Journal articles: 'Application scoring'

1

Ahmad, Rizwan, Ammara Liaquat, and Amna Liaquat. "ALVARADO SCORING SYSTEM;." Professional Medical Journal 25, no. 07 (2018): 1059–63. http://dx.doi.org/10.29309/tpmj/18.4611.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Venugopalan, Vaishnavi, and Chaitanya Vyas. "Comparing and Scoring Selected Four Train Ticketing Mobile Phone Applications." Information Management and Business Review 8, no. 4 (2016): 33–40. http://dx.doi.org/10.22610/imbr.v8i4.1391.

Full text

Abstract:

To find the best train ticket booking mobile application on the bases of application features. Four widely used mobile phone applications (Ixigo, MakeMyTrip, ClearTrip, and IRCTC) for railway ticket booking are selected and application features related to ease of download and use, rating, number of installs, etc. are compared. A practical attempt is made to book a train ticket using all these applications one by one and comparing features such as coach locator, platform locator, route map, fare break-up, showing seat availability, save and pre-fill passenger details, sort search list by train name/number, sort search list by journey duration, sort search list by class, train running status, etc. 1 point is allotted to the applications if a particular feature is available in the applications and 0 is allotted if the feature is not available. Sum of all the points is calculated separately for each application and then ranks are given from 1 to 4 considering the final score. Ixigo mobile application scores the highest among other three train ticketing mobile applications â€“ MakeMyTrip, ClearTrip, and IRCTC. Features such as downloading applications via a miss call or SMS; downloading application from websites of Ixigo, MakeMyTrip, ClearTrip, and IRCTC; and sorting train search list by class on applications are not found in any of these four applications. Furthermore, features are grouped into groups such as â€“ the features only available in top ranking Ixigo and the features not available in top ranking Ixigo but available in any or all other three applications. This research will be of a good value for mobile railway ticket booking application providers as competition is becoming acute and the booking pattern is shifting from using desktop or laptop to mobile phones and tablets.

APA, Harvard, Vancouver, ISO, and other styles

3

Lin, W., P. Kuo, M. Liu, C. Li, C. Lin, and S. Liang. "0434 Clinical Application of Computer Aided Cloud Sleep Scoring System." Sleep 43, Supplement_1 (2020): A166—A167. http://dx.doi.org/10.1093/sleep/zsaa056.431.

Full text

Abstract:

Abstract Introduction According to a survey by World Sleep Society, 45% of the population suffered from sleep disorders. The best way to diagnose these patients is to use Polysomnography (PSG), recording their physiological signals throughout the night. Mostly, sleep technologists manually score sleep stages. Manual scoring is quite subjective and time-consuming. Although the technologist’s judgments are based on scoring standards of the American Academy of Sleep Medicine, fine-tuning scoring results because of different considerations in different sleep centers may be happened. In order to assess the consistency of scoring standards in sleep technologists, we tried to establish a cloud sleep scoring system and evaluate its feasibility in 4 sleep centers in southern Taiwan. Methods We constructed a computer-aided cloud sleep scoring system. Each sleep technologist could score the same test data of PSG online without being restricted by places and hardware equipment. After comparing scoring results of all participants, the scoring system could provide the following reports, including an overall agreement, agreement of each sleep stage and each sleep index. Besides, multi-person scoring results of each epoch with displaying physiological signals were analyzed. Results Seven sleep technologists from 4 hospitals in Tainan, Taiwan joined this study. Standard deviations (SDs) of each sleep stage included 2.64 in Wake stage, 6.90 in N1, 8.31 in N2, 6.87 in N3, 1.38 in REM, respectively. SDs of sleep indexes were 2.64 in sleep efficiency, 2.14 in sleep onset time, 8.35 in wake after sleep onset time, 10.03 in total sleep time, individually. The overall agreement was 89.6%. The satisfaction of this scoring system operation was 85.7%. Conclusion With the cloud sleep scoring system assistance, it was feasible to evaluate the scoring consistency among sleep technologists in different sleep centers. Support This work is supported by the Ministry of Science and Technology, Taiwan. (MOST 108-2634-F-006-012)

APA, Harvard, Vancouver, ISO, and other styles

4

ROGERS, PABLO, DANY ROGERS, and JOSÉ ROBERTO SECURATO. "ABOUT PSYCHOLOGICAL VARIABLES IN APPLICATION SCORING MODELS." Revista de Administração de Empresas 55, no. 1 (2015): 38–49. http://dx.doi.org/10.1590/s0034-759020150105.

