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Histogram-based local descriptors for facial expression recognition (FER): A comprehensive study

Facial expression recognition is a challenging and interesting problem in computer vision and pattern recognition. Geometric variability in both emotion expression and neutral face is a fundamental challenge in facial expression recognition problem. This variability not only directly affects geometric facial expression recognition methods, but also is a critical problem in appearance methods. To overcome this problem, this paper presents an approach which eliminates geometric variability in emotion expression; thus, appearance features can be accurately used for facial expression recognition. Therefore, a fixed geometric model is used for geometric normalization of facial images. This model is defined as one of the emotional expressions. In addition Local Binary Patterns are utilized to represent facial appearance features. Experimental results show that the proposed method is more accurate than the existing works. Also for facial expression recognition, using geometric expression models of facial images where they have larger size in mouth/eyes regions, such as Surprise, gives better results indicating that mouth and eyes are important regions in emotion expression.

Facial expression recognition using geometric normalization and appearance representation

Microgrid deployments are expanding around the world as the most suitable solution to integrate distributed renewable energy sources to meet the increasing load demands and to power-up the remote areas. The installation of DC microgrid can improve system efficiency and reduces the cost of electrical infrastructure compared to the AC microgrid. However, the main challenge of implementing DC microgrid is the existing structure of the AC distribution system. In addition to the previous researches performed on DC microgrids, this paper proposes a framework to assess the technical and financial benefits of implementing the AC and DC microgrids. The power loss, voltage drop and system efficiency have been investigated for the AC and DC microgrids during the steady-state condition. Furthermore, the dynamic behaviors of AC and DC microgrids have been analyzed when each system subjected to disturbance such as short-circuit fault, aiming to evaluate the system response. In the next stage, techno-economic analysis has been carried out to determine the optimal size of solar PV system connected to each AC or DC microgrid with its energy storage, according to the meteorological and load profile data of the selected remote area in Sarawak (Malaysia). The study presented in this paper justifies that DC microgrid is potentially more beneficial than AC microgrid. However, the stability of the system during fault condition is the main problem in the DC microgrid. Therefore, it can be concluded that the protection and control of DC microgrids should be the key areas of future researches.

/pdf/assessment-of-technical-and-financial-benefits-of-ac-and-dc-37y6hwx8bj.pdf

Assessment of technical and financial benefits of AC and DC microgrids based on solar photovoltaic

A handheld device (such as a smartphone/wearable) can be used for tracking and delivering navigation within a building using a wireless interface (such as WiFi or Bluetooth Low Energy), in situations when a traditional navigation system (such as a global positioning system) is unable to function effectively. In this paper, we present an indoor navigation system based on a combination of wall-mounted wireless sensors, a mobile health application (mHealth app), and WiFi/Bluetooth beacons. Such a system can be used to track and trace people with neurological disorders, such as Alzheimer’s disease (AD) patients, throughout the hospital complex. The Contact tracing is accomplished by using Bluetooth low-energy beacons to detect and monitor the possibilities of those who have been exposed to communicable diseases such as COVID-19. The communication flow between the mHealth app and the cloud-based framework is explained elaborately in the paper. The system provides a real-time remote monitoring system for primary medical care in cases where relatives of Alzheimer’s patients and doctors are having complications that may demand medical care or hospitalization. The proposed indoor navigation system has been found to be useful in assisting patients with Alzheimer’s disease (AD) while in the hospital building.

Indoor Navigation Support System for Patients with Neurodegenerative Diseases

This paper presents a new technique to extract the light invariant local feature for facial expression recognition. It is not only robust to monotonic gray-scale changes caused by light variations but also very simple to perform which makes it possible for analyzing images in challenging real-time settings. The local feature for a pixel is computed by finding the direction of the neighboring of the pixel with the particular rank in term of its gray scale value among all the neighboring pixels. When eight neighboring pixels are considered, the direction of the neighboring pixel with the second minima of the gray scale intensity can yield the best performance for the facial expression recognition in our experiment. The facial expression classification in the experiment was performed using a support vector machine on CK+ dataset The average recognition rate achieved is 90.1 ± 3.8%, which is better than other previous local feature based methods for facial expression analysis. The experimental results do show that the proposed feature extraction technique is fast, accurate and efficient for facial expression recognition.

/pdf/a-novel-feature-extraction-technique-for-facial-expression-3r7bwc384d.pdf

A novel feature extraction technique for facial expression recognition

Facial Expression Recognition using Local Arc Pattern

In this paper, we present a financial feasibility analysis and design of an on-board-assisting system for a hybrid solar–diesel-powered boat. The major components of this boat are solar panel, battery bank, speed and direction controller for dc motor, brushless dc motor, diesel engine generator (DEG), and intelligent-assisting system (IAS) to assist the sailor. A DEG is considered to maintain the ability to run the system even during night-time, cloudy, and partially cloudy days. The energy demand posed by the electrical system requires maintaining an appropriate balance between the energy sources-done by an on-board-processing element which facilitates the system to run automatically. The capacity of the battery bank is considered large enough to satisfy electrical power requirement of the system for a whole day during non-charging periods. The optimal configuration for the hybrid system is selected from HOMER simulation results, whereas a financial feasibility analysis of the proposed hybrid solar and DEG-powered boat is performed using a clean energy management software called RETScreen. The IAS also provides solutions to the common naval hazards, such as over-weight and inclement weather by employing depth of submergence detector and GSM network interface. Financial analysis reveals that the proposed system is financially feasible, while tests showed that IAS successfully provides navigational supports to sailors.

/pdf/techno-financial-analysis-and-design-of-on-board-intelligent-44ekiow5be.pdf

Techno-financial analysis and design of on-board intelligent-assisting system for a hybrid solar–DEG-powered boat

Recent technology has modeled VANET (vehicular adhoc network) communication well in terms of privileges to derive vehicular communication technologically to save time, energy, and money. Due to the increase in powerful technology in modern times, VANETs play a vital role in uplifting daily concerns across vehicles and vehicular identities. Hence, to tune VANETs to become compatible with traditional technologies and increase demand, VANETs require upgrading. The severity and frequency of unwanted occurrences have become a considerable concern for our day-to-day lives relating to vehicular position. Thus, verily updated methodologies or working procedures are needed for the future VANET interplay to eradicate such problems occurring through vehicular identities. This article outlines in technology related to VANETS, future developments, and coping issues by deriving comprehensive frameworks, workflow patterns, upgrading procedures including big data, fog computing, SDN (software defined networking), and SIoT (social Internet of Things). This article provides a high-level overview of a complete VANET upgrade solution to address future problem management issues under a range of acceptable scientific themes, indicators, and combinations.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09797696.pdf

Mohammad Shahidul Islam

Papers

Indoor Navigation Support System for Patients with Neurodegenerative Diseases

A novel feature extraction technique for facial expression recognition

Facial Expression Recognition using Local Arc Pattern

Techno-financial analysis and design of on-board intelligent-assisting system for a hybrid solar–DEG-powered boat

A Review on VANET Research: Perspective of Recent Emerging Technologies