Journal articles: 'Open optical network'

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Virgillito, Emanuele, Alessio Ferrari, Andrea D’Amico, and Vittorio Curri. "Statistical Assessment of Open Optical Networks." Photonics 6, no. 2 (June 5, 2019): 64. http://dx.doi.org/10.3390/photonics6020064.

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In order to cope with the increase of the final user traffic, operators and vendors are pushing towards physical layer aware networking as a way to maximize the network capacity. To this aim, optical networks are becoming more and more open by exposing physical parameters enabling fast and reliable estimation of the lightpath quality of transmission. This comes in handy not only from the point of view of the planning and managing of the optical paths but also on a more general picture of the whole optical network performance. In this work, the Statistical Network Assessment Process (SNAP) is presented. SNAP is an algorithm allowing for estimating different network metrics such as blocking probability or link saturation, by generating traffic requests on a graph abstraction of the physical layer. Being aware of the physical layer parameters and transceiver technologies enables assessing their impact on high level network figures of merit. Together with a detailed description of the algorithm, we present a comprehensive review of several results on the networking impact of multirate transceivers, flex-grid spectral allocation as a means to finely exploit lightpath capacity and of different Space Division Multiplexing (SDM) solutions.

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Kumar, Love, Amarpal Singh, and Vishal Sharma. "Analysis on multiple optical line terminal passive optical network based open access network." Frontiers of Optoelectronics 12, no. 2 (October 24, 2018): 208–14. http://dx.doi.org/10.1007/s12200-018-0767-3.

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Szyrkowiec, Thomas, Achim Autenrieth, and Wolfgang Kellerer. "Optical Network Models and Their Application to Software-Defined Network Management." International Journal of Optics 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/5150219.

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Software-defined networking is finding its way into optical networks. Here, it promises a simplification and unification of network management for optical networks allowing automation of operational tasks despite the highly diverse and vendor-specific commercial systems and the complexity and analog nature of optical transmission. Common abstractions and interfaces are a fundamental component for software-defined optical networking. Currently, a number of models for optical networks are available. They all claim to provide open and vendor agnostic management of optical equipment. In this work, we survey and compare the most important models and propose an intent interface for creating virtual topologies which is integrated in the existing model ecosystem.

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Mustafa, Firas M. "Software Defined Networking Based Optical Network: A review." Academic Journal of Nawroz University 9, no. 2 (June 29, 2020): 139. http://dx.doi.org/10.25007/ajnu.v9n2a718.

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In the field of networking, software-defined networking (SDN) has obtained a lot of concentration from both academic and industry, and it aims to provide a flexible and programmable level of control, beside obtain efficient control and management of network systems. For such reasons, the software-defined networks (SDN) can be deemed as an essential task to accomplish these requirements. In the datacenters and networks, the SDN is used to allow the administrators of the networks to start programming, controlling, changing, and managing dynamically the network behavior with open interfaces and a reflection of lower-level functionality because the need for SDN-like switching technology has become evident for many users of network equipment, especially in large data centers. There are many algorithms and applications that have been considered in SDN such as (FP-MA), EON, (EQUAL-APP) (VONCR-APP), and (T-SDN) as use cases for approval purposes because the SDN provides several focal points to the power, operation, and administration of extensive range networks. This paper aims to review Optical Network using SDN, where many types of research papers are present techniques to improve near-optimal traffic engineering and management; measurement and monitoring of the significant parameters of the optical networks and manage the cross-layer issues such as debugging and testing.

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Romanov, O. I., I. V. Svyd, N. I. Korniienko, and A. O. Romanov. "Optical Network Management by ONOS-Based SDN Controller." Radiotekhnika, no. 210 (September 28, 2022): 188–96. http://dx.doi.org/10.30837/rt.2022.3.210.16.

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The possibilities to manage the optical network with a logically centralized SDN control plane based on the Open Network Operating System (ONOS) are investigated. The structure of the controller and its main functional blocks are considered ensuring the collection of information about the state of network elements, the solution of the main control tasks, interaction of control systems built on different technological bases, are considered. The role and place of the open network operating system in the controller structure are shown, the description of the ONOS multilevel architecture in the form of a set of functional modules is given, the purpose and functions of the ONOS subsystems are analyzed, protocols and interfaces making it possible to present the SDN network as a model are described. The peculiarity of the model is that the managed network can be represented as a set of virtual network functions. Therefore, the control process becomes independent of which vendor's equipment was used to build the network, as well as whether the network is built on real physical elements or virtual ones. Using the ONOS allows you to build a logical centralized control plane in the SDN networks. The existing set of functional modules, services and interfaces in the ONOS allows you to perform optical network management tasks. For the further development of the ONOS, it is necessary to develop mathematical models and methods for the optimal solution of control problems in various operating conditions, which will become application-level software modules in the future.

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Troscia, Martina, Andrea Sgambelluri, Francesco Paolucci, Piero Castoldi, Paolo Pagano, and Filippo Cugini. "Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario." Sensors 22, no. 2 (January 7, 2022): 431. http://dx.doi.org/10.3390/s22020431.

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Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

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Zhou, Wei, Xing Jiang, Qingsong Luo, Shanguo Huang, Bingli Guo, Xiang Sun, Shaobo Li, Xiaochuan Tan, Mingyi Ma, and Tianwen Fu. "Design and Implementation of Semi-Physical Platform for Label Based Frame Switching in Integrated Satellite Terrestrial Networks." Applied Sciences 12, no. 13 (July 1, 2022): 6674. http://dx.doi.org/10.3390/app12136674.

