• Journal of Preventive Medicine and Public Health
• /
• v.52 no.2
• /
• pp.131-139
• /
• 2019

Objectives: Self-reporting can be used to determine the incidence and prevalence of hypertension (HTN). The present study was conducted to determine the validity of self-reported HTN and to identify factors affecting discordance between self-reported and objectively measured HTN in participants in the Ravansar Non-Communicable Diseases (RaNCD) cohort. Methods: The RaNCD cohort included permanent residents of Ravansar, Iran aged 35-65 years. Self-reported data were collected before clinical examinations were conducted by well-trained staff members. The gold standard for HTN was anti-hypertensive medication use and blood pressure measurements. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of self-reporting were calculated. Univariate and multivariate logistic regression were used to examine the discordance between self-reported HTN and the gold standard. Results: Of the 10 065 participants in the RaNCD, 4755 (47.4%) were male. The prevalence of HTN was 16.8% based on self-reporting and 15.7% based on medical history and HTN measurements. Of the participants with HTN, 297 (18.8%) had no knowledge of their disease, and 313 (19.9%) had not properly controlled their HTN despite receiving treatment. The sensitivity, specificity, and kappa for self-reported HTN were 75.5%, 96.4%, and 73.4%, respectively. False positives became more likely with age, body mass index (BMI), low socioeconomic status, and female sex, whereas false negatives became more likely with age, BMI, high socioeconomic status, smoking, and urban residency. Conclusions: The sensitivity and specificity of self-reported HTN were acceptable, suggesting that this method can be used for public health initiatives in the absence of countrywide HTN control and detection programs.

• Korean Journal of Culture and Social Issue
• /
• v.14 no.4
• /
• pp.1-18
• /
• 2008

The present study examined the accuracy of polygraph tests through two types of statistical methods with unknown ground truth. One method evaluated the accuracy based on the rates of agreements between polygraph test results of crime suspects and prosecutors' indictment decisions for them. Those crime suspects were tested with polygraph by the Prosecutors' Office of the Republic of Korea between 2000 and 2004. The other method estimated the accuracy by using the latent class analysis based on the frequency distributions of the polygraph results and indictments during 2006. Excluding cases that were 'inconclusive' on the polygraph test, the study showed that the accuracy of the polygraph tests is .914 (SE=.004) for the 2000-2004 data, and .885 (SE=.021) for the 2006 data. With the inclusion of 'inconclusive' cases in the 2006 data, the results from the latent class analysis showed the accuracy in the range between .707 and .734 (SE=.027~.031), with false positives between .078 and .087 (SE=.019~.023), and false negatives between .029 and .078 (SE=.010~.023). The probability that the polygraph test correctly classifies subjects appeared to be in the range between .912 and .925 (SE=.013-.016) for those who lie, and in the range between .867 to .955 (SE=.011-.040) for those who tell the truth.

• The Journal of Bigdata
• /
• v.9 no.1
• /
• pp.75-88
• /
• 2024

Recently, there have been cases reported in the news of individuals experiencing symptoms of food poisoning after consuming raw beef purchased from online platforms, or reviews claiming that cherry tomatoes tasted bitter. This suggests the potential for analyzing food reviews on online platforms to detect food hazards, enabling government agencies, food manufacturers, and distributors to manage consumer food safety risks. This study proposes a classification model that uses sentiment analysis and large language models to analyze food reviews and detect negative ones, multi-labeling key food safety hazards (food poisoning, spoilage, chemical odors, foreign objects). The sentiment analysis model effectively minimized the misclassification of negative reviews with a low False Positive rate using a 'funnel' model. The multi-labeling model for food safety hazards showed high performance with both recall and accuracy over 96% when using GPT-4 Turbo compared to GPT-3.5. Government agencies, food manufacturers, and distributors can use the proposed model to monitor consumer reviews in real-time, detect potential food safety issues early, and manage risks. Such a system can protect corporate brand reputation, enhance consumer protection, and ultimately improve consumer health and safety.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.5
• /
• pp.1123-1129
• /
• 2015

Macro(automatic hunting) of mobile game is a program that touch the screen by defined rules like a game bot in PC online games, and it is used by make various ways like android application or windows application program. This gives honest users deprivation and make to lose their interest. Finally they would leave the game and gradually game life would be shorten. Although many studies to prevent these problems in PC online game are conducted, applying mobile game to PC's way is difficult because mobile games are limited to use the network and device performance is different with PC. In this paper, we propose a framework for macro detection by using the touch event information. A touch event on the mobile game is a necessary control command to the game. Because macro touches the screen with the same pattern, there is a difference between normal user's behavior and macro's operation. In mobile games that casual games are mostly, Touch event is the best difference that identify normal user against macro for a short period of time. As a result of detecting macros used in real mobile game by using the proposed framework it showed 100% accuracy and 0% false positive rate.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.12
• /
• pp.2878-2884
• /
• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location. Then, we propose a new tweet bot detection algorithm by using both an entropy based on geographic variable of each user and device information of each user. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• Journal of Biomedical Engineering Research
• /
• v.38 no.6
• /
• pp.321-329
• /
• 2017

This paper presents a bone metastasis Detection algorithm on abdominal computed tomography images for early detection using fully convolutional neural networks. The images were taken from patients with various cancers (such as lung cancer, breast cancer, colorectal cancer, etc), and thus the locations of those lesions were varied. To overcome the lack of data, we augmented the data by adjusting the brightness of the images or flipping the images. Before the augmentation, when 70% of the whole data were used in the pre-test, we could obtain the pixel-wise sensitivity of 18.75%, the specificity of 99.97% on the average of test dataset. With the augmentation, we could obtain the sensitivity of 30.65%, the specificity of 99.96%. The increase in sensitivity shows that the augmentation was effective. In the result obtained by using the whole data, the sensitivity of 38.62%, the specificity of 99.94% and the accuracy of 99.81% in the pixel-wise. lesion-wise sensitivity is 88.89% while the false alarm per case is 0.5. The results of this study did not reach the level that could substitute for the clinician. However, it may be helpful for radiologists when it can be used as a screening tool.

