Masked Face Inpainting Through Residual Attention UNet

Realistic image restoration with high texture areas such as removing face masks is challenging. The state-of-the-art deep learning-based methods fail to guarantee high-fidelity, cause training instability due to vanishing gradient problems (e.g., weights are updated slightly in initial layers) and spatial information loss. They also depend on intermediary stage such as segmentation meaning require external mask. This paper proposes a blind mask face inpainting method using residual attention UNet to remove the face mask and restore the face with fine details while minimizing the gap with the ground truth face structure. A residual block feeds info to the next layer and directly into the layers about two hops away to solve the gradient vanishing problem. Besides, the attention unit helps the model focus on the relevant mask region, reducing resources and making the model faster. Extensive experiments on the publicly available CelebA dataset show the feasibility and robustness of our proposed model. Code is available at \url{https://github.com/mdhosen/Mask-Face-Inpainting-Using-Residual-Attention-Unet}Comment: 5 pages, 8 figures, Innovations in Intelligent Systems and Applications Conferenc

HiMFR: A Hybrid Masked Face Recognition Through Face Inpainting

To recognize the masked face, one of the possible solutions could be to restore the occluded part of the face first and then apply the face recognition method. Inspired by the recent image inpainting methods, we propose an end-to-end hybrid masked face recognition system, namely HiMFR, consisting of three significant parts: masked face detector, face inpainting, and face recognition. The masked face detector module applies a pretrained Vision Transformer (ViT\_b32) to detect whether faces are covered with masked or not. The inpainting module uses a fine-tune image inpainting model based on a Generative Adversarial Network (GAN) to restore faces. Finally, the hybrid face recognition module based on ViT with an EfficientNetB3 backbone recognizes the faces. We have implemented and evaluated our proposed method on four different publicly available datasets: CelebA, SSDMNV2, MAFA, {Pubfig83} with our locally collected small dataset, namely Face5. Comprehensive experimental results show the efficacy of the proposed HiMFR method with competitive performance. Code is available at https://github.com/mdhosen/HiMFRComment: 7 pages, 6 figures, International Conference on Pattern Recognition Workshop: Deep Learning for Visual Detection and Recognitio

On secrecy performance of mixed generalized Gamma and Málaga RF-FSO variable gain relaying channel

The emergence of an array of new wireless networks has led researchers to evaluate the prospect of utilizing the physical properties of the wireless medium in order to design secure systems. In this paper, the physical layer secrecy performance of a mixed radio frequency-free space optical (RF-FSO) system with variable gain relaying scheme is investigated in the presence of an eavesdropper. We assume that the eavesdropper can wiretap the transmitted confidential data from the RF link only. It is further assumed that the main and eavesdropper RF links are modeled as generalized Gamma (GG) fading channel, and the free space optical (FSO) link experiences Málaga turbulence with pointing error impairment. Our primary concern is to protect this confidential information from being wiretapped. Besides pointing error, the atmospheric turbulence and two types of detection techniques (i.e. heterodyne detection and intensity modulation with direct detection) are also taken into consideration. Utilizing amplify-and-forward (AF) scheme, the novel mathematical closed-form expressions for average secrecy capacity, lower bound of secrecy outage probability, and strictly positive secrecy capacity are derived. As both the links (RF and FSO) undergo generalized fading channels, the derived expressions are also general. We present a unification of some existing works utilizing the proposed model to better clarify the novelty of this work. Finally, all the derived expressions are justified via Monte-Carlo simulations

A comprehensive approach of groundwater vulnerability and potentiality assessment of Melaka catchment in Malaysia / Md. Imran Hosen

maps by ArcGIS software. The GIS is very important and effective tool for handling a large amount of geological and hydrogeological data within short time and minimal error. Pumping test data are collected from 210 shallow and 17 deep boreholes to get well inventory information. Analysis of these data confirmed that the aquifers consisting of schist, sand, limestone as well as volcanic rocks are the most productive for groundwater in the State of Melaka. The term ‘aquifer productivity’ represents the potential of an aquifer to sustain various levels of borehole supply. The aquifer productivity map is classified into three categories namely;- high (>12m3/h), moderate (3.6-12 m3/h) and low (<3.6 m3/h) based on the discharge capacity. The groundwater potentiality of the study area is 35% low, 57% moderate and 8% high. Seven thematic maps defining;- depth to water table, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity are generated and integrated to generate the final DRASTIC vulnerability map. The map is then overlaid on the additional land use map to generate the risk map, which method is called Modified DRASTIC method. Both methods have been validated using groundwater quality data. The vulnerability map are classified into three categories namely;- high (>159), moderate (120-159) and low (80-119). The DRASTIC vulnerability map shows that an area of 11.02% has low vulnerability, an area of 61.53% has moderate vulnerability and 23.45% of the area has high vulnerability in the Melaka State. On the other hand, risk map indicates that 14.40% of the area is low vulnerability (100-139), 47.34% moderate vulnerability (140-175) and 38.26% high vulnerability (>175) in the study area. The most vulnerability is seen around Melaka, Jasin and Alor Gajah City of Melaka. The 52 shallow and 14 deep borehole groundwater samples are analyzed for water quality. The analysis results indicate that groundwater quality is satisfactory for drinking and other purposes, however turbidity, total dissolved solids, iron, chloride and cadmium values are exceeded the limit of the drinking water quality standard in very few cases. The ranges of pH are 4 - 8.2 for shallow and 5.2 - 8.1 for deep boreholes. Therefore, groundwater in the State of Melaka can be used for drinking and other purposes, in which some major treatments are recommended in few cases