Full text

Abstract:

The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default. Therefore, a sample of 555 individuals completed a self-completion questionnaire, which was composed of psychological variables and scales. By adopting the methodology of the logistic regression, the following psychological and behavioral characteristics were found associated with the group of individuals in default: a) negative dimensions related to money (suffering, inequality and conflict); b) high scores on the self-efficacy scale, probably indicating a greater degree of optimism and over-confidence; c) buyers classified as compulsive; d) individuals who consider it necessary to give gifts to children and friends on special dates, even though many people consider this a luxury; e) problems of self-control identified by individuals who drink an average of more than four glasses of alcoholic beverage a day.

APA, Harvard, Vancouver, ISO, and other styles

5

Hu, Wenbin, and Junzi Zhou. "Joint modeling: an application in behavioural scoring." Journal of the Operational Research Society 70, no. 7 (2018): 1129–39. http://dx.doi.org/10.1080/01605682.2018.1487821.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Kaminskyi, Andrii, Maryna Nehrey, and Larysa Zomchak. "Machine learning methods application for consumer banking." SHS Web of Conferences 107 (2021): 12001. http://dx.doi.org/10.1051/shsconf/202110712001.

Full text

Abstract:

Machine learning (ML) methods are effective tools for analysis of many actual problems in modern banking. Increasing growth of data and rapid digitalization underpin the acceleration of ML implementation. These processes are especially noticeable in consumer banking because banks have millions of the retail customers. The first goal of our research is to form an extended review ML application in consumer banking. From one side we have identified the most developed ML methods, which are applied in this segment (for example different types of regressions, fuzzy clustering, neural network, principal component analysis etc.). From the other side, we point out two multi-purpose tools used by banks in consumer segment intensively, namely scoring and clustering. Secondly, our goal is to present some innovative applications of ML methods to the analysis of each task. This includes several applications for scoring models and fuzzy clustering application. All applications are oriented to make banks business processes more effective. Considered applications were realised on real data from the Ukrainian banking industry.

APA, Harvard, Vancouver, ISO, and other styles

7

Willatts, Sheilam M. "The application of scoring systems in adultintensive care." Baillière's Clinical Anaesthesiology 4, no. 2 (1990): 253–69. http://dx.doi.org/10.1016/s0950-3501(05)80287-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Novak, Michael P., and Eddy LaDue. "Application of Recursive Partitioning to Agricultural Credit Scoring." Journal of Agricultural and Applied Economics 31, no. 1 (1999): 109–22. http://dx.doi.org/10.1017/s0081305200028818.

Full text

Abstract:

AbstractRecursive Partitioning Algorithm (RPA) is introduced as a technique for credit scoring analysis, which allows direct incorporation of misclassification costs. This study corroborates nonagricultural credit studies, which indicate that RPA outperforms logistic regression based on within-sample observations. However, validation based on more appropriate out-of-sample observations indicates that logistic regression is superior under some conditions. Incorporation of misclassification costs can influence the creditworthiness decision.

APA, Harvard, Vancouver, ISO, and other styles

9

SHPAER, EUGENE G. "DNA Scoring Matrices: Application to Detect Divergent Repeats." Microbial & Comparative Genomics 2, no. 1 (1997): 75–87. http://dx.doi.org/10.1089/omi.1.1997.2.75.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Kallar, S. K., and F. Chung. "Practical Application of Postanesthetic Discharge Scoring System—PADS." Anesthesiology 77, Supplement (1992): A12. http://dx.doi.org/10.1097/00000542-199209001-00012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Sirio, C. A., and W. A. Knaus. "Application of prognostic scoring in adult intensive care." Current Opinion in Anaesthesiology 3, no. 2 (1990): 241–44. http://dx.doi.org/10.1097/00001503-199004000-00008.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Chopra, Anjali, and Priyanka Bhilare. "Application of Ensemble Models in Credit Scoring Models." Business Perspectives and Research 6, no. 2 (2018): 129–41. http://dx.doi.org/10.1177/2278533718765531.

Full text

Abstract:

Loan default is a serious problem in banking industries. Banking systems have strong processes in place for identification of customers with poor credit risk scores; however, most of the credit scoring models need to be constantly updated with newer variables and statistical techniques for improved accuracy. While totally eliminating default is almost impossible, loan risk teams, however, minimize the rate of default, thereby protecting banks from the adverse effects of loan default. Credit scoring models have used logistic regression and linear discriminant analysis for identification of potential defaulters. Newer and contemporary machine learning techniques have the ability to outperform classic old age techniques. This article aims to conduct empirical analysis on publically available bank loan dataset to study banking loan default using decision tree as the base learner and comparing it with ensemble tree learning techniques such as bagging, boosting, and random forests. The results of the empirical analysis suggest that the gradient boosting model outperforms the base decision tree learner, indicating that ensemble model works better than individual models. The study recommends that the risk team should adopt newer contemporary techniques to achieve better accuracy resulting in effective loan recovery strategies.

