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Vibrations generated from equipment mounted on ships radiate into the water and affect covert operation capabilities. Accordingly, various studies are being conducted to reduce vibration transmitted from mounted equipment. In this study, a system consisting of mounting equipment, a 3-axis active mount, a middle pedestal, and a lower mount of the middle pedestal was modeled using a finite element analysis program, and a mobility model was constructed by calculating the frequency response function between the positions required for analysis. The error signal (primary path) obtained using the mobility model and the response at the operating point by the control force of the actuator (secondary path) are applied to the narrowband Fx-LMS algorithm for vibration control, and the control performance was compared. Through coupling analysis of the middle pedestal, the control influence according to the rigidity of the middle pedestal was analyzed. As a result of the control simulation, the time required for vibration control was controlled approximately 6 times faster in the model, with increased stiffness of the middle pedestal, and the vibration reduction performance was predicted to improve by a minimum of 0.9 dB and a maximum of 13.3 dB. Through this study, a simulation model that can provide a guide for the design of the middle pedestal of a ship was obtained, and it is expected that it can be utilized for a preliminary design review before manufacturing the middle pedestal of a ship.

Active noise control (ANC) algorithms have been developed within the adaptive algorithm framework. However, multichannel ANC systems, which include numerous reference sensors, control speakers, and error microphones, require a very long control filter converging time for control filter estimation. Traditional system identification methods, such as the Wiener filter method, are better suited for such systems because of their relatively shorter converging time. However, they require large amounts of data to achieve accurate statistical estimation. Therefore, this article proposes a control filter estimation method that requires only a short length of data. An iterative Wiener filter solution using Kronecker product decomposition for multichannel ANC systems converts the filter estimation process by breaking down the extensive control filter into multiple shorter control filters through Kronecker product decomposition. This decomposition effectively reduces the high-dimensional system identification problem into manageable low-dimensional ones. Numerical simulations demonstrate the superiority of the proposed method over conventional Wiener filter techniques, especially in scenarios when limited data are available for control filter estimation.

The Internet of Things (IoT) technology has revolutionized various sectors, including healthcare, smart cities, agriculture, education, and homes. The interconnected network of diverse IoT devices used in smart homes allows users to remotely manage lighting, security systems, heating, and household appliances through smart devices. The multitude of interactions and frequent data exchanges in smart homes necessitate robust user authentication. Strengthening smart home security is crucial to ensuring user safety and safeguarding personal information, thereby maximizing the benefits of smart technology. In 2023, Bai et al. proposed an authentication scheme aimed at ensuring anonymity and secure key establishment in smart environments. Although their scheme achieved various security objectives, we identified security vulnerabilities in their proposal. In this paper, we highlight the weaknesses in their scheme and introduce a new, secure, and anonymous authentication scheme. The proposed solution integrates bio-hash techniques for protecting user identity and physical unclonable functions to mitigate device capture attacks. Our scheme establishes a secure session key between the user, gateway, and sensor, providing protection against various known attacks from both internal and external adversaries. Furthermore, we conducted both formal and informal analyses to validate the security of the proposed scheme and compared its performance with related schemes to demonstrate its effectiveness and practical applicability.

As technology advances in autonomous mobile robots, mobile service robots have been actively used more and more for various purposes. Especially, serving robots have been not surprising products anymore since the COVID-19 pandemic. One of the practical problems in operating a serving robot is that it often fails to estimate its pose on a map that it moves around. Whenever the failure happens, servers should bring the serving robot to its initial location and reboot it manually. In this paper, we focus on end-to-end relocalization of serving robots to address the problem. It is to predict robot pose directly from only the onboard sensor data using neural networks. In particular, we propose a deep neural network architecture for the relocalization based on camera-2D LiDAR sensor fusion. We call the proposed method FusionLoc. In the proposed method, the multi-head self-attention complements different types of information captured by the two sensors to regress the robot pose. Our experiments on a dataset collected by a commercial serving robot demonstrate that FusionLoc can provide better performances than previous end-to-end relocalization methods taking only a single image or a 2D LiDAR point cloud as well as a straightforward fusion method concatenating their features.

