Journal Description
Technologies
Technologies
is an international, peer-reviewed, open access journal singularly focusing on emerging scientific and technological trends and is published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within ESCI (Web of Science), Scopus, Inspec, INSPIRE, and other databases.
- Journal Rank: CiteScore - Q1 (Computer Science (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.6 (2022);
5-Year Impact Factor:
3.1 (2022)
Latest Articles
Implementation of a Wireless Sensor Network for Environmental Measurements
Technologies 2024, 12(3), 41; https://doi.org/10.3390/technologies12030041 - 16 Mar 2024
Abstract
Nowadays, the need to monitor different physical variables is constantly increasing and can be used in different applications, from humidity monitoring to disease detection in living beings, using a local or wireless sensor network (WSN). The Internet of Things has become a valuable
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Nowadays, the need to monitor different physical variables is constantly increasing and can be used in different applications, from humidity monitoring to disease detection in living beings, using a local or wireless sensor network (WSN). The Internet of Things has become a valuable approach to climate monitoring, daily parcel monitoring, early disease detection, crop plant counting, and risk assessment. Herein, an autonomous energy wireless sensor network for monitoring environmental variables is proposed. The network’s tree topology configuration, which involves master and slave modules, is managed by microcontrollers embedded with sensors, constituting a key part of the WSN architecture. The system’s slave modules are equipped with sensors for temperature, humidity, gas, and light detection, along with a photovoltaic cell to energize the system, and a WiFi module for data transmission. The receiver incorporates a user interface and the necessary computing components for efficient data handling. In an open-field configuration, the transceiver range of the proposed system reaches up to 750 m per module. The advantages of this approach are its scalability, energy efficiency, and the system’s ability to provide real-time environmental monitoring over a large area, which is particularly beneficial for applications in precision agriculture and environmental management.
Full article
(This article belongs to the Special Issue Perpetual Sensor Nodes for Sustainable Wireless Network Applications)
Open AccessReview
Applications of 3D Reconstruction in Virtual Reality-Based Teleoperation: A Review in the Mining Industry
by
Alireza Kamran-Pishhesari, Amin Moniri-Morad and Javad Sattarvand
Technologies 2024, 12(3), 40; https://doi.org/10.3390/technologies12030040 - 15 Mar 2024
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Although multiview platforms have enhanced work efficiency in mining teleoperation systems, they also induce “cognitive tunneling” and depth-detection issues for operators. These issues inadvertently focus their attention on a restricted central view. Fully immersive virtual reality (VR) has recently attracted the attention of
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Although multiview platforms have enhanced work efficiency in mining teleoperation systems, they also induce “cognitive tunneling” and depth-detection issues for operators. These issues inadvertently focus their attention on a restricted central view. Fully immersive virtual reality (VR) has recently attracted the attention of specialists in the mining industry to address these issues. Nevertheless, developing VR teleoperation systems remains a formidable challenge, particularly in achieving a realistic 3D model of the environment. This study investigates the existing gap in fully immersive teleoperation systems within the mining industry, aiming to identify the most optimal methods for their development and ensure operator’s safety. To achieve this purpose, a literature search is employed to identify and extract information from the most relevant sources. The most advanced teleoperation systems are examined by focusing on their visualization types. Then, various 3D reconstruction techniques applicable to mining VR teleoperation are investigated, and their data acquisition methods, sensor technologies, and algorithms are analyzed. Ultimately, the study discusses challenges associated with 3D reconstruction techniques for mining teleoperation. The findings demonstrated that the real-time 3D reconstruction of underground mining environments primarily involves depth-based techniques. In contrast, point cloud generation techniques can mostly be employed for 3D reconstruction in open-pit mining operations.
