Terahertz remote sensing

Recently, the so-called perfect absorbers, which are light-trapping nanostructures absorbing almost 100% of incident light with a designed wavelength, have attracted significant attention. The perfect absorbers consist of multilayers (absorption, dielectric, and mirror layers), which can be theoretically realized by any combination of materials. However, in order to achieve properties useful for a specific purpose, it is necessary to tune the optical properties of the absorption and dielectric layers by introducing metamaterials into the layered structures. Oblique-angle deposition (OAD) is one of the most powerful techniques to tailor metamaterials, which include well-controlled nanomorphologies significantly smaller than the wavelength of visible light, enabling the control of optical properties of various materials in different wavelength regions, from ultraviolet to infrared, at low costs. In this paper, we present several types of perfect absorbers fabricated by the OAD technique and their applications to photocatalysts, biochemical sensors, optical elements, and thermoplasmonic control of microfluidics.

THz imaging and spectroscopy using intense THz sources at the advanced laser light source

The detection of concealed objects like weapon, explosives, and other dangerous items became very important problem for defending people against terrorist attacks. Recent time, many methods have been developed but number of methods are not efficient to effectively solve this problem. The main aim of the research in this work is devoted to the detection of concealed dangerous objects by increasing sensitivity and resolution in obtained images. In this paper, we propose to use inverse synthetic aperture radar (ISAR) technology for the detection of hidden items in the millimeter-wave length. The millimeter-wave ISAR imaging of concealed cubes and a gun are studied. The theoretical background employed for the reconstruction of measurement results is briefly described. The millimeter-wave ISAR measurement setup is presented. Then, measurements carried out for different scenarios are explained. Finally, the reconstructed results are shown for all conducted measurements.

Detecting concealed objects, anatomical keypoints, and segmenting human body parts in backscatter millimeter-wave images are essential tasks for enhancing airport security and transportation safety. However, the deployment of reliable automated systems is challenged by factors such as poor image quality, scarce detailed annotations, and stringent privacy regulations. To address these issues, we introduce EfficientPoseSegNet, a hybrid deep learning framework designed for efficient annotation use, concealed object detection, and body-aware analysis in security screening images. The model leverages parallel EfficientNet and DenseNet backbones to capture rich multi-scale features from low-resolution scans, refined using a Convolutional Block Attention Module (CBAM) to enhance focus on critical anatomical areas while reducing background noise. Instead of directly predicting joint coordinates, EfficientPoseSegNet outputs spatial heatmaps representing the confidence of anatomical keypoints. These keypoints are then extracted via soft-argmax and used to segment the human body into 17 anatomical regions. To further improve robustness and generalization under weak supervision, we incorporate a task-aware, confidence-weighted adaptation of Stochastic Weight Averaging (SWA), which stabilizes training and enhances multi-task performance. Additionally, we integrate an anomaly detection module that leverages anatomical segmentation features to identify concealed objects in body regions, addressing the ultimate operational goal of airport security screening. Tested on the Transportation Security Administration Passenger Screening Dataset, the model achieves a test loss of 3.9335, mean absolute error of 1.4330 pixels, keypoint accuracy of 99.79% within a 10-pixel threshold, pose estimation accuracy of 99%, segmentation Intersection over Union (IoU) of 97%, and an average anomaly detection AUC of 0.94 across body regions. This approach contributes significantly to Transportation Science and Logistics by enabling scalable, privacy-compliant, and real-time human pose estimation, body part segmentation, and concealed object detection in fast-paced airport screening settings.

The detection of concealed suspicious objects in public places is a critical issue and a popular research topic. Terahertz (THz) imaging technology, as an emerging detection method, can penetrate materials without emitting ionizing radiation, providing a new approach to detecting concealed suspicious objects. This study focuses on the detection of concealed suspicious objects wrapped in different materials such as polyethylene and kraft paper, including items like scissors, pistols, and blades, using THz imaging technology. To address issues such as the lack of texture details in THz images and the contour similarity of different objects, which can lead to missed detections and false alarms, we propose a THz concealed suspicious object detection model based on SMR–YOLO (SPD_Mobile + RFB + YOLO). This model, based on the MobileNext network, introduces the spatial-to-depth convolution (SPD-Conv) module to replace the backbone network, reducing computational and parameter load. The inclusion of the receptive field block (RFB) module, which uses a multi-branch structure of dilated convolutions, enhances the network’s depth features. Using the EIOU loss function to assess the accuracy of predicted box localization further optimizes convergence speed and localization accuracy. Experimental results show that the improved model achieved mAP@0.5 and mAP@0.5:0.95 scores of 98.9% and 89.4%, respectively, representing improvements of 0.2% and 1.8% over the baseline model. Additionally, the detection speed reached 108.7 FPS, an improvement of 23.2 FPS over the baseline model. The model effectively identifies concealed suspicious objects within packages, offering a novel approach for detection in public places.

