Search results for: linear control

Authors: Trishen Naidoo, Anthony Walker, Shaniel Davrajh, Glen Bright

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An investigation into on-line inspection was performed where research is focused on the use of varied inspection (as opposed to 100% inspection) for mass customization (MC). Manufacturers need new methods for quality control in mass customization, and these methods need to address some of the old problems such as over-inspection and bottlenecking. Due to the risks of varied inspection, many manufacturers do not implement it and rather opt for sampling methods. However, there are many advantages of varied inspection and can have applications in mass customization. A control system incorporating fuzzy logic (FL) control is used to perform the variations in inspection usage in a simulated environment. The proposed system can have a key impact in appraisal costs reduction and possibly work-in-process reduction in high variety environments.

Keywords: appraisal costs, fuzzy logic, quality control, work-in-process

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Authors: Mahacine Amrani

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This paper aims at reviewing some Moroccan industrial applications of wavelet especially in the dynamic identification of a process model using Haar wavelet mother response. Two recent Moroccan study cases are described using dynamic data originated by a distillation column and an industrial polyethylene process plant. The purpose of the wavelet scheme is to build on-line dynamic models. In both case studies, a comparison is carried out between the Haar wavelet mother response model and a linear difference equation model. Finally it concludes, on the base of the comparison of the process performances and the best responses, which may be useful to create an estimated on-line internal model control and its application towards model-predictive controllers (MPC). All calculations were implemented using AutoSignal Software.

Keywords: process performance, model, wavelets, Haar, Moroccan

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Authors: Dana M. Ragab, Jasim A Ghaeb

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The Voltage Unbalance Factor (VUF) index is recommended to evaluate system performance under unbalanced operation. However, its calculation requires complex algebra which limits its use in the field. Furthermore, one system cycle is required at least to detect unbalance using the VUF. Ideally unbalance mitigation must be performed within 10 ms for 50 Hz systems. In this work, a linear relation for VUF evaluation in three-phase electrical power system using space vector (SV) is derived. It is proposed to determine the voltage unbalance quickly and accurately and to overcome the constraints associated with the traditional methods of VUF evaluation. Aqaba-Qatrana-South Amman (AQSA) power system is considered to study the system performance under unbalanced conditions. The results show that both the complexity of calculations and the time required to evaluate VUF are reduced significantly.

Keywords: power quality, space vector, unbalance evaluation, three-phase power system

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Authors: Chad Brown

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This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: Mohammad Rahim Rahnama

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Market-transaction price for housing is the main criteria for determining municipality taxes and is determined and announced on an annual basis. Of course, there is a discrepancy between the actual value of transactions in the Bureau of Finance (P for short) or municipality (P´ for short) and the real price on the market (P˝). The present research aims to determine the real price of housing in the metropolis of Mashhad and to pinpoint the price gap with those of the aforementioned apparatuses and identify the factors affecting it. In order to reach this practical objective, Automatic Linear Modeling, which calls for an explanatory research, was utilized. The population of the research consisted of all the residential units in Mashhad, from which 317 residential units were randomly selected. Through cluster sampling, out of the 170 income blocks defined by the municipality, three blocks form high-income (Kosar), middle-income (Elahieh), and low-income (Seyyedi) strata were surveyed using questionnaires during February and March of 2015 and the information regarding the price and specifications of residential units were gathered. In order to estimate the effect of various factors on the price, the relationship between independent variables (8 variables) and the dependent variable of the housing price was calculated using Automatic Linear Modeling in SPSS. The results revealed that the average for housing price index is 788$ per square meter, compared to the Bureau of Finance’s prices which is 10$ and that of municipality’s which is 378$. Correlation coefficient among dependent and independent variables was calculated to be R²=0.81. Out of the eight initial variables, three were omitted. The most influential factor affecting the housing prices is the quality of Quality of construction (Ordinary, Full, Luxury). The least important factor influencing the housing prices is the variable of number of sides. The price gap between low-income (Seyyedi) and middle-income (Elahieh) districts was not confirmed via One-Way ANOVA but their gap with the high-income district (Kosar) was confirmed. It is suggested that city be divided into two low-income and high-income sections, as opposed three, in terms of housing prices.