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Open AccessArticle
Reinforcement-Learning-Based Virtual Inertia Controller for Frequency Support in Islanded Microgrids
by
Mohamed A. Afifi, Mostafa I. Marei and Ahmed M. I. Mohamad
Technologies 2024, 12(3), 39; https://doi.org/10.3390/technologies12030039 - 15 Mar 2024
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As the world grapples with the energy crisis, integrating renewable energy sources into the power grid has become increasingly crucial. Microgrids have emerged as a vital solution to this challenge. However, the reliance on renewable energy sources in microgrids often leads to low
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As the world grapples with the energy crisis, integrating renewable energy sources into the power grid has become increasingly crucial. Microgrids have emerged as a vital solution to this challenge. However, the reliance on renewable energy sources in microgrids often leads to low inertia. Renewable energy sources interfaced with the network through interlinking converters lack the inertia of conventional synchronous generators, and hence, need to provide frequency support through virtual inertia techniques. This paper presents a new control algorithm that utilizes the reinforcement learning agents Twin Delayed Deep Deterministic Policy Gradient (TD3) and Deep Deterministic Policy Gradient (DDPG) to support the frequency in low-inertia microgrids. The RL agents are trained using the system-linearized model and then extended to the nonlinear model to reduce the computational burden. The proposed system consists of an AC–DC microgrid comprising a renewable energy source on the DC microgrid, along with constant and resistive loads. On the AC microgrid side, a synchronous generator is utilized to represent the low inertia of the grid, which is accompanied by dynamic and static loads. The model of the system is developed and verified using Matlab/Simulink and the reinforcement learning toolbox. The system performance with the proposed AI-based methods is compared to conventional low-pass and high-pass filter (LPF and HPF) controllers.
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Open AccessReview
Examining the Landscape of Cognitive Fatigue Detection: A Comprehensive Survey
by
Enamul Karim, Hamza Reza Pavel, Sama Nikanfar, Aref Hebri, Ayon Roy, Harish Ram Nambiappan, Ashish Jaiswal, Glenn R. Wylie and Fillia Makedon
Technologies 2024, 12(3), 38; https://doi.org/10.3390/technologies12030038 - 11 Mar 2024
Abstract
Cognitive fatigue, a state of reduced mental capacity arising from prolonged cognitive activity, poses significant challenges in various domains, from road safety to workplace productivity. Accurately detecting and mitigating cognitive fatigue is crucial for ensuring optimal performance and minimizing potential risks. This paper
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Cognitive fatigue, a state of reduced mental capacity arising from prolonged cognitive activity, poses significant challenges in various domains, from road safety to workplace productivity. Accurately detecting and mitigating cognitive fatigue is crucial for ensuring optimal performance and minimizing potential risks. This paper presents a comprehensive survey of the current landscape in cognitive fatigue detection. We systematically review various approaches, encompassing physiological, behavioral, and performance-based measures, for robust and objective fatigue detection. The paper further analyzes different challenges, including the lack of standardized ground truth and the need for context-aware fatigue assessment. This survey aims to serve as a valuable resource for researchers and practitioners seeking to understand and address the multifaceted challenge of cognitive fatigue detection.
Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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Open AccessArticle
Pioneering a Framework for Robust Telemedicine Technology Assessment (Telemechron Study)
by
Sandra Morelli, Carla Daniele, Giuseppe D’Avenio, Mauro Grigioni and Daniele Giansanti
Technologies 2024, 12(3), 37; https://doi.org/10.3390/technologies12030037 - 08 Mar 2024
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The field of technology assessment in telemedicine is garnering increasing attention due to the widespread adoption of this discipline and its complex and heterogeneous system characteristics, making its application complex. As part of a national telemedicine project, the National Center for Innovative Technologies
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The field of technology assessment in telemedicine is garnering increasing attention due to the widespread adoption of this discipline and its complex and heterogeneous system characteristics, making its application complex. As part of a national telemedicine project, the National Center for Innovative Technologies in Public Health at the Italian National Institute of Health played the role of promoting and utilizing technology assessment tools within partnership projects. This study aims to outline the design, development, and application of assessment methodologies within the telemedicine project proposed by the ISS team, utilizing a specific framework developed within the project. The sub-objectives include evaluating the proposed methodology’s effectiveness and feasibility, gathering feedback for improvement, and assessing its impact on various project components. The study emphasizes the multifaceted nature of action domains and underscores the crucial role of technology assessments in telemedicine, highlighting its impact across diverse realms through iterative interaction cycles with project partners. Both the impact and the acceptance of the methodology have been assessed by means of specific computer-aided web interviewing (CAWI) tools. The proposed methodology received significant acceptance, providing valuable insights for refining future frameworks. The impact assessment revealed a consistent quality improvement trend in the project’s products, evident in methodological consolidations. The overall message encourages similar initiatives in this domain, shedding light on the intricacies of technology assessment implementation. In conclusion, the study serves as a comprehensive outcome of the national telemedicine project, witnessing the success and adaptability of the technology assessment methodology and advocating for further exploration and implementation in analogous contexts.
