Real-time Representation Research Articles

Design and Application of a Network Planning System Based on Digital Twin Network

As a real-time representation of physical entities in the digital world, digital twin (DT) has been widely used in several industrial fields, bringing significant efficiency gains and cost reductions. Network planning is a very important stage in network life cycle management. At this stage, comprehensive and effective use of network data and historical experience can not only greatly reduce the cost of network planning and construction, but also speed up the production and launch of technologies and products. In this paper, a network planning system based on digital twin network (DTN) is proposed. Aiming at the key problems faced by current network planning, we complete the overall architecture design of the system and the detailed design of each unit. Finally, we verified the applications of this system in practice, including the closed-loop process of network planning, the entire life cycle management of data, and the visualization of the whole process of network planning. It is shown that by using this general digital system, the efficiency and accuracy of network planning can be effectively improved and the cost can be reduced.

Modeling of Deadtime Events in Power Converters with Half-Bridge Modules for a Highly Accurate Hardware-in-the-Loop Fixed Point Implementation in FPGA

Hardware-in-the-loop (HIL) simulations of power converters must achieve a truthful representation in real time with simulation steps on the order of microseconds or tens of nanoseconds. The numerical solution for the differential equations that model the state of the converter can be calculated using the fourth-order Runge–Kutta method, which is notably more accurate than Euler methods. However, when the mathematical error due to the solver is drastically reduced, other sources of error arise. In the case of converters that use deadtimes to control the switches, such as any power converter including half-bridge modules, the inductor current reaching zero during deadtimes generates a model error large enough to offset the advantages of the Runge–Kutta method. A specific model is needed for such events. In this paper, an approximation is proposed, where the time step is divided into two semi-steps. This serves to recover the accuracy of the calculations at the expense of needing a division operation. A fixed-point implementation in VHDL is proposed, reusing a block along several calculation cycles to compute the needed parameters for the Runge–Kutta method. The implementation in a low-cost field-programmable gate arrays (FPGA) (Xilinx Artix-7) achieves an integration time of 1μs. The calculation errors are six orders of magnitude smaller for both capacitor voltage and inductor current for the worst case, the one where the current reaches zero during the deadtimes in 78% of the simulated cycles. The accuracy achieved with the proposed fixed point implementation is very close to that of 64-bit floating point and can operate in real time with a resolution of 1μs. Therefore, the results show that this approach is suitable for modeling converters based on half-bridge modules by using FPGAs. This solution is intended for easy integration into any HIL system, including commercial HIL systems, showing that its application even with relatively high integration steps (1μs) surpasses the results of techniques with even faster integration steps that do not take these events into account.

Emotional Effects Induced by the Application of a Cosmetic Product: A Real-Time Electrophysiological Evaluation

Well-being is an essential concept in cosmetics, but its complexity makes it very difficult to measure. The goal of the present study was to use electroencephalography (EEG) to compare the emotions induced by the application of two cosmetic products, and to offer to the experimenter a real-time representation of the participants’ emotional state. Fifteen female subjects participated in a cross-over study. Two cosmetic products of similar consistency were compared and applied from the dominant hand to the non-dominant hand. During the application, the neural activity of each participant was recorded with EEG. We found that the most appreciated product was the one that induced emotions with the most positive valence and the higher arousal, as recorded by EEG. Moreover, the videos recorded of each participant allowed us to attest to the differences in emotion processing for each product in real-time. This exploratory study shows that EEG can be successfully used to assess the emotions induced by the application of a cosmetic product, and in real-time. This technique could be a useful adjunct to other methods of examining emotions, such as observational experiments, surveys, and questionnaires.

Theoretical scheme for finite-temperature dynamics of Kitaev’s spin liquids

In this article, we review the theoretical formulation of finite temperature dynamics of Kitaev’s spin liquid. We present the exact analytical solution of the dynamical spin correlation function at the integrable limit of Kitaev’s model, on the basis of (2018 Phys. Rev. B 98 220404). By combining the analytical solution with the equilibrium classical Monte-Carlo scheme, we construct a formulation to access the finite temperature dynamics of Kitaev’s spin liquid exactly, with a reasonable amount of computational cost. This formulation is based on the real-time representation, which enables us to directly access the experimental observables defined in real frequency, without analytical continuation. The real-time scheme is essential to capturing the resonant features of the spectrum accurately, which occurs e.g. in the chiral spin liquid phase with isolated Majorana zero modes. Accordingly, this scheme provides an effective approach to address the nature of fractional excitations in Kitaev’s spin liquid. As an application, we address the detection of zero mode around the site vacancy through the local resonant spectrum and discuss how the character of Kitaev’s spin liquid emerges in its dynamical signature.

Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors

In this paper, we review the emerging concept of digital twins (DTs) for urban water systems (UWS) based on the literature, stakeholder interviews and analyzing the current DT implementation process in the utility company VCS Denmark (VCS). Here, DTs for UWS are placed in the context of DTs at the component, unit process/operation or hydraulic structure, treatment plant, system, city, and societal levels. A UWS DT is characterized as a systematic virtual representation of the elements and dynamics of the physical system, organized in a star-structure with a set of features connected by data links that are based on standards for open data. This allows the overall functionality to be broken down into smaller, tangible units (features), enabling microservices that communicate via data links to emerge (the most central feature), facilitated by application programing interfaces (APIs). Coupled to the physical system, simulation models and advanced analytics are among the most important features. We propose distinguishing between living and prototyping DTs, where the term “living” refers to coupling observations from an ever-changing physical twin (which may change with, e.g., urban growth) with a simulation model, through a data link connecting the two. A living DT is thus a near real-time representation of an UWS and can be used for operational and control purposes. A prototyping DT represents a scenario for the system without direct coupling to real-time observations, which can be used for design or planning. By acknowledging that different DTs exist, it is possible to identify the value-creation from DTs achieved by different end-users inside and outside a utility organization. Analyzing the DT workflow in VCS shows that a DT must be multifunctional, updateable, and adjustable to support potential value creation across the utility company. This study helps clarify key DT terminology for UWS and identifies steps to create a DT by building upon digital ecosystems (DEs) and open standards for data.

Calculating altmetrics based on the data obtained at users’ accessing library e-catalogs

The authors examine the libraries’ independent calculations and analysis of alternative metrics to determine user-defined relevancy of publications. Logfiles collected by web-servers at users’ accessing e-catalogs may be used for such calculations and analysis. The almetrics’ key advantages as compared to traditional bibliometrics and webometrics are: real-time representation; openness and transparency; coverage of wider non-academic audience; coverage of various sources and research findings. The web-server log-files enable to analyze number of user views of bibliographic records in e-catalog, to rate authors, individual publications and topical queries for a time period. In case of links to full texts, the number of pdf. documents loaded by users and n umber of p ages viewed ( when library computer-based system supports full-text document scrolling mode) may be defined. The authors also discuss specificity of handling log-files for various analysis types: statistical, content addressable, defining sequential sets, clustering. The functionality and table structure of RNPLST’s software module for advanced bibliometric analysis is described. The further task of the study will be to define trends of user behavior and forecasts for user group behavior when using e-catalog.The article is prepared within the framework of the State Order to Russian National Public Library for Science and Technology “Development and improvement of the system of Open Archive of integrated information and library resources of Russian National Public Library for Science and Technology as modern knowledge management system in digital environment: on the way to Open Science” № 075-01300-20-00 for 2020–2022.

Ionospheric and plasmaspheric electron contents from space-time collocated digisonde, COSMIC, and GPS observations and model assessments

An accurate representation of bottomside, topside ionosphere, and plasmasphere electron content remains as one of the important issues for the development of realistic ionosphere and plasmasphere models. The reason is that the full altitude electron density profile specification is restricted by a simultaneous lack of adequate ground or space-based datasets. In this article, we present sensible assimilation of peak parameters in the topside profiles from the FormoSat-3/COSMIC ionospheric occultations with the auto-scaled bottomside profiles from 39 global Digisonde rather than peak to topside extrapolation. Under strict space-time collocation criteria, the integral electron content from the assimilated electron density profiles along with global positioning system derived total electron content demonstrates altitude dependent contributions. The corresponding estimations from the empirical ionospheric and plasmaspheric models (IRI-2016, NeQuick-2, and IRI-Plas 2017) are also assessed to realize their discrepancies with respect to the observed parameters. The statistical comparison metrics show relatively closer overall ionospheric electron content estimates from IRI with the assimilated results, followed by NeQuick and IRI-Plas models, with the last two models showing an opposite behavior between bottomside and topside electron content discrepancies. However, although the total electron content estimations reveal the relatively superior performance of IRI-Plas with successive proficiency of NeQuick and IRI models, the retrieved plasmaspheric electron content data does not evident any clear statistical metrics and dictates further investigation. Nevertheless, this assimilation work leads towards improving the altitudinal representation of ionospheric models, particularly in the context of real-time representation of topside, bottomside, and plasmaspheric electron content through a reconstruction of the complete electron density profile.