Keywords: automatic linear modeling, housing prices, Mashhad, Iran

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: M. J. Shofa, A. Hidayatno, O. M. Armand

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MRP as a production control system is appropriate for the deterministic environment. Unfortunately, most production systems such as customer demands are stochastic. Demand-Driven MRP (DDMRP) is a new approach for inventory control system, and it deals with demand uncertainty. The objective of this paper is to compare the MRP and DDMRP work for a long lead time and uncertain demand in terms of on-hand inventory levels. The evaluation is conducted through a discrete event simulation using purchased part data from an automotive company. The result is MRP gives 50,759 pcs / day while DDMRP gives 34,835 pcs / day (reduce 32%), it means DDMRP is more effective inventory control than MRP in terms of on-hand inventory levels.

Keywords: Demand-Driven MRP, long lead time, MRP, uncertain demand

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Authors: A. Hassoune, M. Khafallah, A. Mesbahi, T. Bouragba

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This work presents an improved strategy of control for charging a lithium-ion battery in an electric vehicle charging station using two charger topologies i.e. single ended primary inductor converter (SEPIC) and forward converter. In terms of rapidity and accuracy, the power system consists of a topology/control diagram that would overcome the performance constraints, for instance the power instability, the battery overloading and how the energy conversion blocks would react efficiently to any kind of perturbations. Simulation results show the effectiveness of the proposed topologies operated with a power management algorithm based on voltage/peak current mode controls. In order to provide credible findings, a low power prototype is developed to test the control strategy via experimental evaluations of the converter topology and its controls.

Keywords: battery storage buffer, charging station, electric vehicle, experimental analysis, management algorithm, switches control

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: Pankaj Negi

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Nowadays the demand for receiving the high quality electrical energy is being increasing as consumer wants not only reliable but also quality power. Custom power instruments are of the most well-known compensators of power quality in distributed network. This paper present a comprehensive review of compensating custom power devices mainly DSTATCOM (distribution static compensator),DVR (dynamic voltage restorer), and UPQC (unified power quality compensator) and also deals with sliding mode control and its applications to custom power devices. The sliding mode control strategy provides robustness to custom power device and enhances the dynamic response for compensating voltage sag, swell, voltage flicker, and voltage harmonics. The aim of this paper is to provide a broad perspective on the status of compensating devices in electric power distribution system and sliding mode control strategies to researchers and application engineers who are dealing with power quality and stability issues.

Keywords: active power filters(APF), custom power device(CPD), DSTATCOM, DVR, UPQC, sliding mode control (SMC), power quality

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Authors: Timothee Gidenne, Xia Pinqi

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In this paper, an investigation of the use of carbon nanotubes (CNTs) reinforced polymer as an actuator for an active flutter suppression to counter the flutter phenomena is conducted. The goal of this analysis is to establish a link between the behavior of the control surface and the actuators to demonstrate the veracity of using such a suppression system for the aeronautical field. A preliminary binary flutter model using simplified unsteady aerodynamics is developed to study the behavior of the wing while reaching the flutter speed and when the control system suppresses the flutter phenomena. The Timoshenko beam theory for bilayer materials is used to match the response of the control surface with the CNTs reinforced polymer (CNRP) actuators. According to Timoshenko theory, results show a good and realistic response for such a purpose. Even if the results are still preliminary, they show evidence of the potential use of CNRP for control surface actuation for the small-scale and lightweight system.

Keywords: actuators, aeroelastic, aeroservoelasticity, carbon nanotubes, flutter, flutter suppression

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Authors: H. Nikzad, S. Yoshitomi

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In this paper, an optimization procedure is applied for 3D Reinforced concrete building structure with shear wall.  In the optimization problem, cross sections of beams, columns and shear wall dimensions are considered as design variables and the optimal cross sections can be derived to minimize the total cost of the structure. As for final design application, the most suitable sections are selected to satisfy ACI 318-14 code provision based on static linear analysis. The validity of the method is examined through numerical example of 15 storied 3D RC building with shear wall.  This optimization method is expected to assist in providing a useful reference in design early stage, and to be an effective and powerful tool for structural design of RC shear wall structures.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures

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Authors: Le Fu, Rui Wu, Gang Feng Liu, Jie Zhao

Abstract:

Normally, impedance control methods are based on a model that connects a spring and damper in parallel. The series connection, namely the Maxwell model, has emerged as a counterpart and draw the attention of robotics researchers. In the theoretical analysis, it turns out that the two pattern are both equivalents to some extent, but notable differences of response characteristics exist, especially in the effect of damping viscosity. However, this novel impedance control design is lack of validation on realistic robot platforms. In this study, stability analysis and experimental evaluation are achieved using a 3-fingered Barrett® robotic hand BH8-282 endowed with tactile sensing, mounted on a torque-controlled lightweight and collaborative robot KUKA® LBR iiwa 14 R820. Object handover and incoming objects catching tasks are executed for validation and analysis. Experimental results show that the series connection pattern has much better performance in natural impact or shock absorption, which indicate promising applications in robots’ safe and physical interaction with humans and objects in various environments.