Assessing Wind Farm Site Suitability in Bangladesh: A GIS-AHP Approach

Wind energy is one of the most attractive renewable energy sources because of its low operating, maintenance, and production costs as well as its low environmental impact. The goal of this study is to discover the best locations in Bangladesh for wind farms to be built and operated efficiently. This study applied the Geographic Information System (GIS) and Analytical Hierarchy (AHP) methodologies to examine the eight important parameters upon which the suitability of locations is highly dependent. This analysis finds that Bangladesh has large regions appropriate for wind farm installation, with 3718.76 km2 and 16,631.14 km2 classified as being of &ldquo;very high&rdquo; and &ldquo;high&rdquo; suitability, respectively. It was also observed that wind speed, land slope, and elevation each had a height-weighted criterion of 32%, 27%, and 12%, respectively, when picking suitable locations. However, the overall viability of this study in identifying suitable sites has been evaluated based on ROC and AUC techniques and found satisfactory as per AUC value. The knowledge gained from this study will help the sustainable and renewable energy development authority (SREDA) of Bangladesh to expedite the renewable energy investment process and will ensure greater certainty in resource development. The findings of this research can be considered as baseline information for the wind energy sector

Assessing Wind Farm Site Suitability in Bangladesh: A GIS-AHP Approach

Wind energy is one of the most attractive renewable energy sources because of its low operating, maintenance, and production costs as well as its low environmental impact. The goal of this study is to discover the best locations in Bangladesh for wind farms to be built and operated efficiently. This study applied the Geographic Information System (GIS) and Analytical Hierarchy (AHP) methodologies to examine the eight important parameters upon which the suitability of locations is highly dependent. This analysis finds that Bangladesh has large regions appropriate for wind farm installation, with 3718.76 km2 and 16,631.14 km2 classified as being of “very high” and “high” suitability, respectively. It was also observed that wind speed, land slope, and elevation each had a height-weighted criterion of 32%, 27%, and 12%, respectively, when picking suitable locations. However, the overall viability of this study in identifying suitable sites has been evaluated based on ROC and AUC techniques and found satisfactory as per AUC value. The knowledge gained from this study will help the sustainable and renewable energy development authority (SREDA) of Bangladesh to expedite the renewable energy investment process and will ensure greater certainty in resource development. The findings of this research can be considered as baseline information for the wind energy sector

Assessing the barriers of integrating technological innovations in textiles sector: Implications towards sustainable production

With the aftermath of the pervasive COVID-19, the recent war between Ukraine and Russia, and the severity of the resource crisis, the global textiles industry has become a significant concern, especially for emerging economies. Technological advancements combining traditional manufacturing processes with cutting-edge technologies may safeguard the textile industry’s supply chain. To establish stability in the value chain of the textiles sector in emerging nations, it is crucial to precisely identify the relevant barriers to combining advanced technologies with traditional textile practices. Consequently, this study aims to determine the significant barriers to merging technological advancements with conventional textile practices and assess their relationships using an integrated framework. To highlight, measure, and analyze the hierarchical interconnections of the barriers to integrating technical innovations in the textile industry in the context of an emerging economy, this study combines fuzzy theory, Pareto analysis, and total interpretive structural modeling (TISM). Following that, the Matriced’ Impacts Cruoses Multiplication Applique a Un Classement (MICMAC) analysis, clusters of barriers, depending on their levels of driving and dependence power, were developed. Based on the literature review and feedback from experts, a total of 19 barriers were discovered, and Pareto analysis was applied to analyze the major and trivial barriers. Based on that analysis, a myriad of evaluations is done for the top barriers (13- to be precise), and their interrelationships have been investigated using fuzzy TISM-fuzzy MICMAC. Lack of government support policies and insufficient incentives, heavy taxation &amp; inadequate capital investment have been identified as the most crucial barriers. The hierarchical model and study’s findings will assist leaders in the textile industry in applying key concepts in strategic planning and decision-making to successfully combine cutting-edge tools and technologies with traditional textile industry practices and ensure a sustainable global textile supply chain

Groundwater quality and hydrogeological characteristics of Malacca state in Malaysia

Groundwater quality and aquifer productivity of Malacca catchment in Peninsular Malaysia are presented in this article. Pumping test data were collected from 210 shallow and 17 deep boreholes to get well inventory information. Data analysis confirmed that the aquifers consisting of schist, sand, limestone and volcanic rocks were the most productive aquifers for groundwater in Malacca state. GIS-based aquifer productivity map was generated based on bedrock and discharge capacity of the aquifers. Aquifer productivity map is classified into three classes, namely high, moderate and low based on discharge capacity. Groundwater potential of the study area is 35, 57 and 8% of low, moderate and high class respectively. Fifty two shallow and 14 deep aquifer groundwater samples were analyzed for water quality. In some cases, groundwater quality analysis indicated that the turbidity, total dissolved solids, iron, chloride and cadmium concentrations exceeded the limit of drinking water quality standards

Robo-Friend : Can a Social Robot Empathize with Your Feelings Effectively?

Social robots are becoming more popular everyday because of their resemblance with human behavior and interaction styles. They should be treated more like companions rather than just a fancy source of entertainment. Recent studies have shown great promise for robots to act as teachers, companions, caregivers and so on. In this study, primarily, a feasibility analysis is done to find out the way how a social robot can be used as a companion where it can sense the emotions of the users, empathize with their feelings and provide feedback with a view to changing their mood. A context study was conducted to make design implications where user experience goals such as inspiration, sense of control, relaxation, accomplishment and confidence were considered in the implementation. Furthermore, a prototype was designed based on a social robot, Pepper which then was interacted with potential users, either in groups or individually. The results support the fact that, a well-implemented social robot can effectively empathize with human users’ emotions.acceptedVersionPeer reviewe