Liliana Aguilar^∗, Salvador W. Nava-Díaz, Gabriel Chavira^†

Computer Systems Science and Engineering, Vol.34, No.5, pp. 297-303, 2019, DOI:10.32604/csse.2019.34.297

Abstract Natural ventilation is a component that provides a positive impact in the quality of air conditions in indoor environments, especially in non-industrial buildings. The maintenance of a continuous entrance of outside air through windows provides to the indoor a feasible and affordable manner to regulate and sustain low standards in theVOC (Volatile Organic Compounds). The technology and the Human Computer-Interaction have contributed to the creation of Intelligent Environments (EI) that provides to humans being a positive and non-intrusive responsiveness of the environment to improve their quality of life in daily activities. The Decision Trees for… More >

Kundur Shantisagar, R. Jegadeeshwaran^*, G. Sakthivel, T. M. Alamelu Manghai

Structural Durability & Health Monitoring, Vol.13, No.3, pp. 303-316, 2019, DOI:10.32604/sdhm.2019.00355

Abstract The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools. This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach. A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe, where the condition of tool is monitored using vibration characteristics. The vibration signals for conditions such as heathy, damaged, thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system. The descriptive statistical features… More >

Aziguli Wulam^1,2, Yingshuai Wang^1,2, Dezheng Zhang^1,2,*, Jingyue Sang³, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1003-1013, 2019, DOI:10.32604/cmc.2019.07704

Abstract In recent years, the models combining traditional machine learning with the deep learning are applied in many commodity recommendation practices. It has been proved better performance by the means of the neural network. Feature engineering has been the key to the success of many click rate estimation model. As we know, neural networks are able to extract high-order features automatically, and traditional linear models are able to extract low-order features. However, they are not necessarily efficient in learning all types of features. In traditional machine learning, gradient boosting decision tree is a typical representative of More >

Kamaljit Kaur^{1, *}, Kuljit Kaur²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 913-946, 2019, DOI:10.32604/cmc.2019.07675

Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the More >

Ahmad Alomari^1,∗, Alain April¹, Carlos Monsalve², Amjad Gawanmeh³

Computer Systems Science and Engineering, Vol.33, No.3, pp. 219-227, 2018, DOI:10.32604/csse.2018.33.219

Abstract Decision trees are among the best-known decision-making techniques and have been used extensively for both data analysis and predictive modeling. BPM+ is a novel process modeling approach that helps represent business process models in a consistent and structured way to meet different stakeholders’ process representation needs. This paper reports on the outcomes of an ontological analysis of the potential use of decision-tree representations as a new BPM+ perspective for the operational level of abstraction. This new perspective effectively demonstrates how a specialized/operational BPM stakeholder perspective can be used to improve the existing organizational business process More >

C. K. Madhusudana¹, N. Gangadhar¹, Hemantha Kumar, Kumar,^*,1, S. Narendranath¹

Structural Durability & Health Monitoring, Vol.12, No.2, pp. 111-127, 2018, DOI:10.3970/sdhm.2018.01262

Abstract This paper presents the fault diagnosis of face milling tool based on machine learning approach. While machining, spindle vibration signals in feed direction under healthy and faulty conditions of the milling tool are acquired. A set of discrete wavelet features is extracted from the vibration signals using discrete wavelet transform (DWT) technique. The decision tree technique is used to select significant features out of all extracted wavelet features. C-support vector classification (C-SVC) and ν-support vector classification (ν-SVC) models with different kernel functions of support vector machine (SVM) are used to study and classify the tool More >

T. M. Alamelu Manghai¹, R. Jegadeeshwaran²

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 149-167, 2017, DOI:10.3970/sdhm.2017.011.149

Abstract Hydraulic brakes in automobiles are an important control component used not only for the safety of the passenger but also for others moving on the road. Therefore, monitoring the condition of the brake components is inevitable. The brake elements can be monitored by studying the vibration characteristics obtained from the brake system using a proper signal processing technique through machine learning approaches. The vibration signals were captured using an accelerometer sensor under a various fault condition. The acquired vibration signals were processed for extracting meaningful information as features. The condition of the brake system can More >

Rahul Kumar Sharma^*1, V. Sugumaran¹, Hemantha Kumar², Amarnath M³

Structural Durability & Health Monitoring, Vol.11, No.1, pp. 1-16, 2017, DOI:10.3970/sdhm.2017.012.001

Abstract Most of the machineries in small or large scale industry have rotating element supported by bearings for rigid support and accurate movement. For proper functioning of machinery, condition monitoring of the bearing is very important. In present study sound signal is used to continuously monitor bearing health as sound signals of rotating machineries carry dynamic information of components. There are numerous studies in literature that are reporting superiority of vibration signal of bearing fault diagnosis. However, there are very few studies done using sound signal. The cost associated with condition monitoring using sound signal (Microphone)… More >

R. Jegadeeshwaran¹, V. Sugumaran², K.P. Soman³

Structural Durability & Health Monitoring, Vol.10, No.1, pp. 81-97, 2014, DOI:10.3970/sdhm.2014.010.081

Abstract In automobile, brake system is an essential part responsible for control of the vehicle. Vibration signals of a rotating machine contain the dynamic information about its health condition. Many research papers have reported the suitability of vibration signals for fault diagnosis applications. Many of them are based on (Fast Fourier Transform) FFT, which have their own drawback with nonstationary signals. Hence, there is a need for development of new methodologies to infer diagnostic information from such non stationary signals. This paper uses vibration signals acquired from a hydraulic brake system under good and simulated faulty… More >

A.S. Koyuncugil¹, N. Ozgulbas²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.2, pp. 39-46, 2009, DOI:10.3970/icces.2009.011.039

Abstract In this paper, a data mining model for detecting financial and operational risk indicators by CHAID Decision Tree is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the More >