Applied Sciences

15 pages, 2294 KiB

Open AccessArticle

Securing SCADA Energy Management System under DDos Attacks Using Token Verification Approach

by Yu-Sheng Yang, Shih-Hsiung Lee, Wei-Che Chen, Chu-Sing Yang, Yuen-Min Huang and Ting-Wei Hou

Appl. Sci. 2022, 12(1), 530; https://doi.org/10.3390/app12010530 - 05 Jan 2022

Cited by 13 | Viewed by 5120

The advanced connection requirements of industrial automation and control systems have sparked a new revolution in the Industrial Internet of Things (IIoT), and the Supervisory Control and Data Acquisition (SCADA) network has evolved into an open and highly interconnected network. In addition, the [...] Read more.

The advanced connection requirements of industrial automation and control systems have sparked a new revolution in the Industrial Internet of Things (IIoT), and the Supervisory Control and Data Acquisition (SCADA) network has evolved into an open and highly interconnected network. In addition, the equipment of industrial electronic devices has experienced complete systemic integration by connecting with the SCADA network, and due to the control and monitoring advantages of SCADA, the interconnectivity and working efficiency among systems have been tremendously improved. However, it is inevitable that the SCADA system cannot be separated from the public network, which indicates that there are concerns over cyber-attacks and cyber-threats, as well as information security breaches, in the SCADA network system. According to this context, this paper proposes a module based on the token authentication service to deter attackers from performing distributed denial-of-service (DDoS) attacks. Moreover, a simulated experiment has been conducted in an energy management system in the actual field, and the experimental results have suggested that the security defense architecture proposed by this paper can effectively improve security and is compatible with real field systems. Full article

(This article belongs to the Special Issue New Security and Privacy Challenges in Industrial Internet of Things)

► Show Figures

Figure 1

14 pages, 1670 KiB

Open AccessArticle

Optimal Route Planning for Truck–Drone Delivery Using Variable Neighborhood Tabu Search Algorithm

by Bao Tong, Jianwei Wang, Xue Wang, Feihao Zhou, Xinhua Mao and Wenlong Zheng

Appl. Sci. 2022, 12(1), 529; https://doi.org/10.3390/app12010529 - 05 Jan 2022

Cited by 14 | Viewed by 3524

Abstract

The optimal delivery route problem for truck–drone delivery is defined as a traveling salesman problem with drone (TSP-D), which has been studied in a wide range of previous literature. However, most of the existing studies ignore truck waiting time at rendezvous points. To [...] Read more.

The optimal delivery route problem for truck–drone delivery is defined as a traveling salesman problem with drone (TSP-D), which has been studied in a wide range of previous literature. However, most of the existing studies ignore truck waiting time at rendezvous points. To fill this gap, this paper builds a mixed integer nonlinear programming model subject to time constraints and route constraints, aiming to minimize the total delivery time. Since the TSP-D is non-deterministic polynomial-time hard (NP-hard), the proposed model is solved by the variable neighborhood tabu search algorithm, where the neighborhood structure is changed by point exchange and link exchange to expand the tabu search range. A delivery network with 1 warehouse and 23 customer points are employed as a case study to verify the effectiveness of the model and algorithm. The 23 customer points are visited by three truck–drones. The results indicate that truck–drone delivery can effectively reduce the total delivery time by 20.1% compared with traditional pure-truck delivery. Sensitivity analysis of different parameters shows that increasing the number of truck–drones can effectively save the total delivery time, but gradually reduce the marginal benefits. Only increasing either the truck speed or drone speed can reduce the total delivery time, but not to the greatest extent. Bilateral increase of truck speed and drone speed can minimize the delivery time. It can clearly be seen that the proposed method can effectively optimize the truck–drone delivery route and improve the delivery efficiency. Full article

(This article belongs to the Special Issue Advances in Capacitated Vehicle Routing Problem—Models, Methods, Applications and New Challenges)

► Show Figures

Figure 1

14 pages, 4122 KiB

Open AccessArticle

An Ultra-Wideband Vivaldi Antenna System for Long-Distance Electromagnetic Detection

by Jinjing Ren, Hezhihan Fan, Qi Tang, Zhongyuan Yu, Yang Xiao and Xiang Zhou

Appl. Sci. 2022, 12(1), 528; https://doi.org/10.3390/app12010528 - 05 Jan 2022

Cited by 8 | Viewed by 3648

Abstract

Enlarging or reducing the antenna beam width of antennas can improve the positioning capability of detection systems. A miniaturized and easily fabricated ultra-wideband (UWB) antenna system for long-distance electromagnetic detection is proposed in this article. Two ultra-wideband Vivaldi antennae were designed. One was [...] Read more.

Enlarging or reducing the antenna beam width of antennas can improve the positioning capability of detection systems. A miniaturized and easily fabricated ultra-wideband (UWB) antenna system for long-distance electromagnetic detection is proposed in this article. Two ultra-wideband Vivaldi antennae were designed. One was the transmitting antenna with a beam width of 90° or above, the other was a narrow beam antenna array with beam width less than 10°, as a receiving antenna. Both proposed antennae feature broadside gain diagrams with stable radiation patterns and wideband impedance matching in the frequency range between 2.5 GHz and 4 GHz. After detecting their frequency and time-domain behaviors, the detection system can achieve measurements covering a radius of 30 m. Full article

(This article belongs to the Special Issue Microwave/Millimeter Wave Circuits and Systems for Emerging Wireless Applications)

► Show Figures

Figure 1

24 pages, 1285 KiB

Open AccessArticle

Data Augmentation for Audio-Visual Emotion Recognition with an Efficient Multimodal Conditional GAN

by Fei Ma, Yang Li, Shiguang Ni, Shao-Lun Huang and Lin Zhang

Appl. Sci. 2022, 12(1), 527; https://doi.org/10.3390/app12010527 - 05 Jan 2022

Cited by 28 | Viewed by 4707

Abstract

Audio-visual emotion recognition is the research of identifying human emotional states by combining the audio modality and the visual modality simultaneously, which plays an important role in intelligent human-machine interactions. With the help of deep learning, previous works have made great progress for [...] Read more.

