• Asian-Australasian Journal of Animal Sciences
• /
• 제25권3호
• /
• pp.353-360
• /
• 2012

Mastitis is a highly morbid disease that requires detection at the subclinical stage. Tropical countries like India mainly depend on milch buffaloes for milk. The present study was conducted to investigate whether the trace minerals viz. copper (Cu), iron (Fe), zinc (Zn), cobalt (Co) and manganese (Mn) and enzyme activity of lactate dehydrogenase (LDH), alkaline phosphatase (ALP) and aspartate aminotransferase (AST) in riverine buffalo milk can be used as an indicator of subclinical mastitis (SCM) with the aim of developing suitable diagnostic kit for SCM. Trace elements and enzyme activity in milk were estimated with Atomic absorption Spectrophotometer, GBC 932 plus and biochemical methods, respectively. Somatic cell count (SCC) was done microscopically. The cultural examination revealed Gram positive bacteria as the most prevalent etiological agent. A statistically significant (p<0.01) increase in SCC, Fe, Zn, Co and LDH occurred in SCM milk containing gram positive bacterial agents only. ALP was found to be elevated in milk infected by both gram positive and negative bacteria. The percent sensitivity, specificity and accuracy, predictive values and likelihood ratios were calculated taking bacterial culture examination and $SCC\geq2{\times}10^5$ cells/ml of milk as the benchmark. Only ALP and Zn, the former being superior, were found to be suitable for diagnosis of SCM irrespective of etiological agents. LDH, Co and Fe can be introduced in the screening programs where Gram positive bacteria are omnipresent. It is recommended that both ALP and Zn be measured together in milk to diagnose buffalo SCM, irrespective of etiology.

• Asian Pacific Journal of Cancer Prevention
• /
• 제14권10호
• /
• pp.6121-6125
• /
• 2013

Background: Endometrial cancers are the most common gynecologic cancers. Endometrial sampling is a preferred procedure for diagnosis of the endometrial pathology. It is performed routinely in many clinics prior to surgery in order to exclude an endometrial malignancy. We aimed to investigate the accuracy of endometrial sampling in the diagnosis of endometrial pathologies and which findings need intra-operative frozen sections. Materials and Methods: Three hundred nine women applying to a university hospital and undergoing endometrial sampling and hysterectomy between 2010 and 2012 were included to this retrospective study. Data were retrieved from patient files and pathology archives. Results: There was 17 patients with malignancy but endometrial sampling could detect this in only 10 of them. The endometrial sampling sensitivity and specificity of detecting cancer were 58.8% and 100%, with negative and positive predictive values of 97.6%, and 100%, respectively. In 7 patients, the endometrial sampling failed to detect malignancy; 4 of these patients had a preoperative diagnosis of complex atypical endometrial hyperplasia and 2 patients had a post-menopausal endometrial polyps and 1 with simple endometrial hyperplasia. Conclusions: There is an increased risk of malignancy in post-menopausal women especially with endometrial polyps and complex atypia hyperplasia. Endometrial sampling is a good choice for the diagnosis of endometrial pathologies. However, the diagnosis should be confirmed by frozen section in patients with post-menopausal endometrial polyps and complex atypia hyperplasia.

• Asian Pacific Journal of Cancer Prevention
• /
• 제13권5호
• /
• pp.1953-1956
• /
• 2012

Objective: The purpose of this study was to correlate the histological diagnosis made during intraoperative frozen section (FS) examination of hysterectomy samples with complex atypical endometrial hyperplasia (CAEH) diagnosed with definitive paraffin block histology. Methods: FS pathology results of 125 patients with a preoperative biopsy showing CAEH were compared retrospectively with paraffin block pathology findings. Results: Paraffin block results were consistent with FS in 78 of 125 patients (62.4%). The FS sensitivity and specificity of detecting cancer were 81.1% and 97.9%, with negative and positive predictive values of 76.7%, and 98.4%, respectively. Paraffin block results were reported as endometrial cancer in 77 of 125 (61.6%) patients. Final pathology was endometrial cancer in 45.3% patients diagnosed at our center and 76.9% for patients who had their diagnosis at other clinics (p=0.018). Paraffin block results were consistent with FS in 62.4% of all cases Consistence was 98.4% in patients who had endometrial cancer in FS. Conclusion: FS does not exclude the possibility of endometrial cancer in patients with the preoperative diagnosis of CAEH. In addition, sufficient endometrial sampling is important for an accurate diagnosis.