The rapid growth of the Internet of Things (IoT) has enabled prompt services over mobile devices. The Global Mobility Network (GLOMONET) is an important global network that allows mobile users to access the Internet anywhere. Although implementing a secure mechanism in GLOMONET is a difficult and complex task due to the computational and processing limitations of most mobile devices, an authentication system is vital for secure communications among such mobile devices. In 2021, Rahmani et al. proposed an authentication method, called the advanced mobile authentication protocol for GLOMONET (AMAPG). However, we found three serious vulnerabilities in AMAPG. First, AMAPG contains large amounts of information on the smart card of the mobile phone. Therefore, they are vulnerable to attacks that steal critical information. Second, it is susceptible to password-guessing attacks. Third, AMAPG cannot guarantee the security of future messages because attackers can steal the session key. In this study, we discuss the weaknesses of AMAPG and propose a new three-factor authentication scheme called the secure mobile authentication scheme for GLOMONET (SMASG). We performed informal and formal security analyses using ProVerif and BAN Logic on SMASG. In addition, we analyzed and compared its performance with that of the latest GLOMONET-based authentication schemes. SMASG saves an average of 93% time in user login and authentication phase.

In phosphor-sensitized-fluorescent organic light-emitting diodes (PSF-OLEDs), triplet excitons generated in the emitting layer (EML) are harvested by the sensitizer and the excitonic energy is efficiently transferred to the fluorescent dopant molecules. Since a phosphorescent sensitizer is typically doped at around 10 wt.%, the sensitizer not only affects cascade energy transfer but also electrical transporting in the PSF-OLEDs. However, the electrical role of phosphorescent metal complex molecules in the EML is unclear. In this study, we report the impact of the phosphorescent sensitizer on the electrical properties of PSF-OLEDs. Through a comprehensive analysis using impedance spectroscopy in conjunction with current density (J)-voltage (V)-luminance (L) properties of the PSF-OLED, it was revealed that 10 wt.% phosphorescent sensitizer forms an electron transporting pathway inside the EML. Thus, the sensitizer molecules transform a unipolar single host into a bipolar mixed host. In other words, the phosphorescent sensitizer is an n-type host in the PSF-OLEDs. As a result, the charge balance and the operating voltage were simultaneously and significantly improved in the PSF-OLEDs.

The aim of this study is to evaluate the wear volume of interim crowns fabricated using digital light processing 3D printing according to the printing angle. A total of five patients undergoing the placement of a single crown on the mandibular molar were included. Interim crowns were fabricated directly in the oral cavity using the conventional method. A digital light processing 3D printer was then used to fabricate crowns with build angles of 0, 45, and 90 degrees. Therefore, four fabricated interim crowns were randomly delivered to the patients, and each was used for one week. Before and after use, the intaglio surfaces of the interim crowns were scanned using a 3D scanner. The volume changes before and after use were measured, and changes in the height of the occlusal surface were evaluated using the root mean square value. Data normality was verified by statistical analysis, and the wear volume in each group was evaluated using a one-way analysis of variance and Tukey’s honestly significant difference test (α = 0.05). Compared with the RMS values of the conventional method (11.88 ± 2.69 µm) and the 3D-printing method at 0 degrees (12.14 ± 2.38 µm), the RMS values were significantly high at 90 degrees (16.46 ± 2.39 µm) (p < 0.05). Likewise, there was a significant difference in the change in volume between the groups (p = 0.002), with a significantly higher volume change value at 90 degrees (1.74 ± 0.41 mm3) than in the conventional method (0.70 ± 0.15 mm3) (p < 0.05). A printing angle of 90 degrees is not recommended when interim crowns are fabricated using digital light processing 3D printing.