Audio-visual emotion recognition is the research of identifying human emotional states by combining the audio modality and the visual modality simultaneously, which plays an important role in intelligent human-machine interactions. With the help of deep learning, previous works have made great progress for audio-visual emotion recognition. However, these deep learning methods often require a large amount of data for training. In reality, data acquisition is difficult and expensive, especially for the multimodal data with different modalities. As a result, the training data may be in the low-data regime, which cannot be effectively used for deep learning. In addition, class imbalance may occur in the emotional data, which can further degrade the performance of audio-visual emotion recognition. To address these problems, we propose an efficient data augmentation framework by designing a multimodal conditional generative adversarial network (GAN) for audio-visual emotion recognition. Specifically, we design generators and discriminators for audio and visual modalities. The category information is used as their shared input to make sure our GAN can generate fake data of different categories. In addition, the high dependence between the audio modality and the visual modality in the generated multimodal data is modeled based on Hirschfeld-Gebelein-Rényi (HGR) maximal correlation. In this way, we relate different modalities in the generated data to approximate the real data. Then, the generated data are used to augment our data manifold. We further apply our approach to deal with the problem of class imbalance. To the best of our knowledge, this is the first work to propose a data augmentation strategy with a multimodal conditional GAN for audio-visual emotion recognition. We conduct a series of experiments on three public multimodal datasets, including eNTERFACE’05, RAVDESS, and CMEW. The results indicate that our multimodal conditional GAN has high effectiveness for data augmentation of audio-visual emotion recognition. Full article

► Show Figures

Figure 1

17 pages, 5622 KiB

Open AccessEditor’s ChoiceArticle

Effect of Rice Straw on Tensile Properties of Tailings Cemented Paste Backfill

by Zeyu Li, Xiuzhi Shi and Xin Chen

Appl. Sci. 2022, 12(1), 526; https://doi.org/10.3390/app12010526 - 05 Jan 2022

Cited by 6 | Viewed by 2702

Abstract

It is important and difficult to improve the tensile strength of backfill material to ensure the stability of goafs. In this study, rice straw (RS) in fiber form is used to improve the tensile properties of cemented paste backfill (CPB). An orthogonal experiment [...] Read more.

It is important and difficult to improve the tensile strength of backfill material to ensure the stability of goafs. In this study, rice straw (RS) in fiber form is used to improve the tensile properties of cemented paste backfill (CPB). An orthogonal experiment was designed, Brazilian indirect tensile strength tests were conducted to test the tensile performance of RS fiber-reinforced cemented paste backfill (RSCPB) under different fiber content (1, 2, 3 kg/m³) and fiber length (0.8~1, 1~3, 3~5 cm), and the microstructure of RSCPB was analyzed with scanning electron microscopy (SEM). The results showed that, compared with the conventional cemented paste backfill (CCPB), the increase in tensile strength of RSCPB ranged from 115.38% to 300.00% at 3 days curing age, 40.91% to 346.15% at 7 days, and −38.10% to 28.00% at 28 days, and the strain was slightly reduced during the curing period. The tensile strength, strain, and percentage increase of the RSCPB compared to the CCBP did not show a monotonic pattern of variation with the RS fiber content and length during the curing period. The RSCPB samples fractured under peak stress, showing obvious brittle failure. In addition, sulfate generated from S²⁻ in the tailings inhibits the hydration reaction, and generates swelling products that form weak structural surfaces, which, in turn, lead to a 28-day tensile strength and strain of RSCPB lower than those at 7 days. Full article

(This article belongs to the Special Issue Research and Enhancement of Mechanical Properties of Cementitious Materials)

► Show Figures

Figure 1

16 pages, 32764 KiB

Open AccessArticle

Negotiating Uneven Terrain by a Simple Teleoperated Tracked Vehicle with Internally Movable Center of Gravity

by Yasuhiro Fukuoka, Kazuyuki Oshino and Ahmad Najmuddin Ibrahim

Appl. Sci. 2022, 12(1), 525; https://doi.org/10.3390/app12010525 - 05 Jan 2022

Cited by 4 | Viewed by 2603

Abstract

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs [...] Read more.

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs at appropriate trajectories, stepping over a high obstacle. To realize a COG movable mechanism with a small number of joints, a number of UGVs have been developed that can shift their COG by moving a mass at a high position above the body. However, these tend to pose a risk of overturning, and the mass must be moved quite far to climb a high step. To address these issues, we design a novel COG shift mechanism, in which the COG can be shifted forward and backward inside the body by moving most of its internal devices. Since this movable mass includes DC motors for driving both tracks, we can extend the range of the COG movement. We demonstrate that a conventional tracked vehicle prototype can traverse a step and a gap between two steps, as well as climb stairs and a steep slope, with a human operating the vehicle movement and the movable mass position. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

► Show Figures

Figure 1

21 pages, 5303 KiB

Open AccessArticle

Mix Design and Engineering Properties of Fiber-Reinforced Pervious Concrete Using Lightweight Aggregates

by Chao-Wei Tang, Chiu-Kuei Cheng and Lee-Woen Ean

Appl. Sci. 2022, 12(1), 524; https://doi.org/10.3390/app12010524 - 05 Jan 2022

Cited by 12 | Viewed by 2635

Abstract

The main purpose of this study was to investigate the mix design and performance of fiber-reinforced pervious concrete using lightweight coarse aggregates instead of ordinary coarse aggregates. There were two main stages in the relevant testing work. First, the properties of the matrix [...] Read more.

The main purpose of this study was to investigate the mix design and performance of fiber-reinforced pervious concrete using lightweight coarse aggregates instead of ordinary coarse aggregates. There were two main stages in the relevant testing work. First, the properties of the matrix were tested with a rheological test and then different amounts of lightweight coarse aggregate and fine aggregate were added to the matrix to measure the properties of the obtained lightweight pervious concrete (LPC). In order to greatly reduce the experimental workload, the Taguchi experimental design method was adopted. An orthogonal array L₉(3⁴) was used, which was composed of four controllable three-level factors. There were four test parameters in this study, which were the lightweight coarse aggregate size, ordinary fine aggregate content, matrix type, and aggregate/binder ratio. The research results confirmed that the use of suitable materials and the optimal mix proportions were the key factors for improving the mechanical properties of the LPC. Due to the use of silica fume, ultrafine silica powder, and polypropylene fibers, the 28-day compressive strength, 28-day flexural strength, and 28-day split tensile strength of the LPC specimens prepared in this study were 4.80–7.78, 1.19–1.86, and 0.78–1.11 MPa, respectively. On the whole, the mechanical properties of the prepared LPC specimens were better than those of the LPC with general composition. Full article

(This article belongs to the Special Issue Advances in High-Performance Fiber-Reinforced Concrete)

► Show Figures

Figure 1

28 pages, 6285 KiB

Open AccessArticle

Indoor-Guided Navigation for People Who Are Blind: Crowdsourcing for Route Mapping and Assistance

by Darius Plikynas, Audrius Indriulionis, Algirdas Laukaitis and Leonidas Sakalauskas

Appl. Sci. 2022, 12(1), 523; https://doi.org/10.3390/app12010523 - 05 Jan 2022

Cited by 5 | Viewed by 2900

Abstract

This paper presents an approach to enhance electronic traveling aids (ETAs) for people who are blind and severely visually impaired (BSVI) using indoor orientation and guided navigation by employing social outsourcing of indoor route mapping and assistance processes. This type of approach is [...] Read more.

