socket.IO base under MEARN stack environment. In addition to architecture description of components composing MR-DSS, design and implementation issues are clarified in more detail. Through experimental testing, it is shown that 1) MR-DSS works functionally well, 2) the networking load performance of MR-DSCMS's REST APIs is better compared to a well-known open source Xibo CMS, and 3) real-time messaging via Socket.IO works much faster than REST APIs.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.71-80
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• 2013

Due to the increased use of mobile devices, there is a lot of discussion on mobile accessibility. Mobile accessibility means that everyone, who includes the disabled, the elderly people, can easily use the functions of mobile devices. In this paper, we presented and implemented a mobile interface using a speech I/O APIs to improve the accessibility. The proposed interfaces are implemented on Android platforms and they used speech recognition and text-to-speech APIs supported as built-in services. In addition, to facilitate the internet access for visually impaired or blind people, we also implemented the web browsing application (web reader).

• Journal of Apiculture
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• v.33 no.4
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• pp.227-237
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• 2018

The majority parasitic bee mites of Thailand in genus Tropilaelaps are infesting colonies of native bees (Apis dorsata) and introduced bees (A. mellifera). The investigation aims to study morphological and genetic variation of Tropilaelaps mites infected different hosts. Adult mites were collected from honey bee brood throughout Thailand. Traditional and geometrical morphometrics were measured on photograph by using TPS program. Additional, COI gene variations were examined by PCR-RFLP and nucleotides sequencing. Tree of mites relationships were constructed by NJ and MP assumptions. Morphometric results indicated T. mercedesae were major species infesting on A. dorsata and A. mellifera. Mophological variation represented at anal and epigynial plate, which the shape of the anal plate apex margin has been key character to identify between T. mercedesae (bell to blunt shape) and T. koenigerum (pear shape). However, the discriminant analysis suggested that geometric results were potential to classify Thai Tropilaelaps populations from different hosts better than traditional morphometric. Otherwise, PCR-RFLP clearly detected the site of Dra I and Xba I digestion of Thai Tropilaelaps morphotypes. The COI sequences of T. koenigerum were founded infesting only A. dorsata in Thailand and four sequences that related to the Thai T. mercedesae morphotypes. The NJ and MP tree were clearly classified Thai Tropilaelaps species which were suggested both from morphological and molecular analysis. This information might be basically of taxonomic status, but this should have implication for controlling these mites in Thailand and other countries.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.2
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• pp.75-82
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• 2009

In this paper, we test for security targeting on APIs of Windows as that is used by many people worldwide. In order to test APIs in DLL fils of Windows OS, we propose Automated Windows API Fuzz Testing(AWAFT) that can execute fuzz testing automatically and implemented the practical tool for AWAFT. AWAFT focuses on buffer overflows and parsing errors of function parameters. Using the tool, we found 177 errors in the system folder of Windows XP SP2. Therefore, AWAFT is useful for security testing of Windows APIs. AWAFT can be applied to libraries of third party software in Windows OS for the security.

• Journal of Apiculture
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• v.34 no.4
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• pp.305-313
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• 2019

Honey bees (Apis mellifera) forage in agricultural areas, and are exposed to diverse pesticide poisoning. Toxic effects on Apis mellifera of different groups of pesticides were tested in the laboratory; fungicide (Metconazole), herbicide (Glyphosate), acaricide (Amitraz), organophosphate insecticide(Fenitrothion) and neonicotinoid insecticides(Thiacloprid, Thiamethoxam, Imidacloprid, Acetamiprid, Dinotefuran and Clothianidin). Commercial formulations were serially diluted from the recommended concentration (RC) to 10-6 times to carry out feeding and contact tests. Toxicity was transformed into lethal dose (LD50) and hazard question (HQ). The acute toxicity of pesticides showed similar patterns between feeding and contact tests. But feeding tests showed greater toxic to honey bee than contact test. The organophosphate and nitro-neonicotinoid insecticides were highly toxic with HQ values ranging greater than 1. However, cyano-neonicotinoids of Thiacloprid and Acetamiprid showed low toxicity. Even at the RC, 24 hr mortalities were 18 and 30%. The acaricide (Amitraz) showed intermediate level of toxicity at RC but negligible at the concentration lower than 10-1 times. A fungicide(Metconazole) and herbicide(Glyphosate) showed minimal impacts. The results imply that the selective use of pesticides could help conservation of pollinators in agricultural production systems.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.79-85
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• 2021

Speech recognition technology refers to a technology in which a computer interprets the speech language spoken by a person and converts the contents into text data. This technology has recently been combined with artificial intelligence and has been used in various fields such as smartphones, set-top boxes, and smart TVs. Examples include Google Assistant, Google Home, Samsung's Bixby, Apple's Siri and SK's NUGU. Google and Daum Kakao offer free open APIs for speech recognition technologies. This paper selects three APIs that are free to use by ordinary users, and compares each recognition rate according to the three types. First, the recognition rate of "numbers" and secondly, the recognition rate of "Ga Na Da Hangul" are conducted, and finally, the experiment is conducted with the complete sentence that the author uses the most. All experiments use real voice as input through a computer microphone. Through the three experiments and results, we hope that the general public will be able to identify differences in recognition rates according to the applications currently available, helping to select APIs suitable for specific application purposes.

• Membrane Journal
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• v.32 no.5
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• pp.304-313
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• 2022

There is evidence that the presence of active pharmaceutical ingredient (APIs) are a danger for aquatic ecosystems and the human health. The presence of APIs such as tetracycline, an antibiotic, in water causes antimicrobial resistance (AMR) in microorganisms inflicting enormous costs on individuals and society. Membranes embedded with catalysts such as TiO₂ or bismuth based catalysts degrade and separate the organic effluents from wastewater. The photocatalytic activity of the catalysts can be enhanced with noble metal doping and addition of carbonaceous materials and formation of heterojunction with other semiconductors. The recollection of photoctalysts is possible through the immobilization of the photocatalysts in polymeric membranes. In this review, the degradation of antibiotics in water is discussed.