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With the explosion of traffic demand in recent years, the integration of satellite optical networks and terrestrial networks (ISTN) creates a promising networking solution for future low-latency, high-rate, and high-capacity communications. Owing to the high cost of deploying and maintaining a satellite optical network, it is critical to carefully design and plan the network to ensure the performance of the network. Thus, a semi-physical simulation platform based on software-defined networks (SDNs) is developed to simulate a satellite optical network and evaluate the performance of the proposed label-based advanced orbiting system (AOS) frame switching method that adheres to the Consultative Committee for Space Data Systems’ recommended standard (CCSDS). The semi-physical simulation platform has two major innovations: (1) adapting and integrating network protocols between the CCSDS and open system interconnect (OSI) reference models, particularly at the data link layer, and (2) the foundation for an SDN-based satellite optical network. In the control plane, real-time VxWorks Simulators serve as controllers to establish and manage various network protocols and the link manager protocol (LMP). Here, network protocols include open shortest path first (OSPF) for routing managing and controlling messages, constraint shortest path first–traffic engineering (CSPF-TE), and constraint-label distribution protocol (CR-LDP) for routing data services. LMP is used to assign and reserve satellite optical link resources. The performance of the architecture and protocols is evaluated via a semi-physical simulation platform.

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Nsafoa-Yeboah, Kenneth, Eric Tutu Tchao, Bright Yeboah-Akowuah, Benjamin Kommey, Andrew Selasi Agbemenu, Eliel Keelson, and Mohammad Monirujjaman Khan. "Software-Defined Networks for Optical Networks Using Flexible Orchestration: Advances, Challenges, and Opportunities." Journal of Computer Networks and Communications 2022 (August 4, 2022): 1–40. http://dx.doi.org/10.1155/2022/5037702.

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Optical networks offer a wide range of benefits to the telecommunication sector worldwide with their provision of higher bandwidth, which leads to faster data speed, longer transmission distance, and improved latency. Currently, the complexity associated with advancements in optical networks poses problems to network flexibility, reliability, and quality of service. Over the years, many reviews and proposals have been implemented by several literature studies to provide solutions for optical networks using software-defined networks and network service orchestrators. This study reviews the significant challenges in current optical network applications, the various solutions rendered by software-defined networks, and network service orchestration, impediments, and gaps in these software-defined networks. This study will go a step further to look into the various improvements and implementations of software-defined networks tailored to solve specific optical network problems. This study further proposes a flexible orchestration architecture for software-defined networks for solving flexibility and scalability problems in optical networks. This proposal uses an open network system (ONOS) SDN controller, leveraging on dockerisation and Kubernetes clusterisation and orchestration. This solution presents a more flexible, reliable, customable, and higher quality of service, which is an improvement upon current solutions in the literature.

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Casellas, Ramon, Alessio Giorgetti, Roberto Morro, Ricardo Martinez, Ricard Vilalta, and Raul Muñoz. "Virtualization of disaggregated optical networks with open data models in support of network slicing." Journal of Optical Communications and Networking 12, no. 2 (November 14, 2019): A144. http://dx.doi.org/10.1364/jocn.12.00a144.

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Ashraf, Muhammad, Sevia Idrus, Farabi Iqbal, Rizwan Butt, and Muhammad Faheem. "Disaster-Resilient Optical Network Survivability: A Comprehensive Survey." Photonics 5, no. 4 (October 12, 2018): 35. http://dx.doi.org/10.3390/photonics5040035.

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Network survivability endeavors to ensure the uninterrupted provisioning of services by the network operators in case of a disaster event. Studies and news reports show that network failures caused by physical attacks and natural disasters have significant impacts on the optical networks. Such network failures may lead to a section of a network to cease to function, resulting in non-availability of services and may increase the congestion within the rest of the network. Therefore, fault tolerant and disaster-resilient optical networks have grasped the attention of the research community and have been a critical concern in network studies during the last decade. Several studies on protection and restoration techniques have been conducted to address the network component failures. This study reviews related previous research studies to critically discuss the issues regarding protection, restoration, cascading failures, disaster-based failures, and congestion-aware routing. We have also focused on the problem of simultaneous cascading failures (which may disturb the data traffic within a layer or disrupt the services at upper layers) along with their mitigating techniques, and disaster-aware network survivability. Since traffic floods and network congestion are pertinent problems, they have therefore been discussed in a separate section. In the end, we have highlighted some open issues in the disaster-resilient network survivability for research challenges and discussed them along with their possible solutions.

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Bhar, Chayan, Goutam Das, Abhishek Dixit, Bart Lannoo, Marlies Van Der Wee, Didier Colle, Debasish Datta, Mario Pickavet, and Piet Demeester. "A Green Open Access Optical Distribution Network with Incremental Deployment Support." Journal of Lightwave Technology 33, no. 19 (October 1, 2015): 4079–92. http://dx.doi.org/10.1109/jlt.2015.2456100.

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Sivaraman, Vijay, Craig Russell, Iain Collings, and Adam Radford. "Architecting a national optical fiber open-access network: The Australian Challenge." IEEE Network 26, no. 4 (2012): 4–10. http://dx.doi.org/10.1109/mnet.2012.6246746.

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Chbat, M. W., E. Grard, L. Berthelon, A. Jourdan, P. A. Perrier, A. Leclert, B. Landousies, et al. "Toward wide-scale all-optical transparent networking: the ACTS optical pan-European network (OPEN) project." IEEE Journal on Selected Areas in Communications 16, no. 7 (1998): 1226–44. http://dx.doi.org/10.1109/49.725192.

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Iyer, Sridhar, and Shree Prakash Singh. "Effect of Traffic Uncertainities on the Design of Mixed Line Rate (MLR) Optical Networks." International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems 6, no. 2 (May 22, 2017): 61. http://dx.doi.org/10.11601/ijates.v6i2.228.

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In the existing studies on Mixed Line Rate (MLR) optical networks, the network design methodology is based on the assumption of deterministic traffic, and hence, the effect of traffic uncertainty on the design of an MLR network remains an open problem of research. In this study, we upgrade our previously proposed cost-efficient mixed integer linear program (MILP) formulation for an MLR network, which considered a specific mean traffic for every network source-destination pair. Our upgraded model employs an optimization technique to account for the traffic uncertainties that an actual MLR optical network may encounter. Our simulation results show that (i) if the MLR network is cost-optimized under the assumption that approximately 10-20% of the demands are at their maximum (or peak) value then, the network demonstrates robustness to traffic peaks in approximately all the other demands, and (ii) the saturation of network cost for a number of source-destination pairs is network topology dependent.

