bluuebunny/crossref_metadata_2025 huggingface dataset:
An Adaptive Spreading Factor Selection Scheme for a Single Channel LoRa Modem
Authors: Kim Seungku , Lee Heonkook , Jeon Sungho
Published: February 2020

When the low power wide area network (LPWAN) was developed for the internet of things (IoT), it attracted significant attention. LoRa, which is one of the LPWAN technologies, provides low-power and long-range wireless communication using a frequency band under 1 GHz. A long-range wide area network (LoRaWAN) provides a simple star topology network that is not scalable; it supports multi-data rates by adjusting the spreading factor, code rate, and bandwidth. This paper proposes an adaptive spreading factor selection scheme for corresponding spreading factors (SFs) between a transmitter and receiver. The scheme enables the maximum throughput and minimum network cost, using cheap single channel LoRa modules. It provides iterative SF inspection and an SF selection algorithm that allows each link to communicate at independent data rates. We implemented a multi-hop LoRa network and evaluated the performance of experiments in various network topologies. The adaptive spreading factor selection (ASFS) scheme showed outstanding end-to-end throughput, peaking at three times the performance of standalone modems. We expect the ASFS scheme will be a suitable technology for applications requiring high throughput on a multi-hop network.
Rapid High-Resolution Mosaic Acquisition for Photoacoustic Remote Sensing
Authors: Abbasi Saad , Bell Kevan , Haji Reza Parsin
Published: February 2020

Mechanical stages are routinely used to scan large expanses of biological specimens in photoacoustic imaging. This is primarily due to the limited field of view (FOV) provided by optical scanning. However, stage scanning becomes impractical at higher scanning speeds, or potentially unfeasible with heavier samples. Also, the slow scan-rate of the stages makes high resolution scanning a time-consuming process. Some clinical applications such as microsurgery require submicron resolution in a reflection-mode configuration necessitating a method that can acquire large field of views with a small raster scanning step size. In this study, we describe a method that combines mechanical stages with optical scanning for the rapid acquisition of high-resolution large FOVs. Optical scanning is used to acquire small frames in a two-dimensional grid formed by the mechanical stages. These frames are captured with specific overlap for effective image registration. Using a step size of 200 nm, we demonstrate mosaics of carbon fiber networks with FOVs of 0.8 × 0.8 mm2 captured in under 70 s with 1.2 µm image resolution. Larger mosaics yielding an imaging area of 3 × 3 mm2 are also shown. The method is validated by imaging a 1 × 1 mm2 section of unstained histopathological human tissue.
Giant Goos-Hänchen Shifts in Au-ITO-TMDCs-Graphene Heterostructure and Its Potential for High Performance Sensor
Authors: Han Lei , Pan Jianxing , Wu Chuan , Li Keliang , Ding Huafeng , Ji Qizheng , Yang Ming , Wang Jin , Zhang Huijie , Huang Tianye
Published: February 2020

In order to improve the performance of surface plasmon resonance (SPR) biosensor, the structure based on two-dimensional (2D) of graphene and transition metal dichalcogenides (TMDCs) are proposed to greatly enhance the Goos-Hänchen (GH) shift. It is theoretically proved that GH shift can be significantly enhanced in SPR structure coated with gold (Au)-indium tin oxide (ITO)-TMDCs-graphene heterostructure. In order to realize high GH shifts, the number of TMDCs and graphene layer are optimized. The highest GH shift (−801.7 λ) is obtained by Au-ITO-MoSe2-graphene hybrid structure with MoSe2 monolayer and graphene bilayer, respectively. By analyzing the GH variation, the index sensitivity of such configuration can reach as high as 8.02 × 105 λ/RIU, which is 293.24 times of the Au-ITO structure and 177.43 times of the Au-ITO-graphene structure. The proposed SPR biosensor can be widely used in the precision metrology and optical sensing.
Investigation of an Ultra Wideband Noise Sensor for Health Monitoring
Authors: Zeng Xuezhi , Robakowski Joakim , Persson Mikael , Monteith Albert , Fhager Andreas
Published: February 2020

Quick on-scene assessment and early intervention is the key to reduce the mortality of stroke and trauma patients, and it is highly desirable to develop ambulance-based diagnostic and monitoring devices in order to provide additional support to the medical personnel. We developed a compact and low cost ultra wideband noise sensor for medical diagnostics and vital sign monitoring in pre-hospital settings. In this work, we demonstrated the functionality of the sensor for respiration and heartbeat monitoring. In the test, metronome was used to manipulate the breathing pattern and the heartbeat rate reference was obtained with a commercial electrocardiogram (ECG) device. With seventeen tests performed for respiration rate detection, sixteen of them were successfully detected. The results also show that it is possible to detect the heartbeat rate accurately with the developed sensor.
3D Printing Technique-Improved Phase-Sensitive OTDR for Breakdown Discharge Detection of Gas-Insulated Switchgear
Authors: Chen Zhen , Zhang Liang , Liu Huanhuan , Peng Peng , Liu Zhichao , Shen Shi , Chen Na , Zheng Shenhui , Li Jian , Pang Fufei
Published: February 2020

