Learning With Imbalanced Data in Smart Manufacturing: A Comparative Analysis

The Internet of Things (IoT) paradigm is revolutionising the world of manufacturing into what is known as Smart Manufacturing or Industry 4.0. The main pillar in smart manufacturing looks at harnessing IoT data and leveraging machine learning (ML) to automate the prediction of faults, thus cutting maintenance time and cost and improving the product quality. However, faults in real industries are overwhelmingly outweighed by instances of good performance (faultless samples); this bias is reflected in the data captured by IoT devices. Imbalanced data limits the success of ML in predicting faults, thus presents a significant hindrance in the progress of smart manufacturing. Although various techniques have been proposed to tackle this challenge in general, this work is the first to present a framework for evaluating the effectiveness of these remedies in the context of manufacturing. We present a comprehensive comparative analysis in which we apply our proposed framework to benchmark the performance of different combinations of algorithm components using a real-world manufacturing dataset. We draw key insights into the effectiveness of each component and inter-relatedness between the dataset, the application context, and the design of the ML algorithm

Quantum three-body system in D dimensions

The independent eigenstates of the total orbital angular momentum operators for a three-body system in an arbitrary D-dimensional space are presented by the method of group theory. The Schr\"{o}dinger equation is reduced to the generalized radial equations satisfied by the generalized radial functions with a given total orbital angular momentum denoted by a Young diagram $[\mu,\nu,0,...,0]$ for the SO(D) group. Only three internal variables are involved in the functions and equations. The number of both the functions and the equations for the given angular momentum is finite and equal to $(\mu-\nu+1)$.Comment: 16 pages, no figure, RevTex, Accepted by J. Math. Phy

Relativistic Aharonov-Casher Phase in Spin One

The Aharonov-Casher (AC) phase is calculated in relativistic wave equations of spin one. The AC phase has previously been calculated from the Dirac-Pauli equation using a gauge-like technique \cite{MK1,MK2}. In the spin-one case, we use Kemmer theory (a Dirac-like particle theory) to calculate the phase in a similar manner. However the vector formalism, the Proca theory, is more widely known and used. In the presence of an electromagnetic field, the two theories are `equivalent' and may be transformed into one another. We adapt these transformations to show that the Kemmer theory results apply to the Proca theory. Then we calculate the Aharonov-Casher phase for spin-one particles directly in the Proca formalism.Comment: 12 page

An overview of smart irrigation systems using IoT

Countries are working into making agriculture more sustainable by integrating different technologies to enhance its operation. Implementing improvements in irrigation systems is crucial for the water-use efficiency and works as a contributor to Sustainable Development Goals (SDGs) under the United Nations specifically Goal 6 and Target 6.4. This paper aims to highlight the contribution of SMART irrigation using Internet of Things (IoT) and sensory systems in relation to the SDGs. The study is based on a qualitative design along with focusing on secondary data collection method. Automated irrigation systems are essential for conservation of water, this improvement could have a vital role in minimizing water usage. Agriculture and farming techniques is also linked with IoT and automation, to make the whole processes much more effective and efficient. Sensory systems helped farmers better understand their crops and reduced the environmental impacts and conserve resources. Through these advanced systems effective soil and weather monitoring takes place along with efficient water management. Irrigation systems have been determined as positive contributor toward optimized irrigation systems that could enhance the use of continuous research and development which focus on enhancing the sustainable operations and cost reduction. Lastly, the challenges and benefits for the implementation of sensory based irrigation systems are discussed. This review will assist researchers and farmers to better understand irrigation techniques and provide an adequate approach would be sufficient to carry out irrigation related activities

On two superintegrable nonlinear oscillators in N dimensions

We consider the classical superintegrable Hamiltonian system given by $H=T+U={p^2}/{2(1+\lambda q^2)}+{{\omega}^2 q^2}/{2(1+\lambda q^2)}$, where U is known to be the "intrinsic" oscillator potential on the Darboux spaces of nonconstant curvature determined by the kinetic energy term T and parametrized by {\lambda}. We show that H is Stackel equivalent to the free Euclidean motion, a fact that directly provides a curved Fradkin tensor of constants of motion for H. Furthermore, we analyze in terms of {\lambda} the three different underlying manifolds whose geodesic motion is provided by T. As a consequence, we find that H comprises three different nonlinear physical models that, by constructing their radial effective potentials, are shown to be two different nonlinear oscillators and an infinite barrier potential. The quantization of these two oscillators and its connection with spherical confinement models is briefly discussed.Comment: 11 pages; based on the contribution to the Manolo Gadella Fest-60 years-in-pucelandia, "Recent advances in time-asymmetric quantum mechanics, quantization and related topics" hold in Valladolid (Spain), 14-16th july 201

Partial discharge detection using low cost RTL-SDR model for wideband spectrum sensing