APA, Harvard, Vancouver, ISO, and other styles

13

Ozerova, M. I., and I. E. Zhigalov. "Application of Fuzzy Logic to Assess Banks' Credit Risk." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 21, no. 2 (2021): 70–78. http://dx.doi.org/10.14529/ctcr210207.

Full text

Abstract:

The banking system is a constantly evolving system. The information environment of the bank is growing, the volumes of processed information are increasing due to the growth of users and banking products. To reduce risks, banks make a financial assessment of the situation of individuals and legal entities. The aim of the work is to develop fuzzy multi-connected models designed to predict the receipt of a positive or negative decision to receive a banking product. The decision is made based on scoring. Scoring consists in assigning points for completing a certain questionnaire developed by underwriters of credit risk assessors. Based on the results of the points gained, the system automatically makes a decision on approving or refusing to issue a loan. Different banks have diffe¬rent scoring models. Purpose of the study. The paper considers the use of fuzzy models for making a decision by a bank to issue a banking product that implements the concept of “soft computing”. Methods. The use of fuzzy logic methods in credit scoring is not new, but it is not widely used in practice because it is expensive to integrate into existing systems. Each bank uses its own indicators of the client's financial reliability in scoring. Most of the indicators in banks are the same, but when deciding to issue different banking products, they have different numerical values. The data of the standard scoring methodology of a real bank were taken as the initial data. To predict a bank's decision to issue a banking product to a client, a fuzzy model was applied, production rules were proposed, and membership functions were determined. The model focused on the simultaneous processing of incoming data from multiple clients and for different banks and different scoring models. Results. The developed mathematical model for assessing the client's rating and predicting the decision to receive a banking product based on the fuzzy inference rule. The obtained results are proposed to be used in a multi-banking web-oriented system of providing banking products to corporate clients.

APA, Harvard, Vancouver, ISO, and other styles

14

Demajo, Lara Marie, Vince Vella, and Alexiei Dingli. "An Explanation Framework for Interpretable Credit Scoring." International Journal of Artificial Intelligence & Applications 12, no. 1 (2021): 19–38. http://dx.doi.org/10.5121/ijaia.2021.12102.

Full text

Abstract:

With the recent boosted enthusiasm in Artificial Intelligence (AI) and Financial Technology (FinTech), applications such as credit scoring have gained substantial academic interest. However, despite the evergrowing achievements, the biggest obstacle in most AI systems is their lack of interpretability. This deficiency of transparency limits their application in different domains including credit scoring. Credit scoring systems help financial experts make better decisions regarding whether or not to accept a loan application so that loans with a high probability of default are not accepted. Apart from the noisy and highly imbalanced data challenges faced by such credit scoring models, recent regulations such as the `right to explanation' introduced by the General Data Protection Regulation (GDPR) and the Equal Credit Opportunity Act (ECOA) have added the need for model interpretability to ensure that algorithmic decisions are understandable and coherent. A recently introduced concept is eXplainable AI (XAI), which focuses on making black-box models more interpretable. In this work, we present a credit scoring model that is both accurate and interpretable. For classification, state-of-the-art performance on the Home Equity Line of Credit (HELOC) and Lending Club (LC) Datasets is achieved using the Extreme Gradient Boosting (XGBoost) model. The model is then further enhanced with a 360-degree explanation framework, which provides different explanations (i.e. global, local feature-based and local instance- based) that are required by different people in different situations. Evaluation through the use of functionally-grounded, application-grounded and human-grounded analysis shows that the explanations provided are simple and consistent as well as correct, effective, easy to understand, sufficiently detailed and trustworthy.

APA, Harvard, Vancouver, ISO, and other styles

15

Li, Han, Xiao Guang Rui, and Xiao Mei Jiang. "Application of Fuzzy Theory in Evaluation of the University Entrance Art Examination Grade." Applied Mechanics and Materials 43 (December 2010): 773–77. http://dx.doi.org/10.4028/www.scientific.net/amm.43.773.

