Data Pre-Processing and Customized Onto-Graph Construction for Knowledge Extraction in Healthcare Domain of Semantic Web

Present electronic world produces enormous amount of data every second in various formats, especially in healthcare units. To efficiently utilize the available data by representing it in the machine readable form, the concept of Semantic web stepped in progressing towards automated knowledge discovery process. In this paper, comprehensive pre-processing techniques have been proposed for preparing the raw data to be presentable in structured format so as to construct the onto-graph for selected features in a health care domain. Cluster based Missing Value Imputation Algorithm (CMVI) has been proposed to enhance the quality of the imputed data which is the most important step during data pre-processing. Missing values were randomly induced into the Pima Indian Diabetic dataset with the missing ratio of 1%, 3% and 5% for each attribute up to 50% of the attributes in the original diabetic dataset. The experimental observations reveal that the quality of the pre-processed data is better compared to raw, unprocessed data in terms of imputation accuracy measured against coefficient of determination (R2 ), Index of agreement (d2 ) and Root Mean Square Error (RMSE).Documented results proved that the proposed techniques are comparatively superior than the traditional approaches with increased R2 & d2 and decreased RMSE scores. Further, importance of knowledge graph and various ontological representation types are discussed in short as construction of .owl file is the first step towards automation in semantic web.

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CBRL and CBRC: Novel Algorithms for Improving Missing Value Imputation Accuracy Based on Bayesian Ridge Regression

Symmetry ◽

10.3390/sym12101594 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1594

Author(s):

Samih M. Mostafa ◽

Abdelrahman S. Eladimy ◽

Safwat Hamad ◽

Hirofumi Amano

Keyword(s):

Missing Data ◽

Missing Values ◽

Mean Absolute Error ◽

Imputation Accuracy ◽

Absolute Error ◽

Coefficient Of Determination ◽

Mean Square ◽

Critical Problem ◽

Imputation Methods ◽

Novel Algorithms

In most scientific studies such as data analysis, the existence of missing data is a critical problem, and selecting the appropriate approach to deal with missing data is a challenge. In this paper, the authors perform a fair comparative study of some practical imputation methods used for handling missing values against two proposed imputation algorithms. The proposed algorithms depend on the Bayesian Ridge technique under two different feature selection conditions. The proposed algorithms differ from the existing approaches in that they cumulate the imputed features; those imputed features will be incorporated within the Bayesian Ridge equation for predicting the missing values in the next incomplete selected feature. The authors applied the proposed algorithms on eight datasets with different amount of missing values created from different missingness mechanisms. The performance was measured in terms of imputation time, root-mean-square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). The results showed that the performance varies depending on missing values percentage, size of the dataset, and the missingness mechanism. In addition, the performance of the proposed methods is slightly better.

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Missing Data - Better "Not to Have Them", but What If You Do? (Part 1)

Marketing ZFP ◽

10.15358/0344-1369-2019-4-21 ◽

2019 ◽

Vol 41 (4) ◽

pp. 21-32

Author(s):

Dirk Temme ◽

Sarah Jensen

Keyword(s):

Missing Data ◽

Statistical Power ◽

Missing Values ◽

Graphical Representation ◽

Marketing Research ◽

Likelihood Estimation ◽

Parameter Estimates ◽

Full Information Maximum Likelihood ◽

Definition Of ◽

Traditional Approaches

Missing values are ubiquitous in empirical marketing research. If missing data are not dealt with properly, this can lead to a loss of statistical power and distorted parameter estimates. While traditional approaches for handling missing data (e.g., listwise deletion) are still widely used, researchers can nowadays choose among various advanced techniques such as multiple imputation analysis or full-information maximum likelihood estimation. Due to the available software, using these modern missing data methods does not pose a major obstacle. Still, their application requires a sound understanding of the prerequisites and limitations of these methods as well as a deeper understanding of the processes that have led to missing values in an empirical study. This article is Part 1 and first introduces Rubin’s classical definition of missing data mechanisms and an alternative, variable-based taxonomy, which provides a graphical representation. Secondly, a selection of visualization tools available in different R packages for the description and exploration of missing data structures is presented.