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Open AccessArticle
Energy Sustainability Indicators for the Use of Biomass as Fuel for the Sugar Industry
by
Reinier Jiménez Borges, Luis Angel Iturralde Carrera, Eduardo Julio Lopez Bastida, José R. García-Martínez, Roberto V. Carrillo-Serrano and Juvenal Rodríguez-Reséndiz
Technologies 2024, 12(3), 36; https://doi.org/10.3390/technologies12030036 - 08 Mar 2024
Abstract
There are numerous analytical and/or computational tools for evaluating the energetic sustainability of biomass in the sugar industry. However, the simultaneous integration of the energetic–exergetic and emergetic criteria for such evaluation is still insufficient. The objective of the present work is to propose
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There are numerous analytical and/or computational tools for evaluating the energetic sustainability of biomass in the sugar industry. However, the simultaneous integration of the energetic–exergetic and emergetic criteria for such evaluation is still insufficient. The objective of the present work is to propose a range of indicators to evaluate the sustainability of the use of biomass as fuel in the sugar industry. For this purpose, energy, exergy, and emergy evaluation tools were theoretically used as sustainability indicators. They were validated in five variants of different biomass and their mixtures in two studies of technologies used in Cuba for the sugar industry. As a result, the energy method showed, for all variants, an increase in efficiency of about 5% in the VU-40 technology compared to the Retal technology. There is an increase in energy efficiency when considering AHRs of 2.8% or Marabu (Dichrostachys cinerea) (5.3%) compared to the variant. Through the study of the exergetic efficiency, an increase of 2% was determined in both technologies for the case of the variant, and an increase in efficiency is observed in the variant of 5% and the variant (5.6%) over the variant. The emergetic method showed superior results for the VU-40 technology over the Retal technology due to higher fuel utilization. In the case of the variant, there was a 7% increase in the renewability ratio and an 11.07% increase in the sustainability index. This is because more energy is produced per unit of environmental load.
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(This article belongs to the Section Environmental Technology)
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Open AccessCommunication
A 28 GHz Highly Linear Up-Conversion Mixer for 5G Cellular Communications
by
Chul-Woo Byeon
Technologies 2024, 12(3), 35; https://doi.org/10.3390/technologies12030035 - 07 Mar 2024
Abstract
In this paper, we present a highly linear direct in-phase/quadrature (I/Q) up-conversion mixer for 5G millimeter-wave applications. To enhance the linearity of the mixer, we propose a complementary derivative superposition technique with pre-distortion. The proposed up-conversion mixer consists of a quadrature generator, LO
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In this paper, we present a highly linear direct in-phase/quadrature (I/Q) up-conversion mixer for 5G millimeter-wave applications. To enhance the linearity of the mixer, we propose a complementary derivative superposition technique with pre-distortion. The proposed up-conversion mixer consists of a quadrature generator, LO buffer amplifiers, and an I/Q up-conversion mixer core and achieves an output third-order intercept point of 15.7 dBm and an output 1 dB compression point of 2 dBm at 27.6 GHz, while it consumes 15 mW at a supply voltage of 1 V. The conversion gain is 11.4 dB and the LO leakage and image rejection ratio are −56 dBc and 61 dB, respectively, in the measurement. The proposed I/Q up-conversion mixer is suitable for 5G cellular communication systems.
Full article
(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G and Beyond Volume II)
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Open AccessArticle
Reinforcement Learning as an Approach to Train Multiplayer First-Person Shooter Game Agents
by
Pedro Almeida, Vítor Carvalho and Alberto Simões
Technologies 2024, 12(3), 34; https://doi.org/10.3390/technologies12030034 - 05 Mar 2024
Abstract
Artificial Intelligence bots are extensively used in multiplayer First-Person Shooter (FPS) games. By using Machine Learning techniques, we can improve their performance and bring them to human skill levels. In this work, we focused on comparing and combining two Reinforcement Learning training architectures,
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Artificial Intelligence bots are extensively used in multiplayer First-Person Shooter (FPS) games. By using Machine Learning techniques, we can improve their performance and bring them to human skill levels. In this work, we focused on comparing and combining two Reinforcement Learning training architectures, Curriculum Learning and Behaviour Cloning, applied to an FPS developed in the Unity Engine. We have created four teams of three agents each: one team for Curriculum Learning, one for Behaviour Cloning, and another two for two different methods of combining Curriculum Learning and Behaviour Cloning. After completing the training, each agent was matched to battle against another agent of a different team until each pairing had five wins or ten time-outs. In the end, results showed that the agents trained with Curriculum Learning achieved better performance than the ones trained with Behaviour Cloning by a matter of 23.67% more average victories in one case. In terms of the combination attempts, not only did the agents trained with both devised methods had problems during training, but they also achieved insufficient results in the battle, with an average of 0 wins.
