Basic Detectors Research Articles

Comprehensive investigation of ternary dysprosium complexes for white light emission: Synthesis, spectroscopic and colorimetric analyses

Dysprosium (Dy3+) containing four single-molecule complexes with 1,3-diketone ligand, TFPB (4,4,4-trifluoro-1-phenyl-1,3-butadionate) along with neutral co-ligands of varying denticity were synthesized and two of them were explored as potential sources of near-white light emission. The choice of ligand as well as the coordination surroundings of Dy(III) ion significantly influence the blue (B: 4F9/2 → 6H15/2) and yellow (Y: 4F9/2 → 6H13/2) emissions. The inclusion of the auxiliary ligand such as topo in D1 leads to reduction in emission intensity compared to D2-D4 due to less effective sensitization. At room temperature, the CIE color coordinates for complexes D1 and D4 approach the coordinates of perfectly balanced and idealized white light (0.333, 0.333). Furthermore, Correlated Color Temperature (CCT) values for D1 and D4 characterize them as cold-white-light emitters, while the complexes D2 and D3 are categorized as a neutral-light emitter. In addition to their visible emissions, the semi-conducting properties and suitable deactivation lifetime corresponding to these synthesized complexes (D1-D4) have also been extensively studied and found potential applications in basic research, security printing, sensors, detectors and OLEDs.

Incipient fault detection based on ensemble learning and distribution dissimilarity analysis in multi-feature processes

Timely and accurate detection of incipient faults has attracted considerable attention and research interest in recent years, due to its potential for the prevention of serious safety incidents and for supporting preventive maintenance. However, most existing methods use single detection model, neglecting the coexistence of multiple features and the local data distribution information found in industrial scenes. To overcome this problem, an incipient fault detection method named multiple model ensemble and distribution dissimilarity analysis (MME-DISSIM) is proposed. First, various multivariate statistical analysis methods are employed as basic detectors to comprehensively capture the feature information hidden in the process data. Second, DISSIM analysis is performed to evaluate the dissimilarity between the current sliding window and each training subset. This evaluation allows for the calculation of weighting factors for each basic detector, which helps to preserve the local distribution information of the current sliding window. Third, ensemble learning is utilized to integrate the statistics from all basic detectors into two detection indices to determine the operation status of the system. In addition, two measurement metrics are defined to quantitatively analyze the fault level of incipient faults. Finally, several experiments on a numerical case, Tennessee Eastman process, and actual PROcess NeTwork Optimization are presented to verify the efficacy and superiority of the proposed method.

Adaptive multimodal feature fusion with frequency domain gate for remote sensing object detection

ABSTRACT Fusing complementary information of visible and infrared radiation modalities can improve object detection performance for unmanned aerial vehicle (UAV) remote sensing images under insufficient illumination conditions. Although previous works have conducted some studies in this field, they have rarely considered the adaptive ability of multimodal feature fusion, which limits the performance improvement space for multimodal detectors. To this end, we propose an adaptive multimodal feature fusion method with a frequency domain gate based on DINO (detection transformer with improved denoising anchor boxes), called multimodal DINO. In our approach, a multimodal feature encoder with underlying feature sharing is designed, which efficiently extracts common and differential features through RGB-guided infrared radiation data transformation. Additionally, an adaptive frequency domain gate is introduced to dynamically learn the degree of dependence on frequency-filtered features of each modality when processing different samples. We evaluate the proposed method on the two multimodal detection remote sensing image datasets, VEDAI and DroneVehicle. Extensive experiments demonstrate that our approach achieves superior performance compared to basic detectors and existing multimodal detection methods. Our code is available at https://github.com/cq100/multimodalDINO.