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Liu, Heng, Adaranijo Peters, Miquel Garrich, and Georgios Zervas. "OSNR Aware Composition of an Open and Disaggregated Optical Node and Network." Journal of Optical Communications and Networking 9, no. 10 (September 19, 2017): 844. http://dx.doi.org/10.1364/jocn.9.000844.

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Bilzer, C., T. Devolder, P. Crozat, and C. Chappert. "Open-Circuit One-Port Network Analyzer Ferromagnetic Resonance." IEEE Transactions on Magnetics 44, no. 11 (November 2008): 3265–68. http://dx.doi.org/10.1109/tmag.2008.2004379.

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Cavalcante, Matheus A., Helder A. Pereira, and Raul C. Almeida. "SimEON: an open-source elastic optical network simulator for academic and industrial purposes." Photonic Network Communications 34, no. 2 (April 5, 2017): 193–201. http://dx.doi.org/10.1007/s11107-017-0697-9.

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Brock, Andrea A., Robert M. Friedman, Reuben H. Fan, and Anna W. Roe. "Optical imaging of cortical networks via intracortical microstimulation." Journal of Neurophysiology 110, no. 11 (December 1, 2013): 2670–78. http://dx.doi.org/10.1152/jn.00879.2012.

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Understanding cortical organization is key to understanding brain function. Distinct neural networks underlie the functional organization of the cerebral cortex; however, little is known about how different nodes in the cortical network interact during perceptual processing and motor behavior. To study cortical network function we examined whether the optical imaging of intrinsic signals (OIS) reveals the functional patterns of activity evoked by electrical cortical microstimulation. We examined the effects of current amplitude, train duration, and depth of cortical stimulation on the hemodynamic response to electrical microstimulation (250-Hz train, 0.4-ms pulse duration) in anesthetized New World monkey somatosensory cortex. Electrical stimulation elicited a restricted cortical response that varied according to stimulation parameters and electrode depth. Higher currents of stimulation recruited more areas of cortex than smaller currents. The largest cortical responses were seen when stimulation was delivered around cortical layer 4. Distinct local patches of activation, highly suggestive of local projections, around the site of stimulation were observed at different depths of stimulation. Thus we find that specific electrical stimulation parameters can elicit activation of single cortical columns and their associated columnar networks, reminiscent of anatomically labeled networks. This novel functional tract tracing method will open new avenues for investigating relationships of local cortical organization.

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Zubairi, J. A. "An Overview of Optical Network Bandwidth and Fault Management." IIUM Engineering Journal 7, no. 1 (September 29, 2010): 47–69. http://dx.doi.org/10.31436/iiumej.v7i1.76.

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This paper discusses the optical network management issues and identifies potential areas for focused research. A general outline of the main components in optical network management is given and specific problems in GMPLS based model are explained. Later, protection and restoration issues are discussed in the broader context of fault management and the tools developed for fault detection are listed. Optical networks need efficient and reliable protection schemes that restore the communications quickly on the occurrence of faults without causing failure of real-time applications using the network. A holistic approach is required that provides mechanisms for fault detection, rapid restoration and reversion in case of fault resolution. Since the role of SDH/SONET is diminishing, the modern optical networks are poised towards the IP-centric model where high performance IP-MPLS routers manage a core intelligent network of IP over WDM. Fault management schemes are developed for both the IP layer and the WDM layer. Faults can be detected and repaired locally and also through centralized network controller. A hybrid approach works best in detecting the faults where the domain controller verifies the established LSPs in addition to the link tests at the node level. On detecting a fault, rapid restoration can perform localized routing of traffic away from the affected port and link. The traffic may be directed to pre-assigned backup paths that are established as shared or dedicated resources. We examine the protection issues in detail including the choice of layer for protection, implementing protection or restoration, backup path routing, backup resource efficiency, subpath protection, QoS traffic survival and multilayer protection triggers and alarm propagation. The complete protection cycle is described and mechanisms incorporated into RSVP-TE and other protocols for detecting and recording path errors are outlined. In addition, MPLS testbed configuration procedure is outlined with suggested topologies. Open issues in this area are identified and current work is highlighted. It is expected that this paper will serve as a catalyst to accelerate the research and development activities in high speed networking.

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Hernandez, Jose Alberto, Marco Quagliotti, Emilio Riccardi, Victor Lopez, Oscar Gonzalez de Dios, and Ramon Casellas. "A Techno-Economic Study of Optical Network Disaggregation Employing Open Source Software Business Models for Metropolitan Area Networks." IEEE Communications Magazine 58, no. 5 (May 2020): 40–46. http://dx.doi.org/10.1109/mcom.001.1900756.

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Murgod, Tejaswini R., and S. Meenakshi Sundaram. "Survey on underwater optical wireless communication: perspectives and challenges." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 1 (January 1, 2019): 138. http://dx.doi.org/10.11591/ijeecs.v13.i1.pp138-146.

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<div><p class="Affiliation">The demand for underwater communication is growing at a faster pace since few decades. Maximizing the communication performance and building efficient network architecture for underwater communication is a challenging task. Due to the reduced bandwidth, high error rate, noise, propagation delay, water currents and increased cost in the network topology, the existing communication techniques are not feasible for underwater communication. Research in high speed underwater transmission technology has become a primary need in today’s world. By using underwater acoustic sensor network high transmission distance can be achieved but with lower data rates, high power consumption, larger delays and with higher cost. Underwater Optical Communication can be used to increase data rates and lower delays but it suffers from high attenuation due to which it cannot be used for data transfer over larger distances. Research in the area of hybrid sensor networks is a challenging task and has many open research challenges, which needs to be solved. In this paper we discuss the various architectures of underwater communication. A comparative study is made on different routing protocols and localization algorithms. The challenges faced by acoustic and optical communication are also discussed.</p></div>

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Karapanagiotis, Christos, Aleksander Wosniok, Konstantin Hicke, and Katerina Krebber. "Time-Efficient Convolutional Neural Network-Assisted Brillouin Optical Frequency Domain Analysis." Sensors 21, no. 8 (April 13, 2021): 2724. http://dx.doi.org/10.3390/s21082724.