Monitoring structural behaviour of concrete beams reinforced with steel and GFRP bars using acoustic emission and digital image correlation techniques

The paper investigates the flexure behaviour and cracking pattern of reinforced concrete beams utilizing steel and GFRP reinforcement using a judicious combination of non-destructive testing techniques of Acoustic Emission (AE) and Digital Image Correlation (DIC). AE parameters including amplitude, number of AE hits, average frequency (AF) and rise angle (RA) successfully correlate with cracking initiation and its progression in steel reinforced concrete (RC) and GFRP RC beams. The plot between AF-RA value effectively classifies the different failure modes in the two types of beams. Simultaneous drop in AF and a significant jump in AE duration at the same instant give a fair indication of critical failure points. AE-XY plots and longitudinal strain profiles obtained from DIC give a real-time representation of progressive AE activity and strains respectively. While AE is proposed to characterize the onset and propagation of the cracking pattern and mode of failure in the beams, DIC assists to visualize the displacement and strain fields while highlighting discontinuities in the displacement field. The work is aimed at developing a health monitoring strategy for RC beams with steel or GFRP bars which is in-situ, non-invasive and provides pre-emptive warning in real-time so that catastrophic failures can be completely avoided.

Clinical implications of plasma circulating tumor DNA in gynecologic cancer patients.

Molecular characterization of cancers is important in dictating prognostic factors and directing therapy. Next-generation sequencing of plasma circulating tumor DNA (ctDNA) offers less invasive, more convenient collection, and a more real-time representation of a tumor and its molecular heterogeneity than tissue. However, little is known about the clinical implications of ctDNA assessment in gynecologic cancer. We describe the molecular landscape identified on ctDNA, ctDNA concordance with tissue-based analysis, and factors associated with overall survival (OS) in gynecologic cancer patients with ctDNA analysis. We reviewed clinicopathologic and genomic information for 105 consecutive gynecologic cancer patients with ctDNA analysis, including 78 with tissue-based sequencing, enrolled in the Profile-Related Evidence Determining Individualized Cancer Therapy (NCT02478931) trial at the University of California San Diego Moores Cancer Center starting July 2014. Tumors included ovarian (47.6%), uterine (35.2%), cervical (12.4%), vulvovaginal (2.9%), and unknown gynecologic primary (1.9%). Most ovarian and uterine cancers (86%) were high grade. 34% (N=17) of ovarian cancers had BRCA alterations, and 22% (N=11) were platinum sensitive. Patients received median 2 (range 0-13) lines of therapy prior to ctDNA collection. Most (75.2%) had at least one characterized alteration on ctDNA analysis, and the majority had unique genomic profiles on ctDNA. Most common alterations were TP53 (N=59, 56.2% of patients), PIK3CA (N=26, 24.8%), KRAS (N=14, 13.3%), BRAF (N=10, 9.5%), ERBB2 (N=8, 7.6%), and MYC (N=8, 7.6%). Higher ctDNA maximum mutation allele frequency was associated with worse OS [hazard ratio (HR): 1.91, P=0.03], while therapy matched to ctDNA alterations (N=33 patients) was independently associated with improved OS (HR: 0.34, P=0.007) compared to unmatched therapy (N=28 patients) in multivariate analysis. Tissue and ctDNA genomic results showed high concordance unaffected by temporal or spatial factors. This study provides evidence for the utility of ctDNA in determining outcome and individualizing cancer therapy in patients with gynecologic cancer.

Real-Time Compact Environment Representation for UAV Navigation.