This paper presents an approach to enhance electronic traveling aids (ETAs) for people who are blind and severely visually impaired (BSVI) using indoor orientation and guided navigation by employing social outsourcing of indoor route mapping and assistance processes. This type of approach is necessary because GPS does not work well, and infrastructural investments are absent or too costly to install for indoor navigation. Our approach proposes the prior outsourcing of vision-based recordings of indoor routes from an online network of seeing volunteers, who gather and constantly update a web cloud database of indoor routes using specialized sensory equipment and web services. Computational intelligence-based algorithms process sensory data and prepare them for BSVI usage. In this way, people who are BSVI can obtain ready-to-use access to the indoor routes database. This type of service has not previously been offered in such a setting. Specialized wearable sensory ETA equipment, depth cameras, smartphones, computer vision algorithms, tactile and audio interfaces, and computational intelligence algorithms are employed for that matter. The integration of semantic data of points of interest (such as stairs, doors, WC, entrances/exits) and evacuation schemes could make the proposed approach even more attractive to BVSI users. Presented approach crowdsources volunteers’ real-time online help for complex navigational situations using a mobile app, a live video stream from BSVI wearable cameras, and digitalized maps of buildings’ evacuation schemes. Full article

(This article belongs to the Special Issue New Trends in Smart Wearable and Interactive Mechatronic Systems)

► Show Figures

Figure 1

14 pages, 977 KiB

Open AccessArticle

DDMF: A Method for Mining Relatively Important Nodes Based on Distance Distribution and Multi-Index Fusion

by Na Zhao, Qian Liu, Ming Jing, Jie Li, Zhidan Zhao and Jian Wang

Appl. Sci. 2022, 12(1), 522; https://doi.org/10.3390/app12010522 - 05 Jan 2022

Cited by 4 | Viewed by 2022

Abstract

In research on complex networks, mining relatively important nodes is a challenging and practical work. However, little research has been done on mining relatively important nodes in complex networks, and the existing relatively important node mining algorithms cannot take into account the indicators [...] Read more.

In research on complex networks, mining relatively important nodes is a challenging and practical work. However, little research has been done on mining relatively important nodes in complex networks, and the existing relatively important node mining algorithms cannot take into account the indicators of both precision and applicability. Aiming at the scarcity of relatively important node mining algorithms and the limitations of existing algorithms, this paper proposes a relatively important node mining method based on distance distribution and multi-index fusion (DDMF). First, the distance distribution of each node is generated according to the shortest path between nodes in the network; then, the cosine similarity, Euclidean distance and relative entropy are fused, and the entropy weight method is used to calculate the weights of different indexes; Finally, by calculating the relative importance score of nodes in the network, the relatively important nodes are mined. Through verification and analysis on real network datasets in different fields, the results show that the DDMF method outperforms other relatively important node mining algorithms in precision, recall, and AUC value. Full article

(This article belongs to the Special Issue Artificial Intelligence in Complex Networks)

► Show Figures

Figure 1

15 pages, 2009 KiB

Open AccessArticle

Automatic Classification of Fatty Liver Disease Based on Supervised Learning and Genetic Algorithm

by Ahmed Gaber, Hassan A. Youness, Alaa Hamdy, Hammam M. Abdelaal and Ammar M. Hassan

Appl. Sci. 2022, 12(1), 521; https://doi.org/10.3390/app12010521 - 05 Jan 2022

Cited by 16 | Viewed by 3422

Abstract

Fatty liver disease is considered a critical illness that should be diagnosed and detected at an early stage. In advanced stages, liver cancer or cirrhosis arise, and to identify this disease, radiologists commonly use ultrasound images. However, because of their low quality, radiologists [...] Read more.

Fatty liver disease is considered a critical illness that should be diagnosed and detected at an early stage. In advanced stages, liver cancer or cirrhosis arise, and to identify this disease, radiologists commonly use ultrasound images. However, because of their low quality, radiologists found it challenging to recognize this disease using ultrasonic images. To avoid this problem, a Computer-Aided Diagnosis technique is developed in the current study, using Machine Learning Algorithms and a voting-based classifier to categorize liver tissues as being fatty or normal, based on extracting ultrasound image features and a voting-based classifier. Four main contributions are provided by our developed method: firstly, the classification of liver images is achieved as normal or fatty without a segmentation phase. Secondly, compared to our proposed work, the dataset in previous works was insufficient. A combination of 26 features is the third contribution. Based on the proposed methods, the extracted features are Gray-Level Co-Occurrence Matrix (GLCM) and First-Order Statistics (FOS). The fourth contribution is the voting classifier used to determine the liver tissue type. Several trials have been performed by examining the voting-based classifier and J48 algorithm on a dataset. The obtained TP, TN, FP, and FN were 94.28%, 97.14%, 5.71%, and 2.85%, respectively. The achieved precision, sensitivity, specificity, and F1-score were 94.28%, 97.05%, 94.44%, and 95.64%, respectively. The achieved classification accuracy using a voting-based classifier was 95.71% and in the case of using the J48 algorithm was 93.12%. The proposed work achieved a high performance compared with the research works. Full article

(This article belongs to the Section Biomedical Engineering)

► Show Figures

Figure 1

18 pages, 25723 KiB

Open AccessArticle

Numerical Simulation Investigation of a Double Skin Transpired Solar Air Collector

by Charles Berville, Florin Bode and Cristiana Croitoru

Appl. Sci. 2022, 12(1), 520; https://doi.org/10.3390/app12010520 - 05 Jan 2022

Cited by 7 | Viewed by 2152

Abstract

Transpired solar collectors (TSC) are one of the most popular solar thermal technologies for building façades. TSC use solar energy to heat the absorber surface, which transmits thermal energy to the ambient air. A variant of TSC, namely, a double skin transpired solar [...] Read more.

Transpired solar collectors (TSC) are one of the most popular solar thermal technologies for building façades. TSC use solar energy to heat the absorber surface, which transmits thermal energy to the ambient air. A variant of TSC, namely, a double skin transpired solar collector (DSTSC), has been analyzed in this paper, thus providing guide values and a technical point of view for engineers, architects, and constructors when designing such transpired solar collectors. Three important parameters were addressed in this study through numerical simulation: the influence of a separation plate introduced in a TSC, turning it into a DSTSC; the air layer thickness influence on the performance of the collector; and the influence of the used absorber materials for the separation plate material. Greater heat exchange efficiency was noticed for the DSTSC at every imposed airflow rate compared with the TSC. Regarding the thickness of the collector, the efficiency gradually increased when increasing the solar collector thickness until it reached a value of 20 cm, though not varying significantly at a thickness of 30 cm. Full article

(This article belongs to the Special Issue Urban Sustainability and Resilience of the Built Environments)

► Show Figures

Figure 1

17 pages, 1825 KiB

Open AccessArticle

Embedded AI-Based Digi-Healthcare

by Zarlish Ashfaq, Rafia Mumtaz, Abdur Rafay, Syed Mohammad Hassan Zaidi, Hadia Saleem, Sadaf Mumtaz, Adnan Shahid, Eli De Poorter and Ingrid Moerman

Appl. Sci. 2022, 12(1), 519; https://doi.org/10.3390/app12010519 - 05 Jan 2022

Cited by 15 | Viewed by 5203

Abstract

Healthcare is an indispensable part of human life and chronic illnesses like cardiovascular diseases (CVD) have a deeply negative impact on the healthcare sector. Since the ever-growing population of chronic patients cannot be managed at hospitals, therefore, there is an urgent need for [...] Read more.

