• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2835-2841
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• 2024

Real-time analysis of metallic mineral grade and slurry concentration is significant for improving flotation efficiency and product quality. This study proposes an online detection method of ore slurry combining the Prompt Gamma Neutron Activation Analysis (PGNAA) technology and artificial neural network (ANN), which can provide mineral information rapidly and accurately. Firstly, a PGNAA analyzer based on a D-T neutron generator and a BGO detector was used to obtain a gamma-ray spectrum dataset of ore slurry samples, which was used to construct and optimize the ANN model for adaptive analysis. The evaluation metrics calculated by leave-one-out cross-validation indicated that, compared with the weighted library least squares (WLLS) approach, ANN obtained more precise and stable results, with mean absolute percentage errors of 4.66% and 2.80% for Fe grade and slurry concentration, respectively, and the highest average standard deviation of only 0.0119. Meanwhile, the analytical errors of the samples most affected by matrix effects was reduced to 0.61 times and 0.56 times of the WLLS method, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.89-98
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• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

• Korean Journal of Construction Engineering and Management
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• v.7 no.6
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• pp.175-184
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• 2006

This study focused on developing Life Cycle Cost(LCC) analysis model for selecting sludge collectors in wastewater treatment system and applying the model to a case study. Cost items are examined through literature review and historical data of a facility. Analysis period, discount rate, energy cost escalation ratio are assumed to reasonable level. Monetary evaluation is performed using historical data and estimations from vendors. Sensitive analysis is executed using Monte Carlo Simulation for assumed factors. Interviews with operators, vendors, constructors, managers are conducted to define factors which indicates ease of maintenance, ease of delivery, technical performance, efficiency, environmental friendship. Factors are representing technical and social factors. Results from LCC analysis and qualitative analysis are evaluate together with Weighted Matrix Evaluation Methods for optimum alternative of sludge collectors.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.141-152
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• 2005

This study focused on the relationships among leaf and smoke components and sensory properties following tobacco leaf blending. A completely randomized experimental design was used to evaluate components of leaf and smoke and sensory properties for sample cigarettes with four mixtures of flue cured and burley tobacco (40:60, 60:40, 80:20 and 100:0). Eleven leaf components, six smoke components, and eight sensory properties of smoking taste were analyzed. A sensory evaluation method known as quantitative descriptive analysis was used to evaluate perceptual strength on a fifteen score scale. Raw data from ten trained panelists were obtained and statistically analyzed. Based on the MANOVA, clustering analysis, correlation matrix and partial least square (PLS) method were applied to find out which smoke component most affected sensory properties. The PLS method was used to remove the influence between explanatory variables in the leaf, smoke components derived from the results. High correlations (p<0.0l) were found among ten specific leaf and smoke components and sensory attributes. Total nitrogen, ammonia, total volatile base, and nitrate in the leaf were significantly correlated (p<0.05) with impact, bitterness, tobacco taste, irritation, smoke volume, and smoke pungency. From the results of PLS analysis, influence variables are used to explain about the correlation. In terms of bitterness, with only two explanatory variables, Leaf $NO_3$ and Leaf crude fiber were enough for guessing their correlation. In the distance weighted least square fitting analysis, carbon monoxide highly influenced bitterness, hay like taste, and smoke volume.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.2
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• pp.146-155
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• 2015

Objectives: The aims of this study were to set up benzene exposure matrices according to industry and process and to assess the risk of those occupational exposure to benzene. Methods: The benzene exposure matrices were assembled depending on industry and process, based on an exposure database provided by KOSHA(the Korean Occupational Safety and Health Agency), which was gathered from a workplace hazards evaluation program in Korea. These exposure matrices were assessed by Hallmark Risk Assessment tool. Results: The benzene was treated 412 industries sector(36%), 2,747 business places, and 471 industrial processes according to database. The arithmetic mean of past decade 8 hours time-weighted average of airborne benzene concentrations in the workplace was 0.10722 ppm. 1.07% of the total sample were greater than OEL, and 59.8% were showed less than the limit of detection. The highest risk values(Danger Value) were seen 36 industries including manufacture of general paints and similar product and 12 processes, such as other painting of manufacture of metal fabricated members. Exposure matrices based on employee exposure data base may provide exposure histories and can be used in epidemiological studies. Conclusions: It was found that more attentions should be paid to 36 among 412 industries and 12 of 471 processes, with a higher risk value.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.93-100
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• 2021

