Two-person device-free localization system based on ZigBee and transformer

Most studies on device-free localization currently focus on single-person scenarios.This paper proposes a novel method for device-free localization that utilizes ZigBee received signal strength indication(RSSI)and a Transformer network structure.The method aims to address the limited research and low accuracy of two-person device-free localization.This paper first describes the construction of the sensor network used for collecting ZigBee RSSI.It then examines the format and features of ZigBee data packages.The algorithm design of this paper is then introduced.The box plot method is used to identify abnormal data points,and a neural network is used to establish the mapping model between ZigBee RSSI matrix and localization coordinates.This neural network includes a Transformer encoder layer as the encoder and a fully connected network as the decoder.The proposed method's classification accuracy was experimentally tested in an online test stage,resulting in an accuracy rate of 98.79%.In conclusion,the proposed two-person localization system is novel and has demonstrated high accuracy.

Hybrid ToA and IMU indoor localization system by various algorithms

In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.

RSS-Based Indoor Localization System with Single Base Station

The paper proposes an Indoor Localization System(ILS)which uses only one fixed Base Station(BS)with simple non-reconfigurable antennas.The proposed algorithm measures Received Signal Strength(RSS)and maps it to the location in the room by estimating signal strength of a direct line of sight(LOS)signal and signal of the first order reflection from the wall.The algorithm is evaluated through both simulations and empirical measurements in a furnished open space office,sampling 21 different locations in the room.It is demonstrated the system can identify user’s real-time location with a maximum estimation error below 0.7 m for 80%confidence Cumulative Distribution Function(CDF)user level,demonstrating the ability to accurately estimate the receiver’s location within the room.The system is intended as a cost-efficient indoor localization technique,offering simplicity and easy integration with existing wireless communication systems.Unlike comparable single base station localization techniques,the proposed system does not require beam scanning,offering stable communication capacity while performing the localization process.

Accuracy and Electromagnetic Safety Evaluation of a Portable Electromagnetic Localization System for Micro Invasive Medical Devices in Vivo

Aiming at localizing the telemetric capsule for detecting gastrointestinal physiological parameters in vivo accurately,a portable alternating current(AC)electromagnetic localization system is designed.To verify the feasibility of the method,the model and construction of the localization system are detailed.And static and dynamic accuracy of the localization system are tested by experiments.Next,we compare the simulating results of the electromagnetic radiation aroused by the localization system with the electromagnetic safety standards of human(ICNIRP guidelines and IEEE standard C95.1-1991).Finally,in terms of the results of the static and dynamic experiments,conclusions are drawn that the accuracy of portable positioning system is high(less than 10 mm)enough to satisfy the localization need of the micro invasive medical devices in vivo,and there is no harm of electromagnetic radiation to human.

Comparison of Indoor Localization Systems Based on Wireless Communications

Localization using a Wireless Sensor Network (WSN) has become a field of interest for researchers in the past years. This information is expected to aid in routing, systems maintenance and health monitoring. For example, many projects aiming to monitor the elderly at home include a personal area network (PAN) which can provide current location of the patient to the medical staff. This article presents an overview of the current trends in this domain. We introduce the mathematical tools used to determine position then we introduce a selection of range-free and range-based proposals. Finally, we provide a comparison of these techniques and suggest possible areas of improvement.

An Image Localization System Based on Single Photon

As an essential part of artificial intelligence,many works focus on image processing which is the branch of computer vision.Nevertheless,image localization faces complex challenges in image processing with image data increases.At the same time,quantum computing has the unique advantages of improving computing power and reducing energy consumption.So,combining the advantage of quantum computing is necessary for studying the quantum image localization algorithms.At present,many quantum image localization algorithms have been proposed,and their efficiency is theoretically higher than the corresponding classical algorithms.But,in quantum computing experiments,quantum gates in quantum computing hardware need to work at very low temperatures,which brings great challenges to experiments.This paper proposes a single-photon-based quantum image localization algorithm based on the fundamental theory of single-photon image classification.This scheme realizes the operation of the mixed national institute of standards and technology database(MNIST)quantum image localization by a learned transformation for non-noise condition,noisy condition,and environmental attack condition,respectively.Compared with the regular use of entanglement between multi-qubits and low-temperature noise reduction conditions for image localization,the advantage of this method is that it does not deliberately require low temperature and entanglement resources,and it improves the lower bound of the localization success rate.This method paves a way to study quantum computer vision.