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(This article belongs to the Section Information and Communication Technologies)
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Open AccessArticle
A Comparison between Kinematic Models for Robotic Needle Insertion with Application into Transperineal Prostate Biopsy
by
Chiara Zandonà, Andrea Roberti, Davide Costanzi, Burçin Gül, Özge Akbulut, Paolo Fiorini and Andrea Calanca
Technologies 2024, 12(3), 33; https://doi.org/10.3390/technologies12030033 - 01 Mar 2024
Abstract
Transperineal prostate biopsy is the most reliable technique for detecting prostate cancer, and robot-assisted needle insertion has the potential to improve the accuracy of this procedure. Modeling the interaction between a bevel-tip needle and the tissue, considering tissue heterogeneity, needle bending, and tissue/organ
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Transperineal prostate biopsy is the most reliable technique for detecting prostate cancer, and robot-assisted needle insertion has the potential to improve the accuracy of this procedure. Modeling the interaction between a bevel-tip needle and the tissue, considering tissue heterogeneity, needle bending, and tissue/organ deformation and movement is a required step to enable robotic needle insertion. Even if several models exist, they have never been compared on experimental grounds. Based on this motivation, this paper proposes an experimental comparison for kinematic models of needle insertion, considering different needle insertion speeds and different degrees of tissue stiffness. The experimental comparison considers automated insertions of needles into transparent silicone phantoms under stereo-image guidance. The comparison evaluates the accuracy of existing models in predicting needle deformation.
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(This article belongs to the Topic Smart Healthcare: Technologies and Applications)
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Open AccessArticle
Measurement of Light-Duty Vehicle Exhaust Emissions with Light Absorption Spectrometers
by
Barouch Giechaskiel, Anastasios Melas, Jacopo Franzetti, Victor Valverde, Michaël Clairotte and Ricardo Suarez-Bertoa
Technologies 2024, 12(3), 32; https://doi.org/10.3390/technologies12030032 - 28 Feb 2024
Abstract
Light-duty vehicle emission regulations worldwide set limits for the following gaseous pollutants: carbon monoxide (CO), nitric oxides (NOX), hydrocarbons (HCs), and/or non-methane hydrocarbons (NMHCs). Carbon dioxide (CO2) is indirectly limited by fleet CO2 or fuel consumption targets. Measurements
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Light-duty vehicle emission regulations worldwide set limits for the following gaseous pollutants: carbon monoxide (CO), nitric oxides (NOX), hydrocarbons (HCs), and/or non-methane hydrocarbons (NMHCs). Carbon dioxide (CO2) is indirectly limited by fleet CO2 or fuel consumption targets. Measurements are carried out at the dilution tunnel with “standard” laboratory-grade instruments following well-defined principles of operation: non-dispersive infrared (NDIR) analyzers for CO and CO2, flame ionization detectors (FIDs) for hydrocarbons, and chemiluminescence analyzers (CLAs) or non-dispersive ultraviolet detectors (NDUVs) for NOX. In the United States in 2012 and in China in 2020, with Stage 6, nitrous oxide (N2O) was also included. Brazil is phasing in NH3 in its regulation. Alternative instruments that can measure some or all these pollutants include Fourier transform infrared (FTIR)- and laser absorption spectroscopy (LAS)-based instruments. In the second category, quantum cascade laser (QCL) spectroscopy in the mid-infrared area or laser diode spectroscopy (LDS) in the near-infrared area, such as tunable diode laser absorption spectroscopy (TDLAS), are included. According to current regulations and technical specifications, NH3 is the only component that has to be measured at the tailpipe to avoid ammonia losses due to its hydrophilic properties and adsorption on the transfer lines. There are not many studies that have evaluated such instruments, in particular those for “non-regulated” worldwide pollutants. For this reason, we compared laboratory-grade “standard” analyzers with FTIR- and TDLAS-based instruments measuring NH3. One diesel and two gasoline vehicles at different ambient temperatures and with different test cycles produced emissions in a wide range. In general, the agreement among the instruments was very good (in most cases, within ±10%), confirming their suitability for the measurement of pollutants.
