Wearable electronic textiles(e-textiles)with embedded electronics offer promising solutions for unobtrusive,real-time health monitoring,enhancing healthcare efficiency.However,their adoption is limited by performance ...Wearable electronic textiles(e-textiles)with embedded electronics offer promising solutions for unobtrusive,real-time health monitoring,enhancing healthcare efficiency.However,their adoption is limited by performance and sustainability challenges in materials,manufacturing,and recycling.This study introduces a sustainable paradigm for the fabrication of fully inkjet-printed Smart,Wearable,and Eco-friendly Electronic Textiles(SWEET)with the first comprehensive assessments of the biodegradability and life cycle assessment(LCA).SWEET addresses existing limitations,enabling concurrent and continuous monitoring of human physiology,including skin surface temperature(at temperature coefficient of resistance,TCR value of~-4.4%℃^(-1))and heart rate(-74 beats per minute,bpm)separately and simultaneously like the industry gold standard,using consistent,versatile,and highly efficient inkjet-printed graphene and Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)-based wearable e-textiles.Demonstrations with a wearable garment on five human participants confirm the system’s capability to monitor their electrocardiogram(ECG)signals and skin temperature.Such sustainable and biodegradable e-textiles decompose by-48%in weight and lost-98%strength over 4months.Life cycle assessment(LCA)reveals that the graphene-based electrode has the lowest climate change impact of-0.037 kg CO_(2) eq,40 times lower than reference electrodes.This approach addresses material and manufacturing challenges,while aligning with environmental responsibility,marking a significant leap forward in sustainable e-textile technology for personalized healthcare management.展开更多
Blockchain technology holds significant promise for driving innovations across diverse industries, businesses, and applications. Recognized as a crucial source of competitive advantage in a fast-evolving environment, ...Blockchain technology holds significant promise for driving innovations across diverse industries, businesses, and applications. Recognized as a crucial source of competitive advantage in a fast-evolving environment, blockchain is anticipated to contribute substantially to sustainable economic and social development. Despite these high expectations, many blockchain projects currently face high failure rates, leading to negative impacts on various aspects of economic and social sustainability, including corporate governance, risk management, financial management, human resources, culture management, and competitiveness. This paper evaluates adoption models, identifying both risk and success factors. It introduces an integrated adoption model designed to operationalize, measure, and manage blockchain-driven business innovation sustainably. An empirical study involving 20 industry sectors and 125 business leaders was conducted to assess the model’s applicability. The findings indicate that the adoption model has the potential to support the sustainable implementation of blockchain technology for business innovations across various industries and applications. Future research and industry activities should continue validating this model through further case studies.展开更多
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...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 architecturebased 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.展开更多
As we move toward the 21st century,increasing awareness of environmental impact is driving a shift toward natural-fiber alternatives.This study explores the utilization of bamboo fiber as the reinforcement for ABS pol...As we move toward the 21st century,increasing awareness of environmental impact is driving a shift toward natural-fiber alternatives.This study explores the utilization of bamboo fiber as the reinforcement for ABS polymer and its impact on the composite’s properties and sustainability.Bamboo fiber rein-forced ABS polymer composite is a biodegradable composite which was pre-pared by using a hot press machine at 180℃ temperature and 50 KN load.Bamboo fiber was collected from local area of Savar,Dhaka,Bangladesh and ABS polymer was collected from local market of Dhaka,Bangladesh.In this study,different properties of composites like physical(bulk density and water ab sorption),mechanical(tensile properties and hardness)and structural(Fourier Transform Infrared Spectroscopy)properties were studied.The bulk density of composites was not altered consistently and it gave greater value for 5% and 15% composites.The water absorption enhanced for all composites with the accumulation of fiber content and soaking time.The reduction of tensile strength and Leeb’s rebound hardness of the composites were observed with the increase of the fiber content in all compositions.Maximum(%)of elongation was found for 5% and 10% composite,and then it was decreased for 15% composite;however,elastic modulus increased with the increased of fiber content in composites.Fourier Transform Infrared(FTIR)spectroscopy study was done for structural characterization.It was observed that,at 15% fiber loading,an extra O-H bond appeared,implying more hydroxyl groups were introduced with the increased fiber content.展开更多
基金funding from Commonwealth Scholarship Commission(CSC)U.K.for a Ph.D.scholarship for Marzia DulalUKRI Research England the Expanding Excellence in England(E3)grant.
文摘Wearable electronic textiles(e-textiles)with embedded electronics offer promising solutions for unobtrusive,real-time health monitoring,enhancing healthcare efficiency.However,their adoption is limited by performance and sustainability challenges in materials,manufacturing,and recycling.This study introduces a sustainable paradigm for the fabrication of fully inkjet-printed Smart,Wearable,and Eco-friendly Electronic Textiles(SWEET)with the first comprehensive assessments of the biodegradability and life cycle assessment(LCA).SWEET addresses existing limitations,enabling concurrent and continuous monitoring of human physiology,including skin surface temperature(at temperature coefficient of resistance,TCR value of~-4.4%℃^(-1))and heart rate(-74 beats per minute,bpm)separately and simultaneously like the industry gold standard,using consistent,versatile,and highly efficient inkjet-printed graphene and Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)-based wearable e-textiles.Demonstrations with a wearable garment on five human participants confirm the system’s capability to monitor their electrocardiogram(ECG)signals and skin temperature.Such sustainable and biodegradable e-textiles decompose by-48%in weight and lost-98%strength over 4months.Life cycle assessment(LCA)reveals that the graphene-based electrode has the lowest climate change impact of-0.037 kg CO_(2) eq,40 times lower than reference electrodes.This approach addresses material and manufacturing challenges,while aligning with environmental responsibility,marking a significant leap forward in sustainable e-textile technology for personalized healthcare management.
文摘Blockchain technology holds significant promise for driving innovations across diverse industries, businesses, and applications. Recognized as a crucial source of competitive advantage in a fast-evolving environment, blockchain is anticipated to contribute substantially to sustainable economic and social development. Despite these high expectations, many blockchain projects currently face high failure rates, leading to negative impacts on various aspects of economic and social sustainability, including corporate governance, risk management, financial management, human resources, culture management, and competitiveness. This paper evaluates adoption models, identifying both risk and success factors. It introduces an integrated adoption model designed to operationalize, measure, and manage blockchain-driven business innovation sustainably. An empirical study involving 20 industry sectors and 125 business leaders was conducted to assess the model’s applicability. The findings indicate that the adoption model has the potential to support the sustainable implementation of blockchain technology for business innovations across various industries and applications. Future research and industry activities should continue validating this model through further case studies.
文摘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 architecturebased 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.
文摘As we move toward the 21st century,increasing awareness of environmental impact is driving a shift toward natural-fiber alternatives.This study explores the utilization of bamboo fiber as the reinforcement for ABS polymer and its impact on the composite’s properties and sustainability.Bamboo fiber rein-forced ABS polymer composite is a biodegradable composite which was pre-pared by using a hot press machine at 180℃ temperature and 50 KN load.Bamboo fiber was collected from local area of Savar,Dhaka,Bangladesh and ABS polymer was collected from local market of Dhaka,Bangladesh.In this study,different properties of composites like physical(bulk density and water ab sorption),mechanical(tensile properties and hardness)and structural(Fourier Transform Infrared Spectroscopy)properties were studied.The bulk density of composites was not altered consistently and it gave greater value for 5% and 15% composites.The water absorption enhanced for all composites with the accumulation of fiber content and soaking time.The reduction of tensile strength and Leeb’s rebound hardness of the composites were observed with the increase of the fiber content in all compositions.Maximum(%)of elongation was found for 5% and 10% composite,and then it was decreased for 15% composite;however,elastic modulus increased with the increased of fiber content in composites.Fourier Transform Infrared(FTIR)spectroscopy study was done for structural characterization.It was observed that,at 15% fiber loading,an extra O-H bond appeared,implying more hydroxyl groups were introduced with the increased fiber content.