Recently, unmanned aerial vehicles (UAVs) have attracted much attention due to their on-demand deployment, high mobility, and low cost. For UAVs navigating in an unknown environment, efficient environment representation is needed due to the storage limitation of the UAVs. Nonetheless, building an accurate and compact environment representation model is highly non-trivial because of the unknown shape of the obstacles and the time-consuming operations such as finding and eliminating the environmental details. To overcome these challenges, a novel vertical strip extraction algorithm is proposed to analyze the probability density function characteristics of the normalized disparity value and segment the obstacles through an adaptive size sliding window. In addition, a plane adjustment algorithm is proposed to represent the obstacle surfaces as polygonal prism profiles while minimizing the redundant obstacle information. By combining these two proposed algorithms, the depth sensor data can be converted into the multi-layer polygonal prism models in real time. Besides, a drone platform equipped with a depth sensor is developed to build the compact environment representation models in the real world. Experimental results demonstrate that the proposed scheme achieves better performance in terms of precision and storage as compared to the baseline.

Abstract 43: Clinical implications of real-world data on plasma circulating tumor DNA in gynecologic cancer patients

Abstract Molecular characterization of individual cancers is increasingly important in dictating prognostic factors and directing therapy. Next-generation sequencing of blood-derived circulating tumor DNA (ctDNA) offers less invasive, more convenient collection and a more real-time representation of a tumor and its molecular heterogeneity than tissue-based analysis. However, little is known about the clinical implications of ctDNA assessment in gynecologic cancer. We report the clinicopathologic and genomic information for 105 gynecologic cancer patients with ctDNA analysis, including 78 patients with tissue-based sequencing, who were enrolled in Profile Related Evidence Determining Individualized Cancer Therapy (PREDICT, NCT02478931). Tumors in our cohort included ovarian (47.6%), uterine (35.2%), cervical (12.4%), vulvar or vaginal (2.9%), and gynecologic cancer of unknown primary (1.9%). The majority of patients (74.3%) had at least one characterized alteration on ctDNA analysis. The most common alterations were in the following genes: TP53 (N=59, 56.2% of patients), PIK3CA (N=26, 24.8%), KRAS (N=14, 13.3%), BRAF (N=10, 9.5%), ERBB2 (N=8, 7.6%), and MYC (N=8, 7.6%). Higher total percentage of ctDNA was associated with worse overall survival (HR 2.18, p=0.008), and therapy matched to ctDNA genomic alterations (N = 33 patients) independently predicted improved overall survival (HR 0.34, p=0.007) as compared to unmatched therapy (N = 28 patients). Tissue and ctDNA genomic results showed high concordance unaffected by temporal or spatial factors. This study provides evidence for the utility of ctDNA in determining outcome and individualizing cancer therapy in patients with gynecologic cancer. Citation Format: Lindsey Michelle Charo, Ramez N. Eskander, Ryosuke Okamura, Sandip Patel, Mina Nikanjam, Richard Layman, David E. Piccioni, Shamei Kato, Michael McHale, Razelle Kurzrock. Clinical implications of real-world data on plasma circulating tumor DNA in gynecologic cancer patients [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 43.

Implementing Secure Routable GOOSE and SV Messages Based on IEC 61850-90-5

Next generation power systems are active networks that handle two-way power flow. They are equipped with extensive communication capabilities to perform dynamic monitoring, protection and control operations. Synchrophasors provide a pseudo real-time representation of grid's current state. Phasor Measurement Units (PMU) placed in different parts of the grid periodically collect synchrophasor data. Then, they send it to a Phasor Data Concentrator (PDCs) through Wide Area Monitoring Systems (WAMS). The entire system formed as PMU Communication Network (PMU-CN) is based on two available frameworks: IEEE C37.118.2 and IEC 61850-90-5. As New York Blackout of 2003 showed that accurate and timely delivery of phasor measurements is vital for secure grid operation. Attacks on PMU-CN may lead to several consequences in the grid and cause physical damage. IEEE C37.118.2 does not specify any security mechanism to mitigate security attacks. To address this gap, security mechanism specified in IEC 61850-90-5 have been implemented using OpenSSL library. A novel toolbox called R-GoSV has been developed to construct PMU messages with cybersecurity mechanisms. Thanks to this tool, custom messages have been transmitted in the network to investigate their effectiveness. Finally, the performance evaluation of the specified security algorithms in terms of computational time sis carried out.