As it is well-known, the passive THz camera allows seeing concealed object without contact with a person and this camera is non-dangerous for a person. Obviously, efficiency of using the passive THz camera depends on its temperature resolution. This characteristic specifies possibilities of the detection for concealed object: minimal size of the object; maximal distance of the detection; image quality. Computer processing of the THz image may lead to many times improving of the image quality without any additional engineering efforts. Therefore, developing of modern novel computer code for its application to THz images is urgent problem. Using appropriate new methods one may expect such temperature resolution which will allow to see banknote in pocket of a person without any real contact. Modern algorithms for computer processing of THz images allow also to see object inside the human body using a temperature trace on the human skin. This circumstance enhances essentially opportunity of passive THz camera applications for counterterrorism problems. We developed new real-time algorithm, based on the correlation function, for the detection of cancelled objects by using computer processing of the passive THz images without their viewing. This algorithm allows us to make a conclusion about presence of forbidden objects on the human body. To see this object with high quality we propose one more algorithm which allows to increase the image quality. Current approach for computer processing of the THz images differs from approaches developed by us early. We apply new algorithms with success to the images captured by passive THz camera TS4 manufactured by ThruVision Inc. The distance between the camera and person is changed from 4 to 10 metres.

The detection of concealed objects in the baggage by non-invasive methods has become a very important issue in the border control process. This paper is concerned with the multiple inverse scattering of the plane wave on various objects or scatterrers by using µ-diff MATLAB open-source toolbox. The acquired information is corelated with the material nature (i.e. steel, salt, neoprene and PVC) for different measured orientation of the scatterers. The non-invasive detection of concealed objects represents a huge challenge, which has attracted particular attention due to a heightened threat of terrorism. The Fourier series and on four integral equations, i.e. Electric Field Integral Equation (EFIE), Magnetic Field Integral Equation (MFIE), Combined Field Integral Equation (CFIE) and Brakhage-Werner Integral Equation (BWIE) generate the approximation framework able to solve the multiple scattering problems. A multi-frequency scattering data approach is adopted and a low frequency domain is proposed for detecting concealed objects in the luggage.

Multispectral systems for detection of concealed dangerous objects are becoming more popular because of their higher effectiveness compared to mono-spectral systems. So far, the problem of detecting objects hidden under clothing was considered only in the case of airports but it is becoming more important for public places like metro stations, and government buildings. Exploration of new spectral bands as well as development of technology result in introduction of new solutions – both mono and multispectral. It has been proved that objects hidden under clothing can be detected and visualized using terahertz (THz) cameras. However, passive THz cameras still offer too low image resolution for objects recognition. Limited range is another issue of passive imagers. On the other hand new infrared cameras offer sufficient parameters to detect objects covered with fabrics in some conditions, as well as high image quality and big pixel resolutions. The purpose of the studies is to investigate and compare the possibilities of using passive cameras operating in long wavelength infrared (LWIR) and THz spectral ranges for detection of concealed objects. For the purpose of investigations, commercial imagers operating in 6.5-11.7 μm and 250GHz (1.25mm) were used. In the article, we present the measurement setup and the results of measurements in various operating conditions. Theoretical studies of both spectral bands focused on detection of objects with passive imagers are also presented.

This paper reports development of a passive millimeter wave imaging system for detection of concealed objects using sparse characterization and reconstruction algorithm based on CS theory. By measuring the radiometric temperatures of different objects, passive millimeter wave imaging can acquire images of objects concealed underneath clothing. In this system a millimeter wave antenna controlled by revolving table receives the passive millimeter signal from target object. As passive millimeter wave images have poor contrast and low signal to noise ratio, traditional segmentation algorithms are unable to detect concealed objects, so this system uses a method which transforms the image signal by a non-adaptive base matrix. The high-dimensional signal will be transformed to a lower dimensional space, and then solve an optimization problem for the highest sparsity of the signal through the gradient projection. We present experimental results of 94GHz passive millimeter wave images.

<div class="htmlview paragraph">Cooling system design considerations for vehicles powered by advanced low temperature charge air cooled engines are reviewed. Current low flow radiator design practices for on highway applications are contrasted to cooling system design considerations for on/off and off highway equipment. The impact of auxiliary heat loads associated with torque convertor oil coolers is outlined and the advantages and disadvantages of optional systems are discussed.</div>

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable computational processing would be required for automatic analysis of the images. The authors present statistical and computational algorithms and their implementations for real-time concealed object detection. The histogram of the image is modeled as a Gaussian mixture distribution, and hidden object areas are segmented by a multilevel scheme involving the expectation-maximization algorithm. The complete algorithm has been implemented in both MATLAB and C++. Experimental and simulation results confirm that the implemented system can achieve real-time detection of concealed objects.