Full text

Abstract:

How to score professional papers of university entrance art examination scientifically and correctly has been one of the concerns of the staff in scoring the art paper. This paper proposed and constructed the model of fuzzy comprehensive evaluation on art professional papers based on fuzzy theory aimed at many ambiguous factors in art papers under general requirements for visual effects in scoring process. The scoring experimental research was implemented on art professional papers using the scoring model and satisfactory results obtained. Therefore the theoretical and experimental basis was laid for practical application of the method.

APA, Harvard, Vancouver, ISO, and other styles

16

Bitencourt-Ferreira, Gabriela, Amauri Duarte da Silva, and Walter Filgueira de Azevedo. "Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2." Current Medicinal Chemistry 28, no. 2 (2020): 253–65. http://dx.doi.org/10.2174/2213275912666191102162959.

Full text

Abstract:

Background: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the development of drugs intended to modulate cellcycle progression and control. Such drugs have potential anticancer activities. Objective: Our goal here is to review recent applications of machine learning methods to predict ligand- binding affinity for protein targets. To assess the predictive performance of classical scoring functions and targeted scoring functions, we focused our analysis on CDK2 structures. Methods: We have experimental structural data for hundreds of binary complexes of CDK2 with different ligands, many of them with inhibition constant information. We investigate here computational methods to calculate the binding affinity of CDK2 through classical scoring functions and machine- learning models. Results: Analysis of the predictive performance of classical scoring functions available in docking programs such as Molegro Virtual Docker, AutoDock4, and Autodock Vina indicated that these methods failed to predict binding affinity with significant correlation with experimental data. Targeted scoring functions developed through supervised machine learning techniques showed a significant correlation with experimental data. Conclusion: Here, we described the application of supervised machine learning techniques to generate a scoring function to predict binding affinity. Machine learning models showed superior predictive performance when compared with classical scoring functions. Analysis of the computational models obtained through machine learning could capture essential structural features responsible for binding affinity against CDK2.

APA, Harvard, Vancouver, ISO, and other styles

17

Hamdoun, Nabila, and Khalid Rguibi. "Impact of AI and Machine Learning on Financial Industry: Application on Moroccan Credit Risk Scoring." Journal of Advanced Research in Dynamical and Control Systems 11, no. 11-SPECIAL ISSUE (2019): 1041–48. http://dx.doi.org/10.5373/jardcs/v11sp11/20193134.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Amat, Oriol, Raffaele Manini, and Marcos Antón Renart. "Credit concession through credit scoring: Analysis and application proposal." Intangible Capital 13, no. 1 (2017): 51. http://dx.doi.org/10.3926/ic.903.

Full text

Abstract:

Purpose: The study herein develops and tests a credit scoring model which can help financial institutions in assessing credit requests. Design/methodology/approach: The empirical study has the objective of answering two questions: (1) Which ratios better discriminate the companies based on their being solvent or insolvent? and (2) What is the relative importance of these ratios? To do this, several statistical techniques with a multifactorial focus have been used (Multivariate Analysis of Variance, Linear Discriminant Analysis, Logit and Probit Models). Several samples of companies have been used in order to obtain and to test the model. Findings: Through the application of several statistical techniques, the credit scoring model has been proved to be effective in discriminating between good and bad creditors. Research limitations: This study focuses on manufacturing, commercial and services companies of all sizes in Spain; Therefore, the conclusions may differ for other geographical locations.Practical implications: Because credit is one of the main drivers of growth, a solid credit scoring model can help financial institutions assessing to whom to grant credit and to whom not to grant credit.Social implications: Because of the growing importance of credit for our society and the fear of granting it due to the latest financial turmoil, a solid credit scoring model can strengthen the trust toward the financial institutions assessment’s. Originality/value: There is already a stream of literature related to credit scoring. However, this paper focuses on Spanish firms and proves the results of our model based on real data. The application of the model to detect the probability of default in loans is original.

APA, Harvard, Vancouver, ISO, and other styles

19

Lingegowda, Jyothi B., K. Sathiyamurthy, Prakash H. Muddegowda, Prasanna G. Konapur, Ramkumar Kurpad Ramachandrarao, and M. Shashikiran. "Application of scoring system in FNAC of thyroid lesions." Indian Journal of Pathology and Oncology 3, no. 3 (2016): 409. http://dx.doi.org/10.5958/2394-6792.2016.00077.6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Whalen, Sean J., and Isaac I. Bejar. "Relational Databases in Assessment: An Application to Online Scoring." Journal of Educational Computing Research 18, no. 1 (1998): 1–13. http://dx.doi.org/10.2190/y8h3-ql30-hvxr-9lmm.

