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Advancements in Packaging Materials: Trends, Sustainability, and Future Prospects

Circular Economy and Sustainability 2025年 1-32页

作者： Cordeiro, Alisha Hussain, Mariya Ramachandran, T. Beemkumar, N. Kumar, Raman Karthikeyan, A. Bupesh Raja, V.K. Thatoi, Dhirendra Nath Mahapatro, Abinash Nanda, Jajneswar Prakash, Chander Patil, Arun Y. Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 + 91 - *** India Department of Mechanical Engineering Vivekananda Global University Rajasthan Jaipur India School of Mechanical Engineering Rayat Bahra University Punjab Kharar 140103 India Faculty of Engineering Sohar University PO Box 44 Sohar PCI 311 Oman Department of Mechanical Engineering Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Punjab Mohali 140307 India Department of Mechanical Engineering Siksha ’O’ Anusandhan (Deemed to be University) Odisha Bhubaneswar 751030 India Department of Mechanical Engineering University Centre for Research and Development Chandigarh University Punjab Gharuan Mohali India Bio-inspired Design and Optimization Centre (BIODOC) Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 India Department of Mechanical Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 India

Packaging plays a crucial role in product transportation, storage, and safety, with materials evolving to meet modern demands. Plastic packaging dominates due to its versatility, while paper and metal alternatives are gaining traction due to recyclability and durability. Bioinspired packaging and damage-tolerant designs are emerging trends, with China leading in research. The COVID-19 pandemic has accelerated the demand for medical packaging, where the United States leads in innovation. Advances in biodegradable materials, including biopolymers, plant-based Fibers, and smart packaging, are shaping the future of the industry. While challenges such as cost, durability, and barrier properties persist, innovations in nanotechnology and active packaging are enhancing performance. The shift toward sustainability and the 3R principles—Reduce, Reuse, Recycle continues to drive research and industry transformation. Compliance with regulatory requirements is increasingly supported by emerging technologies, including IoT, blockchain, and cyber-physical systems. Innovations in medical packaging include nanotechnology for barrier protection, modified atmosphere packaging (MAP), and intelligent packaging (IP), enhancing product quality and safety. Key design considerations focus on tamper-evident features, sterilization, and user-friendly accessibility, especially for children and the elderly. Material selection prioritizes microbial sterility, barrier properties, and durability to ensure product integrity. Sustainability remains a critical focus, with increasing adoption of biodegradable materials and efforts to minimize environmental impact. Future research aims to address gaps in sustainable packaging, regulatory compliance, and advanced material development to further improve packaging efficiency, safety, and eco-friendliness in the medical and pharmaceutical industries. © The Author(s) 2025.

关键词： Biodegradable polymers Bioinspired packaging Medical packaging Smart packaging Sustainable packaging

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Towards Ordinal Data Science

arXiv

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arXiv 2023年

作者： Stumme, Gerd Dürrschnabel, Dominik Hanika, Tom Knowledge & Data Engineering Group Research Center for Information System Design Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Computer Science University of Hildesheim Germany Berlin School of Library and Information Science Humboldt-Universität zu Berlin Germany

Order is one of the main instruments to measure data. In this paper, we will therefore discuss difthe relationship between objects in (empirical) data. ferent means for measuring and ‘calculating’ with However, compared to methods that use numerical ordinal structures — a specific class of directed properties of objects, the amount of ordinal meth- graphs — and show how to infer knowledge from ods developed is rather small. One reason for this is them. Our aim is to establish Ordinal Data Science the limited availability of computational resources as a fundamentally new research agenda. Besides in the last century that would have been required cross-fertilization with other cornerstone machine for ordinal computations. Another reason — partic- learning and knowledge representation methods, a ularly important for this line of research — is that broad range of disciplines will benefit from this en-order-based methods are often seen as too mathe- deavor, including, psychology, sociology, economics, matically rigorous for applying them to real-world web science, knowledge engineering, *** Codes 03G10, 06A15, 68T27, 68T30 Copyright © 2023, The Authors. All rights reserved.

关键词： Data Science

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Archer: adaptive memory compression with page-association-rule awareness for high-speed response of mobile devices 25

Archer: adaptive memory compression with page-association-ru...

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Proceedings of the 23rd USENIX Conference on File and Storage Technologies

作者： Changlong Li Zongwei Zhu Chao Wang Fangming Liu Fei Xu Edwin H.-M. Sha Xuehai Zhou School of Computer Science and Technology East China Normal University and Jianghuai Advance Technology Center Hefei China and MoE Engineering Research Center of Hardware/Software Co-Design Technology and Application School of Software Engineering University of Science and Technology of China Hefei China and Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou China Huazhong University of Science and Technology and Peng Cheng Laboratory School of Computer Science and Technology East China Normal University

ISBN: (纸本)9781939133458

In mobile systems, memory can be compressed page-by-page to save space. This approach is widely adopted because memory data is accessed by page. However, this paper shows that the system response speed is significantly limited by page-grained compression. In this paper, we observe that approximately a quarter of anonymous memory pages are highly correlated, even though the association is implicit. Inspired by this, we propose Archer, an association-rule-aware memory compression framework in mobile systems. Archer demonstrates that memory in mobile devices should be compressed using flexible granularity, rather than relying solely on traditional page compression. To further integrate associationrule mining techniques into system design, we redesign the LRU mechanism and propose an adaptive memory compression region. Experimental results show that the average app launching speed is 1.55x faster when enabling Archer, and the average photographic speed and frame rate increase by 1.42x and 1.31x, respectively, compared to the state-of-the-art.

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ConZone: A Zoned Flash Storage Emulator for Consumer Devices

ConZone: A Zoned Flash Storage Emulator for Consumer Devices

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design, Automation and Test in Europe Conference and Exhibition

作者： Dingcui Yu Jialin Liu Yumiao Zhao Wentong Li Ziang Huang Zonghuan Yan Mengyang Ma Liang Shi MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application East China Normal University Shanghai China College of Computer Science and Technology East China Normal University Shanghai China Software Engineering Institute East China Normal University Shanghai China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Considering the potential benefits to lifespan and performance, zoned flash storage is expected to be incorporated into the next generation of consumer devices. However, due to the limited volatile cache and heterogeneous flash cells of consumer-grade flash storage, adopting a zone abstraction requires additional internal hardware design to maximize its benefits. To understand and efficiently improve the hardware design on consumer-grade zoned flash storage, we present ConZone—the first emulator tailored to the characteristics of consumer-grade zoned flash storage. Users can explore the internal architecture and management strategies of consumer-grade zoned flash storage and integrate the optimization with software. We validate the accuracy of ConZone by realizing a hardware architecture for consumer-grade zoned flash storage and comparing it with the state-of-the-art. We also make a case study for read performance research with ConZone to explore the design of mapping mechanisms and cache management strategies.

关键词： Performance evaluation Accuracy Europe computer architecture Hardware Software Planning Optimization Next generation networking

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ConZone: A Zoned Flash Storage Emulator for Consumer Devices

ConZone: A Zoned Flash Storage Emulator for Consumer Devices

引用

2025 design, Automation and Test in Europe Conference, DATE 2025

作者： Yu, Dingcui Liu, Jialin Zhao, Yumiao Li, Wentong Huang, Ziang Yan, Zonghuan Ma, Mengyang Shi, Liang Software Engineering Institute East China Normal University Shanghai China MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application East China Normal University Shanghai China College of Computer Science and Technology East China Normal University Shanghai China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783982674100

Considering the potential benefits to lifespan and performance, zoned flash storage is expected to be incorporated into the next generation of consumer devices. However, due to the limited volatile cache and heterogeneous flash cells of consumer-grade flash storage, adopting a zone abstraction requires additional internal hardware design to maximize its benefits. To understand and efficiently improve the hardware design on consumer-grade zoned flash storage, we present ConZone - the first emulator tailored to the characteristics of consumer-grade zoned flash storage. Users can explore the internal architecture and management strategies of consumer-grade zoned flash storage and integrate the optimization with software. We validate the accuracy of ConZone by realizing a hardware architecture for consumer-grade zoned flash storage and comparing it with the state-of-the-art. We also make a case study for read performance research with ConZone to explore the design of mapping mechanisms and cache management strategies. © 2025 EDAA.

关键词： Strategic planning

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FedCo: Self-Supervised Learning in Federated Learning with Momentum Contrast

FedCo: Self-Supervised Learning in Federated Learning with M...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Shuai Wei Guitao Cao Cheng Dai Shengxin Dai Bing Guo College of Computer Science Sichuan University Chengdu China MoE Engineering Research Center of SW/HW Co-design Technology and Application East China Normal University Shanghai China MoE Engineering Research Center of SW/HW Co-design Technology and Application MoE(East China Normal University also with Sichuan University) Chengdu China College of Computer Science Sichuan University Chengdu China

Federated learning(FL) enables multiple partici-pants to build a common, robust machine learning model without sharing data, which is a key technique to address data privacy, security, access rights, and access to heterogeneous data. However, existing FL algorithms still fall short of expectations in unsupervised learning and Non-iid data, which are two major challenges that limit the applicability and accuracy. For example, the lack of data labels or skewed feature distributions leads to loss of representativeness of the model, at the same time, tagging client data will increase a lot of costs in real application scenarios, therefore, supervised federated learning greatly limits the applicability of FL. In this paper, we propose a new unsupervised FL algorithm FedCO. In particular, at the parameter aggregation phase, we apply the momentum update queue to improve the training performance, enhance the model accuracy, and lower the labeling costs. At the local client training phase, the common queue that could be regarded as a big dictionary solve the data heterogeneity. The experiment on the benchmark data set shows that our method can be compared to other supervised and semi-supervised federated learning models, which proves the effectiveness of FedCo.

关键词： Training Dictionaries Costs Federated learning Self-supervised learning Tagging Data models

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Unleashing the Power of Big Data: A Comprehensive Analysis and Future Directions

Unleashing the Power of Big Data: A Comprehensive Analysis a...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Annu Sharma Gaurav Kumar Mansoor Farooq Manish Kumar Gupta Saranya Raj Ashok Kumar Rai Department of Computer Science & Application RajaRajeshwari College of Engineering Bengaluru Karnataka India Department of Computer Science & Engineering Indian Institute of Science Education and Research Bhopal Bhopal Madhya Pradesh India Department of Management Studies University of Kashmir Jammu & Kashmir India Department of Information Technology & Computer Application Madan Mohan Malaviya University of Technology Gorakhpure UP India Department of Data Science & Engineering Dronacharya Group of Institutions Greater Noida Uttar Pradesh India Department of Computer Science & Engineering Madan Mohan Malaviya University of Technology Gorakhpure UP India

Big Data (BD) has emerged as a transformative force, offering unprecedented opportunities for organizations to extract valuable insights and drive informed decision-making. This research paper presents a comprehensive analysis of the current state of BD, explores its potential applications across industries, and outlines future directions for maximizing its benefits. This paper examines the key components of BD, including data collection, storage, processing, and analytics. It investigates the technologies and methodologies that enable efficient handling of large volumes of structured and unstructured data. Additionally, it explores the impact of cloud computing, artificial intelligence (AI), and the Internet of Things (IoT) on the growth and utilization of BD. Overall, this research paper provides a comprehensive analysis of BD, its current applications, challenges, and future directions. It serves as a valuable resource for researchers, practitioners, and policymakers seeking to unlock the full power of BD and harness its benefits across diverse domains.

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EVALUATION OF PERFORMANCE OF A CI ENGINE FUELED WITH BIODIESEL PRODUCED FROM UNUSED ALGAE

Journal of Solid Waste Technology and Management

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Journal of Solid Waste Technology and Management 2023年第4期49卷 359-364页

作者： Karmakar, Rachan Kumar, Nitin Rajor, Anita Kundu, Krishnendu Kumar, Rajesh Gahlot, Dinesh Chaudhury, Bhaskerpratap Ragit, S.S. Kumar, Amit Gorai, Sanjoy Gangwar, Pavan SInghal, Rishabh Bhattacharya, Sourish Sharma, Rachna Savita Singh, Narpinder Kumar, Neeraj Graphic Era Deemed to be University Uttarakhand Dehradun India Dept. of Mechanical Engineering Roorkee Institute of Technology Uttarakhand Roorkee India School of Energy and Environment Thapar University Punjab Patiala India Dept. of Biofuel CSIR CMERI CoEFM Punjab Ludhiana India Dept. of Chemistry S.S.J. University Campus Almora Uttarakhand India Dept. of Physics Chandigarh Group of Colleges Punjab Jhanjheri India Dept. of Mechanical Engineering Guru Nanak Institute of Technology Maharashtra Nagpur India Dept. of Computer Application Quantum University Uttarakhand Roorkee India Dept. of Electronics and Communication Engineering IMS Engineering College U.P. Gaziabad India Dept. of Electrical Engineering COER University Uttarakhand Roorkee India Process Design and Engineering Cell Discipline CSIR Central Salt and Marine Chemicals Research Institute Gujrat Bhavnagar India Dept. of Applied Science Roorkee Institute of Technology Uttarakhand Roorkee India School of Agriculture Graphic Era Hill University Uttarakhand Dehradun India Dept. of Food Science and Technology Graphic Era Deemed to be University Uttarakhand Dehradun India

Abundant availability and easy culture process of algae make it a better resource than other vegetable crops for biodiesel production. The oil (with 21% FFA content) extracted from the unused, mixed culture of algae in this experiment was used to produce biodiesel by an ‘acid esterification followed by alkaline esterification’ procedure. After confirming the properties of the biodiesel to be within the limit of ASTM standard, three biodiesel blends (B10, B20 and B30) were used in an internal combustion engine (Four stroke single cylinder VCR engine) and the performance of the engine was observed at different engine loads (0%, 20%, 40%, 80%, 100%, 120%). The little higher brake specific fuel consumption (0.22kg/KWh, 0.25 kg/KWh, 0.26kg/KWh and 0.21kg/KWh respectively for B10, B20, B30 and petro-diesel at overload condition), lower brake power (3.41 kW, 3.37 kW, 3.25 kW, 3.39 kW for diesel, B10, B20 and B30 respectively for B10, B20, B30 and petro-diesel) and mechanical efficiency (63.34, 51.43%, 52.06% and 51.43% for petro-diesel, B10, B20 and B30 respectively) for biodiesel blends took place which might be the results of lower calorific value (40800 kJ/kg), higher density (875.27kg/m3) and viscosity (3.14 mm2/s) of the algal biodiesel than diesel. © 2023 Widener University School of Civil engineering. All rights reserved.

关键词： Biodiesel

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Short-term electricity demand forecasting via variational autoencoders and batch training-based bidirectional long short-term memory

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2022年第PartC期52卷

作者： Moradzadeh, Arash Moayyed, Hamed Zare, Kazem Mohammadi-Ivatloo, Behnam [a]Faculty of Electrical and Computer Engineering University of Tabriz *** Tabriz Iran [b]GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (P. PORTO) P-4200-072 Porto Portugal [c]Information Technologies Application and Research Center İstanbul Ticaret University Istanbul Turkey

Electricity load forecasting is a key aspect for power producers to maximize their economic efficiency in deregulated markets. So far, many solutions have been employed to forecast the consumption load in power grids. However, most of these methods have suffered in modeling the time-series state of data and removing noise from real-world data. Thus, the forecasting results in most cases did not have acceptable accuracy due to the mentioned problems. In this paper, in order to short-term electricity load forecast in Tabriz, Iran, a hybrid technique based on deep learning applications called Variational Autoencoder Bidirectional Long Short-Term Memory (VAEBiLSTM) is presented. Pre-processing, noise cancellation, and time-series state modeling of the data are prominent features of the developed load forecasting model. In addition, in order to prevent overfitting problems in the process of training large amounts of data, the training process is developed in the form of batch training. Load forecasting is done using meteorological and environmental data of Tabriz city as well as historical information and days of the week as input variables. In the hybrid method structure, the Variational Autoencoders are applied to the data for data preprocessing and reconstruction. Then, the normalized, noise-free data is utilized as a dataset for training the Bidirectional Long Short-Term Memory (BiLSTM) network. The proposed training method for BiLSTM is based on batch training. To present the effectiveness of the proposed technique in a comparative approach, the conventional LSTM and Support Vector Regression (SVR) algorithms are also applied to the data. Each network is trained with input data related to the years of 2017 and 2018 to predict the electricity load of the Tabriz city separately for each of the four seasons of the 2019 year. The forecasting results obtained from each method are evaluated by different statistical performance indicators. It can be seen that the proposed

关键词： Electricity demand Load forecasting Deep learning Variational Autoencoders (VAE) Bidirectional long short-term memory (BiLSTM)

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Effects of Air Exposure on the Interfacial Capacitance of Laser-Induced Graphene (LIG) with and without Silver (Ag) Nanoparticle Loading

Effects of Air Exposure on the Interfacial Capacitance of La...

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2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

作者： Goh, Rou Xuan Sultan, Suhana Mohamed Pu, Suan Hui Leow, Pei Ling Lee, Hing Wah Fishlock, Sam J. Chong, Harold M. H. Ling, Ting Yang University of Southampton Malaysia Smart Manufacturing and Systems Research Group Johor Iskandar Puteri79100 Malaysia Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Skudai81310 Malaysia MIMOS Berhad Technology Park Malaysia Centre for Semiconductor & Thin Film Research Kuala Lumpur57000 Malaysia TEDI-London The Engineering & Design Institute LondonSE16 7LG United Kingdom University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

ISBN: (纸本)9798350333312

research on laser-induced graphene (LIG) and LIG with silver nanoparticles loading (Ag-LIG) are increasing by the day as more of its potential are uncovered each day. With the LIG fabrication looking to increase further in the future, it will be useful to confirm and verify any changes in the quality of LIG when it is exposed to the ambient air. In normal laboratory conditions, researchers store samples in petri dishes or any other covered storage, but inevitably the air within the storage will still be in contact with the samples. In this study, we left LIG and Ag-LIG samples in a lidded petri dish after its fabrication and measured the interfacial capacitance of each sample using a standard three-electrode electrochemical setup with a potential range from 0 V to 0.4 V on different days. Results show that the interfacial capacitance of both LIG and Ag-LIG drops as it is left in the storage container longer after its fabrication, with Ag-LIG showing a greater decrease after 10 days compared to LIG. This indicates that the silver nanoparticles played an important part during the oxidation process, making Ag-LIG more sensitive to its environment during prolonged unuse. The findings from this study shows the potential usage of LIG and Ag-LIG as a low-cost single-use indicator for air exposure. © 2023 IEEE.

关键词： Graphene

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