Real-world products and physics-based simulations are becoming interconnected. In particular, real-time capable dynamic simulation has made it possible for simulation models to run in parallel and simultaneously with operating machinery. This capability combined with state observer techniques such as Kalman filtering have enabled the synchronization between simulation and the real world. State estimator techniques can be applied to estimate unmeasured quantities, also referred as virtual sensing, or to enhance the quality of measured signals. Although synchronized models could be used in a number of ways, value creation and business model development are currently defining the most practical and beneficial use cases from a business perspective. The research reported here reveals the communication and collaboration methods that lead to economically relevant technology solutions. Two case examples are given that demonstrate the proposed methodology. The work benefited from the broad perspective of researchers from different backgrounds and the joint effort to drive the technology development towards business relevant cases.
Abstract. Today a number of renewable energy technologies are available for power generation, but fossil fuels are still providing a dominant share nevertheless. In order to decrease the electric bill and save our environment, energy conservation is always crucial. In this paper a very interesting idea is presented which is economically viable to reduce electricity usage in our buildings. An effort has been made to estimate the amount of energy that could be saved in the dormitory section of the IMOP building in Russia. Although there are many ways to reduce the consumption of electricity in this building but here the emphasis is on changing light bulbs inside the rooms, kitchen, toilet and bathroom of each apartment. The scope of the study is to figure out monthly electricity saving by replacing traditional light bulbs by LED light bulbs in the building under consideration. The total investment required and the payback period is also presented.
Rotor bars are one of the most failure-critical components in induction machines. We present an approach for developing a rotor bar fault identification classifier for induction machines. The developed machine learning-based models are based on simulated electrical current and vibration velocity data and measured vibration acceleration data. We introduce an approach that combines sequential model-based optimization and the nested cross-validation procedure to provide a reliable estimation of the classifiers’ generalization performance. These methods have not been combined earlier in this context. Automation of selected parts of the modeling procedure is studied with the measured data. We compare the performance of logistic regression and CatBoost models using the fast Fourier-transformed signals or their extracted statistical features as the input data. We develop a technique to use domain knowledge to extract features from specific frequency ranges of the fast Fourier-transformed signals. While both approaches resulted in similar accuracy with simulated current and measured vibration acceleration data, the feature-based models were faster to develop and run. With measured vibration acceleration data, better accuracy was obtained with the raw fast Fourier-transformed signals. The results demonstrate that an accurate and fast broken rotor bar detection model can be developed with the presented approach.
Background: Medical practitioners often encounter dentine hypersensitivity, which is a challenging problem to manage. Dentine hypersensitivity is characterized by acute, transient discomfort from an exposed dentin region in response to stimuli that is unrelated to any other disease. Objective: To assess the frequency of dentine hypersensitivity and their associated risk factors amongst the patients visiting the dental outpatient department Methodology: The current study was cross-sectional, carried out at the dental outpatient department of Qazi Hussain Ahmad Medical Complex, Nowshera for duration of six months from January 2022 to June 2022. The survey questionnaire included queries about patient’s age, gender, dentine hypersensitivity presence/absence awareness and factors associated with the dentine hypersensitivity. Data analysis was carried out by using IBM SPSS version 23. Results: The overall frequency of dentine hypersensitivity was observed in 98 (35%) patients. Based on gender, dentine hypersensitivity was observed in 35 (27.77%) males and 63 (40.90%) females. The major risk factors of tooth sensitivity were ice cream in 118 (42.14%) participants followed by iced water in 64 (22.86%) participants. Practical implication: There is little information available in Pakistan on how much the general public is familiar of dentine hypersensitivity. Therefore, this study will help to determine the prevalence of dentine hypersensitivity amongst patients who visited the dental outpatient clinic at the Qazi Hussain Ahmad Medical Complex in Nowshera and to analyze the various risk factors associated with it. Conclusion: Our study concludes that dentine hypersensitivity is highly prevalent in patients visiting the dental outpatients department. Dentine hypersensitivity was frequently observed in females as compared to males. Ice cream and iced water were the major risk factors in our study. Keywords: Dentine hypersensitivity; Frequency; Outpatient department; Risk factors
Background: Cancer is considered the most fatal diseases which is accountable for Cancer second leading cause of death in the developed country like United States and contributes to a high mortality rate in all age groups. Patient with cancer face life-threating situation through the period of diseases process. Aim: To explore the spiritual well-being and hopelessness among the leukemia patient and it correlation with each other. Methodology: A descriptive correlation design was used while patient with leukemia were the study participants and HMC and IRNUM were study setting. Sample size of the study was 320 while using consecutive sampling technique. Data was collected through two valid and reliable questionnaires of spiritual well-being and hopelessness, after the approval of study by IRB. Results: In the study majority of the participants were male 213(67%) and female 107(33%) In spiritual well-being the higher number of participants was moderate spiritual well-being (66%), followed by higher spiritual well-being (22%) and poor spiritual well-being (12%). The higher number of participant hopelessness were moderate (49%), then severe hopelessness (28%), and mild hopelessness (23%). Conclusion: The study concluded that there is a positive correlation between spiritual well-being and hopelessness. Spiritual and religious well-being is important to cope with these issues and improves quality of life. Keywords: Hopelessness, Cancer, spiritual well-being, leukemia
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