Feature Ensemble Net: A Deep Framework for Detecting Incipient Faults in Dynamical Processes

How to detect incipient faults has been an important problem in the field of fault detection. Although many types of machine and deep learning methods have been proposed, their performance is not as good as expected. In this article, a novel feature ensemble net (FENet) was developed, particularly for faults 3, 9, and 15 in the Tennessee Eastman process (TEP), which are notoriously difficult to detect. For the input feature layer, features extracted by the basic detectors are integrated to expand the detection ability of FENet. For the hidden feature transformer layers, with sliding-window patches and principal component analysis (PCA), the previous feature matrix is transformed. The sliding-window patches can be used to generate singular values, whereas the patches in the well-known convolution technique can only be vectorized, primarily for performing PCA in PCA-based networks. This enhances the sensitivity of the FENet to incipient faults. For the output feature layer, all feature matrices in the last hidden layer are completely stacked into a large feature matrix. The sliding technique is performed at the decision layer, and a detection index is designed with normalized singular values. The superiority of FENet can be completely verified by a continuous stirred tank heater and TEP. As compared with deep PCA, PCA-based monitoring network, and typical ensemble strategies, such as averaging, voting, stacking, and Bayesian inference, FENet can effectively detect Faults 3, 9, and 15 in TEP.

Design and performance of the prototype Schwarzschild-Couder telescope camera

The prototype Schwarzschild-Couder Telescope (pSCT) is a candidate for a medium-sized telescope in the Cherenkov Telescope Array. The pSCT is based on a novel dual mirror optics design which reduces the plate scale and allows for the use of silicon photomultipliers as photodetectors. The prototype pSCT camera currently has only the central sector instrumented with 25 camera modules (1600 pixels), providing a 2.68$^{\circ}$ field of view (FoV). The camera electronics are based on custom TARGET (TeV array readout with GSa/s sampling and event trigger) application specific integrated circuits. Field programmable gate arrays sample incoming signals at a gigasample per second. A single backplane provides camera-wide triggers. An upgrade of the pSCT camera is in progress, which will fully populate the focal plane. This will increase the number of pixels to 11,328, the number of backplanes to 9, and the FoV to 8.04$^{\circ}$. Here we give a detailed description of the pSCT camera, including the basic concept, mechanical design, detectors, electronics, current status and first light.

Monte Carlo Computational Software and Methods in Radiation Dosimetry

The fast developments and ongoing demands in radiation dosimetry have piqued the attention of many software developers and physicists to create powerful tools to make their experiments more exact, less expensive, more focused, and with a wider range of possibilities. Many software toolkits, packages, and programs have been produced in recent years, with the majority of them available as open source, open access, or closed source. This study is mostly focused to present what are the Monte Carlo software developed over the years, their implementation in radiation treatment, radiation dosimetry, nuclear detector design for diagnostic imaging, radiation shielding design and radiation protection. Ten software toolkits are introduced, a table with main characteristics and information is presented in order to make someone entering the field of computational Physics with Monte Carlo, make a decision of which software to use for their experimental needs. The possibilities that this software can provide us with allow us to design anything from an X-Ray Tube to whole LINAC costly systems with readily changeable features. From basic x-ray and pair detectors to whole PET, SPECT, CT systems which can be evaluated, validated and configured in order to test new ideas. Calculating doses in patients allows us to quickly acquire, from dosimetry estimates with various sources and isotopes, in various materials, to actual radiation therapies such as Brachytherapy and Proton therapy. We can also manage and simulate Treatment Planning Systems with a variety of characteristics and develop a highly exact approach that actual patients will find useful and enlightening. Shielding is an important feature not only to protect people from radiation in places like nuclear power plants, nuclear medical imaging, and CT and X-Ray examination rooms, but also to prepare and safeguard humanity for interstellar travel and space station missions. This research looks at the computational software that has been available in many applications up to now, with an emphasis on Radiation Dosimetry and its relevance in today's environment.