• Parasites, Hosts and Diseases
• /
• v.34 no.2
• /
• pp.121-126
• /
• 1996

For the detection of Cwptospori,mum oocysts, fecal samples were collected from 201 calves which showed diarrhea. Among the 201 samples, 29 samples (14.4%) were positive for Cwptosporinium spry. by the DMSO-modified acid-fast stain (MAFS) , 23 samples (11.4%) were positive by commercial kit (Meridian Diagnostics, Cincinnati, Ohiol and 23 by the indirect immunofluorescence antibody (IFA )assay employing the monoclonal antibody (mAb C6). When tested by both IFA and MAFS, 20 fecal samples were positive for Cwptosporinium oocysts whereas 169 fecal samples were negative. If the MAFS is considered a standard method for oocyst detection, the IFA showed 69% of sensitivity and 98% of specificity. When tested by both IFA and commercial kit, 22 fecal samples were positive for Cwptospori,mum oocysts while 177 samples were negative. One sample tested by IFA was found to be false negative, when compared with the results by commercial kit. The sensitivity of IFA was calculated as high as 96%; the specificity as 99% and the predictive value was also 99%. In the present study, IFA employing the nAb C6 revealed that 23 samples (11.4%) were positive among the 201 calves showing diarrhea. Of 23 IFA positive samples, 4 samples (5%) showed cryptosporidial oocysts more than 105 OPG Therefore. it is concluded that the calves showing cryptosporidial oocysts more than 105 OPG in the feces were highly associated with clinical cryptosporidiosis.

• The Korean Journal of Nuclear Medicine
• /
• v.38 no.4
• /
• pp.311-317
• /
• 2004

Purpose: The purpose of this study was to determine the utility of tumor marker CA 15-3 in the following: the diagnosis of breast cancer relapse after curative mastectomy, and the differentiation or the value of tumor marker by site of metastases. Materials and Methods: Two hundred two patients (median age 48 years) with breast cancer included in the follow-up after curative mastectomy. The tumor marker CA 15-3 was determined by IRMA (CIS BIO INTERNATIONAL, France). Test values > 30 U/ml were considered elevated (positive). Results: Among 202 patients, recurrent diseases were found in 16 patients. CA 15-3 was elevated in 5 of 16 patients with recurrences. There was no false-positive patient who had elevated CA 15-3. Sensitivity and specificity of CA 15-3 for detection of breast cancer recurrence were 31%, and 100%. CA 15-3 was elevated in all of the 4 patients with liver metastases. CA 15-3 was elevated in none of the patients who relapsed with metastasis to bone-only or contralateral breast-only. Conclusion: The tumor marker CA 15-3 in the detection of breast cancer relapse after curative mastectomy is specific, but not sensitive. However, it is useful to rule out liver metastases of breast cancer, which indicates bad prognosis.

• Korean Journal of Veterinary Service
• /
• v.34 no.4
• /
• pp.417-428
• /
• 2011

Species-specific PCR assay was developed for detection of cattle, sheep, goat, horse, dog, pig, chicken, duck, goose, and turkey using mitochondrial 12S rRNA and 16S rRNA as target genes. Also, an internal positive control was used to detect possible false negatives by using 18S rRNA gene. We designed species-specific primers with amplicon length of 190, 219, 350, 467, 241, 119, 171, 229, 111 and 268 bp for cattle, sheep, goat, horse, dog, pig, chicken, duck, goose, and turkey respectively. The specificity of the primers was tested against the other 10 non-target animal species and a cross-reaction was not observed. We developed two multiplex PCR assays for the simultaneous identification of Korea's major livestock species (cattle, pig, chicken and duck) and poultry species (chicken, duck, goose and turkey) from analogous samples, retaining the same specificity. The limit of detection of the multiplex PCR assay (cattle, pig, chicken and duck) ranged between 1 pg and 0.1 pg of template DNA extracts from raw meat. Applying multiplex PCR assays to DNA extracts from experimental pork/beef and pork/chicken tested raw and heat-treated ($120^{\circ}C$ for 30 min) mixtures respectively, detection limit was 0.1% level beef in pork, pork in beef and chicken in pork and 1.0% level pork in chicken. In conclusion, this assay using gel-based capillary electrophoresis would be very useful in highly sensitive and rapid identification of animal species or ingredients in minced meat and other meat products.

• Journal of Convergence for Information Technology
• /
• v.7 no.6
• /
• pp.159-166
• /
• 2017

In this paper, we have experimented to improve the verification performance of speaker change detection on broadcast news. It is to enhance the input noisy speech and to apply the KL distance $D_s$ using the SNR-based weighting function $w_m$. The basic experimental system is the verification system of speaker change using GMM-UBM based KL distance D(Experiment 0). Experiment 1 applies the input noisy speech enhancement using MMSE Log-STSA. Experiment 2 applies the new KL distance $D_s$ to the system of Experiment 1. Experiments were conducted under the condition of 0% MDR in order to prevent missing information of speaker change. The FAR of Experiment 0 was 71.5%. The FAR of Experiment 1 was 67.3%, which was 4.2% higher than that of Experiment 0. The FAR of experiment 2 was 60.7%, which was 10.8% higher than that of experiment 0.