Object counting is an indispensable task in manufacturing and management. Recently, the development of image-processing techniques and deep learning object detection has achieved excellent performance in object-counting tasks. Accordingly, we propose a novel small-size smart counting system composed of a low-cost hardware device and a cloud-based object-counting software server to implement an accurate counting function and overcome the trade-off presented by the computing power of local hardware. The cloud-based object-counting software consists of a model adapted to the object-counting task through a novel DBC-NMS (our own technique) and hyperparameter tuning of deep-learning-based object-detection methods. With the power of DBC-NMS and hyperparameter tuning, the performance of the cloud-based object-counting software is competitive over commonly used public datasets (CARPK and SKU110K) and our custom dataset of small pills. Our cloud-based object-counting software achieves an mean absolute error (MAE) of 1.03 and a root mean squared error (RMSE) of 1.20 on the Pill dataset. These results demonstrate that the proposed smart counting system accurately detects and counts densely distributed object scenes. In addition, the proposed system shows a reasonable and efficient cost–performance ratio by converging low-cost hardware and cloud-based software.

With the development of information technology and the Internet, users can conveniently use roaming services without time and space restrictions. This roaming service is initiated by establishing a session key between a home node, which exists in a home network, and a mobile node, which exists in a foreign network. However, in the process of verifying a legitimate user and establishing a session key, various security threats and privacy exposure issues can arise. This study demonstrates that the authentication scheme for the roaming service proposed in the existing Global Mobility Network (GLOMONET) environment has several vulnerabilities and, hence, is impractical. In addition, the scheme does not satisfy the privacy of the session key or user's identity or password. Accordingly, we propose a new lightweight authentication scheme to compensate for these vulnerabilities and secure a high level of privacy, such as non-traceability. In addition, formal and informal analyses are conducted to examine the safety of the proposed scheme. Based on the results of our analyses, we prove that the proposed scheme is highly secure and applicable to the actual GLOMONET environment.

Internet of Things (IoT) technology has recently been integrated with various healthcare devices to monitor patients’ health status and share it with their healthcare practitioners. Since healthcare data often contain personal and sensitive information, healthcare systems must provide a secure user authentication scheme. Recently, Adavoudi-Jolfaei et al. and Sharma and Kalra proposed a lightweight protocol using hash function encryption only for user authentication on wireless sensor systems. In this paper, we found some weaknesses in target schemes. We propose a novel three-factor lightweight user authentication scheme that addresses these weaknesses and verifies the security of the proposed scheme using a formal verification tool called ProVerif. In addition, our proposed scheme outperforms other proposed symmetric encryption-based schemes or elliptic curve-based schemes.

With the evolution of communication technology and the exponential increase of mobile devices, the ubiquitous networking allows people to use our data and computing resources anytime and everywhere. However, numerous security concerns and complicated requirements arise as these ubiquitous networks are deployed throughout people's lives. To meet the challenge, the user authentication schemes in ubiquitous networks should ensure the essential security properties for the preservation of the privacy with low computational cost. In 2017, Chaudhry et al. proposed a password-based authentication scheme for the roaming in ubiquitous networks to enhance the security. Unfortunately, we found that their scheme remains insecure in its protection of the user privacy. In this paper, we prove that Chaudhry et al.'s scheme is vulnerable to the stolen-mobile device and user impersonation attacks, and its drawbacks comprise the absence of the incorrect login-input detection, the incorrectness of the password change phase, and the absence of the revocation provision. Moreover, we suggest a possible way to fix the security flaw in Chaudhry et al's scheme by using the biometric-based authentication for which the bio-hash is applied in the implementation of a three-factor authentication. We prove the security of the proposed scheme with the random oracle model and formally verify its security properties using a tool named ProVerif, and analyze it in terms of the computational and communication cost. The analysis result shows that the proposed scheme is suitable for resource-constrained ubiquitous environments.

Wireless sensor networks are widely used in many applications such as environmental monitoring, health care, smart grid and surveillance. Many security protocols have been proposed and intensively studied due to the inherent nature of wireless networks. In particular, Wu et al. proposed a promising authentication scheme which is sufficiently robust against various attacks. However, according to our analysis, Wu et al.’s scheme has two serious security weaknesses against malicious outsiders. First, their scheme can lead to user impersonation attacks. Second, user anonymity is not preserved in their scheme. In this paper, we present these vulnerabilities of Wu et al.’s scheme in detail. We also propose a new scheme to complement their weaknesses. We improve and speed up the vulnerability of the Wu et al. scheme. Security analysis is analyzed by Proverif and informal analysis is performed for various attacks.