• Journal of Korea Multimedia Society
• /
• 제11권9호
• /
• pp.1213-1226
• /
• 2008

A recommender system supports people in making recommendations finding a set of people who are likely to provide good recommendations for a given person, or deriving recommendations from implicit behavior such as browsing activity, buying patterns, and time on task. We proposed new recommender system which combined SOM(Self-Organizing Map) neural networks with the Collaborative filtering which most recommender systems hat applied First, we segmented user groups according to demographic characteristics and then we trained the SOM with people's preferences as ito inputs. Finally we applied the classic collaborative filtering to the clustering with similarity in which an recommendation seeker belonged to, and therefore we didn't have to apply the collaborative filtering to the whose data set. Experiments were run for EachMovies data set. The results indicated that the predictive accuracy was increased in terms of MAE(Mean-Absolute-Error).

• KIPS Transactions on Software and Data Engineering
• /
• 제3권7호
• /
• pp.263-270
• /
• 2014

This paper suggests a method for predicting a box-office success of the film. Lately, as the growth of the film industry, a variety of studies for the prediction of market demand is being performed. The product life cycle of film is relatively short cultural goods. Therefore, in order to produce stable profits, marketing costs before opening as well as the number of screen after opening need a plan. To fulfill this plan, the demand for the product and the calculation of economic profit scale should be preceded. The cases of existing researches, as a variable for predicting, primarily use the factors of competition of the market or the properties of the film. However, the proportion of the potential audiences who purchase the goods is relatively insufficient. Therefore, in this paper, in order to consider people's perception of a movie, Twitter was utilized as one of the survey samples. The existing variables and the information extracted from Twitter are defined as off-line and on-line element, and applied those two elements in machine learning by combining. Through the experiment, the proposed predictive techniques are validated, and the results of the experiment predicted the chance of successful film with about 95% of accuracy.

• Journal of Communications and Networks
• /
• 제14권3호
• /
• pp.336-345
• /
• 2012

Autonomous system (AS) business relationships and their inference have been widely studied by network researchers in the past. An important application of inferred AS relationships can be the prediction of AS paths between a source and destination AS within a model. However, besides knowing the topology and inferred AS relationships, AS path prediction within a model needs to be understood in order for us to know how we can derive border gateway protocol (BGP) policies from AS relationships. In this paper, we shed light onto the predictive capabilities of AS relationships by investigating whether they can be translated into BGP policies such that inferred AS paths are consistent with real AS paths, e.g., paths observed from BGP routing tables. Our findings indicate that enforcing constraints such as the well-known valley-free property and the widely assumed preference of customer routes always results in a very low consistency for AS path inference. In addition, this is true irrespective of whether customer, peer, or provider routes are preferred. Apparently, applying such constraints eliminates many "correct" paths that are observed in BGP routing tables and that are propagated in a simple shortest path model where AS relationships are ignored. According to our findings, deriving BGP routing policies for predicting with high accuracy AS paths in a model directly from AS relationships is still difficult.

• Journal of Digital Convergence
• /
• 제15권3호
• /
• pp.157-163
• /
• 2017

Forecasting container cargo volumes is very important factor for port related organizations in inversting in the recent port management. Especially forcasting of domestic and foreign container volume is necessary because adjacent nations are competing each other to handle more container cargoes. Exact forecasting is essential elements for national port policy, however there is still some difficulty in developing the predictive model. In this respect, the purpose of this study is to develop and suggest the forecasting model of container cargo volumes of China using System Dynamics (SD). The monthly data collected from Clarkson's Shipping Intelligence Network from year 2004 to 2015 during 12 years are used in the model. The accuracy of the model was tested by comparisons between actual container cargo volumes and forecasted corgo volumes suggested by the research model. The MAPE values are calcualted as 6.21% for imported cargo volumes and 7.68% for exported cargo volumes respectively. Less than 10% of MAPE value means that the suggested model is very accurate.