Healthcare is an indispensable part of human life and chronic illnesses like cardiovascular diseases (CVD) have a deeply negative impact on the healthcare sector. Since the ever-growing population of chronic patients cannot be managed at hospitals, therefore, there is an urgent need for periodic monitoring of vital parameters and apposite treatment of these patients. In this paper, an Internet of Medical Things (IoMT) -based remote patient monitoring system is proposed which is based on Artificial Intelligence (AI) and edge computing. The primary focus of this paper is to develop an embedded prototype that can be used for remote monitoring of cardiovascular patients. The system will continuously monitor physiological parameters like body temperature, heart rate, and blood oxygen saturation, and then report the health status to the authenticated users. The system employs edge computing to perform multiple functionalities including health status inference using a Machine Learning (ML) model which makes predictions on real-time data, alert notifications in case of an emergency, and transferring data between the sensor network and the cloud. A web-based application is developed for the depiction of raw data and ML results and to provide a direct communication channel between the patient and the doctor. The ML module achieved an accuracy of 96.26% on the test set using the K-Nearest Neighbors (KNNs) algorithm. This solution aims to address the sense of emergency due to the alarming statistics that highlight the mortality rate of cardiovascular patients. The project will enable a smart option based on IoT and ML to improve standards of living and prove crucial in saving human lives. Full article

(This article belongs to the Special Issue Internet of Things (IoT) in Smart Cities)

► Show Figures

Figure 1

19 pages, 7569 KiB

Open AccessArticle

Analytical Model Formulation of Steel Plate Reinforced Concrete Walls against Hard Projectile Impact

by Bo Pu, Xiaoming Wang, Weibing Li and Jun Feng

Appl. Sci. 2022, 12(1), 518; https://doi.org/10.3390/app12010518 - 05 Jan 2022

Cited by 3 | Viewed by 2339

Abstract

Steel plate reinforced concrete (SC) walls can effectively resist projectile impact by preventing the rear concrete fragments flying away, thus attracting much attention in defence technology. This work numerically and analytically investigated the hard projectile perforation of steel plate reinforced concrete walls. Impact [...] Read more.

Steel plate reinforced concrete (SC) walls can effectively resist projectile impact by preventing the rear concrete fragments flying away, thus attracting much attention in defence technology. This work numerically and analytically investigated the hard projectile perforation of steel plate reinforced concrete walls. Impact resistance theories, including cavity expansion analysis as well as the petaling theory of thin steel plates were used to describe the cratering, tunneling and plugging phases of SC walls perforation. Numerical modeling of SC walls perforation was performed to estimate projectile residual velocity and target destructive form, which were validated against the test results. An analytical model for SC wall perforation was established to describe the penetration resistance featuring five stages, i.e., cratering, tunneling and plugging, petaling with plugging and solely petaling. Analytical model predictions matched numerical results well with respect to projectile deceleration evolution as well as residual velocity. From a structural absorbed energy perspective, the effect of front concrete panel and rear steel plate thickness combinations was also studied and analyzed. Finally, equivalent concrete slab thickness was derived with respect to the ballistic limit of SC walls, which may be helpful in the design of a protective strategy. Full article

(This article belongs to the Special Issue Blast and Impact Engineering on Structures and Materials)

► Show Figures

Figure 1

14 pages, 3874 KiB

Open AccessArticle

Analysis of Bluetooth RSSI for Proximity Detection of Ship Passengers

by Qianfeng Lin and Jooyoung Son

Appl. Sci. 2022, 12(1), 517; https://doi.org/10.3390/app12010517 - 05 Jan 2022

Cited by 6 | Viewed by 2470

Abstract

Concern about the health of people who traveled onboard was raised during the COVID-19 outbreak on the Diamond Princess cruise ship. The ship’s narrow space offers an environment conducive to the virus’s spread. Close contact isolation remains one of the most critical current [...] Read more.

Concern about the health of people who traveled onboard was raised during the COVID-19 outbreak on the Diamond Princess cruise ship. The ship’s narrow space offers an environment conducive to the virus’s spread. Close contact isolation remains one of the most critical current measures to stop the virus’s rapid spread. Contacts can be identified efficiently by detecting intelligent devices nearby. The smartphone’s Bluetooth RSSI signal is essential data for proximity detection. This paper analyzes Bluetooth RSSI signals available to the public and compares RSSI signals in two distinct poses: standing and sitting. These features can improve accuracy and provide an essential basis for creating algorithms for proximity detection. This allows for improved accuracy in identifying close contacts and can help ships sustainably manage persons onboard in the post-epidemic era. Full article

(This article belongs to the Special Issue Advanced Marine Engineering and Technology: Sustainable and Smart Marine Engineering)

► Show Figures

Figure 1

15 pages, 5545 KiB

Open AccessArticle

Analysis of the Working Performance of a Back-to-Back Geosynthetic-Reinforced Soil Wall

by Guangqing Yang, Yunfei Zhao, He Wang and Zhijie Wang

Appl. Sci. 2022, 12(1), 516; https://doi.org/10.3390/app12010516 - 05 Jan 2022

Cited by 2 | Viewed by 1963

Abstract

Back-to-back geosynthetic-reinforced soil walls (BBGRSWs) are commonly used in embankments approaching bridges and narrow spaces. However, the available literature and design guidelines for BBGRSWs are limited. The aims of this research were to develop a greater understanding of the working performance of BBGRSWs [...] Read more.

Back-to-back geosynthetic-reinforced soil walls (BBGRSWs) are commonly used in embankments approaching bridges and narrow spaces. However, the available literature and design guidelines for BBGRSWs are limited. The aims of this research were to develop a greater understanding of the working performance of BBGRSWs and to optimize the design method of a BBGRSW to ensure the cost-efficiency as well as the stability of the structure. On the basis of a monitored BBGRSW structure located in China, we established a numerical model. The parameters of the materials used in the actual project were determined through triaxial and tensile tests. The numerical results were compared with the measured results in the field to verify the correctness of the selected parameters. Two parameters were investigated by the FEM method: the reinforcement length and the arrangement. The FEM analysis indicated that post-construction deformations such as displacement and settlement could be reduced by reinforcing the same layer on both sides. Longer reinforcements were needed to achieve the same performance if the reinforcements were cross-arranged. Thus, BBGRSWs can have a superior performance if the reinforcements are connected in the middle from both sides. Even with longer reinforcements, the safety factor of the wall with a cross-arranged reinforcement was smaller than that with same-layered reinforcements. Full article

(This article belongs to the Special Issue Advances in Geosynthetics)

► Show Figures

Figure 1

41 pages, 14464 KiB

Open AccessArticle

In Silico Studies of Tumor Targeted Peptide-Conjugated Natural Products for Targeting Over-Expressed Receptors in Breast Cancer Cells Using Molecular Docking, Molecular Dynamics and MMGBSA Calculations

by Lucy R. Hart, Charlotta G. Lebedenko, Saige M. Mitchell, Rachel E. Daso and Ipsita A. Banerjee

Appl. Sci. 2022, 12(1), 515; https://doi.org/10.3390/app12010515 - 05 Jan 2022

Cited by 6 | Viewed by 3510

Abstract

In this work, in silico studies were carried out for the design of diterpene and polyphenol-peptide conjugates to potentially target over-expressed breast tumor cell receptors. Four point mutations were induced into the known tumor-targeting peptide sequence YHWYGYTPQN at positions 1, 2, 8 and [...] Read more.

