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Compact and highly performing photonic devices are characterized by non-intuitive geometries, a large number of parameters, and multiple figures of merit. Optimization and machine learning techniques have been explored to handle these complex designs, but the existing approaches often overlook stochastic quantities. As an example, random fabrication uncertainties critically determines experimental device performance. Here, we present a novel approach for the stochastic multi-objective design of photonic devices combining unsupervised dimensionality reduction and Gaussian process regression. The proposed approach allows to efficiently identify promising alternative designs and model the statistic of their response. Incorporating both deterministic and stochastic quantities into the design process enables a comprehensive analysis of the device and of the possible trade-offs between different performance metrics. As a proof-of-concept, we investigate surface gratings for fiber coupling in a silicon-on-insulator platform, considering variability in structure sizes, silicon thickness, and multi-step etch alignment. We analyze 86 alternative designs presenting comparable performance when neglecting variability, discovering on the contrary marked differences in yield and worst-case figures for both fiber coupling efficiency and back-reflections. Pareto frontiers demonstrating optimized device robustness are identified as well, offering a powerful tool for the design and optimization of photonic devices with stochastic figures of merit. [ABSTRACT FROM AUTHOR]

Mode division multiplexing (MDM) is currently one of the most attractive multiplexing techniques in optical communications, as it allows for an increase in the number of channels available for data transmission. Optical modal converters are one of the main devices used in this technique. Therefore, the characterization and improvement of these devices are of great current interest. In this work, we present a dataset of 49,736 near-field intensity images of a modal converter based on a long-period fiber grating (LPFG) written on a few-mode fiber (FMF). This characterization was performed experimentally at various wavelengths, polarizations, and temperature conditions when the device converted from LP 01 mode to LP 11 mode. The results show that the modal converter can be tuned by adjusting these parameters, and that its operation is optimal under specific circumstances which have a great impact on its performance. Additionally, the potential application of the database is validated in this work. A modal decomposition technique based on the particle swarm algorithm (PSO) was employed as a tool for determining the most effective combinations of modal weights and relative phases from the spatial distributions collected in the dataset. The proposed dataset can open up new opportunities for researchers working on image segmentation, detection, and classification problems related to MDM technology. In addition, we implement novel artificial intelligence techniques that can help in finding the optimal operating conditions for this type of device. [ABSTRACT FROM AUTHOR]

Real-time monitoring of the state of charge (SOC) of the batteries used in a wide variety of applications is becoming increasingly important, especially given the impetus by the current targets towards "net-zero". In this research, an advanced approach was used involving fiber Bragg grating (FBG)-based sensors that were developed and implemented for the measurement of the key parameters required to ensure optimum battery performance. In this work, one of the biggest challenges to assess (and then map) the data from the sensor system developed is tackled in order to better understand the key parameters of the battery in an efficient and improved way. It is well known that the relationship between the changes in the resonance wavelength of the FBGs used in the sensor system, arising due to change in the electrical parameters of the battery, is complex and dependent on several different factors. In this work, this effect was evaluated by coupling the sensor data to a data-driven regression model approach that was developed for the measurement of the SOC of the batteries used, and this was obtained directly and conveniently from the FBG data. In this comprehensive study, FBG-based sensors were fabricated and then installed onto the battery, which then was subjected to a range of charging–discharging cycles, following which the electrical parameters of the battery were estimated from recorded data using a black-box machine learning (ML) model. Data-driven regression algorithms were employed for the training of the black-box model. The efficiency of the estimation of the SOC of the battery from the FBG-based sensor data was found to be high, at 99.62% (R2 values of Estimated SOC and True SOC line), creating a very satisfactory result for this key measurement. Thus, the work shows the robustness of the FBG-based sensor system combined with the neural network algorithm as an effective way to evaluate the electrical parameters of the battery, which is particularly important, as no physical/electrochemical/electrical model of the system is thus required. [ABSTRACT FROM AUTHOR]

The article discusses the evolution of Ottoman fireplaces, limited scholarly attention. It explores the technical and aesthetic changes in wall-mounted fireplaces between the 17 and 19 centuries, emphasizing their emergence as luxury appliances and their sociocultural significance. It mentions the significance of chimneys in the external profile of dwellings as markers of wealth and social status, particularly in regions central to the Ottoman imperial economy and trade.