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PENGARUH CITRA MEREK DAN KUALITAS BENIH TERHADAP KEPUTUSAN PEMBELIAN PADA PT.PRABU ARGO MANDIRI (Studi Kasus Penjualan Benih Tomat Merk Maya di Purwkarta)

JURISMA : Jurnal Riset Bisnis & Manajemen ◽

10.34010/jurisma.v6i2.434 ◽

2017 ◽

Vol 6 (2) ◽

Author(s):

Ahmad Iskandar

Keyword(s):

Product Quality ◽

Brand Image ◽

Hypothesis Test ◽

Descriptive Analysis ◽

Linear Regression Analysis ◽

Coefficient Of Determination ◽

Decision Variable ◽

Purchasing Decisions ◽

Business World

In the era of globalization, the competition in the business world becomes very tight. Companies vying to be able to continue to compete and survive in the business world. Each consumer must have had the expectation that the products they buy are able to provide satisfaction for them to be making purchasing decisions. Consumer purchasing decisions of companies to seeds virtual brand still low due to the brand image and quality of seeds that are still unsatisfactory.This study aims to determine the responses of respondents regarding brand image, product quality, purchasing decisions and how big an impact on the brand image itself against purchase decisions on the PT. Prabu Argo Mandiri Bandung and how much influence the quality of products on the purchase decision.The method by which the samples is Simple Random Sampling consists of 80 respondents. The method of analysis in this research using descriptive analysis and verification which is composed of multiple linear regression analysis. Product moment correlation analysis, and the coefficient of determination used to measure the level of influence of brand image and product quality on purchasing decisions.The results based on descriptive analysis of brand image variable is in good enough category, variable quality of the product is in the unfavorable category, and the purchase decision variable is in the unfavorable category. The results based on correlation test showed that the brand image is partially significant effect on purchasing decisions by 68% and the product quality is partially significant effect on purchasing decisions by 13%. Hypothesis test results suggested that the increased purchasing decisions partially and simultaneously influence through brand image and product quality.

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Impact of Raw Materials and Processing Techniques on The Microbiological Quality of Egyptian Domiati Cheese

International Journal of Veterinary Science ◽

10.37422/ijvs/20.060 ◽

2020 ◽

Keyword(s):

Raw Materials ◽

Microbiological Quality ◽

Raw Milk ◽

Plate Count ◽

E Coli ◽

Fresh Cheese ◽

Processing Techniques ◽

The Impact ◽

Total Yeast

Domiati cheese is the most popular brand of cheese ripened in brine in the Middle East in terms of consumed quantities. This study was performed to investigate the impact of the microbiological quality of the used raw materials, the applied traditional processing techniques and ripening period on the quality and safety of the produced cheese. Three hundred random composite samples were collected from three factories at Fayoum Governorate, Egypt. Collected samples represent twenty-five each of: raw milk, table salt, calf rennet, microbial rennet, water, environmental air, whey, fresh cheese, ripened cheese & swabs from: worker hands; cheese molds and utensils; tanks. All samples were examined microbiologically for Standard Plate Count (SPC), coliforms count, Staphylococcus aureus (S. aureus) count, total yeast & mould count, presence of E. coli, Salmonellae and Listeria monocytogenes (L. monocytogenes). The mean value of SPC, coliforms, S. aureus and total yeast & mould counts ranged from (79×102 CFU/m3 for air to 13×108 CFU/g for fresh cheese), (7×102 MPN/ cm2 for tank swabs to 80×106 MPN/ml for raw milk), (9×102 CFU/g for salt to 69×106 CFU/g for fresh cheese) and (2×102 CFU/cm2 for hand swabs to 60×104 CFU/g for fresh cheese), respectively. Whereas, E. coli, Salmonella and L. monocytogenes failed to be detected in all examined samples. There were significant differences in all determined microbiological parameters (p ≤0.05) between fresh and ripened cheese which may be attributed to different adverse conditions such as water activity, pH, salt content and temperature carried out to improve the quality of the product.

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New Monitoring Strategy for the Quality Control in the Processing Practice of Scutellariae Radix

Current Pharmaceutical Analysis ◽

10.2174/1573412915666190314121434 ◽

2020 ◽

Vol 16 (3) ◽

pp. 303-311

Author(s):

Qi Huang ◽

Chunsong Cheng ◽

Lili Li ◽

Daiyin Peng ◽

Cun Zhang

Keyword(s):