Keywords: impedance control, Maxwell model, force control, dexterous manipulation

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Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: discrete time, estimation, Kalman filter, Kalman filter gain

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Authors: N. Hadjigeorgiou, A. C. Tsalikidou, E. Hristoforou, P. P. Sotiriadis

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During the last few decades, the continuously increasing demand for accurate and reliable magnetic measurements has paved the way for the development of different types of magnetic sensing systems as well as different measurement techniques. Sensor sensitivity and linearity, signal-to-noise ratio, measurement range, cross-talk between sensors in multi-sensor applications are only some of the aspects that have been examined in the past. In this paper, a fully analog closed loop system in order to optimize the performance of AMR sensors has been developed. The operation of the proposed system has been tested using a Helmholtz coil calibration setup in order to control both the amplitude and direction of magnetic field in the vicinity of the AMR sensor. Experimental testing indicated that improved linearity of sensor response, as well as low noise levels can be achieved, when the system is employed.

Keywords: AMR sensor, closed loop, memory effects, chopper, linearity improvement, sensitivity improvement, magnetic noise, electronic noise

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Authors: Adriana de Paula Lacerda Santos, Bruna Godke, Mauro Lacerda Santos Filho

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Several dams in the world have already collapsed, causing environmental, social and economic damage. The concern to avoid future disasters has stimulated the creation of a great number of laws and rules in many countries. In Brazil, Law 12.334/2010 was created, which establishes the National Policy on Dam Safety. Overall, this policy requires the dam owners to invest in the maintenance of their structures and to improve its monitoring systems in order to provide faster and straightforward responses in the case of an increase of risks. As monitoring tools, visual inspections has provides comprehensive assessment of the structures performance, while auscultation’s instrumentation has added specific information on operational or behavioral changes, providing an alarm when a performance indicator exceeds the acceptable limits. These limits can be set using statistical methods based on the relationship between instruments measures and other variables, such as reservoir level, time of the year or others instruments measuring. Besides the design parameters (uplift of the foundation, displacements, etc.) the dam instrumentation can also be used to monitor the behavior of defects and damage manifestations. Specifically in concrete gravity dams, one of the main causes for the appearance of cracks, are the concrete volumetric changes generated by the thermal origin phenomena, which are associated with the construction process of these structures. Based on this, the goal of this research is to propose a monitoring process of the thermal cracking behavior in concrete gravity dams, through the instrumentation data analysis and the establishment of control values. Therefore, as a case study was selected the Block B-11 of José Richa Governor Dam Power Plant, that presents a cracking process, which was identified even before filling the reservoir in August’ 1998, and where crack meters and surface thermometers were installed for its monitoring. Although these instruments were installed in May 2004, the research was restricted to study the last 4.5 years (June 2010 to November 2014), when all the instruments were calibrated and producing reliable data. The adopted method is based on simple linear correlations procedures to understand the interactions among the instruments time series, verifying the response times between them. The scatter plots were drafted from the best correlations, which supported the definition of the limit control values. Among the conclusions, it is shown that there is a strong or very strong correlation between ambient temperature and the crack meters and flowmeters measurements. Based on the results of the statistical analysis, it was possible to develop a tool for monitoring the behavior of the case study cracks. Thus it was fulfilled the goal of the research to develop a proposal for a monitoring process of the behavior of thermal cracking in concrete gravity dams.

Keywords: concrete gravity dam, dams safety, instrumentation, simple linear correlation

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Authors: D. Chronopoulos, I. Antoniadis, V. Spitas, D. Koulocheris, V. Polenta

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A concept of a simple linear oscillator, incorporating a negative stiffness element is demonstrated to exhibit extraordinary damping properties. This oscillator shares the same overall (static) stiffness, the same mass and the same damping element with a reference classical linear SDOF oscillator. However, it differs from the original SDOF oscillator by appropriately redistributing the component spring stiffness elements and by re-allocating the damping element. Despite the fact that the proposed oscillator incorporates a negative stiffness element, it is designed to be both statically and dynamically stable. Once such an oscillator is optimally designed, it is shown to exhibit an extraordinary apparent damping ratio, which is even several orders of magnitude higher than that of the original SDOF system, especially in cases where the original damping of the SDOF system is low. This damping behavior is not a result of a novel additional extraordinary energy dissipation mechanism, but a result of the phase difference between the positive and the negative stiffness elastic forces, which is in turn a consequence of the proper re-distribution of the stiffness and the damper elements. This fact ensures that an adequate level of elastic forces exists throughout the entire frequency range, able to counteract the inertial and the excitation forces. Next, Acoustic or Phononic Meta-materials are considered, in which one atom is replaced by the concept of the above simple linear oscillator. The results indicate that not only the damping of the meta-material verifies and exceeds the one expected from the so-called "meta-damping" behavior, but also that the band gap of the meta-material can be significantly increased.