In 2010 and 2011, rescue archaeological research took place on the route of the Arad-Timişoara highway in site 7, located in the hilly area of northern Banat, in the southwestern part of the bounds of Pişchia commune in Timiş County. It was identified to the east of the European road E69, Arad-Timişoara, and at a distance of 400 m north of the Măgheruş channel. The archaeological site is a successive overlap of settlements from the Eneolithic, the Bronze Age, from the second Iron Age (La Tène), from the ancient period (3rd–4th centuries AD), from the early medieval period (9th–10th centuries AD), as well as from the medieval era (12th–13th and 16th centuries). Archaeological features from the early medieval period are few, only nine out of a total of about 625: six dwellings (locus 83, locus 92, locus 130, locus 150, locus 177, locus 600), two storage pits (locus 149, locus 602) and an oven outside the dwellings (locus 133). The vast majority of the pottery discovered was modeled with a slow wheel, from a semi-fine paste, usually with mica in the composition, but also with pebbles, from which they have a slightly rough appearance. The ceramic was oxidizing burnt, it has a brick and brown color, of various shades. There are very few fragments from gray or black vessels, reducing burnt. Pots predominate in form, but there are also fragments of bowls. There are also redbrick oxidizing ceramic fragments shaped on a high-speed wheel from a semi-fine paste with pebbles in the composition, which gives it a rough appearance. Of course, there are also hand-made ceramic fragments from the pots. We note the presence of clay trays, usually of large and medium sizes (from locus 149, locus 600, locus 602), as well as clay rollers (from locus 150 dwelling). The settlement dates back to the 9th–10th centuries AD, in the chronological range between the second half of the 9th century and the beginning of the 10th century. Of course, the objects cannot tell who their producers and users were, but in the early medieval period populations of different origins and traditions through processes of acculturation gave rise to the communities that medieval written sources recall: Slavs, Bulgarians and Blachii i.e. shepherds of the Romans lived in the territories once ruled by the Avars in the Danube and Tisa/Tisza region (source from the 12th century: Chronicle of the Anonymous Notary, IX).

In view of the tremendous emissions of toxic gases and particulate matter (PM) by low-power firewood-fueled fireplaces, there is an urgent need for effective measures to lower emissions to keep this renewable and economical source for private home heating available in the future. For this purpose, an advanced combustion air control system was developed and tested on a commercial fireplace (HKD7, Bunner GmbH, Eggenfelden, Germany), complemented with a commercial oxidation catalyst (EmTechEngineering GmbH, Leipzig, Germany) placed in the post-combustion zone. Combustion air stream control of the wood-log charge combustion was realized by five different control algorithms to describe all situations of combustion properly. These control algorithms are based on the signals of commercial sensors representing catalyst temperature (thermocouple), residual oxygen concentration (LSU 4.9, Bosch GmbH, Gerlingen, Germany) and CO/HC-content in the exhaust (LH-sensor, Lamtec Mess- und Regeltechnik für Feuerungen GmbH & Co. KG, Walldorf (Germany)). The actual flows of the combustion air streams, as calculated for the primary and secondary combustion zone, are adjusted by motor-driven shutters and commercial air mass flow sensors (HFM7, Bosch GmbH, Gerlingen, Germany) in separate feedback control loops. For the first time, the residual CO/HC-content (CO, methane, formaldehyde, etc.) in the flue gas is in-situ monitored with a long-term stable AuPt/YSZ/Pt mixed potential high-temperature gas sensor, which allows continuous estimation of the flue gas quality with an accuracy of about ±10%. This parameter is not only an essential input for advanced combustion air stream control but also provides monitoring of the actual combustion quality and logging of this value over a whole heating period. By many firing experiments in the laboratory and by field tests over four months, it could be demonstrated that with this long-term stable and advanced automated firing system, depression of the gaseous emissions by about 90% related to manually operated fireplaces without catalyst could be achieved. In addition, preliminary investigations at a firing appliance complemented by an electrostatic precipitator yielded PM emission depression between 70% and 90%, depending on the firewood load. [ABSTRACT FROM AUTHOR]

An image hiding scheme based on stochastic moiré gratings is proposed, discussed, and illustrated in this paper. The proposed scheme is based on a counter-intuitive optical feature of specially designed stochastic moiré gratings when similar images in the static mode become very different in the time-averaged mode. A soft computing PSO algorithm was used for the construction of stochastic gratings. Complex computational algorithms were required to construct the cover image; however, the decryption process was completely visual. The cover image must oscillate in a predefined direction and at a predefined amplitude (the amplitude of the harmonic oscillation is one of the parameters of the proposed image hiding scheme). Computational experiments were used to demonstrate the efficacy of this optical image hiding scheme based on the stochastic moiré gratings. [ABSTRACT FROM AUTHOR]

Since 2021, the Centro Internazionale di Studi di Architettura Andrea Palladio (CISAAP) in Vicenza and the Department of Architecture at the University of Bologna collaborated for a didactical joint initiative involving students from the Photogrammetry for Architecture course. The main goal was to develop a new teaching approach for architectural education exploiting photogrammetry as a digital tool for joining the Architectural Heritage (AH) documentation with the architecture analysis and design interpretation. Beginning from the new technological advances (semi-automatic workflows and smartphone cameras use), a 'learning-by-doing' didactical method and situated real work problems, a whole systematic process, based on the concept of a digital copy of an architectural artifact as mean to collect and to aggregate knowledge, was developed and inferred to the student. Starting from the designed teaching path, in which the perspectives of the historian, the surveyor, and the designer are blended to get a holistic vision of the architecture, 29 fireplaces by Andrea Palladio were chosen as emblematic case studies. These microarchitectures let students understand the complexities of historic objects and of their digitalization to produce 3D models as outcomes of an acquisition pipeline useful to train them for a future professional career. [ABSTRACT FROM AUTHOR]

Early in the morning of Wednesday 5th February 1766, Stanislaw Leszcziynski (Leczinski), Duke of Lorraine and Bar, fell to the ground, very close to the fireplace in his room. He remained in this position for a long time, exposed to the flames, and suffered serious burns. During the first nine days, physicians used topical agents and dressings, associated with internal drugs, particularly quinine. But septicemia occurred after about two weeks. By February 20th, Stanislaw was in a very poor condition. Some stimulating drugs were administered, but he died three days later. He was 88 years old. [ABSTRACT FROM AUTHOR]

Vibration analysis systems are used to assess the operational condition of machines and electromechanical components in various applications. This work presents a measurement and feature extraction system that analyzes dynamic strain patterns in signals measured by fiber Bragg grating (FBG). The features were used to identify different simulated operational conditions in an electromechanical relay. The selection of the best feature space in the first approach was performed by statistical criteria that determine the threshold values and frequency bands to calculate each signal's switching time and power spectral density (PSD). These parameters are used in the support vector machine (SVM) algorithm, which presents 98 % accuracy for distinguishing four distinct conditions. Another methodology for extracting features, called wavelet scattering transform (WST), was used to demonstrate that it is possible to achieve even better performance levels. The results allow extending the methodology to more complex systems. [ABSTRACT FROM AUTHOR]

In this work, a Fiber Bragg Gratings,"FBG" had been implemented using a package of Optisystem7 as a compensation component for the spreading of optical pulse width equal to12.5ps transmitted by single mode optical fiber having 10km length and dispersion 16ps/nm.km. Moreover, the ideal performance had been investigated by using the mean value of bit error rate and quality factor for fiber communication system having fiber length 100km and bit rate 10Gbps NRZ. Also, ideal fiber grating have been taken under consideration . The results of this study confirm the ability of FBG to act as a dispersion compensation while the ideal performance occurring at QF= 9.51 & BER = 8.7 x10-22at compensation of -1600ps/nm for fiber length of 100km. [ABSTRACT FROM AUTHOR]

An article herein considers the development of a fiber-optic sensor system, based on fiber Bragg gratings. Presently, fiber-optic sensors has become world-widely known amongst sensor technologies, used for monitoring engineering and construction structures. The work is linked with developing the system from fiber-optic sensors on the basis of fiber optic gratings, its characteristics, deformation behavior and temperature, acting at fiber Bragg grating by means of computer modeling. The research is focused at the analysis of characteristics and deformation and temperature behavior of fiber-optic Bragg sensor. Fiber-optic Bragg sensor with tilted grating is used for measuring deformation of the object, the strength of which is changed, dependent on the applied force, as well, for measuring and detecting any temperature deviations, influencing at fiber Bragg grating, which might bring to fire and accidents. In the research, simulation modeling there was made in the MATLAB (Simulink) software. [ABSTRACT FROM AUTHOR]