Scalable electronic readout design for a 100 ps coincidence time resolution TOF-PET system

We have developed a scalable detector readout design for a 100 ps coincidence time resolution (CTR) time of flight (TOF) positron emission tomography (PET) detector technology. The basic scintillation detectors studied in this paper are based on 2 × 4 arrays of 3 × 3 × 10 mm3 ‘fast-LGSO:Ce’ scintillation crystals side-coupled to 6 × 4 arrays of 3 × 3 mm2 silicon photomultipliers (SiPMs). We employed a novel mixed-signal front-end electronic configuration and a low timing jitter Field Programming Gate Array-based time to digital converter for data acquisition. Using a 22Na point source, >10 000 coincidence events were experimentally acquired for several SiPM bias voltages, leading edge time-pickoff thresholds, and timing channels. CTR of 102.03 ± 1.9 ps full-width-at-half-maximum (FWHM) was achieved using single 3 × 3 × 10 mm3 ‘fast-LGSO’ crystal elements, wrapped in Teflon tape and side coupled to a linear array of 3 SiPMs. In addition, the measured average CTR was 113.4 ± 0.7 ps for the side-coupled 2 × 4 crystal array. The readout architecture presented in this work is designed to be scalable to large area module detectors with a goal to create the first TOF-PET system with 100 ps FWHM CTR.

Unsupervised Temporal Contiguity Experience Does Not Break the Invariance of Orientation Selectivity Across Spatial Frequency.

The images projected onto the retina can vary widely for a single object. Despite these transformations primates can quickly and reliably recognize objects. At the neural level, transformation tolerance in monkey inferotemporal cortex is affected by the temporal contiguity statistics of the visual input. Here we investigated whether temporal contiguity learning also influences the basic feature detectors in lower levels of the visual hierarchy, in particular the independent coding of orientation and spatial frequency (SF) in primary visual cortex. Eight male Long Evans rats were repeatedly exposed to a temporal transition between two gratings that changed in SF and had either the same (control SF) or a different (swap SF) orientation. Electrophysiological evidence showed that the responses of single neurons during this exposure were sensitive to the change in orientation. Nevertheless, the tolerance of orientation selectivity for changes in SF was unaffected by the temporal contiguity manipulation, as observed in 239 single neurons isolated pre-exposure and 234 post-exposure. Temporal contiguity learning did not affect orientation selectivity in V1. The basic filter mechanisms that characterize V1 processing seem unaffected by temporal contiguity manipulations.

Radiation Hardness of Scintillation Detectors Based on Organic Plastic Scintillators and Optical Fibers

Scintillation detectors (SD) based on organic plastic scintillators and optical fibers are basic detectors at all modern accelerators and in astrophysics and neutrino physics experiments. In recent years, interest in SD has significantly increased due to the upcoming major upgrade of the LHC and the construction of new accelerators NICA, FAIR, FCC, etc. At the same time, requirements on the stability and reliability of SD operation under new conditions have become stricter, and their fulfillment largely depends on radiation hardness of scintillators, optical fibers, and photodetectors. The review presents the results of the radiation hardness investigations of various scintillators, optical fibers (scintillating, as well as wavelength-shifting and clear), and optical glues used to increase light collection from scintillators by fibers. The influence of various factors (dose, dose rate, type of radiation, scintillator materials, and fluors) on light output, light collection, and transmittance of the irradiated materials and their recovery is considered. Aging of scintillators caused by environmental effects (temperature, humidity) irrespective of radiation is also briefly considered.

A mobile complex to record several secondary cosmic rays components

The paper presents a research of the different components variations of the secondary cosmic rays (SCR). These are being monitored at the Cosmic Rays Laboratory, PGI, Apatity, using an integrated set based on the SCR basic components detectors. Also, besides stationary equipment, a mobile complex has been developed and made, which consists of a scintillation spectrometer, a charged component detector (CCD) based on the Geiger-Muller counters, and a neutron component detector (Е > 1 MeV) based on helium counters SNM-18. The mobile complex was put into operation in the early 2019. It operates in parallel with the basic equipment, recording SCRs. Small dimensions, effective energy consumption and ability to record data onto flash drives allows this complex to be used in SCR-monitoring in remote places, as well as on ships away at sea.

