An Unsupervised Writer Identification Based on Generating ClusterableEmbeddings

The writer identification system identifies individuals based on their handwriting is a frequent topic in biometric authentication and verification systems. Due to its importance, numerous studies have been conducted in various languages. Researchers have established several learning methods for writer identification including supervised and unsupervised learning. However, supervised methods require a large amount of annotation data, which is impossible in most scenarios. On the other hand, unsupervised writer identification methods may be limited and dependent on feature extraction that cannot provide the proper objectives to the architecture and be misinterpreted. This paper introduces an unsupervised writer identification system that analyzes the data and recognizes the writer based on the inter-feature relations of the data to resolve the uncertainty of the features. A pairwise architecture-based Autoembedder was applied to generate clusterable embeddings for handwritten text images. Furthermore, the trained baseline architecture generates the embedding of the data image, and the K-means algorithm is used to distinguish the embedding of individual writers. The proposed model utilized the IAM dataset for the experiment as it is inconsistent with contributions from the authors but is easily accessible for writer identification tasks. In addition, traditional evaluation metrics are used in the proposed model. Finally, the proposed model is compared with a few unsupervised models, and it outperformed the state-of-the-art deep convolutional architectures in recognizing writers based on unlabeled data.     

Nanoarchitectonics: Porous Hydrogel as Bio-sorbent for Effective Remediation of Hazardous Contaminants

The increasing use of heavy metals, dyes, and other metallic or chemical elements causes crucial environmental pollution. Sewage that contains these heavy metals and dyes is discharged into the atmosphere and goes directly into the food cycle, causing cancerous diseases and health deterioration in living organisms. The supreme concern of today’s research is to treat wastewater and effectively remove the hazardous dye molecules from aqueous media and other environmental matrices. Nowadays, technologies are applied to rectify organic and inorganic pollutants from sewage. Among them, adsorption is a fascinating way because it is environmentally friendly, feasible, and economical biomaterials. Chitosan (CS) as bio-sorbent is endowed with valuable characteristics, such as biodegradability, biocompatibility, high reactivity, low-cost, and functional groups (–OH and NH₂) on its surface. CS is used for many applications, either as a single component or composite form. The use of CS as bio-adsorbents is beneficial over regular adsorbents. Chitosan-based hydrogel is one of the very important bio-adsorbents. All these bio-adsorbents are highly used to eradicate toxic dyes, digest harmful industrial sewage, and eliminate pesticides, climatic hazardous waste, and contaminated materials from the environment.

     

MCD Approach for Assessing the Optimal Operating Condition during Sliding Wear Characteristics of LM25/SiC AMCs Processed by an Improved Stir Casting Technique

Silicon - The Sliding wear behaviour of the improved stir cast LM25/SiC composite was investigated using a wear apparatus having pin-on-disc configuration. The tests were conducted at varying...     

Carrageenan-Based Hybrids with Biopolymers and Nano-Structured Materials for Biomimetic Applications

Carrageenan is an algal-originated group of polysaccharides with unusual structural and functional capabilities, desired for different biomimetic applications due to their renewable, biocompatible, and biodegradable nature. Carrageenan-based hybrids (nano-/biocomposites) with different biopolymers and nano-structured materials have been widely reported as potential candidates for bone/cartilage tissue engineering, delivery of drugs/bioactive ingredients, wound healing, and 3D bioprinting applications. Owning to the broad-scale biomimetic applications of carrageenan-based materials, this review aims to summarize carrageenan chemistry and distinct physicochemical features of biopolymeric and/or nanostructured materials-based on carrageenans in a detailed manner. Herein, different biopolymers (such as chitosan, cellulose, starch, and alginates), and nano-structured materials (such as silica nanoparticles, magnetic/non-magnetic nanocarriers, graphene oxide nanoparticles, carbon nanotubes/nanorods, metal oxide nanoparticles) are comprehensively described in combination with carrageenan. However, carrageenan toxicity studies have presented major challenges that need to be addressed when using carrageenan-based materials for biomedical and therapeutic purposes. Several existing challenges, prospects, and research recommendations are described at the end of this review.     

2D Arrays of Soft Actuators Performing Out-of-Plane Local Inflation for Shape Displays

Elementary actuators performing branching or surface swelling are the primary units in the actuator integration system that is leveraged in works requiring a high versatility and complex motion. However, those primary actuator units often lack scalability or compatibility at assembly into a compact form due to the complexity of the structure and the actuation interference between adjacent units. Herein, it is shown that the phase-change actuator in a simple bilayer structure of a top active layer and a bottom constraint layer achieves 1D surface swelling, such that the closely packed 2D array system of this actuator is easily constructed. Upon resistive heating, the active layer inflates based on the phase change of microliquid droplets embedded in an elastomer body. The inflation along the lateral direction of the actuator is suppressed by controlling the thickness ratio between the active and the constraint layers. The actuation of individual units in the array system is performed independently using a switching device with a microcontroller for the parallel application of resistive heating. The application of 2D shape morphing of the actuator arrays in beam steering and shape displays is investigated.     

Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling,validation, and control

This article presents the development of the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality-free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land-based wind turbine models against OpenFAST, an industry-standard platform, for several test cases. Closed-loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user-friendly and computationally efficient capabilities of CRAFTS to facilitate control co-design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.     

The last two decades of computer vision technologies in water resource management: A bibliometric analysis

Efficient management of water resources is an important task given the significance of water in daily lives and economic growth. Water resource management is a specific field of study which deals with the efficient management of water resources towards fulfilling the needs of society and preventing from water-related disasters. Many activities within this domain are getting benefitted with the recent technological advancements. Within many others, computer vision-based solutions have emerged as disruptive technologies to address complex real-world problems within the water resource management domain (e.g., flood detection and mapping, satellite-based water bodies monitoring, monitoring and inspection of hydraulic structures, blockage detection and assessment, drainage inspection and sewer monitoring). However, there are still many aspects within the water resource management domain which can be explored using computer vision technologies. Therefore, it is important to investigate the trends in current research related to these technologies to inform the new researchers in this domain. In this context, this paper presents the bibliometric analysis of the literature from the last two decades where computer vision technologies have been used for addressing problems within the water resource management domain. The analysis is presented in two categories: (a) performance analysis demonstrating highlighted trends in the number of publications, number of citations, top contributing countries, top publishing journals, top contributing institutions and top publishers and (b) science mapping to demonstrate the relation between the bibliographic records based on the co-occurrence of keywords, co-authorship analysis, co-citation analysis and bibliographic coupling analysis. Bibliographic records (i.e., 1059) are exported from the Web of Science (WoS) core collection database using a comprehensive query of keywords. VOSviewer opensource tool is used to generate the network and overlay maps for the science mapping of bibliographic records. Results highlighted important trends and valuable insights related to the use of computer vision technologies in water resource management. An increasing trend in the number of publications and focus on deep learning/artificial intelligence (AI)-based approaches has been reported from the analysis. Further, flood mapping, crack/fracture detection, coastal flood detection, blockage detection and drainage inspections are highlighted as active areas of research.     

Implementation of shooting technique for Buongiorno nanofluid model driven by a continuous permeable surface

The current investigation focuses on the thermal characteristics and heat and mass transfer in the context of their applications. There has been a lot of interest in the utilization of non-Newtonian liquids in various engineering and biological fields. Having such considerable attention on non-Newtonian liquids, the goal is to investigate the flow nature of viscoelastic nanoliquid flow driven by a permeable stretchable surface considering the Buongiorno nanofluid model with suction or injection and mixed convection. This model includes Brownian diffusion, thermophoresis, and radiation effects. The thermal boundary layer theories established the constitutive flow equations, that is, the momentum, diffusion balance, and energy expressions. The established partial differential equations are diminished to dimensionless coupled ordinary differential equations by taking the assistance of proper transformations of nonlinearities. An efficient and validated numerical algorithm is implemented as a computational technique where Mathematica 11.0 environment, a programming tool, is developed for fluid dynamics. The convergence standard had also been recognized for the precision of the relevant parameters by using boundary postulates. The impact of embedded physical quantities of practical interest is examined and offered via the plotted graphs. In addition, the impression of system parameters on drag force, heat, and mass flow coefficient with three-dimensional graphs is also debated.     

Effects of red rice flour addition on the rheological,textural, sensory and bioactive properties of wheat flour-based pan breads

Red rice, rich in fibre and phenolic contents, is one of the underutilised grains. Therefore, the present study developed the wheat/red rice flour (RRF) composites followed by its utilisation in pan breads. It led to an increase in ash and fibre contents of resultant flour combinations, but gluten network became weaker. The values for water absorption were unaffected with RRF replacements ≤15% of wheat flour. Moreover, the proximate estimates of RRF added breads demonstrated increased moisture and fibre contents. Substituted bread combinations were harder with increased gumminess and springiness values; however, cohesion decreased. The per cent change in cohesion and hardness of individual breads upon storage was lesser in composites compared to control suggesting decline in staling phenomenon. Nutritional assessment of both RRF containing flour and breads showed higher total phenolic content and DPPH radical scavenging activity compared to their respective controls. Composite breads also demonstrated reduced glycaemic index suggesting its importance for diabetic patients.     

Chitosan-Based Smart Polymeric Hydrogels and Their Prospective Applications in Biomedicine

With increasing scientific research, knowledge, and socioeconomic awareness, research, and industrial communities are now much more interested in biopolymers-based composite materials with multifaceted functionalities. Biopolymers are easily obtainable, economical, non-hazardous, and abundant. Several natural and synthetic polymers have been used to prepare hydrogels, microbeads, and microfibers for controlled drug release. Due to marvelous properties, chitosan has been widely explored for medical and pharmaceutical applications. In recent years, considerable attention has been paid to the chitosan-based hydrogels for biomedical applications, especially for transplantation, and for improving interfacial interactions for the living tissues. Hydrogels can be synthesized by co-polymerization, condensation, and cross-linking. This review spotlights recent advances in physicochemical characteristics, modification strategies, and smart blended hydrogels for an array of biomedical and pharmaceutical applications. The whole discussion reveals that among all the biopolymers, chitosan is the finest carrier for biomedical applications.