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The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.

The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.

The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.

Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

The purpose of this paper is to provide a detailed insight into the global military robot industry with an emphasis on products and their applications.

Following an introduction which includes a brief historical account, this provides an industry overview, including various market dimensions and a discussion of the geopolitical and technological factors driving market development. The three following sections provide details of land, airborne and marine robots, their capabilities and deployments in recent conflicts. Finally, brief conclusions are drawn.

Military robots which operate on land, in the air and at sea constitute a multi-billion dollar industry which is growing rapidly. It is being driven by geopolitical tensions, notably the military-technology arms race between China and the USA and the conflict in Ukraine, together with technological progress, particularly in AI. Many robots possess multi-functional capabilities, and the leading application is presently intelligence, surveillance and reconnaissance. An increasing number of heavily armed robots are being developed, and AI has the potential to impart these with the capacity to deliver lethal force without human intervention. Although heavily criticised in some quarters, this capability has probably already been deployed on the battlefield. With ever-growing military budgets, escalating political tensions and technological innovations, robots will play an increasingly significant role in future conflicts.

This provides a detail account of military robots and their role in modern warfare.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

This study aims to introduce a multi-configuration, three-finger dexterous hand with integrated high-dimensional sensors and provides an analysis of its design, modeling and kinematics.

A mechanical design scheme of the three-finger dexterous hand with a reconfigurable palm is proposed based on the existing research on dexterous hands. The reconfigurable palm design enables the dexterous hand to achieve four grasping modes to adapt to multiple grasping tasks. To further enhance perception, two six-axis force and torque sensors are integrated into each finger. The forward and inverse kinematics equations of the dexterous hand are derived using the D-H method for kinematics modeling, thus providing a theoretical model for index analysis. The performance is evaluated using three widely applied indicators: workspace, interactivity of fingers and manipulability.

The results of kinematics analysis show that the proposed hand has excellent dexterity. Additionally, three different experiments are conducted based on the proposed hand. The performance of the dexterous hand is also verified by fingertip force, motion accuracy test, grasping and in-hand manipulation experiments based on Feix taxonomy. The results show that the dexterous hand has good grasping ability, reproducing 82% of the natural movement of the human hand in daily grasping activities and achieving in-hand manipulations such as translation and rotation.

A novel three-finger dexterous hand with multi-configuration and integrated high-dimensional sensors is proposed. It performs better than the previously designed dexterous hand in actual experiments and kinematic performance analysis.

The purpose of this paper is to present an optimisation of four-point star-shaped structures produced through additive manufacturing (AM) polylactic acid (PLA). The study also aims to investigate the compression failure mechanism of the structure.

A Taguchi L₉ orthogonal array design of the experiment is adopted in which the input parameters are resolution (0.06, 0.15 and 0.30 mm), print speed (60, 70 and 80 mm/s) and bed temperature (55°C, 60°C, 65°C). The response parameters considered were printing time, material usage, compression yield strength, compression modulus and dimensional stability. Empirical observations during compression tests were used to evaluate the load–response mechanism of the structures.

The printing resolution is the most significant input parameter. Material length is not influenced by the printing speed and bed temperature. The compression stress–strain curve exhibits elastic, plateau and densification regions. All the samples exhibit negative Poisson’s ratio values within the elastic and plateau regions. At the beginning of densification, the Poisson’s ratios change to positive values. The metamaterial printed at a resolution of 0.3 mm, 80 mm/s and 60°C exhibits the best mechanical properties (yield strength and modulus of 2.02 and 58.87 MPa, respectively). The failure of the structure occurs through bending and torsion of the unit cells.

The optimisation study is significant for decision-making during the 3D printing and the empirical failure model shall complement the existing techniques for the mechanical analysis of the metamaterials.

To the best of the authors’ knowledge, for the first time, a new empirical model, based on the uniaxial load response and “static truss concept”, for failure mechanisms of the unit cell is presented.

Identification of the direction of the sound source is very important for human–machine interfacing in the applications such as target detection on military applications and wildlife conservation. Considering its vast applications, this study aims to design, simulate, fabricate and test a bidirectional acoustic sensor having two cantilever structures coated with piezoresistive material for sensing has been designed, simulated, fabricated and tested.