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(This article belongs to the Section Environmental Technology)
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Open AccessReview
Visualization of Spatial–Temporal Epidemiological Data: A Scoping Review
by
Denisse Kim, Bernardo Cánovas-Segura, Manuel Campos and Jose M. Juarez
Technologies 2024, 12(3), 31; https://doi.org/10.3390/technologies12030031 - 28 Feb 2024
Abstract
In recent years, the proliferation of health data sources due to computer technologies has prompted the use of visualization techniques to tackle epidemiological challenges. However, existing reviews lack a specific focus on the spatial and temporal analysis of epidemiological data using visualization tools.
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In recent years, the proliferation of health data sources due to computer technologies has prompted the use of visualization techniques to tackle epidemiological challenges. However, existing reviews lack a specific focus on the spatial and temporal analysis of epidemiological data using visualization tools. This study aims to address this gap by conducting a scoping review following the PRISMA-ScR guidelines, examining the literature from 2000 to 2024 on spatial–temporal visualization techniques when applied to epidemics, across five databases: PubMed, IEEE Xplore, Scopus, Google Scholar, and ACM Digital Library until 24 January 2024. Among 1312 papers reviewed, 114 were selected, emphasizing aggregate measures, web platform tools, and geospatial data representation, particularly favoring choropleth maps and extended charts. Visualization techniques were predominantly utilized for real-time data presentation, trend analysis, and predictions. Evaluation methods, categorized into standard methodology, user experience, task efficiency, and accuracy, were observed. Although various open-access datasets were available, only a few were commonly used, mainly those related to COVID-19. This study sheds light on the current trends in visualizing epidemiological data over the past 24 years, highlighting the gaps in standardized evaluation methodologies and the limited exploration of individual epidemiological data and diseases acquired in hospitals during epidemics.
Full article
(This article belongs to the Section Information and Communication Technologies)
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Open AccessArticle
Mapping Acoustic Frictional Properties of Self-Lubricating Epoxy-Coated Bearing Steel with Acoustic Emissions during Friction Test
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Venkatasubramanian Krishnamoorthy, Ashvita Anitha John, Shubrajit Bhaumik and Viorel Paleu
Technologies 2024, 12(3), 30; https://doi.org/10.3390/technologies12030030 - 24 Feb 2024
Abstract
This work investigates the stick–slip phenomenon during sliding motion between solid lubricant-impregnated epoxy polymer-coated steel bars and AISI 52,100 steel balls. An acoustic sensor detected the stick–slip phenomenon during the tribo-pair interaction. The wear characteristics of the workpiece coated with different epoxy coatings
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This work investigates the stick–slip phenomenon during sliding motion between solid lubricant-impregnated epoxy polymer-coated steel bars and AISI 52,100 steel balls. An acoustic sensor detected the stick–slip phenomenon during the tribo-pair interaction. The wear characteristics of the workpiece coated with different epoxy coatings were observed and scrutinized. The RMS values of the acoustic sensor were correlated with the frictional coefficient to develop a standard based on the acoustic sensor, leading to the detection of the stick–slip phenomenon. As per the findings, the acoustic waveform remained relatively similar to the friction coefficient observed during the study and can be used effectively in detecting the stick–slip phenomenon between steel and polymer interaction. This work will be highly beneficial in industrial and automotive applications with a significant interaction of polymer and steel surfaces.
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(This article belongs to the Section Manufacturing Technology)
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Open AccessArticle
A Kinetic Study of a Photo-Oxidation Reaction between α-Terpinene and Singlet Oxygen in a Novel Oscillatory Baffled Photo Reactor
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Jianhan Chen, Rohen Prinsloo and Xiongwei Ni
Technologies 2024, 12(3), 29; https://doi.org/10.3390/technologies12030029 - 21 Feb 2024
Abstract
By planting LEDs on the surfaces of orifice baffles, a novel batch oscillatory baffled photoreactor (OBPR) together with polymer-supported Rose Bengal (Ps-RB) beads are here used to investigate the reaction kinetics of a photo-oxidation reaction between α-terpinene and singlet oxygen (1O
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By planting LEDs on the surfaces of orifice baffles, a novel batch oscillatory baffled photoreactor (OBPR) together with polymer-supported Rose Bengal (Ps-RB) beads are here used to investigate the reaction kinetics of a photo-oxidation reaction between α-terpinene and singlet oxygen (1O2). In the mode of NMR data analysis that is widely used for this reaction, α-terpinene and ascaridole are treated as a reaction pair, assuming kinetically singlet oxygen is in excess or constant. We have, for the first time, here examined the validity of the method, discovered that increasing α-terpinene initially leads to an increase in ascaridole, indicating that the supply of singlet oxygen is in excess. Applying a kinetic analysis, a pseudo-first-order reaction kinetics is confirmed, supporting this assumption. We have subsequently initiated a methodology of estimating the 1O2 concentrations based on the proportionality of ascaridole concentrations with respect to its maximum under these conditions. With the help of the estimated singlet oxygen data, the efficiency of 1O2 utilization and the photo efficiency of converting molecular oxygen to 1O2 are further proposed and evaluated. We have also identified conditions under which a further increase in α-terpinene has caused decreases in ascaridole, implying kinetically that 1O2 has now become a limiting reagent, and the method of treating α-terpinene and ascaridole as a reaction pair in the data analysis would no longer be valid under those conditions.