The Photometric Stereo Approach and the Visualization of 3D Face Reconstruction

The 3D Morphable models of the human face have prepared myriad of applications in computer vision, human computer interaction and security surveillances. However, due to the variation in size, complexity of training data set, the landmark mapping, the representation in real time and rendering or synthesis of images in three dimensional is limited. In this paper, we extend the approach of the photometric stereo and provide the human face reconstruction in three dimensional. The proposed method consists of two steps. First it automatically detects the face and segment the iris along with statistical features of pupil location in it. Secondly it provides the selection of minimum six features and where iris process to generate the 3D face. In compare with existing methods our approach provides the automation which produces more better and efficient results in contrast to the manual methods.

The Dual Application of Neurofeedback Technique and the Blurred Lines Between the Mental, the Social, and the Moral

Recent neuroscience studies have reported that neurofeedback training with the use of functional magnetic resonance imaging enables the regulation of an individual’s cognitive, emotion-related, and behavioral states through a real-time representation of her brain activities. Since this technique has been applied not only to clinical research to, for example, mitigate mental or psychiatric symptoms but also to non-clinical research to, for example, change the cognition or preferences of a so-called healthy participant, neurofeedback-based cognitive and/or moral enhancements may be realized in the future. However, neurofeedback-based human enhancement is not the only issue that requires neuroethical consideration. I examine why and to what extent the dual application of neurofeedback technique will blur the lines between the mental, the social, and the moral, threatening some social norms, such as individual freedom and diversity. First, I consider the link between the mental and the social in psychiatry. Examining the definition of “mental disorder” provided by the American Psychiatric Association, I show that the mental is partly defined through social performance. Second, I make explicit the link between the social and the moral and argue that moral evaluation of an activity is gently but positively correlated with its social evaluation. Third, I demonstrate the links between the mental, the social, and the moral. In spite of a great deal of effort to distinguish these notions, the possibility of the dual application of this technique blurs the lines between them. Fourth, I examine whether such blurred lines signal sociocultural evolution or dystopia and argue that it can be understood as a beginning of the second advent of ethical virtue. I conclude that further cautious consideration of neuroethics is required because the establishment of this technique may have unique influences on our society.

Fluctuating traffic noise levels calculated from time-dependent traffic data: an engineering approach

Temporal variations of traffic noise levels originate from two effects: (1) traffic variations and (2) atmospheric variations. Traffic variations include variations of traffic volume and vehicle speed, and cause variations of the emission of sound at the source. Atmospheric variations cause variations of the propagation of sound from the source to the receiver. In this article an engineering method is presented for the calculation of temporal variations of traffic noise levels, based on time-dependent data for traffic volume and speed. The method may be combined with engineering models such as the Dutch traffic noise model, the model ISO 9613-2, or the recently developed model Cnossos-EU. The method employs a simple formula for the timedependent effect of atmospheric wind and temperature gradients on sound propagation. The formula is derived fromsound propagation calculations for awide range of atmospheric conditions, performed with the Harmonoise model for traffic noise calculations. The engineering method developed in this article is used for a comparison with measurements near a highway in the Netherlands. Using time-dependent open traffic data for the highway, good agreement is obtained with sound levels recorded over a period of 24 hours. The method is of interest for urban traffic optimizations with environmental constraints, for example bymeans of “city dashboards,” showing real time representations of traffic flow and traffic noise in a city. © 2018 Institute of Noise Control Engineering.

Evaluation of the impact of a virtual self-avatar on gait parameters

Studies in the field of gait rehabilitation frequently use treadmills rather than over-ground walking, in part because treadmills require less space and allow for the capture of multiple gait cycles within a limited motion capture volume. Walking on a treadmill alters some kinematic and spatiotemporal parameters, which may be in part a result of the absence of optical flow. To overcome this limitation, some studies have used immersive virtual environments (VEs) to create an optical flow during treadmill gait. Using a head-mounted device, this has the effect of also hiding a user's body from himself. A real-time representation of the user can be displayed in the VEs, in the form of an animated self-avatar. Little is known on the effect of viewing one's self-avatar on gait patterns. This study aims to quantify the differences between walking in a VE with and without a real-time self-avatar. Eleven healthy participants walked in 3 different conditions. In the 1st condition, participants walked over-ground in a hallway. In the 2nd and 3rd conditions (randomized), participants walked in a virtual replica of the hallway, respectively with and without a real-time self-avatar. Through all conditions, participants wore inertial sensors on their pelvis and lower limbs. Participants’ mean cadence and gait cycle duration were computed for each condition. Conditions were compared using paired t -tests. The 2nd and 3rd conditions were compared. The addition of the self-avatar significantly reduced cadence (−1.9 step/min) and lead to a longer gait cycle duration (+0.04 s), even though they walked at the same speed on the treadmill. These results show that the addition of a self-avatar alters spatiotemporal gait patterns. Different potential explanations for these changes will be discussed. Future work will include analysis of the kinematic data for all conditions.