Full text

Abstract:

The Web has made it possible for interested participants to assemble themselves into virtual educational communities. In this article we discuss the design of online scoring systems that might be used in computer-based educational contexts. The focus is on the design of the software that supports high psychometric and fairness standards. We first describe the system from the point of view of different participants and then discuss the design of the underlying database, which is at the heart of the system. We close with conclusions regarding the advantages of sound database design and online grading.

APA, Harvard, Vancouver, ISO, and other styles

21

Nam, Ky-Youb, In-Hee Choi, and Kwang-Hwi Cho. "QM Scoring Function and its Application to TOP1 Inhibitors." Bulletin of the Korean Chemical Society 32, no. 4 (2011): 1127–28. http://dx.doi.org/10.5012/bkcs.2011.32.4.1127.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Whalen, Sean J., and Isaac I. Bejar. "RELATIONAL DATABASES IN ASSESSMENT: AN APPLICATION TO ONLINE SCORING." ETS Research Report Series 1998, no. 1 (1998): i—17. http://dx.doi.org/10.1002/j.2333-8504.1998.tb01771.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Fong, John, Gary M. Marsh, Leslie A. Stokan, Weilian Sang, Carey Vinson, and Linda Ruhl. "Hospital Quality Performance Report: An Application of Composite Scoring." American Journal of Medical Quality 23, no. 4 (2008): 287–95. http://dx.doi.org/10.1177/1062860608317064.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Price, David B., David G. Tinkelman, Robert J. Nordyke, Sharon Isonaka, and R. J. Halbert. "Scoring System and Clinical Application of COPD Diagnostic Questionnaires." Chest 129, no. 6 (2006): 1531–39. http://dx.doi.org/10.1378/chest.129.6.1531.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Chaplin, JOHN M., CHRISTOPHER J. O'Brien, EDWARD B. Mcneil, and Kourosh Haghighi. "APPLICATION OF PROGNOSTIC SCORING SYSTEMS IN DIFFERENTIATED THYROID CARCINOMA." ANZ Journal of Surgery 69, no. 9 (1999): 625–28. http://dx.doi.org/10.1046/j.1440-1622.1999.01651.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Chakraborty, Shantanu, Takayuki Ito, and Tomonobu Senjyu. "Smart pricing scheme: A multi-layered scoring rule application." Expert Systems with Applications 41, no. 8 (2014): 3726–35. http://dx.doi.org/10.1016/j.eswa.2013.12.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Ramkumar, V., S. Rajasekar, and S. Swamynathan. "Scoring products from reviews through application of fuzzy techniques." Expert Systems with Applications 37, no. 10 (2010): 6862–67. http://dx.doi.org/10.1016/j.eswa.2010.03.036.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Shono, Hideaki, Masayuki Oga, Kyoko Shimomura, et al. "Application of fuzzy logic to the Apgar scoring system." International Journal of Bio-Medical Computing 30, no. 2 (1992): 113–23. http://dx.doi.org/10.1016/0020-7101(92)90074-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Gelpi, Marco, Jonathan Argentiero, Paul W. Jones, and Andreas Ronit. "A Scoring Application for the St. George’s Respiratory Questionnaire." Chest 150, no. 3 (2016): 747–48. http://dx.doi.org/10.1016/j.chest.2016.05.029.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Steyn, Willem J., Samuel F. Ungerer, and Karen I. Theron. "Scoring and Girdling, but not GA3, Increase Yield without Decreasing Return Bloom in ‘Triumph’ Persimmon." HortScience 43, no. 7 (2008): 2022–26. http://dx.doi.org/10.21273/hortsci.43.7.2022.

Full text

Abstract:

The persimmon (Diospyros kaki Thunb.) cultivar Triumph is prone to poor fruit set, particularly in young orchards, in both Israel and South Africa where it is mostly grown. Two applications of 20 mg·L−1 gibberellic acid (GA3) at 30% and 70% full bloom (FB) are recommended as the industry norm to increase fruit set, but results obtained are often unsatisfactory. We conducted experiments during the 2005–06 and 2006–07 seasons in a young orchard (less than 5 years old) and a full-bearing orchard to determine the efficacy of GA3 application and scoring or girdling during FB to increase fruit set and yield in ‘Triumph’ persimmon. We also established the effect of 2005–06 treatments on return bloom in 2006–07. Although GA3 treatments were ineffective in increasing fruit set and reduced cumulative yield over the two seasons as a result of a reduction in return bloom, scoring increased the cumulative yield by 50% compared with the untreated control and by 92% compared with GA3 application in the young orchard. In the full-bearing orchard, scoring or girdling increased the cumulative yield over the 2005–06 and 2006–07 seasons by 52% compared with the industry standard GA3 application and by 22% compared with trees that received scoring/girdling in addition to GA3. Hence, scoring or girdling did not entirely offset the negative effect of GA3 application on return bloom. The increase in fruit numbers in response to fruit set treatment brought about a reduction in fruit mass. In conclusion, the ineffectiveness of GA3 in increasing fruit set and its negative effect on return bloom do not justify its further use to improve fruit set in young or full-bearing ‘Triumph’ orchards in South Africa. Either scoring or girdling can be used to increase yield but will need to be accompanied by pruning and thinning strategies to achieve adequate fruit size and to prevent the onset of alternate bearing resulting from overcropping.