Purpose: (1) To evaluate the trabecular pattern at the femoral attachment of the posterior cruciate ligament (PCL) in patients with a PCL injury; (2) to analyze bone microarchitecture by applying gray level co-occurrence matrix (GLCM)-based texture analysis; and (3) to determine if there is a significant relationship between bone microarchitecture and posterior instability. Materials and Methods: The study included 96 patients with PCL tears. Trabecular patterns were evaluated on T2-weighted MRI qualitatively, and were evaluated by GLCM texture analysis quantitatively. The grades of posterior drawer test (PDT) and the degrees of posterior displacement on stress radiographs were recorded. The 96 patients were classified into two groups: acute and chronic injury. And 27 patients with no PCL injury were enrolled for control. Pearson's correlation coefficient and one-way ANOVA with Bonferroni test were conducted for statistical analyses. This protocol was approved by the Institutional Review Board. Results: A thick and anisotropic trabecular bone pattern was apparent in normal or acute injury (n = 57/61;93.4%), but was not prominent in chronic injury and posterior instability (n = 31/35;88.6%). Grades of PDT and degrees of posterior displacement on stress radiograph were not correlated with texture parameters. However, the texture analysis parameters of chronic injury were significantly different from those of acute injury and control groups (P < 0.05). Conclusion: The trabecular pattern and texture analysis parameters are useful in predicting posterior instability in patients with PCL injury. Evaluation of the bone microarchitecture resulting from altered biomechanics could advance the understanding of PCL function and improve the detection of PCL injury.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.1-9
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• 2022

Objectives: The purpose of this study is to evaluate exposure characteristics of lead using data from the domestic occupational exposure literature. Methods: Occupational airborne exposure data on lead reported in the domestic literature from 1981 to 2018 were collected and re-analyzed. The exposure levels in the data were expressed as an estimated arithmetic mean and a weighted arithmetic mean (WAM) of the number of samples. Lead exposure characteristics were analyzed by industry, process, and year. Results: From a total of 14 documents, 8,305 airborne lead measurements for 17 industries were identified, and the WAM concentration in eight industries exceeded the occupational exposure limit of 50 ㎍/m³. Three industries (battery manufacturing, lead smelting, and litharge manufacturing) accounted for 95% of the total data, and exposure trends could be confirmed over 10 years. Exposure levels continue to decrease in all three industries. Conclusions: Considering the distribution outlook of lead and lead compounds, the main management targets are lead storage battery manufacturing and secondary smelting for lead regeneration.

• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.119-124
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• 1997

