• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.19-28
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• 2019

In this paper, an online video summarization algorithm based on multiple object detection is proposed. As crime has been on the rise due to the recent rapid urbanization, the people's appetite for safety has been growing and the installation of surveillance cameras such as a closed-circuit television(CCTV) has been increasing in many cities. However, it takes a lot of time and labor to retrieve and analyze a huge amount of video data from numerous CCTVs. As a result, there is an increasing demand for intelligent video recognition systems that can automatically detect and summarize various events occurring on CCTVs. Video summarization is a method of generating synopsis video of a long time original video so that users can watch it in a short time. The proposed video summarization method can be divided into two stages. The object extraction step detects a specific object in the video and extracts a specific object desired by the user. The video summary step creates a final synopsis video based on the objects extracted in the previous object extraction step. While the existed methods do not consider the interaction between objects from the original video when generating the synopsis video, in the proposed method, new object clustering algorithm can effectively maintain interaction between objects in original video in synopsis video. This paper also proposed an online optimization method that can efficiently summarize the large number of objects appearing in long-time videos. Finally, Experimental results show that the performance of the proposed method is superior to that of the existing video synopsis algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1726-1743
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• 2014

DDoS (Distributed Denial of Service) has been a continuous threat to the cyber world with the growth in cyber technology. This technical evolution has given rise to a number of ultra-sophisticated ways for the attackers to perform their DDoS attack. In general, the attackers who generate the denial of service, use the vulnerabilities of the TCP. Some of the vulnerabilities like SYN (synchronization) flooding, and IP spoofing are used by the attacker to create these Distributed Reflected Denial of Service (DrDoS) attacks. An attacker, with the assistance of IP spoofing creates a number of attack packets, which reflects the flooded packets to an attacker's intended victim system, known as the primary target. The proposed scheme, Efficient Spoofed Flooding Defense (ESFD) provides two level checks which, consist of probing and non-repudiation, before allocating a service to the clients. The probing is used to determine the availability of the requested client. Non-repudiation is taken care of by the timestamp enabled in the packet, which is our major contribution. The real time experimental results showed the efficiency of our proposed ESFD scheme, by increasing the performance of the CPU up to 40%, the memory up to 52% and the network bandwidth up to 67%. This proves the fact that the proposed ESFD scheme is fast and efficient, negating the impact on the network, victim and primary target.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.9-15
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• 2013

Recently, Intrusion detection system is an important technology in computer network system because of has seen a dramatic increase in the number of attacks. The most of intrusion detection methods do not detect intrusion on real-time because difficult to analyze an auditing data for intrusions. A network intrusion detection system is used to monitors the activities of individual users, groups, remote hosts and entire systems, and detects suspected security violations, by both insider and outsiders, as they occur. It is learns user's behavior patterns over time and detects behavior that deviates from these patterns. In this paper has rule-based component that can be used to encode information about known system vulnerabilities and intrusion scenarios. Integrating the two approaches makes Intrusion Detection System a comprehensive system for detecting intrusions as well as misuse by authorized users or Anomaly users (unauthorized users) using RFM analysis methodology and monitoring collect data from sensor Intrusion Detection System(IDS).

• Journal of Microbiology and Biotechnology
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• v.31 no.5
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• pp.705-709
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• 2021

Porphyromonas gingivalis (P. gingivalis) is a major bacterial pathogen that causes periodontitis, a chronic inflammatory disease of tissues around the teeth. Periodontitis is known to be related to other diseases, such as oral cancer, Alzheimer's disease, and rheumatism. Thus, a precise and sensitive test to detect P. gingivalis is necessary for the early diagnosis of periodontitis. The objective of this study was to optimize a rapid visual detection system for P. gingivalis. First, we performed a visual membrane immunoassay using 3,3',5,5'-tetramethylbenzidine (TMB; blue) and coating and detection antibodies that could bind to the host laboratory strain, ATCC 33277. Antibodies against the P. gingivalis surface adhesion molecules RgpB (arginine proteinase) and Kgp (lysine proteinase) were determined to be the most specific coating and detection antibodies, respectively. Using these two selected antibodies, the streptavidin-horseradish peroxidase (HRP) reaction was performed using a nitrocellulose membrane and visualized with a detection range of 10³-10⁵ bacterial cells/ml following incubation for 15 min. These selected conditions were applied to test other oral bacteria, and the results showed that P. gingivalis could be detected without cross-reactivity to other bacteria, including Streptococcus mutans and Escherichia fergusonii. Furthermore, three clinical strains of P. gingivalis, KCOM 2880, KCOM 2803, and KCOM 3190, were also recognized using this optimized enzyme immunoassay (EIA) system. To conclude, we established optimized conditions for P. gingivalis detection with specificity, accuracy, and sensitivity. These results could be utilized to manufacture economical and rapid detection kits for P. gingivalis.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.61-68
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• 2024

Despite the continuous efforts to mitigate pedestrian accidents at crosswalks, the problem persist. Vulnerable groups, including the elderly and disabled individuals are at a risk of being involved in traffic incidents. This paper proposes the implementation of object detection algorithm using the YOLO v5 model specifically for pedestrians using assistive devices like wheelchairs and crutches. For this research, data was collected and utilized through image crawling, Roboflow, and Mobility Aids datasets, which comprise of wheelchair users, crutch users, and pedestrians. Data augmentation techniques were applied to improve the model's generalization performance. Additionally, ensemble techniques were utilized to mitigate type 2 errors, resulting in 96% recall rate. This demonstrates that employing ensemble methods with a single YOLO model to target transportation-disadvantaged individuals can yield accurate detection performance without overlooking crucial objects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.630-636
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• 2012