In this work, in silico studies were carried out for the design of diterpene and polyphenol-peptide conjugates to potentially target over-expressed breast tumor cell receptors. Four point mutations were induced into the known tumor-targeting peptide sequence YHWYGYTPQN at positions 1, 2, 8 and 10, resulting in four mutated peptides. Each peptide was separately conjugated with either chlorogenate, carnosate, gallate, or rosmarinate given their known anti-tumor activities, creating dual targeting compounds. Molecular docking studies were conducted with the epidermal growth factor receptor (EGFR), to which the original peptide sequence is known to bind, as well as the estrogen receptor (ERα) and peroxisome proliferator-activated receptor (PPARα) using both Autodock Vina and FireDock. Based on docking results, peptide conjugates and peptides were selected and subjected to molecular dynamics simulations. MMGBSA calculations were used to further probe the binding energies. ADME studies revealed that the compounds were not CYP substrates, though most were Pgp substrates. Additionally, most of the peptides and conjugates showed MDCK permeability. Our results indicated that several of the peptide conjugates enhanced binding interactions with the receptors and resulted in stable receptor-ligand complexes; Furthermore, they may successfully target ERα and PPARα in addition to EGFR and may be further explored for synthesis and biological studies for therapeutic applications. Full article

(This article belongs to the Special Issue Selected Papers in the Section Materials 2022)

► Show Figures

Graphical abstract

21 pages, 3033 KiB

Open AccessArticle

Leveraging AI and Machine Learning for National Student Survey: Actionable Insights from Textual Feedback to Enhance Quality of Teaching and Learning in UK’s Higher Education

by Raheel Nawaz, Quanbin Sun, Matthew Shardlow, Georgios Kontonatsios, Naif R. Aljohani, Anna Visvizi and Saeed-Ul Hassan

Appl. Sci. 2022, 12(1), 514; https://doi.org/10.3390/app12010514 - 05 Jan 2022

Cited by 14 | Viewed by 5008

Abstract

Students’ evaluation of teaching, for instance, through feedback surveys, constitutes an integral mechanism for quality assurance and enhancement of teaching and learning in higher education. These surveys usually comprise both the Likert scale and free-text responses. Since the discrete Likert scale responses are [...] Read more.

Students’ evaluation of teaching, for instance, through feedback surveys, constitutes an integral mechanism for quality assurance and enhancement of teaching and learning in higher education. These surveys usually comprise both the Likert scale and free-text responses. Since the discrete Likert scale responses are easy to analyze, they feature more prominently in survey analyses. However, the free-text responses often contain richer, detailed, and nuanced information with actionable insights. Mining these insights is more challenging, as it requires a higher degree of processing by human experts, making the process time-consuming and resource intensive. Consequently, the free-text analyses are often restricted in scale, scope, and impact. To address these issues, we propose a novel automated analysis framework for extracting actionable information from free-text responses to open-ended questions in student feedback questionnaires. By leveraging state-of-the-art supervised machine learning techniques and unsupervised clustering methods, we implemented our framework as a case study to analyze a large-scale dataset of 4400 open-ended responses to the National Student Survey (NSS) at a UK university. These analyses then led to the identification, design, implementation, and evaluation of a series of teaching and learning interventions over a two-year period. The highly encouraging results demonstrate our approach’s validity and broad (national and international) application potential—covering tertiary education, commercial training, and apprenticeship programs, etc., where textual feedback is collected to enhance the quality of teaching and learning. Full article

(This article belongs to the Special Issue ICT and Statistics in Education)

► Show Figures

Figure 1

22 pages, 31076 KiB

Open AccessArticle

Resilience Assessment of a Twin-Tube Motorway Tunnel in the Event of a Traffic Accident or Fire in a Tube

by Ciro Caliendo, Isidoro Russo and Gianluca Genovese

Appl. Sci. 2022, 12(1), 513; https://doi.org/10.3390/app12010513 - 05 Jan 2022

Cited by 7 | Viewed by 2440

Abstract

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its [...] Read more.

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its partial or complete closure. The functionality of the road infrastructure, in the case of an accident in one of the two tubes (each tube presents two lanes with unidirectional traffic under ordinary conditions), was assumed to be recovered both by using the remaining undisrupted lane of the tube interested by the disruptive event (only one lane is closed) and reorganizing the traffic flow by utilizing the adjacent tube for bi-directional traffic (both lanes are closed). The effects of an alternative itinerary individualized in the corresponding open road network were also examined. The level of functionality of the system during the period in which the tube is partially or completely closed was computed as the ratio between the average travel time required to reach a given destination from a specific origin before and after the occurrence of the disruptive event. The resilience metrics were assumed to be resilience loss, recovery speed, and resilience index. The best scenario was found to be the partial closure of the tube in contrast to the complete one. However, in order to contain the negative effects on the functionality of the motorway section due to the complete closure of the tube, it is worth highlighting how the traffic by-pass before the entrance portal of the closed tube should be open in a very short time by the tunnel management team to allow for the quick use of the adjacent tube for bi-directional traffic. An additional improvement, with reference exclusively to passenger cars traveling through the adjacent unblocked tube, might be obtained by activating the variable message signs, located at a sufficient distance from the motorway junction before the entrance portal of the closed tube, in order to suggest an alternative route to heavy good vehicles (HGVs) only. Whereas, when the alternative itinerary is used by all vehicles traveling towards the blocked tube (i.e., both passenger cars and HGVs), this redirectioning of the motorway traffic flow was found to be characterized by an excessive travel time, with it therefore not being advisable. The results obtained might be useful as a decision-making support tool aimed at improving the resilience of twin-tube tunnels. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

► Show Figures

Figure 1

38 pages, 1308 KiB

Open AccessArticle

3D Stress Analysis of Multilayered Functionally Graded Plates and Shells under Moisture Conditions

by Salvatore Brischetto and Roberto Torre

Appl. Sci. 2022, 12(1), 512; https://doi.org/10.3390/app12010512 - 05 Jan 2022

Cited by 8 | Viewed by 1571

Abstract

This paper presents the steady-state stress analysis of single-layered and multilayered plates and shells embedding Functionally Graded Material (FGM) layers under moisture conditions. This solution relies on an exact layer-wise approach; the formulation is unique despite the geometry. It studies spherical and cylindrical [...] Read more.