APA, Harvard, Vancouver, ISO, and other styles

31

Haq, Fesa Asy Syifa Nurul, and Nuryuliani Nuryuliani. "Digitalization On Students Scoring System of SMPN 18 Bekasi." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 13, no. 3 (2019): 283. http://dx.doi.org/10.22146/ijccs.47275.

Full text

Abstract:

Information technology has been supporting the development of school services in the world. But there are still many schools does not using the information technology at all - specially in Indonesia, for example at SMPN 18 Bekasi. As usually like another school they only using Ms. Word and Ms. Excel applications. That is make many differences output in format scoring and mistakes while filling score on the students report format. The application of academic information system in this research have developed using PHP, HTML and MySQL as programming language. It named SIADHEL, means Eighteen Academic Information System (Sistem Informasi Akademik Delapan Belas) . The aims of this project is to provide a good tools for students or their parents to receive the exactly, fast and accurate informations of their students scoring. Teachers can use an integrated and accurate tools as facility to provide data for the Principal to make new policies. This application could be opened by every browser platform, so it will make easier for the users to access the program wherever and anytime.

APA, Harvard, Vancouver, ISO, and other styles

32

Hughes, Gareth, and Fiona J. Burnett. "Evaluation of Probabilistic Disease Forecasts." Phytopathology® 107, no. 10 (2017): 1136–43. http://dx.doi.org/10.1094/phyto-01-17-0023-fi.

Full text

Abstract:

The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast—predictive values—are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

APA, Harvard, Vancouver, ISO, and other styles

33

Saraswati, Mei Sita, Moch Abdul Mukid, and Abdul Hoyyi. "METODE GENERALIZED MEAN DISTANCE-BASED K-NEAREST NEIGHBOR CLASSIFIER (GMDKNN) UNTUK ANALISIS CREDIT SCORING CALON DEBITUR KREDIT TANPA AGUNAN (KTA)." Jurnal Gaussian 8, no. 1 (2019): 149–60. http://dx.doi.org/10.14710/j.gauss.v8i1.26629.

Full text

Abstract:

Unsecured Credit is one of the credit facilities provided by banks, where the prospective debtor can borrow some amount of fund from the bank without having to provide collateral. Credit scoring is a process that aims to assess the worthiness of credit applications and classify the credit applicants into prospective debtors whose the credit application is worthy to be accepted and prospective debtors whose the credit application should be rejected. One of the statistical methods that can be applied in examining the analysis of credit scoring is the Generalized Mean Distance-Based k-Nearest Neighbor (GMDKNN) classifier. Empirical study on this method uses 23,337 data of prospective debtor of unsecured credit in 2018, with the dependent variable being the credit scoring final decision and seven independent variables, i.e. age, child dependent, length of employment, age of the company, income, loan proposed, and duration of credit. Based on the feature selection test, all independent variables are significantly taking effect on the credit scoring final decision. The best classification model is obtained in the parameters k = 137 and p = -1 with the classification performance metrics represented by the values of APER = 0,2580, accuracy = 74,20%, sensitivity = 0,6083, specificity = 0,8393, AUC = 0,7238, and G-Mean = 0,7146.Keywords: Unsecured Credit, credit scoring, classification, Generalized Mean Distance-Based k-Nearest Neighbor (GMDKNN).

APA, Harvard, Vancouver, ISO, and other styles

34

Filatov, Vladyslav, and Аndriy Kaminsky. "Application of the Scoring Approach to Monitoring Function of Central Bank Credit Registry." Scientific Papers NaUKMA. Economics 6, no. 1 (2021): 73–83. http://dx.doi.org/10.18523/2519-4739.2021.6.1.73-83.