In this paper, we propose an improved Multi Gray-Leveling scheme which reduces the problems of the existing Multi Gray-Leveling scheme suggested as a way of prevention against call spam in VoIP environment. The existing scheme having two different time period distinguishes the possibility of call spam by checking the call interval, so that it prevents the spammer's avoidance controlling the call interval. This is the strength of the existing one but it can misunderstand the normal user as a spammer due to taking long term time period. To solve this problem, this paper proposes the upgrade scheme which utilizes the receiver's action pattern as well as the caller's action pattern. It has such a good strength that can do gray leveling via the collected information in the database of VoIP service provider without user's direct involvement. Hence it can be a very effective way of VoIP spam detection.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.33-40
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• 2007

In this paper, low-rate TCP attack as one of shrew attacks is considered and the scaling based dynamic time warping (S-DTW) algorithm is introduced. The low-rate TCP attack can not be detected by the detection method for the previous flooding DoS/DDoS (Denial of Service/Distirbuted Denial of Service) attacks due to its low average traffic rate. It, however, is a periodic short burst that exploits the homogeneity of the minimum retransmission timeout (RTO) of TCP flows and then some pattern matching mechanisms have been proposed to detect it among legitimate input flows. A DTW mechanism as one of detection approaches has proposed to detect attack input stream consisting of many legitimate or attack flows, and shown a depending method as well. This approach, however, has a problem that legitimate input stream may be caught as an attack one. In addition, it is difficult to decide a threshold for separation between the legitimate and the malicious. Thus, the causes of this problem are analyzed through simulation and the scaling by maximum auto-correlation value is executed before computing the DTW. We also discuss the results on applying various scaling approaches and using standard deviation of input streams monitored.

• KSBB Journal
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• v.21 no.5
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• pp.347-352
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• 2006

This study was carried out to establish the optimum condition for cell disruption with a sonificator in the detection of the gram positive bacteria, Bacillus globigii and Streptococcus epidermidis for the purpose of developing automatic fluorometer. The efficiency of sonificator on the Bacillus globigii and Streptococcus epidermidis disruption differed greatly according to the diameter of sonificator probe tip. The larger sonificator probe diameter showed greater disruption. Bacillus globigii was more disruptive than Streptococcus epidermidis. Sonificator probe of the 13 mm diameter was the most efficient one when sample was sonificated for 20 seconds. The detection limits of Bacillus globigii and Streptococcus epidermidis were $10^5CFU/m{\ell}\;and\;5{\times}10^5CFU/m{\ell}$ respectively when samples were sonificated for 20 seconds with a sonificator probe of 13 mm diameter.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2247-2254
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• 2016

Background: The incidence of breast cancer is rising in Oman, and the disease is diagnosed at late stages, when treatment success is limited. Omani women might benefit from better awareness, so that breast cancer can be detected early and treated. This study was conducted to assess Omani women's levels of breast cancer awareness and early detection practice, and explore factors which might influence these levels. Materials and Methods: A mixed methods study was conducted in 2014, including a quantitative survey of 1,372 and a qualitative assessment of 19 Omani women, aged ${\geq}20years$ from five Omani governorates using convenient sampling. Demographic information and scores for awareness levels were used in a multivariate regression model to investigate factors associated with awareness. Thematic analysis and interpretive description were used to analyse the qualitative data. Results: The overall means for early detection and general awareness scores were 0.58 (SD 0.24) and 0.46 (SD 0.21), respectively. General awareness was significantly associated with age, education, income and familiarity with cancer patients (p<0.05), while early detection was significantly associated with age, marital status and education. A majority of women (59.5%) agreed with a belief in 'evil eye' or envy as a risk factor for breast cancer. Women discussed various factors which may empower or inhibit awareness, including the cultural-religion-fatalistic system, personal-familial-environmental system, and healthcare-political-social system. Conclusions: The overall low scores for awareness and early detection, and the survey of local beliefs highlight a severe necessity for a contextually-tailored breast cancer awareness intervention programme in Oman.

• Food Science and Preservation
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• v.30 no.2
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• pp.262-271
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• 2023

The objective of this study is to compare and assess the effectiveness of real-time polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and the selective agar plate method for the detection of Salmonella spp. and Listeria monocytogenes in ready-to-eat (RTE) foods. In RTE foods, the detection performance of the three methods (RT-PCR [SureTect^TM kit and PowerChek^TM kit], LAMP [3M MDS], selective agar) were similar at 0-10, 10-50, 50-100, and 100- CFU/mL of Salmonella spp. and L. monocytogenes. We found that with RT-PCR, the Ct value of salad was significantly higher (p<0.05) than other RTE foods, indicating that fiber plays a critical role as an obstacle to the rapid detection of Salmonella spp. However, the Ct value displayed a mixed pattern according to the inoculation level of L. monocytogenes. The use of rapid detection kits and machines mostly depends on the user's choice, with accuracy, ease of use, and economy being the primary considerations. As an RT-PCR kit, SureTect^TM and PowerChek^TM showed high accuracy in detecting Salmonella spp. and L. monocytogenes in RTE foods, showing that they can replace the existing RT-PCR kits available. Additionally, LAMP also showed excellent detection performance, suggesting that it has the potential to be used as a food safety management tool.