There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.
The Journal of the Korea institute of electronic communication sciences
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v.17
no.6
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pp.1129-1136
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2022
This study leads to the shortcoming that the RSSI distance measurement method is easily affected by the external environment and the position error is large, leading to the problem of optimizing the distance values measured by the RSSI distance measurement nodes in this three-dimensional configuration environment. We proposed the CA-PSO-BP algorithm, which is an improved version of the CA-PSO algorithm. The proposed algorithm allows setting unknown nodes in WSN 3D space. In addition, since CA-PSO was applied to the BP neural network, it was possible to shorten the learning time of the BP network and improve the convergence speed of the algorithm through learning. Through the algorithm proposed in this study, it was proved that the precision of the network location can be increased significantly (15%), and significant results were obtained.
Journal of The Korean Society of Integrative Medicine
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v.10
no.3
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pp.161-172
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2022
Purpose : The study was to promote patient safety by analyzing the effect of dental hygienist's perception of patient safety culture on infection control activities. Methods : The study is based on a survey of 210 dental hygienists in total working in dental settings. To find out infection control activities according to patient safety culture awareness, there were 6 general characteristics, 3 teamwork within the department, 2 infection control systems, 4 surface management, 9 equipment washing, disinfection, and laundry management, 4 infectious wastes, and 3 personal protection phrases.The data was analyzed using the SPSS version 20.0, and p<.05 was adopted to decide on significance. Results : The longer dental hygienists have worked n the dental settings, the more active they become in infection control activities. Among the different types of dental care settings, general (university) hospitals had the largest number of infection control activities, followed by dental clinics, and network dental clinics, in descending order. The dental settings possessing a higher number of dental hygienists were found to conduct more infection control activities than other dental settings. In addition, it was found that when a dental setting adopts a patient safety policy across all the units in the hospital, more systems and procedures for patient safety tend to be established, and that stricter management response to error leads to improvement of infection control activities. Conclusion :In order to enhance infection control activities, infection control activity programs should develop and implement periodic reinforcement of infection control education. regular monitoring of infection control activities.
International conference on construction engineering and project management
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2022.06a
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pp.1226-1236
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2022
Because students majoring in construction-related fields must develop a broad repository of knowledge and skills, effective transferal of these is the primary focus of most academic programs. While inculcation of this body of knowledge is certainly critical, actual construction projects are complicated ventures that involve levels of risk and uncertainty, such as resistant neighboring communities, unforeseen weather conditions, escalating material costs, labor shortages and strikes, accidents on jobsites, challenges with emerging forms of technology, etc. Learning how to develop a level of discernment about potential ways to handle such uncertainty often takes years of costly trial-and-error in the proverbial "school of hard knocks." There is therefore a need to proactively expedite the development of a sharpened intuition when making decisions. The AGC Education and Research Foundation case study committee was formed to address this need. Since its inception in 2011, 14 freely downloadable case studies have thus far been jointly developed by an academics and industry practitioners to help educators elicit varied responses from students about potential ways to respond when facing an actual project dilemma. AGC case studies are typically designed to focus on a particular concern and topics have thus far included: ethics, site logistics planning, financial management, prefabrication and modularization, safety, lean practices, preconstruction planning, subcontractor management, collaborative teamwork, sustainable construction, mobile technology, and building information modeling (BIM). This session will include an overview of the history and intent of the AGC case study program, as well as lively interactive demonstrations and discussions on how case studies can be used both by educators within a typical academic setting, as well as by industry practitioners seeking a novel tool for their in-house training programs.
Deep-learning-based image segmentation is one of the most widely employed lane detection approaches, and it requires a post-process for extracting the key points on the lanes. A general approach for key-point extraction is using a fixed threshold defined by a user. However, finding the best threshold is a manual process requiring much effort, and the best one can differ depending on the target data set (or an image). We propose a novel key-point extraction algorithm that automatically adapts to the target image without any manual threshold setting. In our adaptive key-point extraction algorithm, we propose a line-level normalization method to distinguish the lane region from the background clearly. Then, we extract a representative key point for each lane at a line (row of an image) using a kernel density estimation. To check the benefits of our approach, we applied our method to two lane-detection data sets, including TuSimple and CULane. As a result, our method achieved up to 1.80%p and 17.27% better results than using a fixed threshold in the perspectives of accuracy and distance error between the ground truth key-point and the predicted point.
In this paper, we apply a support vector machine(SVM) that incorporates an optimized nonlinear decision rule over different sets of feature vectors to improve the performance of statistical model-based voice activity detection(VAD). Conventional method performs VAD through setting up statistical models for each case of speech absence and presence assumption and comparing the geometric mean of the likelihood ratio (LR) for the individual frequency band extracted from input signal with the given threshold. We propose a novel VAD technique based on SVM by treating the LRs computed in each frequency bin as the elements of feature vector to minimize classification error probability instead of the conventional decision rule using geometric mean. As a result of experiments, the performance of SVM-based VAD using the proposed feature has shown better results compared with those of reported VADs in various noise environments.