The structure is a piezoresistive acoustic pressure sensor, which consists of two Kapton diaphragms with four piezoresistors arranged in Wheatstone bridge arrangement. The applied acoustic pressure causes diaphragm deflection and stress in diaphragm hinge, which is sensed by the piezoresistors positioned on the diaphragm. The piezoresistive material such as carbon or graphene is deposited at maximum stress area. Furthermore, the Wheatstone bridge arrangement has been formed to sense the change in resistance resulting into imbalanced bridge and two cantilever structures add directional properties to the acoustic sensor. The structure is designed, fabricated and tested and the dimensions of the structure are chosen to enable ease of fabrication without clean room facilities. This structure is tested with static and dynamic calibration for variation in resistance leading to bridge output voltage variation and directional properties.

This paper provides the experimental results that indicate sensor output variation in terms of a Wheatstone bridge output voltage from 0.45 V to 1.618 V for a variation in pressure from 0.59 mbar to 100 mbar. The device is also tested for directionality using vibration source and was found to respond as per the design.

The fabricated devices could not be tested for practical acoustic sources due to lack of facilities. They have been tested for a vibration source in place of acoustic source.

The piezoresistive bidirectional sensor can be used for detection of direction of the sound source.

In defense applications, it is important to detect the direction of the acoustic signal. This sensor is suited for such applications.

The present paper discusses a novel yet simple design of a cantilever beam-based bidirectional acoustic pressure sensor. This sensor fabrication does not require sophisticated cleanroom for fabrication and characterization facility for testing. The fabricated device has good repeatability and is able to detect the direction of the acoustic source in external environment.

This study explores the deep integration of digital technology and cultural heritage to promote the preservation and inheritance of cultural heritage. Focusing on Digital Cultural Heritage (DCH), this research investigates its key role in activating theoretical research and practical applications in cultural heritage.

This study conducted an extensive bibliometric analysis utilizing VOSviewer and Bibliometrix visualization software to meticulously examine DCH research. Insights were gleaned from a dataset comprising 2,997 DCH-related publications harvested from the Web of Science database.

The bibliometric analysis reveals several notable findings: driven by active contributions from Italy, China, Spain, and the USA, the number of DCH publications shows a linear upward trend. Consiglio Nazionale delle Ricerche in Italy emerges as a prominent institution, while the Journal of Cultural Heritage stands out as the most influential journal in the DCH field. Scholars such as Remondino, Guidi, Barazzetti, and Carrozzino have significantly impacted DCH research. Furthermore, an in-depth analysis of keyword co-occurrence networks elucidates six major research trajectories in the DCH field, covering various aspects from cultural heritage digitization to digital humanities.

The study emphasizes the value of global knowledge exchange, interdisciplinary collaboration, innovative technology applications, and digital content provision practices in advancing DCH research.

By delving into the multifaceted landscape of DCH research, this study brings forth original insights into the escalating trends, pivotal contributors, and burgeoning research directions.

The purpose of this paper is to introduce an aid for teaching transverse flux permanent magnet machines (TFPMs) with emphasis on their torque production.

The Lorentz force law is applied to fictitious current loops emulating the permanent magnets (PMs) mounted on the rotor according to different arrangements; the air gap flux density is created by the armature current.

Implemented in a master lecture on special AC machines, the proposed approach has revealed a renewed interest in electromagnetic fundamentals for pedagogical purposes. It makes simple the explanation of the principle of operation of a class of AC machines reputed by the complexity of their magnetic circuits. The latter incorporates axially stacked decoupled sub-circuits, one per phase generating alternating magnetic fields. More specifically, there is common air gap, shared by the machine phases, in which a rotating magnetic field is created by the superposition of the PM contribution and the armature one.

Accounting for the complexity of the magnetic circuits and the three-dimensional (3D) flux paths characterizing TFPMs, a 3D finite element analysis (FEA) is required for the validation of the analytical predictions. Nevertheless, such a 3D FEA validation is far from being obvious to be carried on within a master lecture.

While the basis of Lorentz forces resulting from fictitious current loops emulating PMs has been considered in some referenced papers, its simple and pedagogical application to assess the torque production of several TFPM concepts represents the added value of the present paper.