• Journal of The Korean Society of Agricultural Engineers
• /
• 제59권5호
• /
• pp.93-99
• /
• 2017

A model was developed using Artificial Neural Networks (ANNs) based on Principal Component Analysis (PCA), to accurately predict the air humidity inside an experimental greenhouse located in Daegu (latitude $35.53^{\circ}N$, longitude $128.36^{\circ}E$, and altitude 48 m), South Korea. The weather parameters, air temperature, relative humidity, solar radiation, and carbon dioxide inside and outside the greenhouse were monitored and measured by mounted sensors. Through the PCA of the data samples, three main components were used as the input data, and the measured inside humidity was used as the output data for the ALYUDA forecaster software of the ANN model. The Nash-Sutcliff Model Efficiency Coefficient (NSE) was used to analyze the difference between the experimental and the simulated results, in order to determine the predictive power of the ANN software. The results obtained revealed the variables that affect the inside air humidity through a sensitivity analysis graph. The measured humidity agreed well with the predicted humidity, which signifies that the model has a very high accuracy and can be used for predictions based on the computed $R^2$ and NSE values for the training and validation samples.

• Clinics in Shoulder and Elbow
• /
• 제9권1호
• /
• pp.73-82
• /
• 2006

Purpose: The purpose of the present study was to evaluate the diagnostic efficacy of CT arthrography (CTA) in the assessment of various shoulder pathologies, compared with MR arthrography (MRA) and MRI with arthroscopic correlation. Materials and Methods: CTA in 84 patients, MRA in 70 patients, and MRI in 27 patients were obtained. A radiologist interpreted each image for 5 pathologies: Bankart, SLAP, Hill-Sachs lesion, full-thickness, and partial-thickness rotator cuff tear. Detailed arthroscopic reports were compared with CTA, MRA, and MRI. The sensitivity, specificity, predictive values, and accuracy were calculated. The agreement between each diagnostic modality and arthroscopy was calculated. Diagnostic efficacy was assessed by the areas under the receiver operating characteristic (ROC) curves. Results: The diagnostic values of all three imaging groups were comparable to each other for Bankart, SLAP, Hills-Sachs, and full-thickness cuff tear lesions, but those of CTA were lower than MRI and MRA for partial-thickness cuff tears. The areas under the ROC curves for CTA, MRA, and MRI were not significantly different for all pathologies, except for partial-thickness cuff tears. Conclusion: CTA was equally competent to MRA or MRI in demonstrating Bankart, Hill-Sachs lesions, SLAP, and full thickness rotator cuff tears but not as efficient in diagnosing partial thickness rotator cuff tears.

• Food Science and Biotechnology
• /
• 제16권2호
• /
• pp.238-242
• /
• 2007

Square root models were developed for predicting the kinetics of growth of Listeria monocytogenes in sesame leaves as a function of temperature (4, 10, or $25^{\circ}C$). At these storage temperatures, the primary growth curves fit well ($R^2=0.898$ to 0.980) to a Gompertz equation to obtain lag time (LT) and specific growth rate (SGR). The square root models for natural logarithm transformations of the LT and SGR as a function of temperature were obtained by SAS's regression analysis. As storage temperature ($4-25^{\circ}C$) decreased, LT increased and SGR decreased, respectively. Square root models were identified as appropriate secondary models for LT and SGR on the basis of most statistical indices such as coefficient determination ($R^2=0.961$ for LT, 0.988 for SGR), mean square error (MSE=0.l97 for LT, 0.005 for SGR), and accuracy factor ($A_f=1.356$ for LT, 1.251 for SGR) although the model for LT was partially not appropriate as a secondary model due to the high value of bias factor ($B_f=1.572$). In general, our secondary model supported predictions of the effects of temperature on both LT and SGR for L. monocytogenes in sesame leaves.