Applications of pedagogical agent (PA) systems incorporating animated characters in school settings have mainly addressed students at an individual level. However, how these systems could be used and designed for supporting teachers while taking advantage of artificial intelligence (AI) technology is an open question. Therefore, we carried out a focus group to understand what teachers would expect and need from such a system at a classroom level. Our focus group protocol sought to discover design and practical considerations in four dimensions. 1) System design considerations, where teachers expect the system to incorporate speech recognition and to “learn” from them while doing their practice. 2) System collaboration, teachers wanted support in their pedagogy by considering students’ achievement profiles, and by finding and sorting learning material as needed. 3) PA role in the classroom, we identified the following roles: annotator, scaffolder, peacekeeper, and substitute. 4) PA ethical considerations, teachers perceive PA as a possible replacement threat and controversial opinions on the use and meaning making of this technology. We discuss our findings and present future research directions to develop a PA that could empower teachers with AI pedagogy in the classroom, hence, indirectly supporting learning.KeywordsPedagogical agentClassroom level technologyArtificial intelligence pedagogyFocus groupEducational technology

This paper addresses passive millimeter wave imaging (PMMW) and image fusion for concealed object detection. The PMMW imaging system forms images by means of passive detection of millimeter wave radiation. The PMMW imaging has the capability of detecting concealed metal and dielectric objects under clothing. An image fusion method is developed using the discrete wavelet transform (DWT) and a fusion rule. We adopt the symlets (symmetrical wavelets) for the multi-resolution analysis (MRA). The minimum scheme is applied to the approximation and the weighted-average scheme to the detail coefficients. The experimental and simulation results show the presented technique can detect the concealed object and fuse it with a visual image.

With the advancements in aircraft gas turbine engine technology over the past decade (in materials, structures, and analytical design methods) along with those anticipated for the next decade, there is renewed interest in the Mach 3.0 to 6.0 operating regime for both commercial transports and military weapon systems. The propulsion systems for these airplanes will in all probability be a function of the flight regime selected for a particular application; i.e., a turbofan engine for Mach<4.0, and a dual mode turboramjet for the Mach 4.0 to 6.0 aircraft. There are a number of component technologies that will have to be developed for the propulsion system before these applications can become a reality. This paper addresses some of the tasks that will have to be accomplished relative to one of those components: the exhaust nozzle system. Introduction The exhaust nozzle system is a unique component which requires integration with the airplane system components (engine, winglbody, inlet) as well as special design considerations for acoustics and off-design point operation in order to optimize the overall system performance. The design requirements for the exhaust system stem from two sources: the airplane and the engine (see Figure 1). Requirement 0 Airplane Sustained supersonic/subsonic operation Propulsion system integration Community noiw regulations Landing WeatherItiW brakes 0 Advanced engine technology Dual mode cycle High exhaust system temperature Figure 1. Factors Affecting Nozzle Design. EWct on nozzle Multiple design points. high WA,, and eiector nozzles Drag and propulsion system performance Acoustic design considerations Thrust reverser Bypau ducWvalw, variable area mixers, and secondary air systems Cooling/materia$ High exhaust system pressure ratios With reference to Figure 1, airplane performance and operational requirements have a direct impact on the exhaust system design. For example: sustained high Mach operation requires high nozzle area ratio capability for best efficiency with the nozzle possibly being an integral part of the airplane; for commercial transports, FAA noise regulations impact engine size and require noise ASIA8 excunion/seals/ st~ctures/~~1uaton suppression and treatment techniques; inletlengine airflow mismatching at transonic speeds may necessitate an ejector nozzle to reduce large spillage drags; and, landing operations may call for a thrust reverser for safety as well as prolonging the life of tires and brakes. Manager, Exhaust Systems & Installed Technology Member AIAA The engine cycle aerothermodynamic and operating characteristics also affect the nozzle design (reference Figure 1). For example: high nozzle pressure ratios again mean high area ratios for high performance; large changes in nozzle area ratio to optimize overall performance will more than likely result in nonaxisymmetric nozzles for Mach 4.0 to 6.0 applications; high tailpipe temperatures require more cooling air andlor different cooling schemes; high pressures in the nozzle will require innovative structural design approaches; and installed performance optimization may necessitate auxiliary air systems requiring ejector nozzles for performance optimization as well as for cooling. In addition, integration between the engine and aircraft companies will be absolutely essential in order to optimize the system (airplanelinletlenginelnozzle) installed performance. This paper will discuss some of the issues and design considerations for the Mach 4.0 to 6.0 aircraft with primary emphasis on turboramjet propulsion systems which utilize a common inlet and exhaust system for both operating modes. Some discussion relative to Mach 3f civil transports which utilize turbofan propulsion systems will also be included. Technical Discussion Expanded Airbreathing Propulsion Corridor The operating envelope for future high Mach aircraft is shown on Figure 2 compared to the regime for current aircraft (shaded area). The area of interest for this paper is Mach 2.5 to 6.0 where advanced technology turbofanlturbojet (Mach <4.0) and turboramjet (4.O<M<6.0) propulsion systems are being considered. The aircraft applications include military weapon systems for both defensive and offensive missions and commercial transports.

The following design considerations for long-haul lightwave systems are reviewed: outage and error rate requirements, terminal architecture, regenerator span design and performance specification, capacity upgrade alternatives, and broad-gauge economic factors.