Quality Control ◽

Monitoring Strategy ◽

Scutellariae Radix ◽

Chromatographic Fingerprints ◽

New Strategy ◽

Processed Products ◽

Main Components ◽

Processing Techniques ◽

Multivariate Monitoring

Background: Scutellariae Radix (Huangqin) is commonly processed into 3 products for different clinical applications. However, a simple analytical method for quality control has rarely been reported to quickly estimate the degree of processing Huangqin or distinguish differently processed products or unqualified Huangqin products. Objective: To study a new strategy for quality control in the processing practice of Huangqin. Methods: Seven kinds of flavonoids that mainly exist in Huangqin were determined by HPLC-DAD. Chromatographic fingerprints were established to study the variation and discipline of the 3 processed products of Huangqin. PCA and OPLS-DA were used to classify differently processed products of Huangqin. Results: The results showed that baicalin and wogonoside were the main components in the crude and the alcohol Huangqin herb while baicalein and wogonin mainly existed in carbonized Huangqin. The results of mathematical statistics revealed that the processing techniques can make the quality of medicinal materials more uniform. Conclusion: This multivariate monitoring strategy is suitable for quality control in the processing of Huangqin.

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Comprehensive survey among statistical members of medical ethics committees in Germany on their personal impression of completeness and correctness of biostatistical aspects of submitted study protocols

BMJ Open ◽

10.1136/bmjopen-2019-032864 ◽

2020 ◽

Vol 10 (2) ◽

pp. e032864

Author(s):

Geraldine Rauch ◽

Lorena Hafermann ◽

Ulrich Mansmann ◽

Iris Pigeot

Keyword(s):

Medical Ethics ◽

Missing Values ◽

Sample Size Calculation ◽

Ethics Committees ◽

Secondary Outcome ◽

Study Protocols ◽

Individual Assessment ◽

Statistical Problems ◽

Multiple Comparison Procedures

ObjectivesTo assess biostatistical quality of study protocols submitted to German medical ethics committees according to personal appraisal of their statistical members.DesignWe conducted a web-based survey among biostatisticians who have been active as members in German medical ethics committees during the past 3 years.SettingThe study population was identified by a comprehensive web search on websites of German medical ethics committees.ParticipantsThe final list comprised 86 eligible persons. In total, 57 (66%) completed the survey.QuestionnaireThe first item checked whether the inclusion criterion was met. The last item assessed satisfaction with the survey. Four items aimed to characterise the medical ethics committee in terms of type and location, one item asked for the urgency of biostatistical training addressed to the medical investigators. The main 2×12 items reported an individual assessment of the quality of biostatistical aspects in the submitted study protocols, while distinguishing studies according to the German Medicines Act (AMG)/German Act on Medical Devices (MPG) and studies non-regulated by these laws.Primary and secondary outcome measuresThe individual assessment of the quality of biostatistical aspects corresponds to the primary objective. Thus, participants were asked to complete the sentence ‘In x% of the submitted study protocols, the following problem occurs’, where 12 different statistical problems were formulated. All other items assess secondary endpoints.ResultsFor all biostatistical aspects, 45 of 49 (91.8%) participants judged the quality of AMG/MPG study protocols much better than that of ‘non-regulated’ studies. The latter are in median affected 20%–60% more often by statistical problems. The highest need for training was reported for sample size calculation, missing values and multiple comparison procedures.ConclusionsBiostatisticians being active in German medical ethics committees classify the biostatistical quality of study protocols as low for ‘non-regulated’ studies, whereas quality is much better for AMG/MPG studies.

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Productivity and Nutritional Trait Improvements of Different Tomatoes Cultivated with Effective Microorganisms Technology

Agriculture ◽

10.3390/agriculture11020112 ◽

2021 ◽

Vol 11 (2) ◽

pp. 112

Author(s):

Giuseppina Tommonaro ◽

Gennaro Roberto Abbamondi ◽

Barbara Nicolaus ◽

Annarita Poli ◽

Costantino D’Angelo ◽

...

Keyword(s):

Plant Growth Promoting Bacteria ◽

Effective Microorganisms ◽

Microbial Inoculation ◽

Yield And Quality ◽

Promising Strategy ◽

Plant Growth Promoting ◽

Growth Promoting ◽

Traditional Approaches ◽

Nutritional Aspect

The use of ecofriendly strategies, such as the use of Plant Growth Promoting Bacteria, to improve the yield and quality of crops has become necessary to satisfy the growing demand of food and to avoid the use of chemical fertilizers and pesticides. In this study, we report the effects of an innovative microbial inoculation technique, namely Effective Microorganisms (EM), compared with traditional approaches, on productivity and nutritional aspect of four tomato varieties: Brandywine, Corbarino Giallo, S. Marzano Cirio 3, S. Marzano Antico. Results showed an increase of plant productivity as well as an enhanced antioxidant activity mainly in San Marzano Antico and Brandywine varieties treated with EM technology. Moreover, the polyphenol and carotenoid contents also changed, in response to the plant treatments. In conclusion, the application of EM® technology in agriculture could represent a very promising strategy in agricultural sustainability.