Keywords: wave propagation, periodic structures, wave damping, mechanical engineering

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Authors: Khadija Mushtaq, Mian Saqib Mehmood

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This paper attempts to determine the impact of leadership style and learning orientation on organizational performance in Pakistan. A sample of 158 middle managers selected from sports and surgical factories from Sialkot. The empirical estimation is based on a multiple linear regression analysis of the relationship between leadership style, learning orientation and organizational performance. Leadership style is measure through transformational leadership and transactional leadership. The transformational leadership has insignificant impact on organizational performance. The transactional leadership has positive and significant relation with organizational performance. Learning orientation also has positive and significant relation with organizational performance. Linear regression used to estimate the relation between dependent and independent variables. This study suggests top manger should prefer continuous process for improvement for any change in system rather radical change.

Keywords: transformational leadership, transactional leadership, learning orientation, organizational performance, Pakistan

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Authors: Edwin Javier Cortes, Surupa Shaw

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In recent years, there has been a growing emphasis on enhancing the efficiency and performance of wind and water turbines to meet the increasing demand for sustainable energy sources. One promising approach is the utilization of advanced flow control techniques to optimize aerodynamic performance. This paper explores the application of advanced flow control techniques in both wind and water turbines, aiming to maximize their efficiency and output. By manipulating the flow of air or water around the turbine blades, these techniques offer the potential to improve energy capture, reduce drag, and minimize turbulence-induced losses. The paper will review various flow control strategies, including passive and active techniques such as vortex generators, boundary layer suction, and plasma actuators. It will examine their effectiveness in optimizing turbine performance under different operating conditions and environmental factors. Furthermore, the paper will discuss the challenges and opportunities associated with implementing these techniques in practical turbine designs. It will consider factors such as cost-effectiveness, reliability, and scalability, as well as the potential impact on overall turbine efficiency and lifecycle. Through a comprehensive analysis of existing research and case studies, this paper aims to provide insights into the potential benefits and limitations of advanced flow control techniques for wind and water turbines. It will also highlight areas for future research and development, with the ultimate goal of advancing the state-of-the-art in turbine technology and accelerating the transition towards a more sustainable energy future.

Keywords: flow control, efficiency, passive control, active control

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Authors: Najib K. Dankadai, Ahmad 'Athif Mohd Faudzi, Khairuddin Osman, Muhammad Rusydi Muhammad Razif, IIi Najaa Aimi Mohd Nordin

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Researches in soft actuators are now growing rapidly because of their adequacy to be applied in sectors like medical, agriculture, biological and welfare. This paper presents system identification (SI) and control of the force generated by a two chambers pneumatic soft actuator (PSA). A force mathematical model for the actuator was identified experimentally using data acquisition card and MATLAB SI toolbox. Two control techniques; a predictive functional control (PFC) and conventional proportional integral and derivative (PID) schemes are proposed and compared based on the identified model for the soft actuator flexible mechanism. Results of this study showed that both of the proposed controllers ensure accurate tracking when the closed loop system was tested with the step, sinusoidal and multi step reference input through MATLAB simulation although the PFC provides a better response than the PID.

Keywords: predictive functional control (PFC), proportional integral and derivative (PID), soft actuator, system identification

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Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

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This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling

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Authors: Mehdi Moeinaddini, Zohreh Asadi-Shekari, Muhammad Zaly Shah, Amran Hamzah

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Currently, planners try to have more green travel options to decrease economic, social and environmental problems. Therefore, this study tries to find significant urban travel factors to be used to increase the usage of alternative urban travel modes. This paper attempts to identify the relationship between prominent urban mobility indicators and daily trips by public transport in 30 cities from various parts of the world. Different travel modes, infrastructures and cost indicators were evaluated in this research as mobility indicators. The results of multi-linear regression analysis indicate that there is a significant relationship between mobility indicators and the daily usage of public transport.