This paper presents the steady-state stress analysis of single-layered and multilayered plates and shells embedding Functionally Graded Material (FGM) layers under moisture conditions. This solution relies on an exact layer-wise approach; the formulation is unique despite the geometry. It studies spherical and cylindrical shells, cylinders, and plates in an orthogonal mixed curvilinear coordinate system (

α

,

β

, z). The moisture conditions are defined at the external surfaces and evaluated in the thickness direction under steady-state conditions following three procedures. This solution handles the 3D Fick diffusion equation, the 1D Fick diffusion equation, and the a priori assumed linear profile. The paper discusses their assumptions and the different results they deliver. Once defined, the moisture content acts as an external load; this leads to a system of three non-homogeneous second-order differential equilibrium equations. The 3D problem is reduced to a system of partial differential equations in the thickness coordinate, solved via the exponential matrix method. It returns the displacements and their z-derivatives as a direct result. The paper validates the model by comparing the results with 3D analytical models proposed in the literature and numerical models. Then, new results are presented for one-layered and multilayered FGM plates, cylinders, and cylindrical and spherical shells, considering different moisture contents, thickness ratios, and material laws. Full article

(This article belongs to the Special Issue Recent Advances in Theoretical and Computational Modeling of Composite Materials and Structures)

► Show Figures

Figure 1

14 pages, 1994 KiB

Open AccessArticle

An Evaluation of the Accuracy and Precision of Jump Height Measurements Using Different Technologies and Analytical Methods

by Filipe Conceição, Martin Lewis, Hernâni Lopes and Elza M. M. Fonseca

Appl. Sci. 2022, 12(1), 511; https://doi.org/10.3390/app12010511 - 05 Jan 2022

Cited by 9 | Viewed by 3416

Abstract

This study aims to comprehensively assess the accuracy and precision of five different devices and by incorporating a variety of analytical approaches for measuring countermovement jump height: Qualisys motion system; Force platform; Ergojump; an Accelerometer, and self-made Abalakow jump belt. Twenty-seven male and [...] Read more.

This study aims to comprehensively assess the accuracy and precision of five different devices and by incorporating a variety of analytical approaches for measuring countermovement jump height: Qualisys motion system; Force platform; Ergojump; an Accelerometer, and self-made Abalakow jump belt. Twenty-seven male and female physical education students (23.5 ± 3.8 years; height 170 ± 9.1 cm and body mass 69.1 ± 11.4 kg) performed three countermovement jumps simultaneously measured using five devices. The 3D measured displacement obtained through the Qualisys device was considered in this study as the reference value. The best accuracy (difference from 3D measured displacement) and precision (standard deviation of differences) for countermovement jump measurement was found using the Abalakow jump belt (0.8 ± 14.7 mm); followed by the Force platform when employing a double integration method (1.5 ± 13.9 mm) and a flight-time method employed using Qualisys motion system data (6.1 ± 17.1 mm). The least accuracy was obtained for the Ergojump (−72.9 mm) employing its analytical tools and then for the accelerometer and Force platform using flight time approximations (−52.8 mm and −45.3 mm, respectively). The worst precision (±122.7 mm) was obtained through double integration of accelerometer acceleration data. This study demonstrated that jump height measurement accuracy is both device and analytical-approach-dependent and that accuracy and precision in jump height measurement are achievable with simple, inexpensive equipment such as the Abalakow jump belt. Full article

(This article belongs to the Special Issue Structural Design and Computational Methods)

► Show Figures

Figure 1

10 pages, 3101 KiB

Open AccessArticle

Experimental Evaluation of the Blackbody Radiation Shift in the Cesium Atomic Fountain Clock

by Fan Yang, Xinliang Wang, Jun Ruan, Junru Shi, Sichen Fan, Yang Bai, Yong Guan, Qiang Hao, Hui Zhang, Dandan Liu and Shougang Zhang

Appl. Sci. 2022, 12(1), 510; https://doi.org/10.3390/app12010510 - 05 Jan 2022

Cited by 1 | Viewed by 1420

Abstract

The cesium atomic fountain clock is the world’s most accurate microwave atomic clock. The uncertainty of blackbody radiation (BBR) shift accounts for an increasingly large percentage of the uncertainty associated with fountain clocks and has become a key factor in the performance of [...] Read more.

The cesium atomic fountain clock is the world’s most accurate microwave atomic clock. The uncertainty of blackbody radiation (BBR) shift accounts for an increasingly large percentage of the uncertainty associated with fountain clocks and has become a key factor in the performance of fountain clocks. The uncertainty of BBR shift can be reduced by improving the system environment temperature. This study examined the mechanism by which the BBR shift of the transition frequency between the two hyperfine energy levels of the ¹³³Cs ground state is generated and the calculation method for the BBR shift in the atomic fountain. Methods used to reduce the uncertainty of BBR shift were also examined. A fountain system structure with uniform temperature and good heat preservation was designed, and related technologies, such as that for measuring the temperature of the cesium fountain system, were studied. The results of 20 days of measurements, in combination with computer simulation results, showed that the temperature uncertainty of the atomic action zone is 0.12 °C and that the resulting uncertainty of BBR shift is 2.4 × 10⁻¹⁷. Full article

(This article belongs to the Special Issue Applications of Atomic Physics and Atomic Interferometry)

► Show Figures

Figure 1

16 pages, 1140 KiB

Open AccessArticle

Impedance Spectroscopy Sensing Material Properties for Self-Tuning Ratio Control in Pharmaceutical Industry

by Mihaela Ghita, Isabela Birs, Dana Copot, Ioana Nascu and Clara M. Ionescu

Appl. Sci. 2022, 12(1), 509; https://doi.org/10.3390/app12010509 - 05 Jan 2022

Cited by 2 | Viewed by 1683

Abstract

Following the paradigm shift in the pharmaceutical industry from batch to continuous production, additional instrumentation and revision of control strategies to optimize material flow throughout the downstream processes are required. Tableting manufacturing is one of the most productive in terms of turnover and [...] Read more.

Following the paradigm shift in the pharmaceutical industry from batch to continuous production, additional instrumentation and revision of control strategies to optimize material flow throughout the downstream processes are required. Tableting manufacturing is one of the most productive in terms of turnover and investment into new sensor technologies is an important decision-making step. This paper proposes a continuous solution to detect changes in material properties, and a control algorithm to aid in minimizing risk at the end-product line. Some of the sub-processes involved in tableting manufacturing perform changes in powder and liquid mixtures, granulation, density, therefore changing flow conditions of the raw material. Using impedance spectroscopy in a continuous sensing and monitoring context, it is possible to perform online identification of generalized (fractional) order parametric models where the coefficients are correlated to changes in material properties. The model parameters are then included in a self-tuning control gain used in ratio control as part of the local process control loop. The solution proposed here is easy to implement and poses a significant added value to the current state of art in pharmaceutical manufacturing technologies. Full article

(This article belongs to the Special Issue Impedance Spectroscopy and Its Application in Measurement and Sensor Technology)

► Show Figures

Figure 1

16 pages, 662 KiB

Open AccessArticle

Boundary-Aware Hashing for Hamming Space Retrieval

by Wenjin Hu, Yukun Chen, Lifang Wu, Ge Shi and Meng Jian

Appl. Sci. 2022, 12(1), 508; https://doi.org/10.3390/app12010508 - 05 Jan 2022

Cited by 1 | Viewed by 1485

Abstract

Hamming space retrieval is a hot area of research in deep hashing because it is effective for large-scale image retrieval. Existing hashing algorithms have not fully used the absolute boundary to discriminate the data inside and outside the Hamming ball, and the performance [...] Read more.