Development of an Accurate Low-cost Ultrasonic Localization System for Autonomous Mobile Robots in Indoor Environments

An accurate low-cost ultrasonic localization system is de- veloped for automated mobile robots in indoor environments, which is essential for automatic navigation of mobile robots with various tasks. Although ultrasenic sensors are more cost-effective than other sensors such as Laser Range Finder （LRF） and vision, but they are inaccurate and directionally ambiguons. First, the matched filter is used to measure the distance accurately. For resolving the computational complexity of the matched filter, a new matched filter algorithm with simple compution is proposed. Then, an ultrasonic localization system is proposed which consists of three ultrasonic receivers and two or mote transmitters for improving position and orientation accuracy was developed. Finally, an extended Kalman filter is designed to estimate both the static and dynamic positions and orientations. Various simu lations and experimental results show that the proposed system is effective.

Influence of Synchronization Impairments on an Experimental TDOA/FDOA Localization System

In Electronic Warfare, and more specifically in the domain of passive localization, accurate time synchronization between platforms is decisive, especially on systems relying on TDOA （time difference of arrival） and FDOA （frequency difference of arrival）. This paper investigates this issue by presenting an analysis in terms of final localization performance of an experimental passive localization system based on off-the-shelf components. This system is detailed, as well as the methodology used to carry out the acquisition of real data. This experiment has been realized with two different kinds of clock. The results are analyzed by calculating the Allan deviation and time deviation. The choice of these metrics is explained and their properties are discussed in the scope of an airborne bi-platform passive localization context. Conclusions are drawn regarding the overall localization performance of the system.

Dynamical localization in a non-Hermitian Floquet synthetic system

We investigate the non-Hermitian effects on quantum diffusion in a kicked rotor model where the complex kicking potential is quasi-periodically modulated in the time domain.The synthetic space with arbitrary dimension can be created by incorporating incommensurate frequencies in the quasi-periodical modulation.In the Hermitian case,strong kicking induces the chaotic diffusion in the four-dimension momentum space characterized by linear growth of mean energy.We find that the quantum coherence in deep non-Hermitian regime can effectively suppress the chaotic diffusion and hence result in the emergence of dynamical localization.Moreover,the extent of dynamical localization is dramatically enhanced by increasing the non-Hermitian parameter.Interestingly,the quasi-energies become complex when the non-Hermitian parameter exceeds a certain threshold value.The quantum state will finally evolve to a quasi-eigenstate for which the imaginary part of its quasi-energy is large most.The exponential localization length decreases with the increase of the non-Hermitian parameter,unveiling the underlying mechanism of the enhancement of the dynamical localization by nonHermiticity.

Abnormal Secondary Growth and Histochemical Localization of Alkaloids in Root System of Aconitum flavum Hand.-Mazz.

[Objective] The purpose of this study was to clarify the structure,growth pattern and histochemical localization of alkaloids in root system of Aconitum flavum Hand.-Mazz.[Method] Paraffin sectioning and histochemistry were employed for performing the analysis in this study.[Result] The root system of Aconitum flavum Hand.-Mazz.consists of taproot,lateral root and adventitious root.The primary structure of root system is normal,but secondary structure shows abnormal.The cambium and the extra cambium of taproot form a ＂U＂-shaped secondary vascular bundle and tertiary bundle in abnormal secondary structure.The sieve tube group is made of little sieve tube group which is differentiated from primary phloem and cambium.Meanwhile,the secondary xylem in tuberous root also appears to be a ＂U＂ shape.Parenchyma cells of secondary phloem occupy most of the tuberous root.The sieve tube group of tuberous root is mainly differentiated from parenchyma cell of secondary phloem.[Conclusion] The difference in abnormal secondary structure of taproot and tuberous root are attributed to their varied cambium compose and activity pattern.Alkaloids are mainly accumulated in parenchyma cell of the inside cortex and between bundle in taproot,while parenchyma of secondary phloem and pith in tuberous root.