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(This article belongs to the Topic Smart Manufacturing and Industry 5.0)
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Open AccessArticle
Nested Contrastive Boundary Learning: Point Transformer Self-Attention Regularization for 3D Intracranial Aneurysm Segmentation
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Luis Felipe Estrella-Ibarra, Alejandro de León-Cuevas and Saul Tovar-Arriaga
Technologies 2024, 12(3), 28; https://doi.org/10.3390/technologies12030028 - 21 Feb 2024
Abstract
In 3D segmentation, point-based models excel but face difficulties in precise class delineation at class intersections, an inherent challenge in segmentation models. This is particularly critical in medical applications, influencing patient care and surgical planning, where accurate 3D boundary identification is essential for
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In 3D segmentation, point-based models excel but face difficulties in precise class delineation at class intersections, an inherent challenge in segmentation models. This is particularly critical in medical applications, influencing patient care and surgical planning, where accurate 3D boundary identification is essential for assisting surgery and enhancing medical training through advanced simulations. This study introduces the Nested Contrastive Boundary Learning Point Transformer (NCBL-PT), specially designed for 3D point cloud segmentation. NCBL-PT employs contrastive learning to improve boundary point representation by enhancing feature similarity within the same class. NCBL-PT incorporates a border-aware distinction within the same class points, allowing the model to distinctly learn from both points in proximity to the class intersection and from those beyond. This reduces semantic confusion among the points of different classes in the ambiguous class intersection zone, where similarity in features due to proximity could lead to incorrect associations. The model operates within subsampled point clouds at each encoder block stage of the point transformer architecture. It applies self-attention with k = 16 nearest neighbors to local neighborhoods, aligning with NCBL calculations for consistent self-attention regularization in local contexts. NCBL-PT improves 3D segmentation at class intersections, as evidenced by a 3.31% increase in Intersection over Union (IOU) for aneurysm segmentation compared to the base point transformer model.
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(This article belongs to the Section Assistive Technologies)
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Open AccessCommunication
ARSIP: Automated Robotic System for Industrial Painting
by
Hossam A. Gabbar and Muhammad Idrees
Technologies 2024, 12(2), 27; https://doi.org/10.3390/technologies12020027 - 19 Feb 2024
Abstract
This manuscript addresses the critical need for precise paint application to ensure product durability and aesthetics. While manual work carries risks, robotic systems promise accuracy, yet programming diverse product trajectories remains a challenge. This study aims to develop an autonomous system capable of
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This manuscript addresses the critical need for precise paint application to ensure product durability and aesthetics. While manual work carries risks, robotic systems promise accuracy, yet programming diverse product trajectories remains a challenge. This study aims to develop an autonomous system capable of generating paint trajectories based on object geometries for user-defined spraying processes. By emphasizing energy efficiency, process time, and coating thickness on complex surfaces, a hybrid optimization technique enhances overall efficiency. Extensive hardware and software development results in a robust robotic system leveraging the Robot Operating System (ROS). Integrating a low-cost 3D scanner, calibrator, and trajectory optimizer creates an autonomous painting system. Hardware components, including sensors, motors, and actuators, are seamlessly integrated with a Python and ROS-based software framework, enabling the desired automation. A web-based GUI, powered by JavaScript, allows user control over two robots, facilitating trajectory dispatch, 3D scanning, and optimization. Specific nodes manage calibration, validation, process settings, and real-time video feeds. The use of open-source software and an ROS ecosystem makes it a good choice for industrial-scale implementation. The results indicate that the proposed system can achieve the desired automation, contingent upon surface geometries, spraying processes, and robot dynamics.