In this paper, we propose and demonstrate a gas-insulated switchgear (GIS) breakdown discharge detection system based on improved phase-sensitive optical time domain reflectometry (φ-OTDR) assisted by 3D-printed sensing elements. The sensing element is manufactured by a material with a high Poisson ratio for enhancement of the sensitivity of φ-OTDR to the acoustic emission detection during the breakdown discharge process. In our experiment, seven 3D-printed sensing elements incorporating with optical fibers are attached tightly onto the shell of the GIS, which are monitored by φ-OTDR to localize and detect the acoustic emission signal resulted from the breakdown discharge. Ultimately, thanks to the phase demodulation, acoustic signals induced by the breakdown discharge process can be captured and recovered. Furthermore, the time delay analysis of detected signals acquired by different sensing elements on the GIS breakdown discharge unit is able to distinguish the location of the insulation failure part in the GIS unit. It suggests that the φ-OTDR incorporated with 3D printing technology shows the advantage of robustness in GIS breakdown discharge monitoring and detection.
Detection System for U-Shaped Bellows Convolution Pitches Based on a Laser Line Scanner
Authors: Yang Yutu , Chen Zengtao , Liu Ying , Li Yuting , Hu Zhongkang , Gou Binli
Published: February 2020

An expansion joint is mainly composed of bellows and other components; it is attached on a container shell or pipe to compensate for the additional stress caused by temperature differences and mechanical vibrations. In China, the expansion joint fatigue tests are often used to assess the quality of products. After fatigue tests, convolution pitch will be changed. The amount of change is an important index that can be used to evaluate bellows expansion joints. However, the convolution pitch detection is mainly done manually and randomly by inspection agencies before shipping to the end users. This common practice is not efficient and is often subjective. This paper introduced a novel method for automatically detecting the change of the convolution pitch based on a laser line scanner and data processing technology. The laser line scanner is combined with a precision motorized stage to obtain the point cloud data of the bellows. After denoising and fitting, a peak-finding algorithm is applied to search for the crest of a convolution. The method to find the convolution pitch and the decision that needs to be made to ensure product eligibility are described in detail. A DN500 expansion joint is used as a sample to illustrate the efficiency of the system. The application of the technique intuitively allows a higher precision and relative efficiency in quality inspection of bellows expansion joints. It has also been implemented in the Special Equipment Safety Supervision and Inspection Institute of Jiangsu province with great success.
A Data-Driven Damage Identification Framework Based on Transmissibility Function Datasets and One-Dimensional Convolutional Neural Networks: Verification on a Structural Health Monitoring Benchmark Structure
Authors: Liu Tongwei , Xu Hao , Ragulskis Minvydas , Cao Maosen , Ostachowicz Wiesław
Published: February 2020

Vibration-based data-driven structural damage identification methods have gained large popularity because of their independence of high-fidelity models of target systems. However, the effectiveness of existing methods is constrained by critical shortcomings. For example, the measured vibration responses may contain insufficient damage-sensitive features and suffer from high instability under the interference of random excitations. Moreover, the capability of conventional intelligent algorithms in damage feature extraction and noise influence suppression is limited. To address the above issues, a novel damage identification framework was established in this study by integrating massive datasets constructed by structural transmissibility functions (TFs) and a deep learning strategy based on one-dimensional convolutional neural networks (1D CNNs). The effectiveness and efficiency of the TF-1D CNN framework were verified using an American Society of Civil Engineers (ASCE) structural health monitoring benchmark structure, from which dynamic responses were captured, subject to white noise random excitations and a number of different damage scenarios. The damage identification accuracy of the framework was examined and compared with others by using different dataset types and intelligent algorithms. Specifically, compared with time series (TS) and fast Fourier transform (FFT)-based frequency-domain signals, the TF signals exhibited more significant damage-sensitive features and stronger stability under excitation interference. The utilization of 1D CNN, on the other hand, exhibited some unique advantages over other machine learning algorithms (e.g., traditional artificial neural networks (ANNs)), particularly in aspects of computation efficiency, generalization ability, and noise immunity when treating massive, high-dimensional datasets. The developed TF-1D CNN damage identification framework was demonstrated to have practical value in future applications.
Detection of Salmonella Enterica in Egg Yolk by PCR on a Microfluidic Disc Device Using Immunomagnetic Beads
Authors: Kubo Izumi , Kajiya Mitsutoshi , Aramaki Narumi , Furutani Shunsuke
Published: February 2020

Salmonella enterica is a pathogenic bacterium that causes foodborne illness. One of the vehicle foods of S. enterica are chicken eggs. Efficient collection of the bacterium is necessary to detect it specifically. We developed a method to detect S. enterica by PCR on a microfluidic disc device using a fluorescent probe. Salmonella enterica cells were isolated in the microchambers on the device, followed by thermal lysis and PCR targeting with the invA gene, a gene specific to S. enterica, were observed by measurement of the fluorescent signal that resulted from gene amplification. However, the developed method was unable to discriminate viable cells from dead cells. Consequently, in this study, magnetic beads modified with anti-Salmonella antibody were utilized to detect viable Salmonella cells from egg yolk prior to PCR on the device. While using the antibody-modified beads, egg yolk components, which inhibit PCR, were removed. The collected cells were subsequently detected by PCR of the invA gene on a microfluidic disc device. This method enabled the detection of viable cells without the inhibition of PCR by any egg component. S. enterica was detected at 5.0×104 cells mL−1 or at a higher concentration of egg yolk within 6 h including the sampling time.
Microwave Differential Frequency Splitting Sensor Using Magnetic-LC Resonators
Authors: Ebrahimi Amir , Beziuk Grzegorz , Scott James , Ghorbani Kamran
Published: February 2020

A differential microwave permittivity sensor and comparator is designed using a microstrip transmission line loaded with a magnetic-LC resonator. The microstrip transmission line is aligned with the electric wall of the resonator. The sensor shows a single transmission zero, when it is unloaded or loaded symmetrically on both halves. A second notch appears in the transmission response by asymmetrical dielectric loading on the two halves of the device. The frequency splitting is used to characterize the dielectric properties of the samples under test. The sensitivity of the sensor is enhanced by removing the mutual coupling between the two halves of the magnetic-LC resonator using a metallic wall. The sensors’ operation principle is explained through a circuit model analysis. A prototype of the designed sensor is fabricated and measurements are used for validation of the sensing concept. The sensor can be used for determination of the dielectric properties in solid materials or detecting defects and impurities in solid materials through a comparative measurement with a reference sample.
NaviSoC: High-Accuracy Low-Power GNSS SoC with an Integrated Application Processor
Authors: Borejko Tomasz , Marcinek Krzysztof , Siwiec Krzysztof , Narczyk Paweł , Borkowski Adam , Butryn Igor , Łuczyk Arkadiusz , Pietroń Daniel , Plasota Maciej , Reszewicz Szymon , Wiechowski Łukasz , Pleskacz Witold
Published: February 2020

A dual-frequency all-in-one Global Navigation Satellite System (GNSS) receiver with a multi-core 32-bit RISC (reduced instruction set computing) application processor was integrated and manufactured as a System-on-Chip (SoC) in a 110 nm CMOS (complementary metal-oxide semiconductor) process. The GNSS RF (radio frequency) front-end with baseband navigation engine is able to receive, simultaneously, Galileo (European Global Satellite Navigation System) E1/E5ab, GPS (US Global Positioning System) L1/L1C/L5, BeiDou (Chinese Navigation Satellite System) B1/B2, GLONASS (GLObal NAvigation Satellite System of Russian Government) L1/L3/L5, QZSS (Quasi-Zenith Satellite System development by the Japanese government) L1/L5 and IRNSS (Indian Regional Navigation Satellite System) L5, as well as all SBAS (Satellite Based Augmentation System) signals. The ability of the GNSS to detect such a broad range of signals allows for high-accuracy positioning. The whole SoC (system-on-chip), which is connected to a small passive antenna, provides precise position, velocity and time or raw GNSS data for hybridization with the IMU (inertial measurement unit) without the need for an external application processor. Additionally, user application can be executed directly in the SoC. It works in the −40 to +105 °C temperature range with a 1.5 V supply. The assembled test-chip takes 100 pins in a QFN (quad-flat no-leads) package and needs only a quartz crystal for the on-chip reference clock driver and optional SAW (surface acoustic wave) filters. The radio performance for both wideband (52 MHz) channels centered at L1/E1 and L5/E5 is NF = 2.3 dB, G = 131 dB, with 121 dBc/Hz of phase noise @ 1 MHz offset from the carrier, consumes 35 mW and occupies a 4.5 mm2 silicon area. The SoC reported in the paper is the first ever dual-frequency single-chip GNSS receiver equipped with a multi-core application microcontroller integrated with embedded flash memory for the user application program.
A New Logging-While-Drilling Method for Resistivity Measurement in Oil-Based Mud
Authors: Wu Yongkang , Lu Baoping , Zhang Wei , Jiang Yandan , Wang Baoliang , Huang Zhiyao
Published: February 2020

Resistivity logging is an important technique for identifying and estimating reservoirs. Oil-based mud (OBM) can improve drilling efficiency and decrease operation risks, and has been widely used in the well logging field. However, the non-conductive OBM makes the traditional logging-while-drilling (LWD) method with low frequency ineffective. In this work, a new oil-based LWD method is proposed by combining the capacitively coupled contactless conductivity detection (C4D) technique and the inductive coupling principle. The C4D technique is to overcome the electrical insulation problem of the OBM and construct an effective alternating current (AC) measurement path. Based on the inductive coupling principle, an induced voltage can be formed to be the indirect excitation voltage of the AC measurement path. Based on the proposed method, a corresponding logging instrument is developed. Numerical simulation was carried out and results show that the logging instrument has good measurement accuracy, deep detection depth and high vertical resolution. Practical experiments were also carried out, including the resistance box experiment and the well logging experiment. The results of the resistance box experiment show that the logging instrument has good resistance measurement accuracy. Lastly, the results of the well logging experiment indicate that the logging instrument can accurately reflect the positions of different patterns on the wellbore of the experimental well. Both numerical simulation and practical experiments verify the feasibility and effectiveness of the new method.
Integrated Avoid Collision Control of Autonomous Vehicle Based on Trajectory Re-Planning and V2V Information Interaction
Authors: Lin Fen , Wang Kaizheng , Zhao Youqun , Wang Shaobo
Published: February 2020

An integrated longitudinal-lateral control method is proposed for autonomous vehicle trajectory tracking and dynamic collision avoidance. A method of obstacle trajectory prediction is proposed, in which the trajectory of the obstacle is predicted and the dynamic solution of the reference trajectory is realized. Aiming at the lane changing scene of autonomous vehicles driving in the same direction and adjacent lanes, a trajectory re-planning motion controller with the penalty function is designed. The reference trajectory parameterized output of local reprogramming is realized by using the method of curve fitting. In the framework of integrated control, Fuzzy adaptive (proportional-integral) PI controller is proposed for longitudinal velocity tracking. The selection and control of controller and velocity are realized by logical threshold method; A model predictive control (MPC) with vehicle-to-vehicle (V2V) information interaction modular and the driver characteristics is proposed for direction control. According to the control target, the objective function and constraints of the controller are designed. The proposed method’s performance in different scenarios is verified by simulation. The results show that the autonomous vehicles can avoid collision and have good stability.
SDN-based Handover Scheme in Cellular/IEEE 802.11p Hybrid Vehicular Networks
Authors: Duo Ran , Wu Celimuge , Yoshinaga Tsutomu , Zhang Jiefang , Ji Yusheng
Published: February 2020

With the arrival of 5G, the wireless network will be provided with abundant spectrum resources, massive data transmissions and low latency communications, which makes Vehicle-to-Everything applications possible. However, VANETs always accompany with frequent network topology changes due to the highly mobile feature of vehicles. As a result, the network performance will be affected by the frequent handover. In this paper, a seamless handover scheme is proposed where the Software-Defined Networking (SDN) and Mobile Edge Computing (MEC) technologies are employed to adapt to the dynamic topology change in VANETs. The introduction of SDN provides a global view of network topology and centralized control, which enables a stable transmission layer connection when a handover takes place, so that the upper layer performance is not influenced by the network changes. By employing MEC server, the data are cached in advance before a handover happens, so that the vehicle can restore normal communication faster. In order to confirm the superiority of our proposal, computer simulations are conducted from different aspects. The results show that our proposal can significantly improve the network performance when a handover happens.
SNPL: One Scheme of Securing Nodes in IoT Perception Layer
Authors: Fan Yongkai , Zhao Guanqun , Li Kuan-Ching , Zhang Bin , Tan Gang , Sun Xiaofeng , Xia Fanglue
Published: February 2020

The trustworthiness of data is vital data analysis in the age of big data. In cyber-physical systems, most data is collected by sensors. With the increase of sensors as Internet of Things (IoT) nodes in the network, the security risk of data tampering, unauthorized access, false identify, and others are overgrowing because of vulnerable nodes, which leads to the great economic and social loss. This paper proposes a security scheme, Securing Nodes in IoT Perception Layer (SNPL), for protecting nodes in the perception layer. The SNPL is constructed by novel lightweight algorithms to ensure security and satisfy performance requirements, as well as safety technologies to provide security isolation for sensitive operations. A series of experiments with different types and numbers of nodes are presented. Experimental results and performance analysis show that SNPL is efficient and effective at protecting IoT from faulty or malicious nodes. Some potential practical application scenarios are also discussed to motivate the implementation of the proposed scheme in the real world.
Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration
Authors: Nkenyereye Lionel , Nkenyereye Lewis , Adhi Tama Bayu , Reddy Alavalapati , Song JaeSeung
Published: February 2020

Cloud computing supports many unprecedented cloud-based vehicular applications. To improve connectivity and bandwidth through programmable networking architectures, Software- Defined (SD) Vehicular Network (SDVN) is introduced. SDVN architecture enables vehicles to be equipped with SDN OpenFlow switch on which the routing rules are updated from a SDN OpenFlow controller. From SDVN, new vehicular architectures are introduced, for instance SD Vehicular Cloud (SDVC). In SDVC, vehicles are SDN devices that host virtualization technology for enabling deployment of cloud-based vehicular applications. In addition, the migration of Virtual Machines (VM) over SDVC challenges the performance of cloud-based vehicular applications due the highly mobility of vehicles. However, the current literature that discusses VM migration in SDVC is very limited. In this paper, we first analyze the evolution of computation and networking technologies of SDVC with a focus on its architecture within the cloud-based vehicular environment. Then, we discuss the potential cloud-based vehicular applications assisted by the SDVC along with its ability to manage several VM migration scenarios. Lastly, we provide a detailed comparison of existing frameworks in SDVC that integrate the VM migration approach and different emulators or simulators network used to evaluate VM frameworks’ use cases.
Sensor-Based Smart Clothing for Women’s Menopause Transition Monitoring
Authors: Luo Jie , Mao Aihua , Zeng Zhongwen
Published: February 2020

Aging women usually experience menopause and currently there is no single diagnosing highly-sensitive and -specific test for recognizing menopause. For most employed women at their perimenopause age it is not convenient to visit a clinic for the hormone test, which lasts for consecutive days. This paper develops a suit of sensor-based smart clothing used for home-based and ambulatory health monitoring for women’s menopause transition. Firstly, a survey analysis is conducted to determine the biological signals measured by sensors for indicating the symptoms of menopausal transition and also the body areas with salient symptoms to implant the sensors on the clothing. Then, the smart clothing is designed with a set of temperature and relative humidity sensors on different locations and with a microcontroller to transmit the measured data to the computer. With the smoothed data as input, a new detection algorithm for hot flashes is proposed by recognition of the concurrent occurrence of heat and sweating rise/down, and can figure out the frequency, intensity, and duration—triple dimension information of a hot flash, which is helpful to achieve precise diagnosis for menopausal transition. The smart clothing and the detection algorithm are verified by involving a group of women subjects to participate in a hot flash monitoring experiment. The experimental results show that this smart clothing monitoring system can effectively measure the skin temperature and relative humidity data and work out the frequency, duration, and intensity information of a hot flash pertaining in different body areas for individuals, which are accordant with the practice reported by the subjects.
A Baseband Wireless Spectrum Hypervisor for Multiplexing Concurrent OFDM Signals
Authors: de Figueiredo Felipe A. P. , Mennes Ruben , Jabandžić Irfan , Jiao Xianjun , Moerman Ingrid
Published: February 2020

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the current ones. This situation calls for novel ways to increase the spectral efficiency. Therefore, in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, i.e., the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The proposed architecture is a non-intrusive and highly optimized wireless hypervisor that multiplexes the signals of several different and concurrent multi-carrier-based radio access technologies with numerologies that are multiple integers of one another, which are also referred in our work as radio access technologies with correlated numerology. For example, the proposed architecture can multiplex the signals of several Wi-Fi access points, several LTE base stations, several WiMAX base stations, etc. As it able to multiplex the signals of radio access technologies with correlated numerology, it can, for instance, multiplex the signals of LTE, 5G-NR and NB-IoT base stations. It abstracts a radio frequency front-end into a configurable number of virtual RF front ends, making it possible for such different technologies to share the same RF front-end and consequently reduce the costs and increasing the spectral efficiency by employing densification, once several networks share the same infrastructure or by dynamically accessing free chunks of spectrum. Therefore, the main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.
Prediction of Limb Joint Angles Based on Multi-Source Signals by GS-GRNN for Exoskeleton Wearer
Authors: Xie Hualong , Li Guanchao , Zhao Xiaofei , Li Fei
Published: February 2020

To enable exoskeleton wearers to walk on level ground, estimation of lower limb movement is particularly indispensable. In fact, it allows the exoskeleton to follow the human movement in real time. In this paper, the general regression neural network optimized by golden section algorithm (GS-GRNN) is used to realize prediction of the human lower limb joint angle. The human body hip joint angle and the surface electromyographic (sEMG) signals of the thigh muscles are taken as the inputs of a neural network to predict joint angles of lower limbs. To improve the prediction accuracy in different gait phases, the plantar pressure signals are also added into the input. After that, the error between the prediction result and the actual data decreases significantly. Finally, compared with the prediction result of the BP neural network, GRNN shows splendid prediction performance for its less processing time and higher prediction accuracy.
Stabilization and Validation of 3D Object Position Using Multimodal Sensor Fusion and Semantic Segmentation
Authors: Muresan Mircea Paul , Giosan Ion , Nedevschi Sergiu
Published: February 2020

The stabilization and validation process of the measured position of objects is an important step for high-level perception functions and for the correct processing of sensory data. The goal of this process is to detect and handle inconsistencies between different sensor measurements, which result from the perception system. The aggregation of the detections from different sensors consists in the combination of the sensorial data in one common reference frame for each identified object, leading to the creation of a super-sensor. The result of the data aggregation may end up with errors such as false detections, misplaced object cuboids or an incorrect number of objects in the scene. The stabilization and validation process is focused on mitigating these problems. The current paper proposes four contributions for solving the stabilization and validation task, for autonomous vehicles, using the following sensors: trifocal camera, fisheye camera, long-range RADAR (Radio detection and ranging), and 4-layer and 16-layer LIDARs (Light Detection and Ranging). We propose two original data association methods used in the sensor fusion and tracking processes. The first data association algorithm is created for tracking LIDAR objects and combines multiple appearance and motion features in order to exploit the available information for road objects. The second novel data association algorithm is designed for trifocal camera objects and has the objective of finding measurement correspondences to sensor fused objects such that the super-sensor data are enriched by adding the semantic class information. The implemented trifocal object association solution uses a novel polar association scheme combined with a decision tree to find the best hypothesis–measurement correlations. Another contribution we propose for stabilizing object position and unpredictable behavior of road objects, provided by multiple types of complementary sensors, is the use of a fusion approach based on the Unscented Kalman Filter and a single-layer perceptron. The last novel contribution is related to the validation of the 3D object position, which is solved using a fuzzy logic technique combined with a semantic segmentation image. The proposed algorithms have a real-time performance, achieving a cumulative running time of 90 ms, and have been evaluated using ground truth data extracted from a high-precision GPS (global positioning system) with 2 cm accuracy, obtaining an average error of 0.8 m.
Vertical Profiles of Pollution Particle Concentrations in the Boundary Layer above Paris (France) from the Optical Aerosol Counter LOAC Onboard a Touristic Balloon
Authors: Renard Jean-Baptiste , Michoud Vincent , Giacomoni Jérôme
Published: February 2020

Atmospheric pollution by particulate matter represents a significant health risk and needs continuous monitoring by air quality networks that provide mass concentrations for PM10 and PM2.5 (particles with diameter smaller than 10 μm and 2.5 μm, respectively). We present here a new approach to monitor the urban particles content, using six years of aerosols number concentration measurements for particles in the 0.2−50 μm size range. These measurements are performed by the Light Optical Aerosols Counter (LOAC) instrument onboard the tethered touristic balloon “Ballon de Paris Generali”, in Paris, France. Such measurements have allowed us first to detect at ground a seasonal variability in the particulate matter content, due to the origin of the particles (anthropogenic pollution, pollens), and secondly, to retrieve the mean evolution of particles concentrations with height above ground up to 150 m. Measurements were also conducted up to 300 m above ground during major pollution events. The vertical evolution of concentrations varies from one event to another, depending on the origin of the pollution and on the meteorological conditions. These measurements have shown the interest of performing particle number concentrations measurements for the air pollution monitoring in complement with regulatory mass concentrations measurement, to better evaluate the intensity of the pollution event and to better consider the effect of smallest particles, which are more dangerous for human health.
Adaptive Spoofing Suppression Algorithm for GNSS Based on Multiple Antennas Array
Authors: Fan Guangwei , Gan Xingli , Yu Baoguo , Rong Qiang , Sheng Chuanzhen
Published: February 2020

The signals of navigation satellites are easily affected by spoofing interference, causing the wrong position, speed or Universal Time Coordinate of the receiver to be calculated. Traditional detection and suppression algorithms are used only to eliminate the spoofing signals, which may lead to an insufficient number of satellites for positioning. An adaptive spoofing suppression algorithm (ASSA) based on a multiple antenna array is proposed in this study. The ASSA can use the cross-correlation gain of multiple antenna array to adaptively generate nulling and realize the simultaneous suppression of multiple spoofing signals. Moreover, ASSA does not need to capture and track spoofing separately, thus reducing the complexity of implementation and calculation. Experiments were conducted to verify the proposed system under different conditions, and the results show that ASSA can suppress multiple spoofings with little impact on positioning performance. Under the condition of spoofing, ASSAs were (2.22 m, 2.41 m, 4.43 m) in the static test and (2.27 m, 2.43 m, 4.64 m) in the kinematic test, which are good positioning performances for both. In addition, the ASSA is applied before capturing signals, which is beneficial to identifying and eliminating spoofing earlier and faster.
A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems
Authors: Carminati Marco , Turolla Andrea , Mezzera Lorenzo , Di Mauro Michele , Tizzoni Marco , Pani Gaia , Zanetto Francesco , Foschi Jacopo , Antonelli Manuela
Published: February 2020

A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.
Comments on: “Comparison of Methods Study between a Photonic Crystal Biosensor and Certified ELISA to Measure Biomarkers of Iron Deficiency in Chronic Kidney Disease Patients”
Authors: Abbas Naseem , Naqvi Rizwan Ali
Published: February 2020

We recently read, with great interest, the article entitled “Comparison of Methods Study between a Photonic Crystal Biosensor and Certified ELISA to Measure Biomarkers of Iron Deficiency in Chronic Kidney Disease Patients” [...]
A Semi-Physical Platform for Guidance and Formations of Fixed-Wing Unmanned Aerial Vehicles
Authors: Yang Jun , Thomas Arun Geo , Singh Satish , Baldi Simone , Wang Ximan
Published: February 2020

Unmanned Aerial Vehicles (UAVs) have multi-domain applications, fixed-wing UAVs being a widely used class. Despite the ongoing research on the topics of guidance and formation control of fixed-wing UAVs, little progress is known on implementation of semi-physical validation platforms (software-in-the-loop or hardware-in-the-loop) for such complex autonomous systems. A semi-physical simulation platform should capture not only the physical aspects of UAV dynamics, but also the cybernetics aspects such as the autopilot and the communication layers connecting the different components. Such a cyber-physical integration would allow validation of guidance and formation control algorithms in the presence of uncertainties, unmodelled dynamics, low-level control loops, communication protocols and unreliable communication: These aspects are often neglected in the design of guidance and formation control laws for fixed-wing UAVs. This paper describes the development of a semi-physical platform for multi-fixed wing UAVs where all the aforementioned points are carefully integrated. The environment adopts Raspberry Pi’s programmed in C++, which can be interfaced to standard autopilots (PX4) as a companion computer. Simulations are done in a distributed setting with a server program designed for the purpose of routing data between nodes, handling the user inputs and configurations of the UAVs. Gazebo-ROS is used as a 3D visualization tool.
Dual-Band Circularly Polarized Dielectric Resonator Antenna for WLAN and WiMAX Applications
Authors: Altaf Amir , Seo Munkyo
Published: February 2020

In this paper, a new dual-band circularly polarized (CP) dielectric resonator antenna for WLAN and WiMAX applications is proposed. The dielectric resonator has an asymmetric Y-shaped geometry. By properly selecting the length of the arms, the pairs of fundamental (TE 111 ) and second-order (TE 211 ) are excited separately at the design frequencies to radiate the CP wave. The measurement shows that the fabricated antenna exhibits a wide impedance bandwidth for |S 11 | < −10 dB of 62.07% (2.2–4.18 GHz). The far-field measurements in the broadside direction demonstrated a dual-band CP response with 3 dB ARBWs of 4.92%(2.38–2.5 GHz) at the lower and 12.64% (3.26–3.70 GHz) at the upper band. The measured CP bands cover the entire frequency range of WLAN (2.401–2.495 GHz) and WiMAX (3.4–3.69 GHz) at the lower and upper bands, respectively.
Design of sofware defined radio (SDR) in 88 MHz to 800 MHz multiband frequency based Audio Receipt System at Raspberry
Authors: Wijanto Heroe
Published: February 2020

Abstract – Technology radio communication is currently developing, initially SDR (Software Defined Radio) is used by amateur radio to communicate , but with the presence of the SDR technology will have a major influence on technological development in the field of radio communication. SDR technology can replace several devices in a certain frequency range and mode, especially on military tactical equipment, so that it has a light weight, smaller dimensions and is reconfigurable in addition to this (multiband). In the future this technology will be very necessary to overcome various kinds of obstacles in many of these things. Because of that Software Defined Radio (SDR), problems in the technology platform can be easily other than that in terms of education its use can facilitate learning about the system general radio communication.

 

Keywords : Software Defined Radio (SDR), reconfigurable, multiband
Algoritma Perencanaan Jalur Kendaraan Otonom di Lingkungan Perkotaan dari Sudut Pandang Filosofi Kuhn dan Filosofi Popper
Authors: Aria Muhammad
Published: February 2020

Abstrak – Kendaraan otonom dapat bermanfaat untuk meningkatkan keselamatan, efisiensi, aksesibilitas dan kenyamanan transportasi. Salah satu tugas penting yang harus dilakukan oleh kendaraan otonom adalah melakukan perencanaan jalur melalui lingkungan perkotaan yang dinamis dimana terdapat kendaraan lain dan pejalan kaki. Menuruf filosofi Kuhn, sebuah keilmuan memiliki siklus hidupnya sendiri-sendiri. Siklus hidup suatu keilmuan terdiri dari fase kelahiran, fase pembuktian dan fase diterimanya keilmuan baru tersebut menjadi apa yang disebut sebagai ilmu normal. Demikian juga dengan perkembangan keilmuan perencaan jalur, algoritma perencanaan jalur untuk kendaraan otonom masih terus diteliti dan dikembangkan oleh berbagai peneliti. Studi baru terus dilakukan dalam upaya menemukan teknik perencanaan jalur yang dapat diterima secara umum, sehingga algoritma tersebut akan menjadi ilmu normal. Menutur filosofi Popper, setiap algoritma yang diusulkan harus dapat diuji menggunakan prinsip falsifikasi untuk menentukan apakah teknik yang diusulkan tersebut akhirnya bisa menjadi ilmu normal atau tidak. Maka makalah ini bertujuan untuk memberikan gambaran mengenai siklus keilmuan perencanaan jalur kendaraan otonom. Makalah ini juga bertujuan untuk membandingkan penelitian-penelitian terkini mengenai algoritma perencanaan jalur untuk kendaraan otonom di daerah perkotaan. Dalam membandingkan algoritma-algoritma tersebut akan digunakan prinsip falsifikasi Popper. Hasil perbandingan yang disajikan dalam makalah ini akan membantu mendapatkan wawasan mengenai kelebihan dan kekurangan dari masing-masing algoritma, serta akan membantu juga untuk memilih algoritma yang digunakan dalam desain sistem kendaraan otonom.

 

Kata Kunci : Kendaraan otonom, algoritma perencanaan jalur, lingkungan perkotaan, siklus keilmuan Khun, falsifikasi Popper
La enseñanza de la diversidad cultural en la formación docente. Cinco dilemas para el debate
Authors: Martínez Laura Victoria , Diez María Laura
Published: February 2020

Este trabajo reúne algunas reflexiones sobre la enseñanza de la diversidad cultural en la formación docente. Las discusiones presentadas se orientan por experiencias y reco-rridos en distintos ámbitos de formación docente en el nivel universitario y terciario, así como en espacios de capacitación. Se apoyan, al mismo tiempo, en reflexiones que surgen de la investigación etnográfica en el campo de la antropología y educación. Luego de contextualizar el lugar de la temática en el currículo actual de nivel superior, se postulan algunos dilemas vinculados a la enseñanza de categorías y discusiones centrales del enfoque antropológico sobre la diversidad cultural. En particular, se desa-rrolla este planteo a través del concepto de cultura, el paradigma de la diversidad en sus aspectos históricos y jurídicos, y sus articulaciones con las nociones de alteridad, y desigualdad. Finalmente, se destaca la relevancia pedagógica de reponer la proble-matización de los aspectos normativos y prescriptivos de la diversidad como marco institucional y como mandato docente.
Mujeres Mapuce entretejiendo conocimientos y memorias de resistencia. Notas de investigación
Authors: Alonso Graciela , Lincan Eva , Paz Anabella
Published: February 2020

El artículo reflexiona sobre categorías que entendemos densifican el abordaje de la investigación en clave intercultural en el trabajo con mujeres mapuce. En ese sentido, las categorías intersección, fusión, memoria y ancestralidad nos permiten pensar que los procesos interculturales, dentro y fuera de los espacios mapuce, proyectan sus con-tenidos y metodologías sobre la base de la resignificación y transmisión de pedagogías ancestrales en clave generacional y de resistencia a un conjunto de opresiones.
O Lazer no Pedaço
Authors: Pavez Cristienne Magalhães Pereira , Dias Vera Lúcia Nehls
Published: February 2020

Este estudo apresenta um olhar acerca das áreas de lazer no centro de Joinville/SC a partir dos estudos do antropólogo José G. Cantor Magnani e suas categorias de análise que ajudam a interpretar a dinâmica de um determinado lugar. O artigo se divide em três partes, sendo a primeira introdutória com abordagem teórica sobre o direito a cidade e os espaços de lazer, a segunda traz uma revisão sobre alguns textos de Magnani que enfocam o lazer em áreas centrais e, na terceira, se apresenta um pequeno estudo de caso da Praça Nereu Ramos, situada na área Central da cidade de Joinville/SC onde são realizadas reflexões com base no autor estudado. Este estudo foi realizado com apoio documental, uma pesquisa qualitativa que procura utilizar as bases teóricas de análise de Magnani em um caso empírico particular. Como resultados, se tem uma análise dos espaços centrais de lazer e uma reflexão sobre suas significações no mundo contemporâneo.
Ocupar o Espaço Público!
Authors: Falcão Denise
Published: February 2020

Encontrar músicos tocando nas ruas de cidades turísticas é cada vez mais corriqueiro. A condição básica para que essa prática social aconteça é a ocupação do espaço público. Os processos de turistificação dessas metrópoles, acarretam a privatização do espaço social transformando-o em espaço para consumo. Nesse ponto nevrálgico, essa investigação, fruto de uma pesquisa etnográfica, debruça-se na intenção de compreender as relações presentes na ocupação dos espaços públicos pelos músicos de rua em duas cidades cosmopolitas e turísticas: Rio de Janeiro e Barcelona. Recorte de uma tese doutoral, esse artigo, envolveu observação de campo e 23 entrevistas. As análises, seguindo os pressupostos etnográficos de reconhecimento de significados culturais e pessoais, evidenciaram tanto a luta dos músicos de rua pelo “direito à cidade”, como suas “artes de fazer” em táticas cotidianas para resistir e não ser banido pela ordem social vigente na ocupação do espaço público.
Entre o Tempo Livre e a Educação
Authors: Cruz Junior Gilson , Bungenstab Gabriel Carvalho
Published: February 2020

Este ensaio reflete sobre as relações entre juventude, mídias e lazer, buscando identificar as principais demandas formativas advindas dessa relação, bem como apresentar algumas das respostas dadas a elas. A relevância dos meios de comunicação no âmbito do lazer já é antiga e remonta a um passado não tão recente em que mídias massivas como a TV já ocupavam parte significativa do tempo livre das massas. Com a ascensão das mídias digitais, surgem novos recursos voltados à informação, criação e sociabilidade, cujas potencialidades têm sido amplamente reconhecidas e divulgadas. Nesse sentido, as apropriações dos jovens são objeto de intensos debates, ora pela originalidade e vanguardismo apresentados por elas, ora pelos discursos deterministas e essencialistas que tem ocultado suas contradições e insuficiências.
PENGARUH NILAI AKUNTANSI TERHADAP PENGELOLAAN KEUANGAN MAHASISWA (STEBIS IGM)
Authors: FADILLA FADILLA
Published: February 2020

Penelitian ini bertujuan untuk menetahui bagaimana pemahaman Mahasiswa STEBIS (Sekolah Tinggi Ekonomi dan Bisnis Syariah) dalam pelajaran Akuntansi, serta sejauh mana pemahaman mahasiswa tersebut dapat berpengaruh dalam pengalokasian keuangan mereka. Pemahaman mahasiswa diukur dengan nilai Akuntansi, sedangkan pengelolaan keuangan di ukur dengan menghitung berapa banyak pengeluaran mereka setiap bulannya yang di-proxi dengan uang saku/ uang jajan mereka setiap bulannya. Populasi dalam penelitian ini adalah mahasiswa STEBIS angkatan tahun 205-2016, dari program studi perbankan dan ekonomi syariah. Metode analisis yang digunakan adalah regeresil inier sederhana. Hasil uj t menunjukkan bahwa nilai akuntansi berpengaruh terhadap uang saku. Nilai signifikansinya adalah -0,016.