• International Journal of Contents
• /
• v.13 no.1
• /
• pp.38-44
• /
• 2017

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.5
• /
• pp.824-829
• /
• 2015

The rotary type testing machine undergoes mechanical stress as an external force is applied. In case of the rotary type testing machine, even a tiny flaw results in a fatal demage because the size of the machine is huge. Therefore, when designing the rotary type testing machine, it is necessary to secure a safety factor with the mechanical stress analysis in order to prevent the machine from being destroyed due to scattering or transformation of rotating field. This thesis proposes a LSM rotary type tesitng machine which rotates at the speed of up to 600km/h. And the mechanical stress is considered in order that the safety factor remains above 1.5 at the maximum speed. In addition, because normal force as well as thrust occurs in the machine, the normal force exerted was considered through the strength analysis. Finally, a design plan which enables to weaken the normal force affecting the rotary type testing machine is introduced and its validity is proved by the results of FEM analysis.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2007.10a
• /
• pp.21-24
• /
• 2007

This paper deals with introduction of testing equipments for the evaluation of dynamic tensile characteristics of auto-body steel sheets and the crashworthiness of auto-body members. The servo-hydraulic high speed material testing machine was developed for tensile tests at the intermediate strain rate to obtain the tensile material properties at the strain rate under 500/sec. The split Hopkinson bar apparatus using the elastic wave was developed for dynamic material characteristics at the high strain rate ranged from 1,000 to 10,000/sec. The servo-hydraulic high speed crash testing machine is the equipment for the evaluation of the collapse load and crashworthiness of auto-body members. High speed carrying truck crashes to specimen with the maximum velocity of 17 m/sec.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.318-326
• /
• 2022

Marketing stress testing is a new method of identifying the company's strengths and weaknesses in a turbulent environment. Technically, this is a complex procedure, so it involves artificial intelligence and machine learning. The main problem is currently the development of methodological approaches to the development of the company's digital model, which will provide a framework for machine learning. The aim of the study was to identify and develop an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. This aim provided the company's activities to be considered as a set of elements (business processes, products) and factors that affect them (marketing environment). The article proposes an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. The proposed approach includes four main elements that are subject to parameterization: elements of the company's internal environment, factors of the marketing environment, the company' core competency and factors impacting the company. Matrices for evaluating the results of the work of expert groups to determine the degree of influence of the marketing environment factors were developed. It is proposed to distinguish between mega-level, macro-level, meso-level and micro-level factors depending on the degree of impact on the company. The methodological limitation of the study is that it involves the modelling method as the only one possible at this stage of the study. The implementation limitation is that the proposed approach can only be used if the company plans to use machine learning for marketing stress testing.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.13 no.1
• /
• pp.199-203
• /
• 1989

본 연구에서 제작된 시험기는 연구자 개인의 경제적 수준에서 충분이 제작이 가능한 것이다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.275-280
• /
• 1999

This study is object to program development of fatigue test for universal testing machine. Fatigue program is consist of test simulation, data analysis and print report by control fatigue testing program which expansively applies tension-compression tests with using oil pressure mechanism by Visual Basic software running under windows 98.

• Smart Structures and Systems
• /
• v.30 no.3
• /
• pp.255-261
• /
• 2022

When no extensometer is available in a generic tensile-compression test carried out by a universal testing machine (for instance the model BIONIX from Material Testing Systems (MTS)), the test results only provide the relative displacement between the machine grips. The test does not provide any information on the local behaviour of the material. This contribution presents the potential of an application of Digital Image Correlation (DIC) toward the reconstruction of the behaviour along the specimen. In particular, the authors test a Ni-Ti shape memory alloys (SMA) specimen with emphasis on the coupling of the two measurement techniques.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.11
• /
• pp.34-41
• /
• 2001

This study is to investigate the energy absorption characteristics of CFRP(Carbon-Fiber Reinforced Plastics) tubes on static and dynamic tests. Axial static compression tests have been carried out using the static testing machine(Shin-gang buckling testing machine) and dynamic compression tests have been utilized using an vertical crushing testing machine. When such tubes are subjected to crushing loads, the response is complex and depends on the interaction between the different mechanisms that could control the crushing process. The collapse characteristics and energy absorption have been examined for various tubes. Energy absorption of the tubes are increased as changes in the lay-up which may increase the modulus of tubes. The results have been varied significantly as a function of ply orientation and interlaminar number.

• Journal of KIISE
• /
• v.43 no.9
• /
• pp.953-962
• /
• 2016

Model-based testing is a technique for performing the test by using a model that represents the behavior of the system as a system specification. Industrial domains such as automotive, military/aerospace, medical, railway and nuclear power generation require model-based testing and code coverage-based testing to improve the quality of software. Despite the fact that both model-based testing and code coverage-based testing are required, difficulty in achieving a high coverage using model-based testing caused by the abstraction level difference between the test model and the source code, results in the need for performing model-based testing separately. In this study, to overcome the limitations of the existing model-based testing, we proposed the state machine transformation method to effectively improve the code coverage using the protocol state machine, one of the typical modeling methods is used as the test model in model-based testing, as the test model. In addition, we performed a case study of both systems and analyzed the effectiveness of the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.05a
• /
• pp.188-188
• /
• 2004

Modal testing and analysis is a primary tool for obtaining reliable models to represent the dynamics of structures. When a structure is tested in order to collect measured data in modal testing, we usually use attached accelerometers to pick up the response data. Change in modal parameters due to the mass of transducers in modal testing is a well-known problem. The disadvantages are the shift of measured modal frequencies and the change of modal shapes, which can cause inaccurate results in further analysis. Modal analysis methods in frequency domain are based on a set of measured frequency response functions(FRF).(omitted)