Full text

Abstract:

The Central Bank Credit Registry was established in Ukraine in 2018. The two key functions which are fulfilled by Credit Register are monitoring and credit information sharing. This paper is devoted to applying a scoring approach for monitoring function realization in segments of individuals. The logic of using scoring tools to monitoring is based on an objective to create an effective form which reflects the dynamic of the above-mentioned segment. Data mining procedures for Credit Registry were realized and most significant characteristics were chosen. Correlation analysis for characteristics was applied. Different approaches to construct scoring for monitoring functions were analyzed. Namely, logistic regression, Machine Learning, method grounded on tree created by the XGBoost algorithm. Last method demonstrated the best efficiency for scoring construction and can be developed for implementation. The views expressed are those of the authors and do not necessarily reflect those of the National Bank of Ukraine. JEL classіfіcatіon: G21

APA, Harvard, Vancouver, ISO, and other styles

35

Billiet, Lieven, Sabine Van Huffel, and Vanya Van Belle. "Interval Coded Scoring: a toolbox for interpretable scoring systems." PeerJ Computer Science 4 (April 2, 2018): e150. http://dx.doi.org/10.7717/peerj-cs.150.

Full text

Abstract:

Over the last decades, clinical decision support systems have been gaining importance. They help clinicians to make effective use of the overload of available information to obtain correct diagnoses and appropriate treatments. However, their power often comes at the cost of a black box model which cannot be interpreted easily. This interpretability is of paramount importance in a medical setting with regard to trust and (legal) responsibility. In contrast, existing medical scoring systems are easy to understand and use, but they are often a simplified rule-of-thumb summary of previous medical experience rather than a well-founded system based on available data. Interval Coded Scoring (ICS) connects these two approaches, exploiting the power of sparse optimization to derive scoring systems from training data. The presented toolbox interface makes this theory easily applicable to both small and large datasets. It contains two possible problem formulations based on linear programming or elastic net. Both allow to construct a model for a binary classification problem and establish risk profiles that can be used for future diagnosis. All of this requires only a few lines of code. ICS differs from standard machine learning through its model consisting of interpretable main effects and interactions. Furthermore, insertion of expert knowledge is possible because the training can be semi-automatic. This allows end users to make a trade-off between complexity and performance based on cross-validation results and expert knowledge. Additionally, the toolbox offers an accessible way to assess classification performance via accuracy and the ROC curve, whereas the calibration of the risk profile can be evaluated via a calibration curve. Finally, the colour-coded model visualization has particular appeal if one wants to apply ICS manually on new observations, as well as for validation by experts in the specific application domains. The validity and applicability of the toolbox is demonstrated by comparing it to standard Machine Learning approaches such as Naive Bayes and Support Vector Machines for several real-life datasets. These case studies on medical problems show its applicability as a decision support system. ICS performs similarly in terms of classification and calibration. Its slightly lower performance is countered by its model simplicity which makes it the method of choice if interpretability is a key issue.

APA, Harvard, Vancouver, ISO, and other styles

36

Kroemer, R. T. "Molecular modelling probes: docking and scoring." Biochemical Society Transactions 31, no. 5 (2003): 980–84. http://dx.doi.org/10.1042/bst0310980.

Full text

Abstract:

A general introduction to molecular modelling techniques in the area of protein–ligand interactions is given. Methods covered range from binding-site analysis to statistical treatment of sets of ligands. The main focus of this paper is on docking and scoring. After an outline of the main concepts, two specific application examples are given.

APA, Harvard, Vancouver, ISO, and other styles

37

Setemen, Komang, Luh Joni Erawati Dewi, and I. Ketut Purnamawan. "Computer-based peer assessment as a part of learning process." SHS Web of Conferences 42 (2018): 00024. http://dx.doi.org/10.1051/shsconf/20184200024.

Full text

Abstract:

This study aimed to develop prototype of computer based peer assessment application. This application is used for learning assessment which involves the students in learning process, either individually or in group. This study was research and development (R&D) model which adopted 4D model (Define, Design, Develop, and Disseminate). Prototype of this application was developed by utilizing internet media (online). The users of this system are lectures and students. In this application, the lecturers has roles to design the scoring rubrics, give the tasks, and assess the students’ tasks. The students had roles to submit the tasks, and assess their pairs. Every kind of scoring rubrics can be implemented in some subject matters which have same characteristics (sharing rubrics). This application is expected to produce transparent, quick, correct, and accurate scoring. It is also efficient for lecturers in students assessment. The online-based application design will make this application become an electronic assessment which can be accessed whenever and wherever.