Keywords: green travel modes, urban travel indicators, daily trips by public transport, multi-linear regression analysis

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Authors: Shruti Motiwale, Xianlin Zhou, Reuben H. Kraft

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Military and sports personnel are often required to wear heavy helmets for extended periods of time. This leads to excessive cyclic loads on the neck and an increased chance of injury. Computational models offer one approach to understand and predict the time progression of disc degeneration under severe cyclic loading. In this paper, we have applied an analytic non-linear damage evolution model to estimate damage evolution in an intervertebral disc due to cyclic loads over decade-long time periods. We have also proposed a novel strategy for inclusion of recovery in the damage model. Our results show that damage only grows 20% in the initial 75% of the life, growing exponentially in the remaining 25% life. The analysis also shows that it is crucial to include recovery in a damage model.

Keywords: cervical spine, computational biomechanics, damage evolution, intervertebral disc, continuum damage mechanics

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Authors: Sina Mahdavi, Faeze Noruzpur, Aysuda Noruzpur

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This paper proposes a high linear, low power and wideband Variable Gain Amplifier (VGA) with a direct current (DC) gain range of -10.2dB to 60.7dB. By applying the proposed idea to the folded cascade amplifier, it is possible to achieve a 71dB DC gain, 35MHz (-3dB) bandwidth, accompanied by high linearity and low sensitivity as well. It is noteworthy that the proposed idea can be able to apply on every differential amplifier, too. Moreover, the total power consumption and unity gain bandwidth of the proposed VGA is 1.41mW with a power supply of 1.8 volts and 4.37GHz, respectively, and 0.8pF capacitor load is applied at the output nodes of the amplifier. Furthermore, the proposed structure is simulated in whole process corners and different temperatures in the region of -60 to +90 ºC. Simulations are performed for all corner conditions by HSPICE using the BSIM3 model of the 180nm CMOS technology and MATLAB software.

Keywords: variable gain amplifier, low power, low voltage, folded cascade, amplifier, DC gain

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: S. Oudjemia, F. Alim, S. Seddiki

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This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

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Authors: Habtemariam Alemu

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It has been known that the performance of position and force control is highly affected by both robot dynamic and environment stiffness uncertainties. In this paper, joint space hybrid force and position control strategy with self-selecting matrix using artificial neural network compensator is proposed. The objective of the work is to improve controller robustness by applying a neural network technique in order to compensate the effect of uncertainties in the robot model. Simulation results for a 6 degree of freedom (6-DoF) manipulator and different types of environments showed the effectiveness of the suggested approach. 6-DoF Puma 560 family robot manipulator is chosen as industrial robot and its efficient dynamic model is designed using Matlab/SimMechanics library.

Keywords: robot manipulator, force/position control, artificial neural network, Matlab/Simulink

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Authors: Lochan Basyal

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Global Automation is an emerging technology of today’s era and is based on Internet of Things (IoT). Global automation deals with the controlling of electrical appliances throughout the world. The fabrication of this system has been carried out with interfacing an electrical control system module to Raspberry Pi. An electrical control system module includes a relay driver mechanism through which appliances are controlled automatically in respective condition. In this research project, one email ID has been assigned to Raspberry Pi, and the users from different location having different email ID can mail to Raspberry Pi on assigned email address “[email protected]” with subject heading “Device Control” with predefined command on compose email line. Also, a notification regarding current working condition of this system has been updated on respective user email ID. This approach is an innovative way of implementing smart automation system through which a user can control their electrical appliances like light, fan, television, refrigerator, etc. in their home with the use of email facility. The development of this project helps to enhance the concept of smart home application as well as industrial automation.

Keywords: control circuit, e-mail, global automation, internet of things, IOT, Raspberry Pi

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Authors: Prashant G. Metri

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A numerical model is developed to study nano liquid film flow over an unsteady stretching sheet in the presence of hydromagnetic have been investigated. Similarity transformations are used to convert unsteady boundary layer equations to a system of non-linear ordinary differential equations. The resulting non-linear ordinary differential equations are solved numerically using Runge-Kutta-Fehlberg and Newton-Raphson schemes. A relationship between film thickness β and the unsteadiness parameter S is found, the effect of unsteadiness parameter S, and the hydromagnetic parameter S, on the velocity and temperature distributions are presented. The present analysis shows that the combined effect of magnetic field and viscous dissipation has a significant influence in controlling the dynamics of the considered problem. Comparison with known results for certain particular cases is in excellent agreement.

Keywords: boundary layer flow, nanoliquid, thin film, unsteady stretching sheet

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