A novel ECG detector performance metric and its relationship with missing and false heart rate limit alarms

PurposePerformance of ECG beat detectors is traditionally assessed on long intervals (e.g.: 30min), but only incorrect detections within a short interval (e.g.: 10s) may cause incorrect (i.e., missed+false) heart rate limit alarms (tachycardia and bradycardia). We propose a novel performance metric based on distribution of incorrect beat detection over a short interval and assess its relationship with incorrect heart rate limit alarm rates. Basic proceduresSix ECG beat detectors were assessed using performance metrics over long interval (sensitivity and positive predictive value over 30min) and short interval (Area Under empirical cumulative distribution function (AUecdf) for short interval (i.e., 10s) sensitivity and positive predictive value) on two ECG databases. False heart rate limit and asystole alarm rates calculated using a third ECG database were then correlated (Spearman's rank correlation) with each calculated performance metric. Main findingsFalse alarm rates correlated with sensitivity calculated on long interval (i.e., 30min) (ρ=−0.8 and p<0.05) and AUecdf for sensitivity (ρ=0.9 and p<0.05) in all assessed ECG databases. Sensitivity over 30min grouped the two detectors with lowest false alarm rates while AUecdf for sensitivity provided further information to identify the two beat detectors with highest false alarm rates as well, which was inseparable with sensitivity over 30min. Principal conclusionsShort interval performance metrics can provide insights on the potential of a beat detector to generate incorrect heart rate limit alarms.

Visual Stimulus Speed Does Not Influence the Rapid Emergence of Direction Selectivity in Ferret Visual Cortex

Sensory experience is necessary for the development of some receptive field properties of neurons in primary sensory cortical areas. However, it remains unclear whether the parameters of an individual animal's experience play an instructive role and influence the tuning parameters of cortical sensory neurons as selectivity emerges, or rather whether experience merely permits the completion of processes that are fully seeded at the onset of experience. Here we have examined whether the speed of visual stimuli that are presented to visually naive ferrets can influence the parameters of speed tuning and direction selectivity in cortical neurons. Visual experience is necessary for the development of direction selectivity in carnivores. If, during development, cortical neurons had the flexibility to choose from among different inputs with a range of spatial positions and temporal delays, then correlation-based plasticity mechanisms could instruct the precise spatiotemporal selectivity that underlies speed tuning and direction selectivity, and the parameters of an individual animal's experience would influence the tuning that emerges. Alternatively, the tuning parameters of these neurons may already be established at the onset of visual experience, and experience may merely permit the expression of this tuning. We found that providing different groups of animals with either slow (12.5 deg/s) or fast (50 deg/s) visual stimuli resulted in emergence of direction selectivity, but that speed tuning and direction selectivity were similar in the two groups. These results are more consistent with a permissive role for experience in the development of direction selectivity.SIGNIFICANCE STATEMENT The proper development of brain circuits and neural response properties depends on both nature (factors independent of experience) and nurture (factors dependent on experience). In this study, we examined whether the quality of visual experience of an individual animal influences the development of basic sensory detectors in primary visual cortex. We found that, although visual experience is required for the development of direction selectivity, tuning for stimulus speed could not be altered by specific experience with slow or fast stimuli. These results suggest that the tuning parameters for direction selectivity are specified independently of an animal's sensory experience, and that a range of experiences can promote the proper mature expression of direction selectivity in primary visual cortex.

Scintillation Detectors in Modern High Energy Physics Experiments and Prospect of Their use in Future Experiments

The scintillation detector (SD) based on organic plastic scintillator (OPS) is one of the basic detectors in HEP experiments. Technologies for production of OPSs as strips and tiles, their optical and physical properties, light collection based on wavelength shifting (WLS) fibers coupled to multipixel vacuum and silicon PMs are presented. SDs are multifunctional: calorimeters, triggers, tracking, time-of-flight and veto systems are the examples of their applications. The use of SDs in many HEP experiments on the search for quarks, new particles and H bosons (D0, ATLAS, CMS), quark-gluon plasma (ALICE), CP violation (LHCb, KLOE), ν-oscillation (MINOS, OPERA), cosmic particles (AMS-02) are discussed. SDs hold great promise for future HEP experiments due to their ability of high segmentation, WLS fiber light collection and multipixel silicon PM readout.