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Clay-Based Brick Porosity Estimation Using Image Processing Techniques

Journal of Intelligent Systems ◽

10.1515/jisys-2018-0191 ◽

2019 ◽

Vol 29 (1) ◽

pp. 1226-1234

Author(s):

Safa Jida ◽

Hassan Ouallal ◽

Brahim Aksasse ◽

Mohammed Ouanan ◽

Mohamed El Amraoui ◽

...

Keyword(s):

Electron Microscopy ◽

Image Processing ◽

Scanning Electron Microscopy ◽

Computer Vision ◽

Image Processing Techniques ◽

Processing Techniques ◽

Porosity Estimation ◽

Microscopy Images ◽

Scanning Electron

Abstract This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation.

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Systematic Review of the Integrative Medicine Recommendations for Patients with Pancreatic Cancer

Surgeries ◽

10.3390/surgeries2020022 ◽

2021 ◽

Vol 2 (2) ◽

pp. 216-230

Author(s):

Andrew A. Gumbs ◽

Manana Gogol ◽

Gaya Spolverato ◽

Hebatallah Taher ◽

Elie K. Chouillard

Keyword(s):

Systematic Review ◽

Pancreatic Cancer ◽

Integrative Medicine ◽

Lifestyle Changes ◽

Randomized Controlled ◽

Nutrition Supplementation ◽

Traditional Therapies ◽

Traditional Approaches

Introduction: Integrative medicine (IM) is a relatively new field where non-traditional therapies with peer-reviewed evidence are incorporated or integrated with more traditional approaches. Methods: A systematic review of the literature from the last 10 years was done by searching clinical trials and randomized-controlled trials on Pubmed that discuss nutrition, supplementation, and lifestyle changes associated with “Pancreatic Cancer.” Results: Only 50 articles ultimately met the inclusion criteria for this review. A total of 15 articles discussed the role of obesity and 10 discussed the influence of stress in increasing the risk of pancreatic cancer. Six discussed the potential beneficial role of Vitamins, 5 of cannabinoids, 4 an anti-inflammatory diet, 3 of nut consumption, 2 of green tea consumption, 2 of curcumin supplementation, 1 role of melatonin, and 1 of probiotics. One article each was found on the theoretical benefits of adhering to either a Mediterranean or ketogenic diet. Discussion: As more surgeons become interested in IM, it is hoped that more diseases where the curative treatment is mainly surgical can benefit from the all-encompassing principles of IM in an effort to improve quality of life and survival in patients with pancreatic cancer.

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MMoOn Core – the Multilingual Morpheme Ontology

Semantic Web ◽

10.3233/sw-200412 ◽

2020 ◽

pp. 1-29

Author(s):

Bettina Klimek ◽

Markus Ackermann ◽

Martin Brümmer ◽

Sebastian Hellmann

Keyword(s):

Semantic Web ◽

Linked Data ◽

Semantic Model ◽

Lexical Resources ◽

Domain Specific ◽

Word Forms ◽

Language Data ◽

Core Ontology ◽

Machine Readable ◽

Rapid Emergence

In the last years a rapid emergence of lexical resources has evolved in the Semantic Web. Whereas most of the linguistic information is already machine-readable, we found that morphological information is mostly absent or only contained in semi-structured strings. An integration of morphemic data has not yet been undertaken due to the lack of existing domain-specific ontologies and explicit morphemic data. In this paper, we present the Multilingual Morpheme Ontology called MMoOn Core which can be regarded as the first comprehensive ontology for the linguistic domain of morphological language data. It will be described how crucial concepts like morphs, morphemes, word forms and meanings are represented and interrelated and how language-specific morpheme inventories can be created as a new possibility of morphological datasets. The aim of the MMoOn Core ontology is to serve as a shared semantic model for linguists and NLP researchers alike to enable the creation, conversion, exchange, reuse and enrichment of morphological language data across different data-dependent language sciences. Therefore, various use cases are illustrated to draw attention to the cross-disciplinary potential which can be realized with the MMoOn Core ontology in the context of the existing Linguistic Linked Data research landscape.

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