Hamming space retrieval is a hot area of research in deep hashing because it is effective for large-scale image retrieval. Existing hashing algorithms have not fully used the absolute boundary to discriminate the data inside and outside the Hamming ball, and the performance is not satisfying. In this paper, a boundary-aware contrastive loss is designed. It involves an exponential function with absolute boundary (i.e., Hamming radius) information for dissimilar pairs and a logarithmic function to encourage small distance for similar pairs. It achieves a push that is bigger than the pull inside the Hamming ball, and the pull is bigger than the push outside the ball. Furthermore, a novel Boundary-Aware Hashing (BAH) architecture is proposed. It discriminatively penalizes the dissimilar data inside and outside the Hamming ball. BAH enables the influence of extremely imbalanced data to be reduced without up-weight to similar pairs or other optimization strategies because its exponential function rapidly converges outside the absolute boundary, making a huge contrast difference between the gradients of the logarithmic and exponential functions. Extensive experiments conducted on four benchmark datasets show that the proposed BAH obtains higher performance for different code lengths, and it has the advantage of handling extremely imbalanced data. Full article

► Show Figures

Figure 1

11 pages, 1730 KiB

Open AccessArticle

Study of ^222−220Rn Measurement Systems Based on Electrostatic Collection by Using Geant4+COMSOL Simulation

by Luigi Rinaldi, Fabrizio Ambrosino, Vincenzo Roca, Antonio D’Onofrio and Carlo Sabbarese

Appl. Sci. 2022, 12(1), 507; https://doi.org/10.3390/app12010507 - 05 Jan 2022

Cited by 5 | Viewed by 2223

Abstract

Using Monte Carlo (with Geant4) and COMSOL simulations, the authors have defined a useful tool to reproduce the alpha spectroscopy of ²²²Rn, ²²⁰Rn and their ionized daughters by measurement systems based on electrostatic collection on a silicon detector, inside a metallic [...] Read more.

Using Monte Carlo (with Geant4) and COMSOL simulations, the authors have defined a useful tool to reproduce the alpha spectroscopy of ²²²Rn, ²²⁰Rn and their ionized daughters by measurement systems based on electrostatic collection on a silicon detector, inside a metallic chamber. Several applications have been performed: (i) simulating commercial devices worldwide used, and comparing them with experimental theoretical results; (ii) studying of realization of new measurement systems through investigation of the detection efficiency versus different chamber geometries. New considerations and steps forward have been drawn. The present work is a novelty in the literature concerning this research framework. Full article

(This article belongs to the Special Issue Spectrometric Methods for Measurement and Control of Environmental Radioactivity)

► Show Figures

Figure 1

10 pages, 1078 KiB

Open AccessArticle

Effects of Minimalist Footwear and Foot Strike Pattern on Plantar Pressure during a Prolonged Running

by Marta Izquierdo-Renau, Roberto Sanchis-Sanchis, Jose I. Priego-Quesada, Alberto Encarnación-Martínez, Ana Queralt and Pedro Pérez-Soriano

Appl. Sci. 2022, 12(1), 506; https://doi.org/10.3390/app12010506 - 05 Jan 2022

Viewed by 3870

Abstract

The use of minimalist shoes (MS) in running involves changes in running mechanics compared to conventional shoes (CS), but there is still little research analysing the effects of this footwear on plantar pressure, which could help to understand some risk injury factors. Moreover, [...] Read more.

The use of minimalist shoes (MS) in running involves changes in running mechanics compared to conventional shoes (CS), but there is still little research analysing the effects of this footwear on plantar pressure, which could help to understand some risk injury factors. Moreover, there are no studies examining the effects of a prolonged running and foot strike patterns on baropodometric variables in MS. Therefore, the aim of this study was to analyse the changes produced using MS on plantar pressure during a prolonged running, as well as its interaction with the time and foot strike pattern. Twenty-one experienced minimalist runners (age 38 ± 10 years, MS running experience 2 ± 1 years) ran with MS and CS for 30 min at 80% of their maximal aerobic speed, and mean pressure, peak pressure, contact time, centre of pressure velocity, relative force and contact area were analysed using a pressure platform. Foot strike pattern and time were also considered as factors. The multivariable linear regression mixed models showed that the use of MS induced, at the end of a prolonged running, higher peak pressure (p = 0.008), lower contact time (p = 0.004) and lower contact area (p < 0.001) than using CS. Also, runners with forefoot strike pattern using MS, compared to midfoot and rearfoot patterns, showed higher mean and peak pressure (p < 0.001) and lower contact time and area (p < 0.05). These results should be considered when planning training for runners using MS, as higher peak pressure values when using this type of footwear could be a risk factor for the development of some foot injuries. Full article

(This article belongs to the Special Issue Biomechanics in Sport Performance and Injury Preventing)

► Show Figures

Figure 1

11 pages, 6651 KiB

Open AccessArticle

Silicon Ribbon-Based Dual-Beam Optical Phased Array with Low Crosstalk and Large FoV

by Hsun-Yuan Chi, Wei Hong, Hsuan Lai, Shih-Hsiang Hsu and Che-Chang Chang

Appl. Sci. 2022, 12(1), 505; https://doi.org/10.3390/app12010505 - 05 Jan 2022

Cited by 1 | Viewed by 1966

Abstract

In this paper, a silicon ribbon (SR)-based microstructure is developed and added to a 32-channel optical phased array (OPA) to reduce the crosstalk between the antennas of grating waveguides. The spacing between the chirped grating antennas can be as close as 600 nm [...] Read more.

In this paper, a silicon ribbon (SR)-based microstructure is developed and added to a 32-channel optical phased array (OPA) to reduce the crosstalk between the antennas of grating waveguides. The spacing between the chirped grating antennas can be as close as 600 nm to effectively improve the field of view (FoV) of the OPA in the horizontal direction to 95 degrees. This SR-based approach substantially reduces the side lobe by 10 dB, effectively suppressing the noise and increasing the main lobe by 6 dB and considerably expanding the grating length with linear energy decay. The full width at the half maximum of the light spot reaches about 0.24 degrees. The antenna sites can simultaneously be scanned vertically by bi-directional inputs, effectively increasing the FoV to 30 degrees in the vertical direction. Full article

► Show Figures

Figure 1

19 pages, 2072 KiB

Open AccessArticle

Clickbait Detection Using Deep Recurrent Neural Network

by Abdul Razaque, Bandar Alotaibi, Munif Alotaibi, Shujaat Hussain, Aziz Alotaibi and Vladimir Jotsov

Appl. Sci. 2022, 12(1), 504; https://doi.org/10.3390/app12010504 - 05 Jan 2022

Cited by 9 | Viewed by 2981

Abstract

People who use social networks often fall prey to clickbait, which is commonly exploited by scammers. The scammer attempts to create a striking headline that attracts the majority of users to click an attached link. Users who follow the link can be redirected [...] Read more.