Recognition and localization system of the robot for harvesting Hangzhou White Chrysanthemums

To realize the robotic harvesting of Hangzhou White Chrysanthemums,the quick recognition and 3D vision localization system for target Chrysanthemums was investigated in this study.The system was comprised of three main stages.Firstly,an end-effector and a simple freedom manipulator with three degrees were designed to meet the quality requirements of harvesting Hangzhou White Chrysanthemums.Secondly,a segmentation based on HSV color space was performed.A fast Fuzzy C-means(FCM)algorithm based on S component was proposed to extract the target image from irrelevant background.Thirdly,binocular stereo vision was used to acquire the target spatial information.According to the shape of Hangzhou White Chrysanthemums,the centroids of stamens were selected as feature points to match in the right and left images.The experimental results showed that the proposed method was able to recognize Hangzhou White Chrysanthemums with the accuracy of 85%.When the distance between target and baseline was 150-450 mm,the errors between the calculated and measured distance were less than 14 mm,which could meet the requirements of the localization accuracy of the harvesting robot.

Waveform diversity based sonar system for target localization

A new monostatic array system taking advantage of diverse waveforms to improve the performance of underwater tar- get localization is proposed. Unlike the coherent signals between different elements in common active array, the transmitted signals from different elements here are spatially orthogonal waveforms which allow for array processing in the transit mode and result in an extension of array aperture. The mathematical derivation of Capon estimator for this sonar system is described in detail. And the performance of this orthogonal-waveform based sonar is an- alyzed and compared with that of its phased-array counterpart by water tank experiments. Experimental results show that this sonar system could achieve 12 dB-15 dB additional array gain over its phased-array counterpart, which means a doubling of maximum detection range. Moreover, the angular resolution is significantly improved at lower SNR.

Passive Localization of Multiple Sources Using Joint RSS and AOA Measurements in Spectrum Sharing System

In spectrum sharing systems,locating mul-tiple radiation sources can efficiently find out the in-truders,which protects the shared spectrum from ma-licious jamming or other unauthorized usage.Com-pared to single-source localization,simultaneously lo-cating multiple sources is more challenging in prac-tice since the association between measurement pa-rameters and source nodes are not known.More-over,the number of possible measurements-source as-sociations increases exponentially with the number of sensor nodes.It is crucial to discriminate which measurements correspond to the same source before localization.In this work,we propose a central-ized localization scheme to estimate the positions of multiple sources.Firstly,we develop two computa-tionally light methods to handle the unknown RSS-AOA measurements-source association problem.One method utilizes linear coordinate conversion to com-pute the minimum spatial Euclidean distance sum-mation of measurements.Another method exploits the long-short-term memory(LSTM)network to clas-sify the measurement sequences.Then,we propose a weighted least squares(WLS)approach to obtain the closed-form estimation of the positions by linearizing the non-convex localization problem.Numerical re-sults demonstrate that the proposed scheme could gain sufficient localization accuracy under adversarial sce-narios where the sources are in close proximity and the measurement noise is strong.

Global localization of in-pipe robot based on ultra-long wave antenna array and global position system

A global localization system of in-pipe robot is introduced in this paper.Global position system(GPS)is applied to monitor the motion of robot along the whole pipeline which is equally divided intomany segments by tracking stations.The definite segment in which robot existing can be detected and thisis long-range localization.Ultra-long wave(ULW)is adopted to solve the problem of metallic shieldingand realize effective communication between inside and outside of pipeline.ULW emitter is carried byrobot.When the plant is broken or defects on pipe-wall are inspected,the robot will stop moving.Anten-na array is presented and disposed upon the definite segment to search the accurate location of robot,andthis is short-range localization.In this paper,five-antenna array is adopted and an effective linear signalfusion algorithm is presented.The localization precision reaches R < 25cm.By tests in Shengli oil field,the whole system is verified with robust solutions.

An efficient transient gene expression system for protein subcellular localization assay and genome editing in citrus protoplasts

Protoplast has been widely used in biotechnologies to circumvent the breeding obstacles in citrus, including long juvenility, polyembryony, and male/female sterility. The protoplast-based transient gene expression system is a powerful tool for gene functional characterization and CRISPR/Cas9 genome editing in higher plants, but it has not been widely used in citrus. In this study, the polyethylene glycol(PEG)-mediated method was optimized for citrus callus protoplast transfection, with an improved transfection efficiency of 68.4%. Consequently, the efficiency of protein subcellular localization assay was increased to 65.8%, through transient expression of the target gene in protoplasts that stably express the fluorescent organelle marker protein. The gene editing frequencies in citrus callus protoplasts reached 14.2% after transient expression of CRISPR/Cas9 constructs. We demonstrated that the intronic polycistronic tRNAgRNA(inPTG) genome editing construct was functional in both the protoplast transient expression system and epicotyl stable transformation system in citrus. With this optimized protoplast transient expression system, we improved the efficiency of protein subcellular localization assay and developed the genome editing system in callus protoplasts, which provides an approach for prompt test of CRISPR vectors.

