Facial expression recognition using lightweight deep learning modeling

Facial expression is a type of communication and is useful in many areas of computer vision, including intelligent visual surveillance, human-robot interaction and human behavior analysis. A deep learning approach is presented to classify happy, sad, angry, fearful, contemptuous, surprised and disgusted expressions. Accurate detection and classification of human facial expression is a critical task in image processing due to the inconsistencies amid the complexity, including change in illumination, occlusion, noise and the over-fitting problem. A stacked sparse auto-encoder for facial expression recognition (SSAE-FER) is used for unsupervised pre-training and supervised fine-tuning. SSAE-FER automatically extracts features from input images, and the softmax classifier is used to classify the expressions. Our method achieved an accuracy of 92.50% on the JAFFE dataset and 99.30% on the CK+ dataset. SSAE-FER performs well compared to the other comparative methods in the same domain

Adaptive Virtual Impedance Control with MPC’s Cost Function for DG Inverters in a Microgrid with Mismatched Feeder Impedances for Future Energy Communities

More and more distributed generations (DGs), such as wind, PV or battery bank sources, are connected to electric systems or customer loads. However, the locations of these DGs are based on the highest energy that can be potentially harvested for electric power generation. Therefore, these locations create different line impedances based on the distance from the DGs to the loads or the point of common coupling (PCC). This paper presents an adaptive virtual impedance (AVI) in the predictive control scheme in order to ensure power sharing accuracy and voltage stability at the PCC in a microgrid network. The reference voltage from mismatched feeder impedances was modified by utilizing the suggested AVI-based predictive control for creating equal power sharing between the DGs in order to avoid overburdening any individual DG with low-rated power. The AVI strategy used droop control as the input control for generating equal power sharing, while the AVI output was used as the reference voltage for the finite control set–model predictive control (FCS-MPC) for creating a minimum voltage error deviation for the cost function (CF) for the inverter’s vector switching pattern in order to improve voltage stability at the PCC. The proposed AVI-based controller was tested using two DG inverter circuits in a decentralized control mode with different values of line impedance and rated power. The performance of the suggested controller was compared via MATLAB/Simulink with that of a controller based on static virtual impedance (SVI) in terms of efficiency of power sharing and voltage stability at the PCC. From the results, it was found that (1) the voltage transient magnitude for the AVI-based controller was reduced within less than 0.02 s, and the voltage at the PCC was maintained with about 0.9% error which is the least as compared with those for the SVI-based controller and (2) equal power sharing between the DGs increased during the change in the load demand when using the AVI-based controller as compared with using the SVI-based controller. The proposed controller was capable of giving more accurate power sharing between the DGs, as well as maintaining the voltage at the PCC, which makes it suitable for the power generation of consumer loads based on DG locations for future energy communities

Developing a Comprehensive Shipment Policy through Modified EPQ Model Considering Process Imperfections, Transportation Cost, and Backorders

Background: Determining the optimum shipment quantity in a traditional production system is a competitive business dimension, and developing a reliable shipment policy is decisive for long-term objectives. Currently, significant research in this domain has mainly focused on the optimum shipment lot sizing in a perfect production system without considering the imperfections in the production processes and logistics. It has been well established that the real production inventory system acts as an imperfection in the overall production management loop. Methods: This research deals with designing a new shipment policy considering the imperfections in the production processes and undertaking some influential factors, such as the transportation cost, the actual production inventory, defective items, and backorders. Results: In the developed mathematical framework, the lot-sizing problems, imperfections in the production processes, retailers, and distributors are considered with equal-sized shipment policy to attain pragmatic and real-time results. Conclusions: The developed framework considers an all-unit-discount transportation cost structure. The numerical computations, as well as sensitivity analysis, are performed to point out the specifications and validation of the proposed model

Developing a Comprehensive Shipment Policy through Modified EPQ Model Considering Process Imperfections, Transportation Cost, and Backorders

Background: Determining the optimum shipment quantity in a traditional production system is a competitive business dimension, and developing a reliable shipment policy is decisive for long-term objectives. Currently, significant research in this domain has mainly focused on the optimum shipment lot sizing in a perfect production system without considering the imperfections in the production processes and logistics. It has been well established that the real production inventory system acts as an imperfection in the overall production management loop. Methods: This research deals with designing a new shipment policy considering the imperfections in the production processes and undertaking some influential factors, such as the transportation cost, the actual production inventory, defective items, and backorders. Results: In the developed mathematical framework, the lot-sizing problems, imperfections in the production processes, retailers, and distributors are considered with equal-sized shipment policy to attain pragmatic and real-time results. Conclusions: The developed framework considers an all-unit-discount transportation cost structure. The numerical computations, as well as sensitivity analysis, are performed to point out the specifications and validation of the proposed model