People who use social networks often fall prey to clickbait, which is commonly exploited by scammers. The scammer attempts to create a striking headline that attracts the majority of users to click an attached link. Users who follow the link can be redirected to a fraudulent resource, where their personal data are easily extracted. To solve this problem, a novel browser extension named ClickBaitSecurity is proposed, which helps to evaluate the security of a link. The novel extension is based on the legitimate and illegitimate list search (LILS) algorithm and the domain rating check (DRC) algorithm. Both of these algorithms incorporate binary search features to detect malicious content more quickly and more efficiently. Furthermore, ClickBaitSecurity leverages the features of a deep recurrent neural network (RNN). The proposed ClickBaitSecurity solution has greater accuracy in detecting malicious and safe links compared to existing solutions. Full article

► Show Figures

Figure 1

26 pages, 9270 KiB

Open AccessArticle

Design Proposal for Masonry Infill Walls Subject to Seismic Actions

by João Leite, Paulo B. Lourenço and Nuno Mendes

Appl. Sci. 2022, 12(1), 503; https://doi.org/10.3390/app12010503 - 05 Jan 2022

Cited by 1 | Viewed by 1688

Abstract

Several factors influence the behaviour of masonry infilled frames, which have been the subject of previous research with moderate success. The new generation of European design standards imposes the need to prevent the brittle collapse of infills and makes the structural engineer accountable [...] Read more.

Several factors influence the behaviour of masonry infilled frames, which have been the subject of previous research with moderate success. The new generation of European design standards imposes the need to prevent the brittle collapse of infills and makes the structural engineer accountable for this requirement, yet it fails to provide sufficient information for masonry infill design. The present study aimed to compare experimental results with the provisions of the standard for the computation of the demand and capacity of infilled frames. Three reinforced concrete buildings with different infill solutions were constructed at a 1:1.5 scale. The infill walls were tested until collapse, or severe damage, using the shake table of the National Laboratory for Civil Engineering, Portugal, and their response was measured using accelerometers attached to the walls. The European normative standard provides results close to the experimental ones as far as demand and capacity are concerned. Based on the experiments, two design proposals for infill walls are presented here, one for the definition of the natural frequency of the infills, and another for a reduction factor to account for the presence of openings in the out-of-plane capacity of infills. Full article

(This article belongs to the Special Issue Advanced Seismic Evaluation of Relevant Architectures)

► Show Figures

Figure 1

8 pages, 4839 KiB

Open AccessArticle

Evaluating the Relationship between Mandibular Third Molar and Mandibular Canal with Semiautomatic Segmentation: A Pilot Study on CBCT Datasets

by Rossana Izzetti, Marco Nisi, Stefano Gennai and Filippo Graziani

Appl. Sci. 2022, 12(1), 502; https://doi.org/10.3390/app12010502 - 05 Jan 2022

Cited by 2 | Viewed by 2185

Abstract

Inferior alveolar nerve injury is the main complication in mandibular third molar surgery. In this context, cone-beam computed tomography (CBCT) has become of crucial importance in evaluating the relationship between mandibular third molar and inferior alveolar nerve. Due to the growing interest in [...] Read more.

Inferior alveolar nerve injury is the main complication in mandibular third molar surgery. In this context, cone-beam computed tomography (CBCT) has become of crucial importance in evaluating the relationship between mandibular third molar and inferior alveolar nerve. Due to the growing interest in preoperative planning in oral surgery, several post-processing techniques have been implemented to obtain three-dimensional reconstructions of a volume of interest. In the present study, segmentation techniques were retrospectively applied to CBCT images in order to evaluate whether post-processing could offer better visualization of the structures of interest. Forty CBCT examinations performed for inferior third molar impaction were analyzed. Segmentation and volumetric reconstructions were performed. A dataset composed of multiplanar reconstructions for each study case, including segmented images, was submitted for evaluation to two oral surgeons, two general practitioners and four residents in oral surgery. The visualization of root morphology, canal course, and the relationship with mandibular cortical bone on both native CBCT and segmented images were assessed. Inter-rater agreement showed values of intraclass correlation coefficient (ICC) above 0.8 for all the examined parameters. Oral surgeons presented higher ICC values (p < 0.05). Segmented images can improve preoperative evaluation of the third molar and its relationship with the surrounding anatomical structures compared to native CBCT images. Further evaluation is needed to validate these preliminary results. Full article

(This article belongs to the Special Issue Materials and Technologies in Oral Research)

► Show Figures

Figure 1

32 pages, 4020 KiB

Open AccessReview

Progress in the Development of Electrodeposited Catalysts for Direct Liquid Fuel Cell Applications

by Kranthi Kumar Maniam, Raghuram Chetty, Ravikumar Thimmappa and Shiladitya Paul

Appl. Sci. 2022, 12(1), 501; https://doi.org/10.3390/app12010501 - 05 Jan 2022

Cited by 8 | Viewed by 2809

Abstract

Fuel cells are a key enabling technology for the future economy, thereby providing power to portable, stationary, and transportation applications, which can be considered an important contributor towards reducing the high dependencies on fossil fuels. Electrocatalyst plays a vital role in improving the [...] Read more.

Fuel cells are a key enabling technology for the future economy, thereby providing power to portable, stationary, and transportation applications, which can be considered an important contributor towards reducing the high dependencies on fossil fuels. Electrocatalyst plays a vital role in improving the performance of the low temperature fuel cells. Noble metals (Pt, Pd) supported on carbon have shown promising performance owing to their high catalytic activity for both electroreduction and electrooxidation and have good stability. Catalyst preparation by electrodeposition is considered to be simple in terms of operation and scalability with relatively low cost to obtain high purity metal deposits. This review emphasises the role of electrodeposition as a cost-effective method for synthesising fuel cell catalysts, summarising the progress in the electrodeposited Pt and Pd catalysts for direct liquid fuel cells (DLFCs). Moreover, this review also discusses the technological advances made utilising these catalysts in the past three decades, and the factors that impede the technological advancement of the electrodeposition process are presented. The challenges and the fundamental research strategies needed to achieve the commercial potential of electrodeposition as an economical, efficient methodology for synthesising fuel cells catalysts are outlined with the necessary raw materials considering current and future savings scenario. Full article

(This article belongs to the Special Issue Recent Advances in Application of Coatings and Films)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Appl. Sci., Volume 12, Issue 1 (January-1 2022) – 530 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI