Real-Time Three-Dimensional Pedestrian Localization System Using Smartphones.

Robust and accurate three-dimensional localization is essential for personal navigation, emergency rescue, and worker monitoring in indoor environments. For localization technology to be employed in various applications, it is necessary to reduce infrastructure dependence and limit the maximum error bound. This study aims to accurately estimate the location of various people using smartphones in a building with a cloud platform-based localization system. The proposed technology is modularized in a hierarchical structure to sequentially estimate the floor and location. This system comprises four localization modules: course level detection, fine level detection (FLD), fine location tracking (FLT), and level change detection (LCD). Each module operates organically according to the current user status. The position estimation range is defined as a total of three phases, and an appropriate location estimation module suitable for the corresponding phase operates to estimate the user's location gradually and precisely. When the user's floor is determined by an FLD, the two-dimensional position of the user is estimated by an FLT module that tracks the user's position by comparing the received signal strength indicator vector sequence and radio map. Also, LCD recognizes the user's floor change and converts the user's phase. To verify the proposed technology, various experiments were conducted in a six-story building, and an average accuracy of less than 2 m was obtained.

Identification of Chemical Vapor Mixture Assisted by Artificially Extended Database for Environmental Monitoring.

A fully integrated sensor array assisted by pattern recognition algorithm has been a primary candidate for the assessment of complex vapor mixtures based on their chemical fingerprints. Diverse prototypes of electronic nose systems consisting of a multisensory device and a post processing engine have been developed. However, their precision and validity in recognizing chemical vapors are often limited by the collected database and applied classifiers. Here, we present a novel way of preparing the database and distinguishing chemical vapor mixtures with small data acquisition for chemical vapors and their mixtures of interest. The database for individual vapor analytes is expanded and the one for their mixtures is prepared in the first-order approximation. Recognition of individual target vapors of NO2, HCHO, and NH3 and their mixtures was evaluated by applying the support vector machine (SVM) classifier in different conditions of temperature and humidity. The suggested method demonstrated the recognition accuracy of 95.24%. The suggested method can pave a way to analyze gas mixtures in a variety of industrial and safety applications.

Ionic contrast across a lipid membrane for Debye length extension: towards an ultimate bioelectronic transducer.

Despite technological advances in biomolecule detections, evaluation of molecular interactions via potentiometric devices under ion-enriched solutions has remained a long-standing problem. To avoid severe performance degradation of bioelectronics by ionic screening effects, we cover probe surfaces of field effect transistors with a single film of the supported lipid bilayer, and realize respectable potentiometric signals from receptor-ligand bindings irrespective of ionic strength of bulky solutions by placing an ion-free water layer underneath the supported lipid bilayer. High-energy X-ray reflectometry together with the circuit analysis and molecular dynamics simulation discovered biochemical findings that effective electrical signals dominantly originated from the sub-nanoscale conformational change of lipids in the course of receptor-ligand bindings. Beyond thorough analysis on the underlying mechanism at the molecular level, the proposed supported lipid bilayer-field effect transistor platform ensures the world-record level of sensitivity in molecular detection with excellent reproducibility regardless of molecular charges and environmental ionic conditions.

Underground Parking Lot Navigation System Using Long-Term Evolution Signal.

Some of the shopping malls, airports, hospitals, etc. have underground parking lots where hundreds of vehicles can be parked. However, first-time visitors find it difficult to determine their current location and need to keep moving the vehicle to find an empty parking space. Moreover, they need to remember the parked location, and find a nearby staircase or elevator to move toward the destination. In such a situation, if the user location can be estimated, a new navigation system can be offered, which can assist users. This study presents an underground parking lot navigation system using long-term evolution (LTE) signals. As the proposed system utilizes LTE network signals for which the infrastructure is already installed, no additional infrastructure is required. To estimate the location of the vehicle, the signal strength of the LTE signal is accumulated, and the location of the vehicle is estimated by comparing it with the previously stored database of the LTE received signal strength (RSS). In addition, the acceleration and gyroscope sensors of a smartphone are used to improve the vehicle position estimation performance. The effectiveness of the proposed system is verified by conducting an experiment in a large shopping-mall underground parking lot where approximately 500 vehicles can be parked. From the results of the experiment, an error of less than an average of 10 m was obtained, which shows that seamless navigation is possible using the proposed system even in an environment where GNSS does not function.

On-Chip Chemiresistive Sensor Array for On-Road NO x Monitoring with Quantification.

The adverse effects of air pollution on respiratory health make air quality monitoring with high spatial and temporal resolutions essential especially in cities. Despite considerable interest and efforts, the application of various types of sensors is considered immature owing to insufficient sensitivity and cross-interference under ambient conditions. Here, a fully integrated chemiresistive sensor array (CSA) with parts-per-trillion sensitivity is demonstrated with its application for on-road NO x monitoring. An analytical model is suggested to describe the kinetics of the sensor responses and quantify molecular binding affinities. Finally, the full characterization of the system is connected to implement on-road measurements on NO x vapor with quantification as its ultimate field application. The obtained results suggest that the CSA shows potential as an essential unit to realize an air-quality monitoring network with high spatial and temporal resolutions.

Surface Correlation-Based Fingerprinting Method Using LTE Signal for Localization in Urban Canyon.

The Global Satellite Navigation System (GNSS) used in various location-based services is accurate and stable in outdoor environments. However, it cannot be utilized in an indoor environment because of low signal availability and degradation of accuracy due to the multipath distortion of satellite signals in urban areas. On the contrary, LTE signals are available almost everywhere in urban areas and are quite stable without much variation throughout the year. This is because of the fixed location of base stations and the well-maintained policy of mobile communication service providers. Its varied stability and reliability make LTE signals a more viable method for localization. However, there are some complexities in utilizing LTE signals including signal interference distortion phenomena during propagation multipath fading, and various types of noise. In this paper, we propose a surface correlation-based fingerprinting method to utilize LTE signals for localization in urban areas. The surface correlation converts timely measured signal strength into spatial pattern using the walking distance from a Pedestrian Dead-Reckoning (PDR). The surface correlation is carried out by comparing the spatial signal strength pattern of a pedestrian`s movement trajectory with a fingerprinting database to estimate the location. A reference trajectory of the moving pedestrian is chosen to have a greater correlation among the multiple trajectory candidates generated from a link-based fingerprinting database. By comparing spatial signal strength patterns, the proposed method can improve robustness in localization overcoming the accuracy degradation problem due to RF multipath and noise that are dominant in the conventional RSS measurement-based LTE localization scheme. The test results in urban areas demonstrate that the proposed surface correlation-based fingerprinting method has improved performance compared to the other conventional methods, thus proving to be a useful complementary method to the GNSS in urban areas.

Imaging and Differentiation of Retinal Ganglion Cells in Ex Vivo Experimental Optic Nerve Degeneration by Differential Interference Contrast Microscopy.

Purpose: Apoptotic loss of retinal ganglion cells (RGCs) is involved in various optic neuropathies, and its extent is closely related to visual impairment. Direct imaging and counting of RGCs is beneficial to the evaluation of RGC loss, but these processes are challenging with the conventional techniques, due to the transparency and hypo-reflectivity of RGCs as light-transmitting structures of the retina. Differential interference contrast (DIC) microscopy, which can provide real-time images of transparent specimens, is utilized to image neuronal cells including RGCs in the ganglion cell layer (GCL). Methods: Herein, we show that the neuronal cells within each GCL in an explanted rat retina, including the inner nuclear layer and the outer nuclear layer, can be imaged selectively by transmission-type DIC microscopy. RGCs were also differentiated from non-RGCs by the objective method. Results: RGCs were differentiated from non-RGCs in the GCL by their morphological features on DIC images with the aid of retrograde fluorescence labeling. Loss of RGCs was detected in optic-nerve-transection and retinal-ischemia-reperfusion models by DIC imaging. The images obtained from the reflection-type DIC microscopy were comparable to those from the transmission-type DIC microscopy. Conclusions: This method enables direct optical visualization of RGCs in experimental optic-nerve degeneration, thus providing the opportunity for more accurate evaluation of optic neuropathies as well as more effective investigation of diseases.

Highly Sensitive Color Tunablility by Scalable Nanomorphology of a Dielectric Layer in Liquid-Permeable Metal-Insulator-Metal Structure.

A liquid-permeable concept in a metal-insulator-metal (MIM) structure is proposed to achieve highly sensitive color-tuning property through the change of the effective refractive index of the dielectric insulator layer. A semicontinuous top metal film with nanoapertures, adopted as a transreflective layer for MIM resonator, allows to tailor the nanomorphology of a dielectric layer through selective etching of the underneath insulator layer, resulting in nanopillars and hollow voids in the insulator layer. By allowing outer mediums to enter into the hollow voids of the dielectric layer, such liquid-permeable MIM architecture enables to achieve the wavelength shift as large as 323.5 nm/RIU in the visible range, which is the largest wavelength shift reported so far. Our liquid-permeable approaches indeed provide dramatic color tunablility, a real-time sensing scheme, long-term durability, and reproducibility in a simple and scalable manner.

Artificial Rod and Cone Photoreceptors with Human-Like Spectral Sensitivities.

Photosensitive materials contain biologically engineered elements and are constructed using delicate techniques, with special attention devoted to efficiency, stability, and biocompatibility. However, to date, no photosensitive material has been developed to replace damaged visual-systems to detect light and transmit the signal to a neuron in the human body. In the current study, artificial nanovesicle-based photosensitive materials are observed to possess the characteristics of photoreceptors similar to the human eye. The materials exhibit considerably effective spectral characteristics according to each pigment. Four photoreceptors originating from the human eye with color-distinguishability are produced in human embryonic kidney (HEK)-293 cells and partially purified in the form of nanovesicles. Under various wavelengths of visible light, electrochemical measurements are performed to analyze the physiological behavior and kinetics of the photoreceptors, with graphene, performing as an electrode, playing an important role in the lipid bilayer deposition and oxygen reduction processes. Four nanovesicles with different photoreceptors, namely, rhodopsin (Rho), short-, medium-, and longwave sensitive opsin 1 (1SW, 1MW, 1LW), show remarkable color-dependent characteristics, consistent with those of natural human retina. With four different light-emitting diodes for functional verification, the photoreceptors embedded in nanovesicles show remarkably specific color sensitivity. This study demonstrates the potential applications of light-activated platforms in biological optoelectronic industries.

Chemiresistive Electronic Nose toward Detection of Biomarkers in Exhaled Breath.

Detection of gas-phase chemicals finds a wide variety of applications, including food and beverages, fragrances, environmental monitoring, chemical and biochemical processing, medical diagnostics, and transportation. One approach for these tasks is to use arrays of highly sensitive and selective sensors as an electronic nose. Here, we present a high performance chemiresistive electronic nose (CEN) based on an array of metal oxide thin films, metal-catalyzed thin films, and nanostructured thin films. The gas sensing properties of the CEN show enhanced sensitive detection of H2S, NH3, and NO in an 80% relative humidity (RH) atmosphere similar to the composition of exhaled breath. The detection limits of the sensor elements we fabricated are in the following ranges: 534 ppt to 2.87 ppb for H2S, 4.45 to 42.29 ppb for NH3, and 206 ppt to 2.06 ppb for NO. The enhanced sensitivity is attributed to the spillover effect by Au nanoparticles and the high porosity of villi-like nanostructures, providing a large surface-to-volume ratio. The remarkable selectivity based on the collection of sensor responses manifests itself in the principal component analysis (PCA). The excellent sensing performance indicates that the CEN can detect the biomarkers of H2S, NH3, and NO in exhaled breath and even distinguish them clearly in the PCA. Our results show high potential of the CEN as an inexpensive and noninvasive diagnostic tool for halitosis, kidney disorder, and asthma.

Highly sensitive and selective sugar detection by terahertz nano-antennas.

Molecular recognition and discrimination of carbohydrates are important because carbohydrates perform essential roles in most living organisms for energy metabolism and cell-to-cell communication. Nevertheless, it is difficult to identify or distinguish various carbohydrate molecules owing to the lack of a significant distinction in the physical or chemical characteristics. Although there has been considerable effort to develop a sensing platform for individual carbohydrates selectively using chemical receptors or an ensemble array, their detection and discrimination limits have been as high in the millimolar concentration range. Here we show a highly sensitive and selective detection method for the discrimination of carbohydrate molecules using nano-slot-antenna array-based sensing chips which operate in the terahertz (THz) frequency range (0.5-2.5 THz). This THz metamaterial sensing tool recognizes various types of carbohydrate molecules over a wide range of molecular concentrations. Strongly localized and enhanced terahertz transmission by nano-antennas can effectively increase the molecular absorption cross sections, thereby enabling the detection of these molecules even at low concentrations. We verified the performance of nano-antenna sensing chip by both THz spectra and images of transmittance. Screening and identification of various carbohydrates can be applied to test even real market beverages with a high sensitivity and selectivity.

Enhanced nonlinear optical characteristics of copper-ion-doped double crossover DNAs.

The modification of deoxyribonucleic acid (DNA) samples by sequencing the order of bases and doping copper ions opens the possibility for the design of novel nanomaterials exhibiting large optical nonlinearity. We investigated the nonlinear characteristics of copper-ion doped double crossover DNA samples for the first time to the best of our knowledge by using Z-scan and four-wave mixing methods. To accelerate the nonlinear characteristics, we prepared two types of unique DNA nanostructures composed of 148 base pairs doped with copper ions with a facile annealing method. The outstanding third-order nonlinear optical susceptibility of the copper-ion-doped DNA solution, 1.19 × 10(-12) esu, was estimated by the conventional Z-scan measurement, whereas the four-wave mixing experiment was also investigated. In the visible spectral range, the copper-ion-doped DNA solution samples provided competent four-wave mixing signals with a remarkable conversion efficiency of -4.15 dB for the converted signal at 627 nm. The interactions between DNA and copper ions contribute to the enhancement of nonlinearity due to structural and functional changes. The present study signifies that the copper-ion-doped double crossover DNA is a potential candidate as a highly efficient novel material for further nonlinear optical applications.

Broadband supercontinuum generation using a hollow optical fiber filled with copper-ion-modified DNA.

We experimentally demonstrated supercontinuum generation through a hollow core photonic bandgap fiber (HC-PBGF) filled with DNA nanocrystals modified by copper ions in a solution. Both double-crossover nano DNA structure and copper-ion-modified structure provided a sufficiently high optical nonlinearity within a short length of hollow optical fiber. Adding a higher concentration of copper ion into the DNA nanocrystals, the bandwidth of supercontinuum output was monotonically increased. Finally, we achieved the bandwidth expansion of about 1000 nm to be sufficient for broadband multi-spectrum applications.

Observation of terahertz-radiation-induced ionization in a single nano island.

Terahertz (THz) electromagnetic wave has been widely used as a spectroscopic probe to detect the collective vibrational mode in vast molecular systems and investigate dielectric properties of various materials. Recent technological advances in generating intense THz radiation and the emergence of THz plasmonics operating with nanoscale structures have opened up new pathways toward THz applications. Here, we present a new opportunity in engineering the state of matter at the atomic scale using THz wave and a metallic nanostructure. We show that a medium strength THz radiation of 22 kV/cm can induce ionization of ambient carbon atoms through interaction with a metallic nanostructure. The prepared structure, made of a nano slot antenna and a nano island located at the center, acts as a nanogap capacitor and enhances the local electric field by two orders of magnitudes thereby causing the ionization of ambient carbon atoms. Ionization and accumulation of carbon atoms are also observed through the change of the resonant condition of the nano slot antenna and the shift of the characteristic mode in the spectrum of the transmitted THz waves.

A pseudolite-based positioning system for legacy GNSS receivers.

The ephemeris data format of legacy GPS receivers is improper for positioning stationary pseudolites on the ground. Therefore, to utilize pseudolites for navigation, GPS receivers must be modified so that they can handle the modified data formats of the pseudolites. Because of this problem, the practical use of pseudolites has so far been limited. This paper proposes a pseudolite-based positioning system that can be used with unmodified legacy GPS receivers. In the proposed system, pseudolites transmit simulated GPS signals. The signals use standard GPS ephemeris data format and contain ephemeris data of simulated GPS satellites, not those of pseudolites. The use of the standard format enables the GPS receiver to process pseudolite signals without any modification. However, the position output of the GPS receiver is not the correct position in this system, because there are additional signal delays from each pseudolite to the receiver. A post-calculation process was added to obtain the correct receiver position using GPS receiver output. This re-estimation is possible because it is based on known information about the simulated signals, pseudolites, and positioning process of the GPS receiver. Simulations using generated data and live GPS data are conducted for various geometries to verify the proposed system. The test results show that the proposed system provides the desired user position using pseudolite signals without requiring any modifications to the legacy GPS receiver. In this initial study, a pseudolite-only indoor system was assumed. However, it can be expanded to a GPS-pseudolite system outdoors.

A wireless monitoring sub-nA resolution test platform for nanostructure sensors.

We have constructed a wireless monitoring test platform with a sub-nA resolution signal amplification/processing circuit (SAPC) and a wireless communication network to test the real-time remote monitoring of the signals from carbon nanotube (CNT) sensors. The operation characteristics of the CNT sensors can also be measured by the ISD-VSD curve with the SAPC. The SAPC signals are transmitted to a personal computer by Bluetooth communication and the signals from the computer are transmitted to smart phones by Wi-Fi communication, in such a way that the signals from the sensors can be remotely monitored through a web browser. Successful remote monitoring of signals from a CNT sensor was achieved with the wireless monitoring test platform for detection of 0.15% methanol vapor with 0.5 nA resolution and 7 Hz sampling rate.

Pattern recognition for selective odor detection with gas sensor arrays.

This paper presents a new pattern recognition approach for enhancing the selectivity of gas sensor arrays for clustering intelligent odor detection. The aim of this approach was to accurately classify an odor using pattern recognition in order to enhance the selectivity of gas sensor arrays. This was achieved using an odor monitoring system with a newly developed neural-genetic classification algorithm (NGCA). The system shows the enhancement in the sensitivity of the detected gas. Experiments showed that the proposed NGCA delivered better performance than the previous genetic algorithm (GA) and artificial neural networks (ANN) methods. We also used PCA for data visualization. Our proposed system can enhance the reproducibility, reliability, and selectivity of odor sensor output, so it is expected to be applicable to diverse environmental problems including air pollution, and monitor the air quality of clean-air required buildings such as a kindergartens and hospitals.

Implementation of a vector-based tracking loop receiver in a pseudolite navigation system.

We propose a vector tracking loop (VTL) algorithm for an asynchronous pseudolite navigation system. It was implemented in a software receiver and experiments in an indoor navigation system were conducted. Test results show that the VTL successfully tracks signals against the near-far problem, one of the major limitations in pseudolite navigation systems, and could improve positioning availability by extending pseudolite navigation coverage.