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(This article belongs to the Section Assistive Technologies)
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Open AccessArticle
A National Innovation System Concept-Based Analysis of Autonomous Vehicles’ Potential in Reaching Zero-Emission Fleets
by
Nalina Hamsaiyni Venkatesh and Laurencas Raslavičius
Technologies 2024, 12(2), 26; https://doi.org/10.3390/technologies12020026 - 08 Feb 2024
Abstract
Change management for technology adoption in the transportation sector is often used to address long-term challenges characterized by complexity, uncertainty, and ambiguity. Especially when technology is still evolving, an analysis of these challenges can help explore different alternative future pathways. Therefore, the analysis
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Change management for technology adoption in the transportation sector is often used to address long-term challenges characterized by complexity, uncertainty, and ambiguity. Especially when technology is still evolving, an analysis of these challenges can help explore different alternative future pathways. Therefore, the analysis of development trajectories, correlations between key system variables, and the rate of change within the entire road transportation system can guide action toward sustainability. By adopting the National Innovation System concept, we evaluated the possibilities of an autonomous vehicle option to reach a zero-emission fleet. A case-specific analysis was conducted to evaluate the industry capacities, performance of R&D organizations, main objectives of future market-oriented reforms in the power sector, policy implications, and other aspects to gain insightful perspectives. Environmental insights for transportation sector scenarios in 2021, 2030, and 2050 were explored and analyzed using the COPERT v5.5.1 software program. This study offers a new perspective for road transport decarbonization research and adds new insights to the obtained correlation between the NIS dynamics and achievement of sustainability goals. In 2050, it is expected to achieve 100% carbon neutrality in the PC segment and ~85% in the HDV segment. Finally, four broad conclusions emerged from this research as a consequence of the analysis.
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(This article belongs to the Section Environmental Technology)
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Open AccessCommunication
Exploiting PlanetScope Imagery for Volcanic Deposits Mapping
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Maddalena Dozzo, Gaetana Ganci, Federico Lucchi and Simona Scollo
Technologies 2024, 12(2), 25; https://doi.org/10.3390/technologies12020025 - 08 Feb 2024
Abstract
During explosive eruptions, tephra fallout represents one of the main volcanic hazards and can be extremely dangerous for air traffic, infrastructures, and human health. Here, we present a new technique aimed at identifying the area covered by tephra after an explosive event, based
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During explosive eruptions, tephra fallout represents one of the main volcanic hazards and can be extremely dangerous for air traffic, infrastructures, and human health. Here, we present a new technique aimed at identifying the area covered by tephra after an explosive event, based on processing PlanetScope imagery. We estimate the mean reflectance values of the visible (RGB) and near infrared (NIR) bands, analyzing pre- and post-eruptive data in specific areas and introducing a new index, which we call the ‘Tephra Fallout Index (TFI)’. We use the Google Earth Engine computing platform and define a threshold for the TFI of different eruptive events to distinguish the areas affected by the tephra fallout and quantify the surface coverage density. We apply our technique to the eruptive events occurring in 2021 at Mt. Etna (Italy), which mainly involved the eastern flank of the volcano, sometimes two or three times within a day, making field surveys difficult. Whenever possible, we compare our results with field data and find an optimal match. This work could have important implications for the identification and quantification of short-term volcanic hazard assessments in near real-time during a volcanic eruption, but also for the mapping of other hazardous events worldwide.
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(This article belongs to the Special Issue Image and Signal Processing)
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Open AccessCommunication
High Affinity of Nanoparticles and Matrices Based on Acid-Base Interaction for Nanoparticle-Filled Membrane
by
Tsutomu Makino, Keisuke Tabata, Takaaki Saito, Yosimasa Matsuo and Akito Masuhara
Technologies 2024, 12(2), 24; https://doi.org/10.3390/technologies12020024 - 07 Feb 2024
Abstract
The introduction of nanoparticles into the polymer matrix is a useful technique for creating highly functional composite membranes. Our research focuses on the development of nanoparticle-filled proton exchange membranes (PEMs). PEMs play a crucial role in efficiently controlling the electrical energy conversion process
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The introduction of nanoparticles into the polymer matrix is a useful technique for creating highly functional composite membranes. Our research focuses on the development of nanoparticle-filled proton exchange membranes (PEMs). PEMs play a crucial role in efficiently controlling the electrical energy conversion process by facilitating the movement of specific ions. This is achieved by creating functionalized nanoparticles with polymer coatings on their surfaces, which are then combined with resins to create proton-conducting membranes. In this study, we prepared PEMs by coating the surfaces of silica nanoparticles with acidic polymers and integrating them into a basic matrix. This process resulted in the formation of a direct bond between the nanoparticles and the matrix, leading to composite membranes with a high dispersion and densely packed nanoparticles. This fabrication technique significantly improved mechanical strength and retention stability, resulting in high-performance membranes. Moreover, the proton conductivity of these membranes showed a remarkable enhancement of more than two orders of magnitude compared to the pristine basic matrix, reaching 4.2 × 10−4 S/cm at 80 °C and 95% relative humidity.