Smart Wound Dressings for Diabetic Chronic Wounds.

Given their severity and non-healing nature, diabetic chronic wounds are a significant concern to the 30.3 million Americans diagnosed with diabetes mellitus (2015). Peripheral arterial diseases, neuropathy, and infection contribute to the development of these wounds, which lead to an increased incidence of lower extremity amputations. Early recognition, debridement, offloading, and controlling infection are imperative for timely treatment. However, wound characterization and treatment are highly subjective and based largely on the experience of the treating clinician. Many wound dressings have been designed to address particular clinical presentations, but a prescriptive method is lacking for identifying the particular state of chronic, non-healing wounds. The authors suggest that recent developments in wound dressings and biosensing may allow for the quantitative, real-time representation of the wound environment, including exudate levels, pathogen concentrations, and tissue regeneration. Development of such sensing capability could enable more strategic, personalized care at the onset of ulceration and limit the infection leading to amputation. This review presents an overview of the pathophysiology of diabetic chronic wounds, a brief summary of biomaterial wound dressing treatment options, and biosensor development for biomarker sensing in the wound environment.

Quality of Experience for 3-D Immersive Media Streaming

Recent advances in media capture and processing technologies have enabled new forms of true 3-D media content that increase the degree of user immersion. The demand for more engaging forms of entertainment means that content distributors and broadcasters need to fine-tune their delivery mechanisms over the Internet as well as develop new models for quantifying and predicting user experience of these new forms of content. In the work described in this paper, we undertake one of the first studies into the quality of experience (QoE) of real-time 3-D media content streamed to virtual reality (VR) headsets for entertainment purposes, in the context of game spectating. Our focus is on tele-immersive media that embed real users within virtual environments of interactive games. A key feature of engaging and realistic experiences in full 3-D media environments, is allowing users unrestricted viewpoints. However, this comes at the cost of increased network bandwidth and the need of limiting network effects in order to transmit a realistic, real-time representation of the participants. The visual quality of 3-D media is affected by geometry and texture parameters while the temporal aspects of smooth movement and synchronization are affected by lag introduced by network transmission effects. In this paper, we investigate varying network conditions for a set of tele-immersive media sessions produced in a range of visual quality levels. Further, we investigate user navigation issues that inhibit free viewpoint VR spectating of live 3-D media. After reporting on a study with multiple users we analyze the results and assess the overall QoE with respect to a range of visual quality and latency parameters. We propose a neural network QoE prediction model for 3-D media, constructed from a combination of visual and network parameters.

Modeling and analyzing real-time wireless sensor and actuator networks using actors and model checking

Programmers often use informal worst-case analysis and debugging to ensure that schedulers satisfy real-time requirements. Not only can this process be tedious and error-prone, it is inherently conservative and thus likely to lead to an inefficient use of resources. We propose to use model checking to find a schedule which optimizes the use of resources while satisfying real-time requirements. Specifically, we represent a Wireless sensor and actuator network (WSAN) as a collection of actors whose behaviors are specified using a Java-based actor language extended with operators for real-time scheduling and delay representation. We show how the abstraction mechanism and the compositionality of actors in the actor model may be used to incrementally build a model of a WSAN's behavior from node-level and network models. We demonstrate the approach with a case study of a distributed real-time data acquisition system for high-frequency sensing using Timed Rebeca modeling language and the Afra model checking tool.

Real-Time Data Representation Control in Convolution Neural Networks Based Indoor Wi-Fi Localization for Internet of Things

Real-Time Data Representation Control in Convolution Neural Networks Based Indoor Wi-Fi Localization for Internet of Things