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To our knowledge, this is the first report on a machine-learning-assisted Brillouin optical frequency domain analysis (BOFDA) for time-efficient temperature measurements. We propose a convolutional neural network (CNN)-based signal post-processing method that, compared to the conventional Lorentzian curve fitting approach, facilitates temperature extraction. Due to its robustness against noise, it can enhance the performance of the system. The CNN-assisted BOFDA is expected to shorten the measurement time by more than nine times and open the way for applications, where faster monitoring is essential.

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Xu, Quanfu, Keming Chen, Guangyao Zhou, and Xian Sun. "Change Capsule Network for Optical Remote Sensing Image Change Detection." Remote Sensing 13, no. 14 (July 6, 2021): 2646. http://dx.doi.org/10.3390/rs13142646.

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Change detection based on deep learning has made great progress recently, but there are still some challenges, such as the small data size in open-labeled datasets, the different viewpoints in image pairs, and the poor similarity measures in feature pairs. To alleviate these problems, this paper presents a novel change capsule network by taking advantage of a capsule network that can better deal with the different viewpoints and can achieve satisfactory performance with small training data for optical remote sensing image change detection. First, two identical non-shared weight capsule networks are designed to extract the vector-based features of image pairs. Second, the unchanged region reconstruction module is adopted to keep the feature space of the unchanged region more consistent. Third, vector cosine and vector difference are utilized to compare the vector-based features in a capsule network efficiently, which can enlarge the separability between the changed pixels and the unchanged pixels. Finally, a binary change map can be produced by analyzing both the vector cosine and vector difference. From the unchanged region reconstruction module and the vector cosine and vector difference module, the extracted feature pairs in a change capsule network are more comparable and separable. Moreover, to test the effectiveness of the proposed change capsule network in dealing with the different viewpoints in multi-temporal images, we collect a new change detection dataset from a taken-over Al Udeid Air Basee (AUAB) using Google Earth. The results of the experiments carried out on the AUAB dataset show that a change capsule network can better deal with the different viewpoints and can improve the comparability and separability of feature pairs. Furthermore, a comparison of the experimental results carried out on the AUAB dataset and SZTAKI AirChange Benchmark Set demonstrates the effectiveness and superiority of the proposed method.

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Merchant, Michael A. "Classifying open water features using optical satellite imagery and an object-oriented convolutional neural network." Remote Sensing Letters 11, no. 12 (October 20, 2020): 1127–36. http://dx.doi.org/10.1080/2150704x.2020.1825869.

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Estellés, V., M. Campanelli, T. J. Smyth, M. P. Utrillas, and J. A. Martínez-Lozano. "AERONET and ESR sun direct products comparison performed on Cimel CE318 and Prede POM01 solar radiometers." Atmospheric Chemistry and Physics Discussions 12, no. 2 (February 7, 2012): 4341–71. http://dx.doi.org/10.5194/acpd-12-4341-2012.

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Abstract. The European Skynet Radiometers network (EuroSkyRad or ESR) has been recently established as a research network of European Prede POM sun – sky radiometers. Moreover, ESR is federated with SKYNET (SKYrad NETwork), an international network mostly present in East Asia. In contrast to SKYNET, the European network also integrates users of the Cimel CE318 sunphotometer. Keeping instrumental duality in mind, a set of open source algorithms has been developed consisting of two modules for: (1) the retrieval of direct sun products from the sun extinction measurements; and (2) the inversion of the sky radiance to derive aerosol optical properties. In this study we evaluate the ESR direct sun products (spectral aerosol optical depth, Angström wavelength exponent and columnar content of water vapour) in comparison with the AERosol RObotic NETwork (AERONET) products. Specifically, we have applied the ESR algorithm to a Cimel CE318 and Prede POM01L simultaneously for a 4 yr database measured at the Burjassot site (Valencia, Spain), and compared the resultant products with the AERONET direct sun retrievals obtained with the same Cimel CE318 instrument. The comparison show that aerosol optical depth differences are mostly within the nominal uncertainty of 0.003 for a standard calibration instrument, and fall within the nominal AERONET uncertainty of 0.01–0.02 for a field instrument. Therefore, we present an open source code that can be used for both radiometers and whose results are comparable to those of AERONET and SKYNET.

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Mukherjee, Lipi, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, Bryan A. Franz, and P. Jeremy Werdell. "Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters." Remote Sensing 12, no. 9 (April 30, 2020): 1421. http://dx.doi.org/10.3390/rs12091421.

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Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

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Dasari, Venkat R., and Travis S. Humble. "OpenFlow arbitrated programmable network channels for managing quantum metadata." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 16, no. 1 (October 10, 2016): 67–77. http://dx.doi.org/10.1177/1548512916661781.

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Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-defined network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. We conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.

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Banerjee, A., G. Kramer, and B. Mukherjee. "Fair sharing using dual service-level agreements to achieve open access in a passive optical network." IEEE Journal on Selected Areas in Communications 24, no. 8 (August 2006): 32–44. http://dx.doi.org/10.1109/jsac.2006.1665144.

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Banerjee, A., G. Kramer, and B. Mukherjee. "Fair sharing using dual service-level agreements to achieve open access in a passive optical network." IEEE Journal on Selected Areas in Communications 24, no. 8 (August 2006): 32–44. http://dx.doi.org/10.1109/jsac.2006.1677253.

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Liu, Chenfang, Hao Sun, Yanjie Xu, and Gangyao Kuang. "Multi-Source Remote Sensing Pretraining Based on Contrastive Self-Supervised Learning." Remote Sensing 14, no. 18 (September 16, 2022): 4632. http://dx.doi.org/10.3390/rs14184632.

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SAR-optical images from different sensors can provide consistent information for scene classification. However, the utilization of unlabeled SAR-optical images in deep learning-based remote sensing image interpretation remains an open issue. In recent years, contrastive self-supervised learning (CSSL) methods have shown great potential for obtaining meaningful feature representations from massive amounts of unlabeled data. This paper investigates the effectiveness of CSSL-based pretraining models for SAR-optical remote-sensing classification. Firstly, we analyze the contrastive strategies of single-source and multi-source SAR-optical data augmentation under different CSSL architectures. We find that the CSSL framework without explicit negative sample selection naturally fits the multi-source learning problem. Secondly, we find that the registered SAR-optical images can guide the Siamese self-supervised network without negative samples to learn shared features, which is also the reason why the CSSL framework outperforms the CSSL framework with negative samples. Finally, we apply the CSSL pretrained network without negative samples that can learn the shared features of SAR-optical images to the downstream domain adaptation task of optical transfer to SAR images. We find that the choice of a pretrained network is important for downstream tasks.