Energy Efficient Strategy for WSN Technology Using Modified HGAF Technique

Due to the rapid growth in technologies has led to the development of sensor nodes. As we know that wireless sensor network is collection of small and large number of sensor node. These sensor nodes are used for different domain like environmental research, health care, monitor, military, and record the physical activity. These nodes communicate with each other and forward the message to base station. For communication of these node different algorithms used Geographical adaptive fidelity (GAF) is one of them. Dropping energy utilization in wireless sensor network directly affects the network lifetime. HGAF is one of the important multiple location based on routing system algorithm. The main function of HGAF technique is to turn-off the unnecessary nodes in the network without interrupting the other connected node. In this paper we proposed a technique known as modified HGAF and it design as a power saving method. In the proposed technique the size of cell structure in grid changed and communication method improve due to those changes.  Based on the result the proposed technique increase 25% in dead node ratio and also increase the network

Shipment Policy for an Economic Production Quantity Model Considering Imperfection and Transportation Cost

Determining replenishment lot size and number of shipments in a traditional production setup has been of great interest among researchers during the last decades. In order to survive modern competition, the manufacturer has to make good decisions about the lot size that is to be shipped to the retailer. Recently, several researchers have developed mathematical models for modelling different real-world situations; however, these models are lacking due to a combination of imperfection in process and shipment lot sizing. Therefore, in the proposed research, shipment policy for an imperfect production setup has been developed with transportation costs taken into consideration. The model analyzed lot sizing for manufacturers and retailers with imperfections in terms of equally sized shipments. Furthermore, an all-unit-discount policy for shipment is considered in the proposed research, and at the end, numerical computation and sensitivity analyses are carried out to gain more insight into the specifications of the model

A Comprehensive Motivation of Multilayer Control Levels for Microgrids: Synchronization, Voltage and Frequency Restoration Perspective

The current paradigm in integrating intermittent renewable energy sources into microgrids presents various technical challenges in terms of reliable operation and control. This paper performs a comprehensive justification of microgrid trends in dominant control strategies. It covers multilayer hierarchical control schemes, which are able to integrate seamlessly with coordinated control strategies. A general overview of the hierarchical control family that includes primary, secondary, tertiary controls is presented. For power sharing accuracy and capability, droop and non-droop-based controllers are comprehensively studied to address further development. The voltage and frequency restoration techniques are discussed thoroughly based on centralized and decentralized method in order to highlights the differences for better comprehend. The comprehensive studies of grid synchronization strategies also overviewed and analyzed under balanced and unbalanced grid conditions. The details studies for each control level are displayed to highlight the benefits and shortcomings of each control method. A future prediction from the authors’ point of view is also provided to acknowledge which control is adequate to be adopted in proportion to their products applications and a possibility technique for self-synchronization is given in this paper

Investigation on Multisampling Deadbeat Current Control With Time-Delay Compensation in Grid-Connected Inverter

The control of voltage source converters (VSCs) is now implemented on digital microprocessors. This digitalization has the drawback of time delay in the control loop. The goal of this research work was to investigate improvements that can be obtained from the combination of model-based and model-free time-delay compensation approaches. Deadbeat control (DBC) from model-based techniques and the method of moving the control variable’s sampling instants, or the pulse-width modulation (PWM) updating instants, from model-free time-delay compensation techniques, were put together as the proposed new method of time-delay compensation in this study. These controllers were thoroughly examined in terms of control algorithm design, system stability analysis, and sensitivity analysis of plant parameter perturbations. In addition, thorough Simulink-based computer simulations were conducted in this work to assess the performance of each controller. The proposed method compensated about 80 µs as compared with the time delay compensated by the conventional single-sampling method. This research work was limited to simulations only; hence, conducting experiments to further validate this research work could be a direction for further research

Syntax and semantics question analysis using user modelling and relevance feedback

A Question Answering (QA) system aims to provide relevant answers to users’ natural language (NL) questions by consulting its knowledge base (KB). Providing users with the most relevant answers to their questions is an issue. Many answers returned are not relevant to the questions, and this issue is due to many factors. One such factor is the ambiguity yield during the semantic analysis of lexical extracted from the user’s question. The existing techniques did not consider some of the terms, called modifier terms, in the user’s question which are claimed to have a significant impact of returning the correct answer. The objective of this study is to present the syntax and semantic question analysis using user modelling (UM) and relevance feedback (RF). This analysis interprets all the modifier terms in the user’s question in order to yield correct answers. A combination of UM and RF is used to increase the accuracy of the returned answer. UM helps the QA system to understand the user’s question and manage for question adjustment. RF provides an extended framework for the QA system to avoid or remedy the ambiguity of the user’s question. The analysis utilizes Vector Space Model (VSM) to semantically interpret and correctly converts modifier terms into a quantifiable form. The finding of this analysis demonstrates a good precision percentage of 94.7% in returning relevant answers for each NL question