Biao Zhang;Jinjia Cao;Shuang Lin;Xiaomeng Li;Yulong Zhang;Xiaochang Zheng;Wei Chen;Yingming Song
Nuclear Engineering and Technology
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v.56
no.1
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pp.160-166
/
2024
The inversion of radiation field distribution is of great significance in the decommissioning sites of nuclear facilities. However, the radiation fields often contain multiple mixtures of radionuclides, making the inversion extremely difficult and posing a huge challenge. Many radiation field reconstruction methods, such as Kriging algorithm and neural network, can not solve this problem perfectly. To address this issue, this paper proposes an optimized inverse distance weighted (IDW) interpolation algorithm for reconstructing the gamma radiation field. The algorithm corrects the difference between the experimental and simulated scenarios, and the data is preprocessed with normalization to improve accuracy. The experiment involves setting up gamma radiation fields of three Co-60 radioactive sources and verifying them by using the optimized IDW algorithm. The results show that the mean absolute percentage error (MAPE) of the reconstruction result obtained by using the optimized IDW algorithm is 16.0%, which is significantly better than the results obtained by using the Kriging method. Importantly, the optimized IDW algorithm is suitable for radiation scenarios with multiple radioactive sources, providing an effective method for obtaining radiation field distribution in nuclear facility decommissioning engineering.
To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.
Purpose In a cyclosporine experiment using a robotic liquid handing system has found a deviation of its standard curve and low reproducibility of patients's results. The difference of the test is that methanol is mixed with samples and the extractions are used for the test. Therefore, we assumed that the abnormal test results came from using methanol and conducted this test. In a manual of a robotic liquid handling system mentions that we can choose several setting parameters depending on the viscosity of the liquids being used, the size of the sampling tips and the motor speeds that you elect to use but there's no exact order. This study was undertaken to confirm pipetting ability depending on types of liquids and investigate proper setting parameters for the optimum dispensing ability. Materials and Methods 4types of liquids(water, serum, methanol, PEG 6000(25%)) and $TSH^{125}I$ tracer(515 kBq) are used to confirm pipetting ability. 29 specimens for Cyclosporine test are used to compare results. Prepare 8 plastic tubes for each of the liquids and with multi pipette $400{\mu}l$ of each liquid is dispensed to 8 tubes and $100{\mu}l$ of $TSH^{125}I$ tracer are dispensed to all of the tubes. From the prepared samples, $100{\mu}l$ of liquids are dispensed using a robotic liquid handing system, counted and calculated its CV(%) depending on types of liquids. And then by adjusting several setting parameters(air gap, dispense time, delay time) the change of the CV(%)are calcutated and finds optimum setting parameters. 29 specimens are tested with 3 methods. The first(A) is manual method and the second(B) is used robotic liquid handling system with existing parameters. The third(C) is used robotic liquid handling system with adjusted parameters. Pipetting ability depending on types of liquids is assessed with CV(%). On the basis of (A), patients's test results are compared (A)and(B), (A)and(C) and they are assessed with %RE(%Relative error) and %Diff(%Difference). Results The CV(%) of the CPM depending on liquid types were water 0.88, serum 0.95, methanol 10.22 and PEG 0.68. As expected dispensing of methanol using a liquid handling system was the problem and others were good. The methanol's dispensing were conducted by adjusting several setting parameters. When transport air gap 0 was adjusted to 2 and 5, CV(%) were 20.16, 12.54 and when system air gap 0 was adjusted to 2 and 5, CV(%) were 8.94, 1.36. When adjusted to system air gap 2, transport air gap 2 was 12.96 and adjusted to system air gap 5, Transport air gap 5 was 1.33. When dispense speed was adjusted 300 to 100, CV(%) was 13.32 and when dispense delay was adjusted 200 to 100 was 13.55. When compared (B) to (A), the result increased 99.44% and %RE was 93.59%. When compared (C-system air gap was adjusted 0 to 5) to (A), the result increased 6.75% and %RE was 5.10%. Conclusion Adjusting speed and delay time of aspiration and dispense was meaningless but changing system air gap was effective. By adjusting several parameters proper value was found and it affected the practical result of the experiment. To optimize the system active efforts are needed through the test and in case of dispensing new types of liquids proper test is required to check the liquid is suitable for using the equipment.
Seo Jeong-min;Jeong Cheon-young;Park Young-hwan;Song Ki-won
The Journal of Korean Society for Radiation Therapy
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v.15
no.1
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pp.35-40
/
2003
I. Purpose Confirming an error to be able to break out in a method to move couch manually while operator sees the skin marks on patient in case of curing head who got 2 targets adjoined, so we analyze coordinates price of couch, evaluate reproducibility and precision of change movements between targets. II. Materials and Methods In radiotherapy, for confirming errors in manual movements by operators by exchanging between two targets to treat patient head, we read coordinates price(vertical, longitudinal, lateral three directions of couch) shown on a monitor of LINAC( CL 2100, Varian, USA) in order to evaluate accuracy about the length that moved in time for moving couch manually. After reading movement length of coordinates recorded in three directions of all treatment, we compared distance between targets recorded in RTP(Pinnacle, ADAC, USA) with reading coordinates price of couch, setting actually done the same patient for ten times, coordinates were recorded, treated for evaluating averages and degrees of errors and standard deviations. III. Results In method to confirm skin marks of patient by operators' view and to move couch manually, average standard deviations of movements between two targets are vertical 1.4mm, longitudinal 0.9mm, lateral 2.2mm in each direction. As for the error in straight dimension, it is about 3.6mm averages and 5.1mm maximum. The average of errors in each directions was vertical 1mm, longitudinal 0.7mm, lateral 2.7mm. The greatest error broke out in lateral direction with $25\%$ of all cases ; to exceed an error average. IV. Conclusions If operators moved manually couch for changing target points, errors about 3.6mm average degrees occur. It is important that operators confirm the errors prices of actual couch coordinates for asking a correct movement between the targets adjoined each other ; in case of treatment demanding high precision like 3D conformal therapy or IMRT. Therefore, if we apply couch coordinates confirmation to reproducibility and to precision evaluation of treatment, it's expected that we can execute high-quality radiotherapy.
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