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Kumar T.M, Sanjeev, Ciji P. Kurian, Susan Varghese, Anil Upadhyaya, Anupriya John, and Varsha Nayak. "A Prototype of Wireless Networked IoT Based Lighting Control in Open Platform." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 3 (May 18, 2020): 405–16. http://dx.doi.org/10.2174/2352096512666190123125600.

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Background: The lighting researchers are keenly looking for the huge benefits of the internet of things on an open platform which provides the cost gains in addition to other environmental benefits. Connected systems interact with the software and analyse real-time building conditions, and feed information into the building controls network. Methods: This paper presents a wireless networked system for lighting control in buildings which connect the power of the Internet of Things. After analysing the ZigBee network on QualNet v7.4, a Digi Mesh network was set up using XBee modules using the XBee Configuration and Test Utility [XCTU] Software v6.3.11. The ThingSpeak cloud platform along with MATLAB 2017b provides the necessary cloud support to enable this network to communicate over the internet. The results indicate that the XBee S2C module functioning in the API mode when flashed with the DigiMesh firmware offers the best option for forming a self-healing mesh network. An aggregator node acts as an information sink and collects the sensor data from all the sensor nodes and passes it on to the cloud via the Raspberry gateway. Results: The algorithm on the cloud can read this sensor data and compute the necessary Pulse Width Modulation [PWM] signals required to control the brightness of a dimmable LED luminaire. The system also takes into consideration the zone-wise occupancy in the room while computing the PWM values to be sent to the luminaires. Conclusion: The use of the concept of open platform sensors and actuators is the significance of the work.

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Liu, J., K. Ozga, X. Liu, Z. Zhen, K. J. Plucinski, M. Szota, and I. V. Kityk. "The Relationship between the Monomer Chain Length and the Electro-Optical Properties of Polymer Dispersed Liquid Crystals." Archives of Metallurgy and Materials 61, no. 1 (March 1, 2016): 457–60. http://dx.doi.org/10.1515/amm-2016-0082.

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Five polymers dispersed liquid crystalline (LC) films were fabricated using photo-polymerizable monomers with different lengths of carbon chains. These LC films have shown different electro-optical (EO) properties. Through their SEM pictures, the relationship between the linear electro-optical effect and the mesh size of the polymer network was explored. With the increase of number of photo-polymerizable monomers, the mesh size of the polymer network would become larger. So the liquid crystal molecules would be easily oriented in the electric field and therefore, the threshold voltage and saturation voltage would decrease. The open state response times were also reduced and the off state response times would be extended. The DFT simulations have shown principal role of the ground state dipole moments in the observed electro-optical efficiency.

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Estellés, V., M. Campanelli, T. J. Smyth, M. P. Utrillas, and J. A. Martínez-Lozano. "Evaluation of the new ESR network software for the retrieval of direct sun products from CIMEL CE318 and PREDE POM01 sun-sky radiometers." Atmospheric Chemistry and Physics 12, no. 23 (December 5, 2012): 11619–30. http://dx.doi.org/10.5194/acp-12-11619-2012.

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Abstract. The European Skynet Radiometers network (EuroSkyRad or ESR) has been recently established as a research network of European PREDE sun-sky radiometers. Moreover, ESR is federated with SKYNET, an international network of PREDE sun-sky radiometers mostly present in East Asia. In contrast to SKYNET, the European network also integrates users of the CIMEL CE318 sky–sun photometer. Keeping instrumental duality in mind, a set of open source algorithms has been developed consisting of two modules for (1) the retrieval of direct sun products (aerosol optical depth, wavelength exponent and water vapor) from the sun extinction measurements; and (2) the inversion of the sky radiance to derive other aerosol optical properties such as size distribution, single scattering albedo or refractive index. In this study we evaluate the ESR direct sun products in comparison with the AERosol RObotic NETwork (AERONET) products. Specifically, we have applied the ESR algorithm to a CIMEL CE318 and PREDE POM simultaneously for a 4-yr database measured at the Burjassot site (Valencia, Spain), and compared the resultant products with the AERONET direct sun measurements obtained with the same CIMEL CE318 sky–sun photometer. The comparison shows that aerosol optical depth differences are mostly within the nominal uncertainty of 0.003 for a standard calibration instrument, and fall within the nominal AERONET uncertainty of 0.01–0.02 for a field instrument in the spectral range 340 to 1020 nm. In the cases of the Ångström exponent and the columnar water vapor, the differences are lower than 0.02 and 0.15 cm, respectively. Therefore, we present an open source code program that can be used with both CIMEL and PREDE sky radiometers and whose results are equivalent to AERONET and SKYNET retrievals.

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Zhao, Zixin, Menghang Zhou, Yijun Du, Junxiang Li, Chen Fan, Xuchao Zhang, Xiang Wei, and Hong Zhao. "Robust phase unwrapping algorithm based on Zernike polynomial fitting and Swin-Transformer network." Measurement Science and Technology 33, no. 5 (February 2, 2022): 055002. http://dx.doi.org/10.1088/1361-6501/ac4ac2.

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Abstract Phase unwrapping plays an important role in optical phase measurements. In particular, phase unwrapping under heavy noise conditions remains an open issue. In this paper, a deep learning-based method is proposed to conduct the phase unwrapping task by combining Zernike polynomial fitting and a Swin-Transformer network. In this proposed method, phase unwrapping is regarded as a regression problem, and the Swin-Transformer network is used to map the relationship between the wrapped phase data and the Zernike polynomial coefficients. Because of the self-attention mechanism of the transformer network, the fitting coefficients can be estimated accurately even under extremely harsh noise conditions. Simulation and experimental results are presented to demonstrate the outperformance of the proposed method over the other two polynomial fitting-based methods. This is a promising phase unwrapping method in optical metrology, especially in electronic speckle pattern interferometry.

