Identifying Technical Debt through a Code Comment Mining Tool

2019 ◽

Vol 13 (1) ◽

pp. 27-36

Author(s):

Andreas Neubert

Keyword(s):

Data Mining ◽

Human Error ◽

Predictive Analysis ◽

Data Mining Algorithm ◽

It Infrastructure ◽

Monitoring Procedure ◽

Manual Recording ◽

Mining Tool ◽

General Cargo ◽

Different Characteristics

Due to the different characteristics of the piece goods (e.g. size and weight), they are transported in general cargo warehouses by manually-operated industrial trucks such as forklifts and pallet trucks. Since manual activities are susceptible to possible human error, errors occur in logistical processes in general cargo warehouses. This leads to incorrect loading, stacking and damage to storage equipment and general cargo. It would be possible to reduce costs arising from errors in logistical processes if these errors could be remedied in advance. This paper presents a monitoring procedure for logistical processes in manually-operated general cargo warehouses. This is where predictive analysis is applied. Seven steps are introduced with a view to integrating predictive analysis into the IT infrastructure of general cargo warehouses. These steps are described in detail. The CRISP4BigData model, the SVM data mining algorithm, the data mining tool R, the programming language C++ for the scoring in general cargo warehouses represent the results of this paper. After having created the system and installed it in general cargo warehouses, initial results obtained with this method over a certain time span will be compared with results obtained without this method through manual recording over the same period.

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Identifying Key Fraud Indicators in the Automobile Insurance Industry Using SQL Server Analysis Services

Studia Universitatis Babe-Bolyai Oeconomica ◽

10.2478/subboec-2019-0009 ◽

2019 ◽

Vol 64 (2) ◽

pp. 53-71

Author(s):

Botond Benedek ◽

Ede László

Keyword(s):

Neural Network ◽

Decision Tree ◽

Naive Bayes ◽

Insurance Industry ◽

Naïve Bayes ◽

Sql Server ◽

Categorical Variables ◽

Automobile Insurance ◽

Price Determination ◽

Mining Tool

Abstract Customer segmentation represents a true challenge in the automobile insurance industry, as datasets are large, multidimensional, unbalanced and it also requires a unique price determination based on the risk profile of the customer. Furthermore, the price determination of an insurance policy or the validity of the compensation claim, in most cases must be an instant decision. Therefore, the purpose of this research is to identify an easily usable data mining tool that is capable to identify key automobile insurance fraud indicators, facilitating the segmentation. In addition, the methods used by the tool, should be based primarily on numerical and categorical variables, as there is no well-functioning text mining tool for Central Eastern European languages. Hence, we decided on the SQL Server Analysis Services (SSAS) tool and to compare the performance of the decision tree, neural network and Naïve Bayes methods. The results suggest that decision tree and neural network are more suitable than Naïve Bayes, however the best conclusion can be drawn if we use the decision tree and neural network together.

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Performance Comparison among Meta Classifier Algorithms in WEKA

International Journal of Advanced Science Computing and Engineering ◽

10.30630/ijasce.1.2.11 ◽

2019 ◽

Vol 1 (2) ◽

pp. 106-112

Author(s):

Nur Amiratun Nazihah Roslan ◽

Hairulnizam Mahdin ◽

Shahreen Kasim

Keyword(s):

Social Networking ◽

Performance Comparison ◽

Data Availability ◽

Data Mining Tool ◽

Huge Data ◽

Technology Advancement ◽

The Social ◽

The World ◽

Media Platform ◽

Mining Tool

With the rise of social networking approach, there has been a surge of users generated content all over the world and with that in an era where technology advancement are up to the level where it could put us in a step ahead of pathogens and germination of diseases, we couldn’t help but to take advantage of that advancement and provide an early precaution measures to overcome it. Twitter on the other hand are one of the social media platform that provides access towards a huge data availability. To manipulate those data and transform it into an important information that could be used in many different scope that could help improve people’s life for the better. In this paper, we gather all algorithm that are available inside Meta Classifier to compare between them on which algorithm suited the most with the dengue fever dataset. This research are using WEKA as the data mining tool for data analyzation.

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Complete genome of mangrove-derived anti-MRSA streptomycete, Streptomyces pluripotens MUSC 135T

Progress In Microbes & Molecular Biology ◽

10.36877/pmmb.a0000004 ◽

2018 ◽

Vol 1 (1) ◽

Author(s):

Hooi-Leng Ser ◽

Kok-Gan Chan ◽

Wen-Si Tan ◽

Wai-Fong Yin ◽

Bey-Hing Goh ◽

...

Keyword(s):

Complete Genome ◽

Methicillin Resistant Staphylococcus Aureus ◽

Gene Clusters ◽

Salmonella Typhi ◽

Bacteriocin Production ◽

Trna Genes ◽

Genus Streptomyces ◽

Mining Tool ◽

Bioactive Potential ◽

Effective Drugs

Microorganisms serve as attractive resources, owing to their ability to synthesize structurally-diverse substanceswith various bioactivities. Within the Bacteria domain, members of the genus Streptomyces have demonstrated remarkableability to produce clinically useful, secondary metabolites such as anticancer, antioxidants, antivirals and antibacterials.Streptomyces pluripotens MUSC 135T was isolated as novel strain from mangrove forest in Malaysia. This strain exhibitedbroad spectrum bacteriocin against several pathogens including methicillin-resistant Staphylococcus aureus (MRSA) strainATCC BAA-44, Salmonella typhi ATCC 19430T and Aeromonas hydrophila ATCC 7966T. Thus, the strain was selected forwhole genome sequencing as an attempt to explore its bioactive potential. Here we report the first complete genome of S.pluripotens MUSC 135T genome which comprise of 7.35 Mbp with G+C content of 69.9 %. A total of 6,404 open readingframes (ORFs) were predicted, along with 18 rRNA and 69 tRNA genes. Using bacteriocin mining tool, BAGEL detectedeights gene clusters associated with bacteriocin production including lanthipeptides and linear azol(in)e-containing peptides(LAPs). Members of Streptomyces have contributed greatly towards improving lives, particularly against deadly infectionsand chronic diseases. The availability of S. pluripotens MUSC 135T genome sequence has opened new window for drugdiscovery, particularly for effective drugs against harmful pathogens such as MRSA and certainly deserves further detailedstudy.

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