APA, Harvard, Vancouver, ISO, and other styles

38

Wu, Desheng, and David L. Olson. "A TOPSIS Data Mining Demonstration and Application to Credit Scoring." International Journal of Data Warehousing and Mining 2, no. 3 (2006): 16–26. http://dx.doi.org/10.4018/jdwm.2006070102.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Baridam, Barilee. "Application of the Codon-based Scoring Method in Motif Detection." International Journal of Computer Applications 92, no. 9 (2014): 1–4. http://dx.doi.org/10.5120/16034-4811.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Shahin, R., W. Hussein, A. El-Sherif, and H. Mahgoub. "SCORING MODELS FOR PROCESS MONTIORING IN INDUSTRY A MECHATRONIC APPLICATION." International Conference on Applied Mechanics and Mechanical Engineering 15, no. 15 (2012): 1–14. http://dx.doi.org/10.21608/amme.2012.37053.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Rysová, Kateřina, Magdaléna Rysová, Michal Novák, Jiří Mírovský, and Eva Hajičová. "EVALD – a Pioneer Application for Automated Essay Scoring in Czech." Prague Bulletin of Mathematical Linguistics 113, no. 1 (2019): 9–30. http://dx.doi.org/10.2478/pralin-2019-0004.

Full text

Abstract:

Abstract In the paper, we present EVALD applications (Evaluator of Discourse) for automated essay scoring. EVALD is the first tool of this type for Czech. It evaluates texts written by both native and non-native speakers of Czech. We describe first the history and the present in the automatic essay scoring, which is illustrated by examples of systems for other languages, mainly for English. Then we focus on the methodology of creating the EVALD applications and describe datasets used for testing as well as supervised training that EVALD builds on. Furthermore, we analyze in detail a sample of newly acquired language data – texts written by non-native speakers reaching the threshold level of the Czech language acquisition required e.g. for the permanent residence in the Czech Republic – and we focus on linguistic differences between the available text levels. We present the feature set used by EVALD and – based on the analysis – we extend it with new spelling features. Finally, we evaluate the overall performance of various variants of EVALD and provide the analysis of collected results.

APA, Harvard, Vancouver, ISO, and other styles

42

Volkova, V. S., V. B. Gisin, and V. I. Solov'ev. "Data Mining Techniques: Modern Approaches to Application in Credit Scoring." Digest Finance 22, no. 4 (2017): 400–412. http://dx.doi.org/10.24891/el.22.4.400.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Volkova, E. S., V. B. Gisin, and V. I. Solov'ev. "Data mining techniques: Modern approaches to application in credit scoring." Finance and Credit 23, no. 34 (2017): 2044–60. http://dx.doi.org/10.24891/fc.23.34.2044.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Rouvillain, J. L., C. Derancourt, N. Moore, and P. Devos. "Scoring of medical publications with SIGAPS software: Application to orthopedics." Orthopaedics & Traumatology: Surgery & Research 100, no. 7 (2014): 821–25. http://dx.doi.org/10.1016/j.otsr.2014.06.020.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Volkova, V. S., V. B. Gisin, and V. I. Solov'ev. "Data Mining Techniques: Modern Approaches to Application in Credit Scoring." Digest Finance 22, no. 4 (2017): 400–412. http://dx.doi.org/10.24891/df.22.4.400.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

WU, Zhen-jie, Hua-mao YE, Ming-min LI, et al. "Application of R.E.N.A.L. scoring system in robotic laparoscopic partial nephrectomy." Academic Journal of Second Military Medical University 35, no. 4 (2014): 383. http://dx.doi.org/10.3724/sp.j.1008.2014.00383.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Maes, B., P. Meeus, L. Michaux, et al. "Application of the International Prognostic Scoring System for myelodysplastic syndromes." Annals of Oncology 10, no. 7 (1999): 825–30. http://dx.doi.org/10.1023/a:1008335814674.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Giudici, Paolo. "Bayesian data mining, with application to benchmarking and credit scoring." Applied Stochastic Models in Business and Industry 17, no. 1 (2001): 69–81. http://dx.doi.org/10.1002/asmb.425.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Kim, Young-Ju. "Injury severity scoring systems: a review of application to practice." Nursing in Critical Care 17, no. 3 (2012): 138–50. http://dx.doi.org/10.1111/j.1478-5153.2012.00498.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

V, Kalaivani, and Khyati Melanta. "APPLICATION OF AMIT JAIN’S SCORING SYSTEM IN DIABETIC FOOT AMPUTEES." Journal of Evolution of Medical and Dental Sciences 5, no. 28 (2016): 1413–17. http://dx.doi.org/10.14260/jemds/2016/333.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Application scoring'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles