Technologies (Basel)最新文献

{"title":"Recent Advances in the 3D Printing of Pure Copper Functional Structures for Thermal Management Devices","authors":"Yue Hao Choong, Manickavasagam Krishnan, Manoj Gupta","doi":"10.3390/technologies11050141","DOIUrl":"https://doi.org/10.3390/technologies11050141","url":null,"abstract":"Thermal management devices such as heat exchangers and heat pipes are integral to safe and efficient performance in multiple engineering applications, including lithium-ion batteries, electric vehicles, electronics, and renewable energy. However, the functional designs of these devices have until now been created around conventional manufacturing constraints, and thermal performance has plateaued as a result. While 3D printing offers the design freedom to address these limitations, there has been a notable lack in high thermal conductivity materials beyond aluminium alloys. Recently, the 3D printing of pure copper to sufficiently high densities has finally taken off, due to the emergence of commercial-grade printers which are now equipped with 1 kW high-power lasers or short-wavelength lasers. Although the capabilities of these new systems appear ideal for processing pure copper as a bulk material, the performance of advanced thermal management devices are strongly dependent on topology-optimised filigree structures, which can require a very different processing window. Hence, this article presents a broad overview of the state-of-the-art in various additive manufacturing technologies used to fabricate pure copper functional filigree geometries comprising thin walls, lattice structures, and porous foams, and identifies opportunities for future developments in the 3D printing of pure copper for advanced thermal management devices.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136184511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Enhanced Lightweight Security Gateway Protocol for the Edge Layer","authors":"Md Masum Reza, Jairo Gutierrez","doi":"10.3390/technologies11050140","DOIUrl":"https://doi.org/10.3390/technologies11050140","url":null,"abstract":"With the rapid expansion of the Internet of Things (IoT), the necessity for lightweight communication is also increasing due to the constrained capabilities of IoT devices. This paper presents the design of a novel lightweight protocol called the Enhanced Lightweight Security Gateway Protocol (ELSGP) based on a distributed computation model of the IoT layer. This model introduces a new type of node called a sub-server to assist edge layer servers and IoT devices with computational tasks and act as a primary gateway for dependent IoT nodes. This paper then introduces six features of ELSGP with developed algorithms that include access token distribution and validation, authentication and dynamic interoperability, attribute-based access control, traffic filtering, secure tunneling, and dynamic load distribution and balancing. Considering the variability of system requirements, ELSGP also outlines how to adopt a system-defined policy framework. For fault resiliency, this paper also presents fault mitigation mechanisms, especially Trust and Priority Impact Relation for Byzantine, Cascading, and Transient faults. A simulation study was carried out to validate the protocol’s performance. Based on the findings from the performance evaluation, further analysis of the protocol and future research directions are outlined.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135969573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Carbohydrates on the Formation Process and Performance of Micro-Arc Oxidation Coatings on AZ31B Magnesium Alloy","authors":"Yingxiu Du, Mingyue Hu, Xiaohua Tu, Chengping Miao, Yang Zhang, Jiayou Li","doi":"10.3390/technologies11050139","DOIUrl":"https://doi.org/10.3390/technologies11050139","url":null,"abstract":"An environmentally friendly alkaline electrolyte of silicate and borate, which contained the addition of carbohydrates (lactose, starch, and dextrin), was applied to produce micro-arc oxidation (MAO) coatings on AZ31B magnesium alloy surfaces in constant current mode. The effects of the carbohydrates on the performance of the MAO coatings were investigated using a scanning electron microscope (SEM), an X-ray diffractometer (XRD), energy-dispersive spectroscopy (EDS), the salt spray test, potentiodynamic polarization curves, and electrochemical impedance spectroscopy (EIS). The results show that the carbohydrates effectively inhibited spark discharge, so the anodized growth process, surface morphology, composition, and corrosion resistance of the MAO coatings were strongly dependent on the carbohydrate concentration. This is ascribed to the surface adsorption layer formed on the surface of the magnesium alloy. When the carbohydrate concentration was 10 g/L, smooth, compact, and thick MAO coatings with excellent corrosion resistance on the magnesium alloy were obtained.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heuristic Weight Initialization for Diagnosing Heart Diseases Using Feature Ranking","authors":"Musulmon Lolaev, Shraddha M. Naik, Anand Paul, Abdellah Chehri","doi":"10.3390/technologies11050138","DOIUrl":"https://doi.org/10.3390/technologies11050138","url":null,"abstract":"The advent of Artificial Intelligence (AI) has had a broad impact on life to solve various tasks. Building AI models and integrating them with modern technologies is a central challenge for researchers. These technologies include wearables and implants in living beings, and their use is known as human augmentation, using technology to enhance human abilities. Combining human augmentation with artificial intelligence (AI), especially after the recent successes of the latter, is the most significant advancement in their applicability. In the first section, we briefly introduce these modern applications in health care and examples of their use cases. Then, we present a computationally efficient AI-driven method to diagnose heart failure events by leveraging actual heart failure data. The classifier model is designed without conventional models such as gradient descent. Instead, a heuristic is used to discover the optimal parameters of a linear model. An analysis of the proposed model shows that it achieves an accuracy of 84% and an F1 score of 0.72 with only one feature. With five features for diagnosis, the accuracy achieved is 83%, and the F1 score is 0.74. Moreover, the model is flexible, allowing experts to determine which variables are more important than others when implementing diagnostic systems.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134943783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of PLGA Concentration in Electrospinning Solution on Biocompatibility, Morphology and Mechanical Properties of Nonwoven Scaffolds","authors":"Arsalan D. Badaraev, Tuan-Hoang Tran, Anastasia G. Drozd, Evgenii V. Plotnikov, Gleb E. Dubinenko, Anna I. Kozelskaya, Sven Rutkowski, Sergei I. Tverdokhlebov","doi":"10.3390/technologies11050137","DOIUrl":"https://doi.org/10.3390/technologies11050137","url":null,"abstract":"In this work, the effects of weight concentration on the properties of poly(lactide-co-glycolide) polymeric scaffolds prepared by electrospinning are investigated, using four different weight concentrations of poly(lactide-co-glycolide) for the electrospinning solutions (2, 3, 4, 5 wt.%). With increasing concentration of poly(lactide-co-glycolide) in the electrospinning solutions, their viscosity increases significantly. The average fiber diameter of the scaffolds also increases with increasing concentration. Moreover, the tensile strength and maximum elongation at break of the scaffold increase with increasing electrospinning concentration. The prepared scaffolds have hydrophobic properties and their wetting angle does not change with the concentration of the electrospinning solution. All poly(lactide-co-glycolide) scaffolds are non-toxic toward fibroblasts of the cell line 3T3-L1, with the highest numbers of cells observed on the surface of scaffolds prepared from the 2-, 3- and 4-wt.% electrospinning solutions. The results of the analysis of mechanical and biological properties indicate that the poly(lactide-co-glycolide) scaffolds prepared from the 4 wt.% electrospinning solution have optimal properties for future applications in skin tissue engineering. This is due to the fact that the poly(lactide-co-glycolide) scaffolds prepared from the 2 wt.% and 3 wt.% electrospinning solution exhibit low mechanical properties, and 5 wt.% have the lowest porosity values, which might be the cause of their lowest biological properties.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135481966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preparation and Characterization of Fluorine-Containing Polyimide Films with Enhanced Output Performance for Potential Applications as Negative Friction Layers for Triboelectric Nanogenerators","authors":"Zhen Pan, Shunqi Yuan, Xi Ren, Zhibin He, Zhenzhong Wang, Shujun Han, Yuexin Qi, Haifeng Yu, Jingang Liu","doi":"10.3390/technologies11050136","DOIUrl":"https://doi.org/10.3390/technologies11050136","url":null,"abstract":"Nanotechnologies are being increasingly widely used in advanced energy fields. Triboelectric nanogenerators (TENGs) represent a class of new-type flexible energy-harvesting devices with promising application prospects in future human societies. As one of the most important parts of TENG devices, triboelectric materials play key roles in the achievement of high-efficiency power generation. Conventional polymer tribo-negative materials, such as polytetrafluoroethylene (PTFE), polyvinylidene difluoride (PVDF), and the standard polyimide (PI) film with the Kapton® trademark based on pyromellitic anhydride (PMDA) and 4,4′-oxydianiline (ODA), usually suffer from low output performance. In addition, the relationship between molecular structure and triboelectric properties remains a challenge in the search for novel triboelectric materials. In the current work, by incorporating functional groups of trifluoromethyl (–CF3) with strong electron withdrawal into the backbone, a series of fluorine-containing polyimide (FPI) negative friction layers have been designed and prepared. The derived FPI-1 (6FDA-6FODA), FPI-2 (6FDA-TFMB), and FPI-3 (6FDA-TFMDA) resins possessed good solubility in polar aprotic solvents, such as the N,N-dimethylacetamide (DMAc) and N-methyl-2-pyrrolidone (NMP). The PI films obtained via the solution-casting procedure showed glass transition temperatures (Tg) higher than 280 °C with differential scanning calorimetry (DSC) analyses. The TENG prototypes were successfully fabricated using the developed PI films as the tribo-negative layers. The electron-withdrawing trifluoromethyl (–CF3) units in the molecular backbones of the PI layers provided the devices with an apparently enhanced output performance. The FPI-3 (6FDA-TFMDA) layer-based TENG devices showcased an especially impressive open-circuit voltage and short-circuit current, measuring 277.8 V and 9.54 μA, respectively. These values were 4~5 times greater when compared to the TENGs manufactured using the readily accessible Kapton® film.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135744196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Airborne Pathogens: A Computational Approach Utilizing Surface Acoustic Wave Sensors for Microorganism Detection","authors":"Sharon P. Varughese, S. Merlin Gilbert Raj, T. Jesse Joel, Sneha Gautam","doi":"10.3390/technologies11050135","DOIUrl":"https://doi.org/10.3390/technologies11050135","url":null,"abstract":"The persistent threat posed by infectious pathogens remains a formidable challenge for humanity. Rapidly spreading infectious diseases caused by airborne microorganisms have far-reaching global consequences, imposing substantial costs on society. While various detection technologies have emerged, including biochemical, immunological, and molecular approaches, these methods still exhibit significant limitations such as time-intensive procedures, instability, and the need for specialized operators. This study presents an innovative solution that harnesses the potential of surface acoustic wave (SAW) sensors for the detection of airborne microorganisms. The research involves the establishment of a sensor model within the framework of COMSOL Multiphysics, utilizing a predefined piezoelectric multi-physics interface and employing a 2D modeling approach. Chitosan, selected as the sensing film for the model, interfaces with lithium niobate (LiNbO3), the chosen piezoelectric material responsible for detecting airborne pathogens. The analysis of microbe presence centers on solid displacement and electric potential frequencies, operating within the 850–900 MHz range. Notably, the first and second resonant frequencies are identified at 856 and 859 MHz, respectively. To enhance understanding, this study proposes a novel mathematical model grounded in Stokes’ Law and mass balance equations. This model serves to analyze microbe concentration, offering a fresh perspective on quantifying the presence of airborne pathogens. Through these endeavors, this research contributes to advancing the field of airborne microorganism detection, offering a promising avenue for addressing the challenges posed by infectious diseases.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135829070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparison of Monte Carlo-Based and PINN Parameter Estimation Methods for Malware Identification in IoT Networks","authors":"Marcos Severt, Roberto Casado-Vara, Angel Martín del Martín del Rey","doi":"10.3390/technologies11050133","DOIUrl":"https://doi.org/10.3390/technologies11050133","url":null,"abstract":"Malware propagation is a growing concern due to its potential impact on the security and integrity of connected devices in Internet of Things (IoT) network environments. This study investigates parameter estimation for Susceptible-Infectious-Recovered (SIR) and Susceptible–Infectious–Recovered–Susceptible (SIRS) models modeling malware propagation in an IoT network. Synthetic data of malware propagation in the IoT network is generated and a comprehensive comparison is made between two approaches: algorithms based on Monte Carlo methods and Physics-Informed Neural Networks (PINNs). The results show that, based on the infection curve measured in the IoT network, both methods are able to provide accurate estimates of the parameters of the malware propagation model. Furthermore, the results show that the choice of the appropriate method depends on the dynamics of the spreading malware and computational constraints. This work highlights the importance of considering both classical and AI-based approaches and provides a basis for future research on parameter estimation in epidemiological models applied to malware propagation in IoT networks.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136343785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Scale CNN: An Explainable AI-Integrated Unique Deep Learning Framework for Lung-Affected Disease Classification","authors":"Ovi Sarkar, Md. Robiul Islam, Md. Khalid Syfullah, Md. Tohidul Islam, Md. Faysal Ahamed, Mominul Ahsan, Julfikar Haider","doi":"10.3390/technologies11050134","DOIUrl":"https://doi.org/10.3390/technologies11050134","url":null,"abstract":"Lung-related diseases continue to be a leading cause of global mortality. Timely and precise diagnosis is crucial to save lives, but the availability of testing equipment remains a challenge, often coupled with issues of reliability. Recent research has highlighted the potential of Chest X-ray (CXR) images in identifying various lung diseases, including COVID-19, fibrosis, pneumonia, and more. In this comprehensive study, four publicly accessible datasets have been combined to create a robust dataset comprising 6650 CXR images, categorized into seven distinct disease groups. To effectively distinguish between normal and six different lung-related diseases (namely, bacterial pneumonia, COVID-19, fibrosis, lung opacity, tuberculosis, and viral pneumonia), a Deep Learning (DL) architecture called a Multi-Scale Convolutional Neural Network (MS-CNN) is introduced. The model is adapted to classify multiple numbers of lung disease classes, which is considered to be a persistent challenge in the field. While prior studies have demonstrated high accuracy in binary and limited-class scenarios, the proposed framework maintains this accuracy across a diverse range of lung conditions. The innovative model harnesses the power of combining predictions from multiple feature maps at different resolution scales, significantly enhancing disease classification accuracy. The approach aims to shorten testing duration compared to the state-of-the-art models, offering a potential solution toward expediting medical interventions for patients with lung-related diseases and integrating explainable AI (XAI) for enhancing prediction capability. The results demonstrated an impressive accuracy of 96.05%, with average values for precision, recall, F1-score, and AUC at 0.97, 0.95, 0.95, and 0.94, respectively, for the seven-class classification. The model exhibited exceptional performance across multi-class classifications, achieving accuracy rates of 100%, 99.65%, 99.21%, 98.67%, and 97.47% for two, three, four, five, and six-class scenarios, respectively. The novel approach not only surpasses many pre-existing state-of-the-art (SOTA) methodologies but also sets a new standard for the diagnosis of lung-affected diseases using multi-class CXR data. Furthermore, the integration of XAI techniques such as SHAP and Grad-CAM enhanced the transparency and interpretability of the model’s predictions. The findings hold immense promise for accelerating and improving the accuracy and confidence of diagnostic decisions in the field of lung disease identification.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136342688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast and Efficient Entropy Coding Architectures for Massive Data Compression","authors":"Francesc Auli-Llinas","doi":"10.3390/technologies11050132","DOIUrl":"https://doi.org/10.3390/technologies11050132","url":null,"abstract":"The compression of data is fundamental to alleviating the costs of transmitting and storing massive datasets employed in myriad fields of our society. Most compression systems employ an entropy coder in their coding pipeline to remove the redundancy of coded symbols. The entropy-coding stage needs to be efficient, to yield high compression ratios, and fast, to process large amounts of data rapidly. Despite their widespread use, entropy coders are commonly assessed for some particular scenario or coding system. This work provides a general framework to assess and optimize different entropy coders. First, the paper describes three main families of entropy coders, namely those based on variable-to-variable length codes (V2VLC), arithmetic coding (AC), and tabled asymmetric numeral systems (tANS). Then, a low-complexity architecture for the most representative coder(s) of each family is presented—more precisely, a general version of V2VLC, the MQ, M, and a fixed-length version of AC and two different implementations of tANS. These coders are evaluated under different coding conditions in terms of compression efficiency and computational throughput. The results obtained suggest that V2VLC and tANS achieve the highest compression ratios for most coding rates and that the AC coder that uses fixed-length codewords attains the highest throughput. The experimental evaluation discloses the advantages and shortcomings of each entropy-coding scheme, providing insights that may help to select this stage in forthcoming compression systems.","PeriodicalId":472933,"journal":{"name":"Technologies (Basel)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134960359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}