Localization of pallets in warehouses using passive RFID system

Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.

CD93 and GIPC expression and localization during central nervous system inflammation

CD93 and GAIP-interacting protein, C termius （GIPC） have been shown to interactively alter phagocytic processes of immune cells. CD93 and GIPC expression and localization during cen-tral nervous system inflammation have not yet been reported. In this study, we established a rat model of brain inlfammation by lipopolysaccharide injection to the lateral ventricle. In the brain of rats with inlfammation, western blots showed increased CD93 expression that decreased over time. GIPC expression was unaltered. Immunohistochemistry demonstrated extensive distribution of CD93 expression mainly in cell membranes in the cerebral cortex. After lipopoly-saccharide stimulation, CD93 expression increased and then reduced, with distinct staining in the cytoplasm and nucleus. Double immunolfuorescence staining in cerebral cortex of normal rats showed that CD93 and GIPC widely expressed in resting microglia and neurons. CD93 was mainly expressed in microglial and neuronal cell membranes, while GIPC was expressed in both cell membrane and cytoplasm. In the cerebral cortex at 9 hours after model establishment, CD93-immunoreactive signal diminished in microglial membrane, with cytoplasmic transloca-tion and aggregation detected. GIPC localization was unaltered in neurons and microglia. These results are the ifrst to demonstrate CD93 participation in pathophysiological processes of central nervous system inlfammation.

Computer Decision Support System for Skin Cancer Localization and Classification

In this work,we propose a new,fully automated system for multiclass skin lesion localization and classification using deep learning.The main challenge is to address the problem of imbalanced data classes,found in HAM10000,ISBI2018,and ISBI2019 datasets.Initially,we consider a pretrained deep neural network model,DarkeNet19,and fine-tune the parameters of third convolutional layer to generate the image gradients.All the visualized images are fused using a High-Frequency approach along with Multilayered Feed-Forward Neural Network(HFaFFNN).The resultant image is further enhanced by employing a log-opening based activation function to generate a localized binary image.Later,two pre-trained deep models,Darknet-53 and NasNet-mobile,are employed and fine-tuned according to the selected datasets.The concept of transfer learning is later explored to train both models,where the input feed is the generated localized lesion images.In the subsequent step,the extracted features are fused using parallel max entropy correlation(PMEC)technique.To avoid the problem of overfitting and to select the most discriminant feature information,we implement a hybrid optimization algorithm called entropy-kurtosis controlled whale optimization(EKWO)algorithm.The selected features are finally passed to the softmax classifier for the final classification.Three datasets are used for the experimental process,such as HAM10000,ISBI2018,and ISBI2019 to achieve an accuracy of 95.8%,97.1%,and 85.35%,respectively.

Mobile Robot Localization and Navigation System Based on Monocular Vision

A system for mobile robot localization and navigation was presented.With the proposed system,the robot can be located and navigated by a single landmark in a single image.And the navigation mode may be following-track,teaching and playback,or programming.The basic idea is that the system computes the differences between the expected and the recognized position at each time and then controls the robot in a direction to reduce those differences.To minimize the robot sensor equipment,only one omnidirectional camera was used.Experiments in disturbing environments show that the presented algorithm is robust and easy to implement,without camera rectification.The rootmean-square error(RMSE) of localization is 1.4,cm,and the navigation error in teaching and playback is within 10,cm.

Klein Paradox and Disorder-Induced Delocalization of Dirac Quasiparticles in One-Dimensional Systems

Dirac particle penetration is studied theoretically with Dirac equation in one-dimensional systems. We investigate a one-dimensional system with N barriers where both barrier height and well width are constants randomly distributed in certain range. The one-parameter scaling theory for nonrelatiyistic particles is still valid for massive Dirac particles. In the same disorder sample, we find that the localization length of relativistic particles is always larger than that of nonrelativistic particles and the transmission coefficient related to incident particle in both cases fits the form T～ exp（-αL）. More interesting, massless relativistic particles are entirely delocalized no matter how big the energy of incident particles is.