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(This article belongs to the Special Issue Smart Systems (SmaSys2023))
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Multistage Malware Detection Method for Backup Systems
by
Pavel Novak, Vaclav Oujezsky, Patrik Kaura, Tomas Horvath and Martin Holik
Technologies 2024, 12(2), 23; https://doi.org/10.3390/technologies12020023 - 05 Feb 2024
Abstract
This paper proposes an innovative solution to address the challenge of detecting latent malware in backup systems. The proposed detection system utilizes a multifaceted approach that combines similarity analysis with machine learning algorithms to improve malware detection. The results demonstrate the potential of
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This paper proposes an innovative solution to address the challenge of detecting latent malware in backup systems. The proposed detection system utilizes a multifaceted approach that combines similarity analysis with machine learning algorithms to improve malware detection. The results demonstrate the potential of advanced similarity search techniques, powered by the Faiss model, in strengthening malware discovery within system backups and network traffic. Implementing these techniques will lead to more resilient cybersecurity practices, protecting essential systems from hidden malware threats. This paper’s findings underscore the potential of advanced similarity search techniques to enhance malware discovery in system backups and network traffic, and the implications of implementing these techniques include more resilient cybersecurity practices and protecting essential systems from malicious threats hidden within backup archives and network data. The integration of AI methods improves the system’s efficiency and speed, making the proposed system more practical for real-world cybersecurity. This paper’s contribution is a novel and comprehensive solution designed to detect latent malware in backups, preventing the backup of compromised systems. The system comprises multiple analytical components, including a system file change detector, an agent to monitor network traffic, and a firewall, all integrated into a central decision-making unit. The current progress of the research and future steps are discussed, highlighting the contributions of this project and potential enhancements to improve cybersecurity practices.
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(This article belongs to the Section Information and Communication Technologies)
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Angle Calculus-Based Thrust Force Determination on the Blades of a 10 kW Wind Turbine
by
José Rafael Dorrego-Portela, Adriana Eneida Ponce-Martínez, Eduardo Pérez-Chaltell, Jaime Peña-Antonio, Carlos Alberto Mateos-Mendoza, José Billerman Robles-Ocampo, Perla Yazmin Sevilla-Camacho, Marcos Aviles and Juvenal Rodríguez-Reséndiz
Technologies 2024, 12(2), 22; https://doi.org/10.3390/technologies12020022 - 05 Feb 2024
Abstract
In this article, the behavior of the thrust force on the blades of a 10 kW wind turbine was obtained by considering the characteristic wind speed of the Isthmus of Tehuantepec. Analyzing mechanical forces is essential to efficiently and safely design the different
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In this article, the behavior of the thrust force on the blades of a 10 kW wind turbine was obtained by considering the characteristic wind speed of the Isthmus of Tehuantepec. Analyzing mechanical forces is essential to efficiently and safely design the different elements that make up the wind turbine because the thrust forces are related to the location point and the blade rotation. For this reason, the thrust force generated in each of the three blades of a low-power wind turbine was analyzed. The angular position ( ) of each blade varied from 0° to 120°, the blades were segmented (r), and different wind speeds were tested, such as cutting, design, average, and maximum. The results demonstrate that the thrust force increases proportionally with increasing wind speed and height, but it behaves differently on each blade segment and each angular position. This method determines the angular position and the exact blade segment where the smallest and the most considerable thrust force occurred. Blade 1, positioned at an angular position of 90°, is the blade most affected by the thrust force on P15. When the blade rotates 180°, the thrust force decreases by 9.09 N; this represents a 66.74% decrease. In addition, this study allows the designers to know the blade deflection caused by the thrust force. This information can be used to avoid collision with the tower. The thrust forces caused blade deflections of 10% to 13% concerning the rotor radius used in this study. These results guarantee the operation of the tested generator under their working conditions.
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(This article belongs to the Collection Electrical Technologies)
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