Partial discharge (PD) is one of the predominant factors to be controlled to ensure reliability and undisrupted functions of power generators, motors, Gas Insulated Switchgear (GIS) and grid connected power distribution equipment, especially in the future smart grid. The emergence of wireless technology has provided numerous opportunities to optimise remote monitoring and control facilities that can play a significant role in ensuring swift control and restoration of HV plant equipment. In order to monitor PD, several approaches have been employed, however, the existing schemes do not provide an optimal approach for PD signal analysis, and are very costly. In this paper an RTL-SDR (Software Defined Radio) based spectrum analyser has been proposed in order to provide a potentially low cost solution for PD detection and monitoring. Initially, a portable spectrum analyser has been used for PD detection that was later replaced by an RTL-SDR device. The proposed schemes exhibit promising results for spectral detection within the VHF and UHF band

A population-based study of 15,000 people on Knowledge and awareness of lung cancer symptoms and risk factors in Saudi Arabia

Background: Lung cancer is currently the most fatal form of cancer worldwide, ranking as the fourth most prevalent type in Saudi Arabia, particularly among males. This trend is expected to increase with growing population, lifestyle changes, and aging population. Understanding the awareness of the Saudi population regarding the risk factors and symptoms of lung cancer is necessary to attenuate the predicted increase in cases. Method: A cross-sectional, population-based survey was performed using a previously validated questionnaire (Lung CAM). Multiple linear regression analysis was used to assess variables associated with deficiency in knowledge and awareness of risk factors and symptoms of lung cancer. Results: Majority of the 15,099 respondents were male (65%), aged between 18 and 30 years (53%), 50% of which were educated up to a bachelor’s degree level. Overall awareness of lung cancer signs and symptoms was 53%, with painful cough and coughing up blood being the best-known symptoms. Conversely, persistent shoulder pain (44%) and clubbing fingers (47%) were the least known lung cancer symptoms. Also, 60% of the respondents showed low confidence in identifying the signs and symptoms of lung cancer. The overall awareness of the risk factors for lung cancer development was 74%, with first-hand (74%) and second-hand (68%) smoking being the most known risk factors. However, only ≤ 62% know the other non-smoking risk factors. Awareness of the risk factors and symptoms of lung cancer depended on age, gender, education, marital and employment status (p < 0.001). Conclusion: Public awareness of the risk factors and symptoms of lung cancer in Saudi Arabia is inadequate and heavily dependent on education and socio-economic status. Awareness can be improved through campaigns to raise awareness about other lesser-known lung cancer risk factors and symptoms

Investigation the nonlinear optical properties of silver nanoparticles using femtosecond laser

© 2020 Published under licence by IOP Publishing Ltd. In this research, the fabrication of silver nanoparticles and experimental nonlinear response (NLO). The fabrication of the silver nanoparticles has been done using E-Beam evaporation on a glass substrate (Ag-NPs) and investigation of their nonlinear optical response (NLO). The silver nanoparticles was evaluated by optical spectrum (UV-Vis) that shows localized surface Plasmon band at 375 nm. The experiment shows the nonlinear absorption and nonlinear refraction effect of silver nanoparticles, the silver nanoparticles is analysed by Z-Scan technique using a femtoseconds laser with 800 nm wavelength. The result shows the nonlinear absorption (NLA) is at 4.8710-4cmW-1, while (NLR) is at 7.9410-9cmW-1

A population-based study of 15,000 people on Knowledge and awareness of lung cancer symptoms and risk factors in Saudi Arabia

Background: Lung cancer is currently the most fatal form of cancer worldwide, ranking as the fourth most prevalent type in Saudi Arabia, particularly among males. This trend is expected to increase with growing population, lifestyle changes, and aging population. Understanding the awareness of the Saudi population regarding the risk factors and symptoms of lung cancer is necessary to attenuate the predicted increase in cases. Method: A cross-sectional, population-based survey was performed using a previously validated questionnaire (Lung CAM). Multiple linear regression analysis was used to assess variables associated with deficiency in knowledge and awareness of risk factors and symptoms of lung cancer. Results: Majority of the 15,099 respondents were male (65%), aged between 18 and 30 years (53%), 50% of which were educated up to a bachelor’s degree level. Overall awareness of lung cancer signs and symptoms was 53%, with painful cough and coughing up blood being the best-known symptoms. Conversely, persistent shoulder pain (44%) and clubbing fingers (47%) were the least known lung cancer symptoms. Also, 60% of the respondents showed low confidence in identifying the signs and symptoms of lung cancer. The overall awareness of the risk factors for lung cancer development was 74%, with first-hand (74%) and second-hand (68%) smoking being the most known risk factors. However, only ≤ 62% know the other non-smoking risk factors. Awareness of the risk factors and symptoms of lung cancer depended on age, gender, education, marital and employment status (p < 0.001). Conclusion: Public awareness of the risk factors and symptoms of lung cancer in Saudi Arabia is inadequate and heavily dependent on education and socio-economic status. Awareness can be improved through campaigns to raise awareness about other lesser-known lung cancer risk factors and symptoms