Copyright of Studies of Lithuania's History is the property of Lietuvos Istorijos Studijos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study develops a fault detection device for the fiber Bragg grating (FBG) sensing system and a fault detection method to realize the rapid detection of the FBG sensing system on airplanes. According to the distribution of FBG sensors on airplanes, the FBG sensing system is built based on wavelength division multiplexing (WDM) and space division multiplexing (SDM) technologies. Furthermore, the hardware and software of the fault detection device and the relevant FBG demodulator are studied in detail. Additionally, in view of the similar features of the healthy FBG sensor in the same measuring point, a rapid fault diagnosis method based on a synthetical anomaly index is proposed. The features (light intensity I, signal length L, standard deviation of original sample σ and energy value in time-domain P) of FBG sensors are extracted. The aggregation center value of the above feature values is obtained through the loop iteration method. Furthermore, the separation degrees of features are calculated and then form the synthetical anomaly index so as to make an effective diagnosis of the state of the FBG sensor. Finally, the designed fault detection instrument and proposed fault detection method are used to monitor the 25 FBG sensors on the airplane, the results indicated that three faulty and two abnormal FBG sensors on the airplane are identified, showing the effectiveness of the proposed fault detection method. [ABSTRACT FROM AUTHOR]

In several European rural communities, woody biomass is counted among the most important energy sources for heating and cooking. However, the use of old-fashioned fireplaces may affect indoor and outdoor air quality. To depict this situation and to plan the necessary improvement interventions, a pilot action was implemented in a typical mountainous Mediterranean area (Anogeia, Crete). The action involved: (1) identification of the quantities, use and source of the woody biomass used in the community based on the analysis of data collected through a systematic survey; (2) on-site indoor and outdoor measurements of air quality (CO2, CO, NOX, PM), during winter and summer. Based on this survey, around 70% of the study area households in Anogeia using woody biomass for heating purposes in low energy efficiency systems resulted in high firewood consumption. Fifty-three per cent of occupants did not consider indoor air quality as a result of wood burning. The air quality analysis showed very high concentrations of indoor air pollutants in most old buildings with seniors using traditional heating systems. The type of main/supplementary heating system used in a dwelling depends on factors such as the size of the dwelling, year of construction, education level and age of occupants. The results also demonstrate a strong correlation between the heating season (summer/winter) and the concentrations of air pollutants in the sampling sites. [ABSTRACT FROM AUTHOR]

Copyright of Electronic Turkish Studies is the property of Electronic Turkish Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Classical models of epidemic spreading based on making contact within a susceptible population assume a constant infection rate and uniform mixing. As such, they cannot account for surges and waves which have been observed in practice. This paper describes the spreading as a byproduct of interacting with a threat surface S(x, y) containing susceptible populations at location (x, y) in a 2D grid. The discretized grid acts as a transmission vector for COVID-19 and may explain why COVID-19 spreading exhibits surges rather than obey a smooth logistics curve. Furthermore, the strong correlation between infection cases and population indicates that population and distribution of population over a 2D area may explain most of why infection cases surge and waves form. It is impossible to obtain an accurate prediction of the extent of spreading without taking public sentiment, spatial separation, and size of populations into account. The best predictor of the ultimate spread of COVID-19 considers population as well as infection rate. We find that a terrain-based model is capable of modeling surges and waves of epidemics in most countries and regions where public sentiment is mild. In other cases where public sentiment is opposed to social distancing, wearing masks, and generally against public health policy, a two or three phase approach is necessary, whereby each phase is fit with different parameters, suggesting that public sentiment has a bigger influence on contagion spreading than population. We validate our results through simulation of outbreaks in a diverse set of countries and regions, e.g., a county in the US, Bahrain, Israel, United Kingdom, Germany, South Korea, and Italy. [ABSTRACT FROM AUTHOR]

Micrometeoroid and orbital debris (MMOD) can cause serious impact damage to long-term on-orbit spacecraft. MMOD impact detection and location are essential to improve the safety and reliability of the on-orbit spacecraft. In this article, a combined artificial neural network (ANN) and Mahalanobis distance method for MMOD impact detection and location based on fiber Bragg grating (FBG) sensor network is proposed. The inputs of the proposed ANN are the Mahalanobis distances determined by the wavelength changes of the FBG sensors at impact points and reference points. A finite element model is developed to explore the relationship between the Mahalanobis distance and the actual distance, which proved to be nonlinear based on the finite element simulation results of MMOD impacts. Four FBG sensors were installed on the back of the test board and sampled at a frequency of 100 Hz using a four-channel FBG demodulator. A total of 360 impact experiments were carried out on this experiment system. The average location error of the proposed method is 0.89 cm, which is 39% and 31% lower compared with the Mahalanobis distance discriminant analysis method and the ANN method, respectively. The combined ANN and Mahalanobis distance method reduces the location errors and has higher accuracy of position prediction. [ABSTRACT FROM AUTHOR]