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E M Abou Hussein, E. M. Abou Hussein. "Characterization of Some Chemical and Physical Properties of Lithium Borate Glasses Doped With CuO and/or TeO2." Journal of the chemical society of pakistan 41, no. 1 (2019): 52. http://dx.doi.org/10.52568/000717/jcsp/41.01.2019.

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Glasses used in this study are prepared economically at a relatively low melting temperature (650-750oC). Presence of alkalis such as Na2O works as a flux and enhances the melting process. A Simple comparative study between the effect of doping Cu2+ and/or Te4+ ions in lithium borate glasses before and after gamma irradiation has been discussed. Density, molar volume, optical UV transmittance, optical band gap energies, DC electrical conductivity and chemical durability of the prepared glasses are measured. It is found that doping with Cu2+ ions makes a disruption in the glassy network by increasing the number of non-bridging oxygens (NBO) forming a more open network structure. While doping with the fourfold Te4+ ions enhances the crosslinking of the glassy network giving more rigid structure since the relatively high molecular weights of Te4+ ions allow them to bond strongly with the glassy network. The last two assumptions can elucidate results obtained from the last measurements.

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Praveen Kumar, S., T. Jaya, and Prithiviraj Rajalingam. "Implementation of Quantum Key Distribution network simulation in Quantum Channel." Journal of Physics: Conference Series 2335, no. 1 (September 1, 2022): 012056. http://dx.doi.org/10.1088/1742-6596/2335/1/012056.

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Abstract The aim is to analyze the efficiency of a communication method, Quantum key distribution. This newly popularized method of communication uses the principles of quantum mechanics. The simulation environment allows researchers to create complex network topologies and a high degree of control and repeatable experiments, allowing them to conduct studies and verify their outcomes. It would be costly to implement QKD in reality, which would need optical and Internet connections between network nodes and the verification of a certain network method or protocol. Thus, the performance analysis here is done in open-source software called NS-3 or Network Simulator- 3, which has an in-built module called QKD netsim for creating the quantum channel.

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Pishnamazi, Behnam, and Ehsan Koushki. "Study of nonlinear optical diffraction patterns using machine learning models based on ResNet 152 architecture." AIP Advances 13, no. 1 (January 1, 2023): 015020. http://dx.doi.org/10.1063/5.0135380.

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As the advancements in the field of artificial intelligence and nonlinear optics continues, new methods can be used to better describe and determine nonlinear optical phenomena. In this research, we aimed to analyze the diffraction patterns of an organic material and determine the nonlinear optical phase change and nonlinear refraction index of the material in question by utilizing the ResNet 152 convolutional neural network architecture in the regions of laser intensity that the diffraction rings are not clearly distinguishable. This approach can open new sights for optical material characterization in situations where the conventional methods do not apply.

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Yuan, Panli, Qingzhan Zhao, Xingbiao Zhao, Xuewen Wang, Xuefeng Long, and Yuchen Zheng. "A transformer-based Siamese network and an open optical dataset for semantic change detection of remote sensing images." International Journal of Digital Earth 15, no. 1 (September 12, 2022): 1506–25. http://dx.doi.org/10.1080/17538947.2022.2111470.

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Bajpai, Rochak, Sujata Sengar, Sridhar Iyer, and Shree Prakash Singh. "Performance Evaluation of OOK, DPSK and Duo-binary Modulation Format based Mixed-Line-Rate (MLR) Optical Network." International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems 7, no. 3 (November 17, 2018): 35. http://dx.doi.org/10.11601/ijates.v7i3.256.

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With the steady increase in the heterogeneous Internet traffic, the optical wavelength division multiplexed (WDM) networks based on a mixed line rate (MLR) strategy have emerged as an efficient-solution. Also, with the migration from the legacy to the higher line rate(s), the advanced modulation format(s) (MF) is/are required. However, use of appropriate MF(s) for the higher line rate(s) still remains an open problem. In this article, we compare the performance of an On-Off Keying (OOK), Differential Phase Shift Keying (DPSK) and Duo-binary (DB) MF based MLR network in the presence of various physical layer impairment(s) (PLIs) for which, we propose a mathematical model based on various MFs. As a novelty, we validate the proposed theoretical model’s results by comparing them with the results obtained through simulations from OptSim, which has not been conducted in any existing study(s) thus far. Our simulation results show that the DB MF is perfectly suitable for high spectral-efficient MLR systems owing to its high resistance to various PLIs.

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Zhang, Jun, and Fu Xiang Peng. "Routing Strategy and Quality of Service (QoS) Realization Research of Guangxi Meteorology Network." Advanced Engineering Forum 6-7 (September 2012): 919–23. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.919.

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Large cover area and long distance transmission are main characteristics of a meteorological communication network. A satellite communication technology has been mainly adopted in the field of meteorological communication for a long time, because an optical communication technology has become the important support technology during a new network transformation, meteorological departments establish a nationwide meteorological broadband network. The paper aims at the structure of the Guangxi meteorological broadband network, points out how to use a routing strategy which combines a border gateway protocol (BGP) with an open shortest path first interior gateway protocol (OSPF) to solve the problem of entire network routing flapping and provides a basic method to dynamically realize the quality of service (QoS) guarantee of various kinds of service data in the meteorological broadband communication network by combining meteorological data services and class based queueing (CBQ).

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Yung, Man-Hong, Xun Gao, and Joonsuk Huh. "Universal bound on sampling bosons in linear optics and its computational implications." National Science Review 6, no. 4 (April 9, 2019): 719–29. http://dx.doi.org/10.1093/nsr/nwz048.