Purpose: To assess the utility of magnetic resonance(MR) cerebral blood volume (CBV) map in the evaluation of brain tumors. Materials and Methods: We performed perfusion MR imaing preoperatively in the consecutive IS patients with intracranial masses(3 meningiomas, 2 glioblastoma multiformes, 3 low grade gliomas, 1 lymphoma, 1 germinoma, 1 neurocytoma, 1 metastasis, 2 abscesses, 1 radionecrosis). The average age of the patients was 42 years (22yr -68yr), composed of 10 males and S females. All MR images were obtained at l.ST imager(Signa, CE Medical Systems, Milwaukee, Wisconsin). The regional CBV map was obtained on the theoretical basis of susceptibility difference induced by first pass circulation of contrast media. (contrast media: IScc of gadopentate dimeglumine, about 2ml/sec by hand, starting at 10 second after first baseline scan). For each patient, a total of 480 images (6 slices, 80 images/slice in 160 sec) were obtained by using gradient echo(CE) single shot echo-planar image(EPI) sequence (TR 2000ms, TE SOms, flip angle $90^{\circ}$, FOV $240{\times}240mm,{\;}matrix{\;}128{\times}128$, slice-thick/gap S/2.S). After data collection, the raw data were transferred to CE workstation and rCBV maps were generated from the numerical integration of ${\Delta}R2^{*} on a voxel by voxel basis, with home made software (${\Delta}R2^{*}=-ln (S/SO)/TE). For easy visual interpretation, relative RCB color coding with reference to the normal white matter was applied and color rCBV maps were obtained. The findings of perfusion MR image were retrospectively correlated with Cd-enhanced images with focus on the degree and extent of perfusion and contrast enhancement. Results: Two cases of glioblastoma multiforme with rim enhancement on Cd-enhanced Tl weighted image showed increased perfusion in the peripheral rim and decreased perfusion in the central necrosis portion. The low grade gliomas appeared as a low perfusion area with poorly defined margin. In 2 cases of brain abscess, the degree of perfusion was similar to that of the normal white matter in the peripheral enhancing rim and was low in the central portion. All meningiomas showed diffuse homogeneous increased perfusion of moderate or high degree. One each of lymphoma and germinoma showed homogenously decreased perfusion with well defined margin. The central neurocytoma showed multifocal increased perfusion areas of moderate or high degree. A few nodules of the multiple metastasis showed increased perfusion of moderate degree. One radionecrosis revealed multiple foci of increased perfusion within the area of decreased perfusion. Conclusion: The rCBV map appears to correlate well with the perfusion state of brain tumor, and may be helpful in discrimination between low grade and high grade gliomas. The further study is needed to clarify the role of perfusion MR image in the evaluation of brain tumor.

• Archives of Plastic Surgery
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• v.32 no.3
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• pp.335-342
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• 2005

This study was undertaken to investigate possibility of the allogenic type I collagen inducing osteoinduction or osteoconduction at critical sized bone defect in the rabbit. Twenty Newzealand white rabbit, weighted from 2.8 kg to 3.5 kg, were used in this study. The skull was exposed and two bony defects were created with diameter of 10 mm. Group I(n=10), the bony defects was grafted from the other side bone. Group II(n=10), the bony defects was grafted by the allogenic type I collagen with bone morphogenic protein(BMP). Group III(n=10), the bony defects was grafted by the allogenic type I collagen only. Group IV(n=10), the bony defects was lefted with no grafts. The grafted bones and allogenic type I collagen were investigated with radiologic densitometry, histologic analysis and immunohistochemistry after 12 weeks. No major difference was observed in the gross finding between Group I, II, III, but dura mater was exposed in bony defect,the Group IV. The radiologic study demonstrated more bony opacity in the Group I, but the other groups did not demonstrate a significant difference. In the histologic study, grafted bone edge was completely consolidated with original bone in group I and new bone ingrew into the grafted allogenic type I collagen(group II, III),but there is no bone regeneration from the original bony edge in the group IV. The percent of the new bone formation by cross-sectional area was considered statistically significant at a p value of less than 0.05(p<0.05). In the immunohistochemistry study about BMP antibodies, the group IV demonstrated osteogenic activity in front of advancing original bone edge, in which the osteoblast stained strongly for BMP antibodies, but other group does not demonstrated any osteoblastic expression. There was no immunologic rejection. In conclusion, this results do not demonstrate that the allogenic type I collagen is useful for bone substitute, but the characters of the collagen, such as pliability, easy-handling, sponge-like structure, are useful in interpositional bone graft substitutes. The further evaluation of long term results about the resorption, immunologic tissue reaction, response of applied tissue growth factor to the allogenic collagen is needed.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.