• Food Science of Animal Resources
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• v.41 no.4
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• pp.563-588
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• 2021

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.19-25
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• 2024

This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

• Parasites, Hosts and Diseases
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• v.53 no.4
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• pp.493-496
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• 2015

Toxoplasmosis, caused by Toxoplasma gondii, is a parasitic zoonosis with worldwide distribution. The present study investigated the prevalence of T. gondii in dogs in Zhanjiang city, southern China, using both serological and molecular detection. A total of 364 serum samples and 432 liver tissue samples were collected from the slaughter house between December 2012 and January 2013 and were examined for T. gondii IgG antibody by ELISA and T. gondii DNA by semi-nested PCR based on B1 gene, respectively. The overall seroprevalence of T. gondii IgG antibody was 51.9%, and T. gondii DNA was detected in 37 of 432 (8.6%) liver tissue samples. These positive DNA samples were analyzed by PCR-RFLP at 3'- and 5'-SAG2. Only 8 samples gave the PCR-RFLP data, and they were all classified as type I, which may suggest that the T. gondii isolates from dogs in Zhanjiang city may represent type I or type I variant. This study revealed the high prevalence of T. gondii infection in dogs in Zhanjiang city, southern China. Integrated measures should be taken to prevent and control toxoplasmosis in dogs in this area for public health concern.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3885-3906
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• 2020

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.

• Smart Structures and Systems
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• v.20 no.1
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• pp.75-83
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• 2017

Effectively monitoring the concrete cracks is an urgent question to be solved in the structural safety monitoring while cracks in hydraulic concrete structures are ubiquitous. In this paper, two experiments are designed based on the measuring principle of Pulse-Pre pump Brillouin Optical Time Domain Analysis (PPP-BOTDA) utilizing Brillouin optical fiber sensor to monitor concrete cracks. More specifically, "V" shaped optical fiber sensor is proposed to determine the position of the initial crack and the experiment illustrates that the concrete crack position can be located by the mutation position of optical fiber strain. Further, Brillouin distributed optical fiber sensor and preinstall cracks are set at different angles and loads until the optical fiber is fractured. Through the monitoring data, it can be concluded that the variation law of optical fiber strain can basically reflect the propagation trend of the cracks in hydraulic concrete structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2479-2487
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• 2009

Earlier researches on Sensor Networks preferred symmetric key-based authentication schemes in consideration of limitations in network resources. However, recent advancements in cryptographic algorithms and sensor-node manufacturing techniques have opened suggestion to public key-based solutions such as Merkle tree-based schemes. This paper proposes a new concept of public key-based authentication using Polynomial Secret Sharing that can be effectively applied to sensor networks and a detection of malicious node using the hash function. This scheme is based on exponential distributed data concept, a derivative from Shamir's (t,n) threshold scheme, in which the authentication of neighbouring nodes are done simultaneously while minimising resources of sensor nodes and providing network scalability.

• Bulletin of the Korean Chemical Society
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• v.35 no.11
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• pp.3326-3330
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• 2014

A quinoline-thiooxorhodamine conjugate fluorescent sensor (1) has been synthesized. Sensor 1 exhibits high selectivity and sensitivity to $Hg^{2+}$ in $H_2O$/DMSO (95/5, v/v, HEPES 20 mM, pH = 7.4) solution with fluorescence detection. Other tested metal ions do not induce any significant fluorescence intensity changes. Sensor 1 interacts with $Hg^{2+}$ through a 1:1 binding stoichiometry with a good anti-inference ability. In addition, fluorescent imaging of $Hg^{2+}$ in Hela cells is also successfully demonstrated.

• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2326-2330
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• 2014

A carbazole-based Schiff base CB2 was synthesized and applied as a highly selective and sensitive fluorescent probe for $Cu^{2+}$ in $H_2O$-DMSO (8/2, v/v, pH = 7.4) solution. CB2 exhibits an excellent selectivity to $Cu^{2+}$ over other examined metal ions with a prominent fluorescence "turn-on" at 475 nm. CB2 and $Cu^{2+}$ forms a 1:2 binding ratio complex with detection limit of $9.5{\mu}M$. In addition, the $Cu^{2+}$ recognition process is hardly interfered by other examined metal ions.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1327-1337
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• 2017

Photovoltaic (PV) systems are influenced by disproportionate impacts on energy production caused by frequent mismatch cases. The occurrence of multiple maximum power points (MPPs) adds complexity to the tracking process in various PV systems. However, current maximum-power point tracking (MPPT) techniques exhibit limited performance. This paper introduces an enhanced simulated annealing (ESA)-based GMPPT technique against multiple MPP issues in P-V curve with different PV system structures. The proposed technique not only distinguishes global and local MPPs but also performs rapid convergence speed and high tracking accuracy of irradiance changing and restart capability detection. Moreover, the proposed global maximum power tracking algorithm can be applied in the central converter of DMPPT and hybrid PV system to meet various application scenarios. Its effectiveness is verified by simulation and test results.

• Bulletin of the Korean Chemical Society
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• v.35 no.2
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• pp.489-493
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• 2014

A phenylbenzimidazole derivatized sensor (L) that behaves as a ratiometric fluorescent receptor for $Zn^{2+}$ in water has been described. In HEPES buffer at pH 7.4, sensor L displays a weak fluorescence emission band at 367 nm. Upon addition of $Zn^{2+}$, the emission intensity at 367 nm is decreased, concomitantly, a new emission band centered at 426 nm is developed, thus facilitates a ratiometric $Zn^{2+}$ sensing behavior. Sensor L binds $Zn^{2+}$ through a 1:1 binding stoichiometry with high selectivity over other metal cations. Sensor L displays a linear response to $Zn^{2+}$ concentration from 0 to $6.0{\times}10^{-5}M$, sensor L also exhibits high sensitivity to $Zn^{2+}$ with a detection limit of $3.31{\times}10^{-7}M$.