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ABSTRACT In linear optics, photons are scattered in a network through passive optical elements including beam splitters and phase shifters, leading to many intriguing applications in physics, such as Mach–Zehnder interferometry, the Hong–Ou–Mandel effect, and tests of fundamental quantum mechanics. Here we present the fundamental limit in the transition amplitudes of bosons, applicable to all physical linear optical networks. Apart from boson sampling, this transition bound results in many other interesting applications, including behaviors of Bose–Einstein condensates (BEC) in optical networks, counterparts of Hong–Ou–Mandel effects for multiple photons, and approximating permanents of matrices. In addition, this general bound implies the existence of a polynomial-time randomized algorithm for estimating the transition amplitudes of bosons, which represents a solution to an open problem raised by Aaronson and Hance (Quantum Inf Comput 2012; 14: 541–59). Consequently, this bound implies that computational decision problems encoded in linear optics, prepared and detected in the Fock basis, can be solved efficiently by classical computers within additive errors. Furthermore, our result also leads to a classical sampling algorithm that can be applied to calculate the many-body wave functions and the S-matrix of bosonic particles.

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Fan, Zhongkui, and Ye-Peng Guan. "Face recognition based on full convolutional neural network based on transfer learning model." Computer Science and Information Systems, no. 00 (2021): 28. http://dx.doi.org/10.2298/csis200922028f.

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Deep learning has achieved a great success in face recognition (FR), however, little work has been done to apply deep learning for face photo-sketch recognition. This paper proposes an adaptive scale local binary pattern extraction method for optical face features. The extracted features are classified by Gaussian process. The most authoritative optical face test set LFW is used to train the trained model. Test, the test accuracy is 98.7%. Finally, the face features extracted by this method and the face features extracted from the convolutional neural network method are adapted to sketch faces through transfer learning, and the results of the adaptation are compared and analyzed. Finally, the paper tested the open-source sketch face data set CUHK Face Sketch database(CUFS) using the multimedia experiment of the Chinese University of Hong Kong. The test result was 97.4%. The result was compared with the test results of traditional sketch face recognition methods. It was found that the method recognized High efficiency, it is worth promoting.

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Holik, Martin, Tomas Horvath, Vaclav Oujezsky, Petr Munster, Adrian Tomasov, and Sobeslav Valach. "MongoDB Database as Storage for GPON Frames." Sensors 20, no. 21 (October 30, 2020): 6208. http://dx.doi.org/10.3390/s20216208.

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This work is focused on creating an open-source software-based solution for monitoring traffic transmitted through gigabit passive optical network. In this case, the data are captured by the field-programmable gate array (FPGA) card and reassembled using parsing software from a passive optical network built on the International Telecommunication Unit telecommunication section (ITU-T) G.984 gigabit-capable passive optical network GPON recommendation. Then, the captured frames are converted by suitable software into GPON frames, which will be further processed for analysis. Due to the high transfer rate of GPON recommendations, the work describes the issue of writing to the Mongo database system. In order to achieve the best possible results and minimal loss of transmitted frames, a series of tests were performed. The proposed test scenarios are based on different database writing approaches and are implemented in the Python and C# programming languages. Based on our results, it has been shown that the high processing speed is too high for Python processing. Critical operations must be implemented in the C# programming language. Due to rapid application development, Python can only be used for noncritical time-consuming data processing operations.

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Nicolas, Nabil, and Etienne Roux. "3D Imaging and Quantitative Characterization of Mouse Capillary Coronary Network Architecture." Biology 10, no. 4 (April 7, 2021): 306. http://dx.doi.org/10.3390/biology10040306.

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Characterization of the cardiac capillary network structure is of critical importance to understand the normal coronary functional properties and coronary microvascular diseases. The aim of our study was to establish an accessible methodology for 3D imaging and 3D processing to quantitatively characterize the capillary coronary network architecture in mice. Experiments were done on C57BL/6J mice. 3D imaging was performed by light sheet microscopy and confocal microscopy on iDISCO+ optical cleared hearts after labelling of the capillary endothelium by lectin injection. 3D images were processed with the open source software ImageJ. Non-visual image segmentation was based of the frequency distribution of the voxel greyscale values, followed by skeletonization and distance mapping. Capillary networks in left and right ventricles and septum were characterized by the volume network density, the fractal dimension, the number of segments and nodes and their ratio, the total network length, and the average length, diameter, and tortuosity of the segments. Scale-dependent parameter values can be impacted by the resolution limit of the 3D imaging technique. The proposed standardized methodology for 3D image processing is easily accessible for a biologist in terms of investment and difficulty level, and allows the quantification of the 3D capillary architecture and its statistical comparison in different conditions.

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Akbari Rokn Abadi, Saeedeh, Amirhossein Mohammadi, and Somayyeh Koohi. "WalkIm: Compact image-based encoding for high-performance classification of biological sequences using simple tuning-free CNNs." PLOS ONE 17, no. 4 (April 15, 2022): e0267106. http://dx.doi.org/10.1371/journal.pone.0267106.

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The classification of biological sequences is an open issue for a variety of data sets, such as viral and metagenomics sequences. Therefore, many studies utilize neural network tools, as the well-known methods in this field, and focus on designing customized network structures. However, a few works focus on more effective factors, such as input encoding method or implementation technology, to address accuracy and efficiency issues in this area. Therefore, in this work, we propose an image-based encoding method, called as WalkIm, whose adoption, even in a simple neural network, provides competitive accuracy and superior efficiency, compared to the existing classification methods (e.g. VGDC, CASTOR, and DLM-CNN) for a variety of biological sequences. Using WalkIm for classifying various data sets (i.e. viruses whole-genome data, metagenomics read data, and metabarcoding data), it achieves the same performance as the existing methods, with no enforcement of parameter initialization or network architecture adjustment for each data set. It is worth noting that even in the case of classifying high-mutant data sets, such as Coronaviruses, it achieves almost 100% accuracy for classifying its various types. In addition, WalkIm achieves high-speed convergence during network training, as well as reduction of network complexity. Therefore WalkIm method enables us to execute the classifying neural networks on a normal desktop system in a short time interval. Moreover, we addressed the compatibility of WalkIm encoding method with free-space optical processing technology. Taking advantages of optical implementation of convolutional layers, we illustrated that the training time can be reduced by up to 500 time. In addition to all aforementioned advantages, this encoding method preserves the structure of generated images in various modes of sequence transformation, such as reverse complement, complement, and reverse modes.

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Novelli, Fabio, Chun Yu Ma, Nidhi Adhlakha, Ellen M. Adams, Thorsten Ockelmann, Debasish Das Mahanta, Paola Di Pietro, Andrea Perucchi, and Martina Havenith. "Nonlinear TeraHertz Transmission by Liquid Water at 1 THz." Applied Sciences 10, no. 15 (July 30, 2020): 5290. http://dx.doi.org/10.3390/app10155290.

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The solvation properties of liquid water originate from the transient network of hydrogen-bonded molecules. In order to probe the coupling between the different modes of this network, nonlinear terahertz (THz) spectroscopy techniques are required. Ideally, these techniques should use a minimal volume and capitalize on sensitive field-resolved detection. Here we performed open aperture z-scan transmission experiments on static liquid cells, and detect the THz fields with electro-optical techniques. We show that it is possible to quantify the nonlinear response of liquid water at ~1 THz even when large signals originate from the sample holder windows.

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Leoni, Alessandro, Pietro Nannipieri, Daniele Davalle, Luca Fanucci, and David Jameux. "SHINe: Simulator for Satellite on-Board High-Speed Networks Featuring SpaceFibre and SpaceWire Protocols." Aerospace 6, no. 4 (April 12, 2019): 43. http://dx.doi.org/10.3390/aerospace6040043.

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The continuous innovation of satellite payloads is leading to an increasing demand of data-rate for on-board satellite networks. In particular, modern optical detectors generate and need to transfer data at more than 1 Gbps, a speed that cannot be satisfied with standardized technologies such as SpaceWire. To fill this gap, the European Space Agency (ESA) is supporting the development of a new high-speed link standard, SpaceFibre. SpaceFibre provides a data-rate higher than 6.25 Gbps, together with the possibility to use multiple Virtual Channels running over the same physical link, each one configurable with flexible Quality of Service parameters. These features make a SpaceFibre network very appealing but also complex to set up in order to achieve the desired end-to-end requirements. To help this process, a Simulator for HIgh-speed Network (SHINe) based on the open-source toolkit OMNeT++ has been developed and is presented in this paper. It supports the simulation of SpaceFibre and SpaceWire protocols in order to help both the final steps of the standardization process and the system engineers in the setup and test of new networks. SHINe allows to precisely simulate common network metrics, such as latency and bandwidth usage, and it can be connected to real hardware in a Hardware-in-the-Loop configuration.

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Ullah, Shakir, Saeed Ur Rehman, and Peter Han Joo Chong. "A Comprehensive Open-Source Simulation Framework for LiFi Communication." Sensors 21, no. 7 (April 2, 2021): 2485. http://dx.doi.org/10.3390/s21072485.

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Light Fidelity (LiFi) is a new candidate for wireless networking that utilizes the visible light spectrum and exploits the existing lighting infrastructure in the form of light-emitting diodes (LEDs). It provides point-to-point and point-to-multipoint communication on a bidirectional channel at very high data rates. However, the LiFi has small coverage, and its optical gain is closely related to the receiver’s directionality vis-à-vis the transmitter, therefore it can experience frequent service outages. To provide reliable coverage, the LiFi is integrated with other networking technologies such as wireless fidelity (WiFi) thus forming a hybrid system. The hybrid LiFi/WiFi system faces many challenges including but not limited to seamless integration with the WiFi, support for mobility, handover management, resource sharing, and load balancing. The existing literature has addressed one or the other aspect of the issues facing LiFi systems. There are limited free source tools available to holistically address these challenges in a scalable manner. To this end, we have developed an open-source simulation framework based on the network simulator 3 (ns-3), which realizes critical aspects of the LiFi wireless network. Our developed ns-3 LiFi framework provides a fully functional AP equipped with the physical layer and medium access control (MAC), a mobility model for the user device, and integration between LiFi and WiFi with a handover facility. Simulation results are produced to demonstrate the mobility and handover capabilities, and the performance gains from the LiFi-WiFi hybrid system in terms of packet delay, throughput, packet drop ratio (PDR), and fairness between users. The source code of the framework is made available for the use of the research community.

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Pedersen, Ole-Magnus, and Ekaterina Kim. "Arctic Vision: Using Neural Networks for Ice Object Classification, and Controlling How They Fail." Journal of Marine Science and Engineering 8, no. 10 (September 30, 2020): 770. http://dx.doi.org/10.3390/jmse8100770.

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Convolutional neural networks (CNNs) have been shown to be excellent at performing image analysis tasks in recent years. Even so, ice object classification using close-range optical images is an area where their use has barely been touched upon, and how well CNNs perform this classification task is still an open question, especially in the challenging visual conditions often found in the High Arctic. The present study explores the use of CNNs for such ice object classification, including analysis of how visual distortion of optical images impacts their performance and comparisons to human experts and novices. To account for the model’s tendency to predict the presence of very few classes for any given image, the use of a loss-weighting scheme pushing a model towards predicting a higher number of classes is proposed. The results of this study show that on clean images, given the class definitions and labeling scheme used, the networks perform better than some humans. At least for some classes of ice objects, the results indicate that the network learned meaningful features. However, the results also indicate that humans are much better at adapting to new visual conditions than neural networks.

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Sun, Junwei, Juntao Han, Gaoyong Han, Yanfeng Wang, and Peng Liu. "Memristive Hopfield Neural Network for Reasoning with Incomplete Information and Its Circuit Implementation." Journal of Nanoelectronics and Optoelectronics 16, no. 9 (September 1, 2021): 1401–11. http://dx.doi.org/10.1166/jno.2021.3104.

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Memristor-based neural networks have been extensively studied, but reasoning as an important topic of artificial intelligence is rarely implemented directly by circuit. Reasoning, as an important part of artificial intelligence, is an open and challenging problem to be solved. In this paper, memristive hopfield neural network is designed to realize reasoning. The designed circuit consists of four modules, namely a signal processing module, an iterator module, a signal input module and a signal output module. The signal processing module performs iterative operations under the control of the iterator module, so that the output signals of memristive hopfield neural network can converge to the final states. Reasoning is one of the basic forms of thinking, and is the process of drawing result from one or several given conditions. A guessing game for athletes is completed by the designed circuit which can reason the name of the athlete from incomplete information. The simulation results verify the feasibility of the circuit for reasoning.

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Journal articles on the topic 'Open optical network'

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