눈 검출에서의 픽셀 선택을 이용한 신뢰 척도

본 논문에서는, 눈 검출에서의 픽셀 선택 방법을 이용한 편향 판별 분석(BDA) 기반의 신뢰 척도를 제안하고 이를 이용하여 hybrid 눈 검출기를 설계한다. 이를 위해 눈 조각 영상에서 먼저 판별 분석에 유용한 픽셀들을 선택하여 부분 영상을 만들고, 부분 영상에 BDA를 적용하여 신뢰 척도를 위한 특징 공간을 구성한다. Hybrid 눈 검출기를 구성하는 기본 검출기로는 상호 보완적인 특성을 가진 HFED와 MFED를 사용하였다. 주어진 영상에 대해, 기본 검출기들에 의해 생성된 눈 좌표를 가지고 생성한 눈 조각 영상의 부분 영상들을 BDA 특징공간에 투영하여 positive 샘플의 평균과의 거리를 측정함으로써 그 정확성을 측정하고, 기본 검출기의 결과들 중에서 신뢰도가 높은 결과를 최종 눈 검출 결과로 사용한다. 다양한 얼굴 데이터베이스들에 대한 실험 결과에서, 제안한 방법은 검출된 눈 좌표의 정확도 측면에서 뿐만 아니라 검출된 눈 좌표를 이용한 얼굴 인식 성능에서도 다른 방법들보다 우수한 결과를 나타내었다. In this paper, we propose a new confidence measure using pixel selection for eye detection and design a hybrid eye detector. For this, we produce sub-images by applying a pixel selection method to the eye patches and construct the BDA(Biased Discriminant Analysis) feature space for measuring the confidence of the eye detection results. For a hybrid eye detector, we select HFED(Haar-like Feature based Eye Detector) and MFED(MCT Feature based Eye Detector), which are complementary to each other, as basic detectors. For a given image, each basic detector conducts eye detection and the confidence of each result is estimated in the BDA feature space by calculating the distances between the produced eye patches and the mean of positive samples in the training set. Then, the result with higher confidence is adopted as the final eye detection result and is used to the face alignment process for face recognition. The experimental results for various face databases show that the proposed method performs more accurate eye detection and consequently results in better face recognition performance compared with other methods.

Scintigraphic evaluation of the kidney

There are more than one technique used to evaluate the kidney, besides the standard ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), there is also renal scintigraphy. The renal nuclear medicine procedures are grouped as in vitro (urine counting wells, basic probe detectors for clearance studies) and in vivo procedures (static and/or dynamic examinations done with planar gamma cameras, and single-photon emission computed tomography (SPECT) to determine kidney parameters or for cortical imaging). Renal scintigraphy has been a useful tool, since the early 1950s, in the diagnosis and management of many pathological changes in the kidney, especially in measuring renal function (e.g. obstructive/nonobstructive uropathies, renal inflammatory diseases, tumours, renal hypertension, and renal transplant viability).

ИК-ФОТОЭЛЕКТРОНИКА: ФОТОННЫЕ ИЛИ ТЕПЛОВЫЕ ДЕТЕКТОРЫ? ПЕРСПЕКТИВЫ

Abstract. Infrared (IR) detectors play now an increasing role in different areas of human activity (e.g., in environmental surveillance, fire safety control, communications, space surveillance of the Earth, medical diagnostics, security and military applications, tracking and targeting, etc.). Discussed in the paper are issues associated with the development and exploitation of up to date basic IR radiation detectors and large-size (matrix) focal plane arrays (FPAs). Progress in research and development for applications IR FPAs has rendered significant influence on infrared technologies. Comparison of FPA detector performance characteristics is given with account of operational conditions and performance limits.

Compressed baryonic matter at FAIR: JINR participation

The scientific mission of the Compressed Baryonic Matter(CBM) experiment is the study of the nuclear matter properties at the high baryon densities in heavy ion collisions at the Facility of Antiproton and Ion Research (FAIR) in Darmstadt. We present the results on JINR participation in the CBM experiment. JINR teams are responsible on the design, the coordination of superconducting(SC) magnet manufacture, its testing and installation in CBM cave. Together with Silicon Tracker System it will provide the momentum resolution better 1[Formula: see text] for different configuration of CBM setup. The characteristics and technical aspects of the magnet are discussed. JINR plays also a significant role in the manufacture of two straw tracker station for the muon detection system. JINR team takes part in the development of new method for simulation, processing and analysis experimental data for different basic detectors of CBM.

Target detection based on a dynamic subspace

For hyperspectral target detection, it is usually the case that only part of the targets pixels can be used as target signatures, so can we use them to construct the most proper background subspace for detecting all the probable targets? In this paper, a dynamic subspace detection (DSD) method which establishes a multiple detection framework is proposed. In each detection procedure, blocks of pixels are calculated by the random selection and the succeeding detection performance distribution analysis. Manifold analysis is further used to eliminate the probable anomalous pixels and purify the subspace datasets, and the remaining pixels construct the subspace for each detection procedure. The final detection results are then enhanced by the fusion of target occurrence frequencies in all the detection procedures. Experiments with both synthetic and real hyperspectral images (HSI) evaluate the validation of our proposed DSD method by using several different state-of-the-art methods as the basic detectors. With several other single detectors and multiple detection methods as comparable methods, improved receiver operating characteristic curves and better separability between targets and backgrounds by the DSD methods are illustrated. The DSD methods also perform well with the covariance-based detectors, showing their efficiency in selecting covariance information for detection.

Generalized Detection Fusion for Hyperspectral Images

The purpose of this paper is to introduce a general type of detection fusion that allows combining a set of basic detectors into one more versatile detector. The fusion can be performed based on the spectral information contained in a pixel, the global characteristics of the background and target spaces, as well as spatial local information. As an example of generalized fusion, we introduce a new class of detectors called the directional segmented matched filters (DSMFs). We then concentrate on the more basic type of fusion that does not use the spatial local information. Our goal is to build a theoretical foundation for the future more sophisticated detectors. Within this setup, we define max-min and min-max types of fusion, which turn out to be equivalent to the geometric approach to continuum fusion already introduced in the literature. Nevertheless, this new framework allows natural formulation of other types of approaches, such as discrete fusion, without the continuity assumption. This new formalism also allows formulation of a general theorem about the relationship between the max-min and min-max detectors. We also provide experimental results that demonstrate the benefits of the new approach. We compare two new detectors with the global matched filter using two different targets in an AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) image. The results show that various forms of the DSMFs dominate depending on the target type.

Utilizing a Magnetic Locator to Search for Buried Firearms and Miscellaneous Weapons at a Controlled Research Site*,†

Forensic personnel generally use basic all-metal detectors for weapon searches because of their ease of use and cost efficiency. For ferromagnetic targets, an alternative easy to use and low-cost geophysical tool is a magnetic locator. The following study was designed to demonstrate the effectiveness of a common, commercially available magnetic locator in forensic weapon searches by determining the maximum depth of detection for 32 metallic forensic targets and testing the effects of metallic composition on detection. Maximum depth of detection was determined for 16 decommissioned street-level firearms, six pieces of assorted scrap metals, and 10 blunt or bladed weapons by burying each target at 5-cm intervals until the weapons were no longer detected. As expected, only ferromagnetic items were detected; weapons containing both ferromagnetic and nonferromagnetic components were generally detected to shallower depths. Overall, the magnetic locator can be a useful addition to weapon searches involving buried ferromagnetic weapons.