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[Display omitted] • Molecular-level light-emitting origins were strategically imparted to paper. • The morphology of AIE self-assembly can be adjusted on demand. • AFP-FP exhibited high selectivity, sensitivity and repeatable recognition of NH 3. • AFP-FP integrated with smartphone realized the visual food spoilage monitoring. Biogenic amines containing NH 3 are important indicators for conducting full-scale appraisal of food spoilage and disease diagnosis. However, the currently-used detection methods of NH 3 have several limitations such as time-consuming high cost, and inability to provide visual real-time monitoring. Therefore, researchers have attempted to explore strategies for quantitative real-time monitoring of NH 3 for food spoilage has attracted widespread attentions. Herein, we developed sustainable, fast response, hypersensitized, user-friendly and molecular-level light-emitting biomass-based materials (AFP-FP) containing on-demand nanostructured brain-cells-inspired aggregation-induced-emission (AIE) self-assembles for real-time visual monitoring of seafood spoilage. The 2-hydroxy-5-methyl-isophthalaldehyde-based AIE probe (AFP) was synthesized using a simple "one-step" route. AFP-FP exhibited high selectivity, sensitivity, repeatable and quantitative recognition (y = 7.292×103x + 7.621×104, R = 0.990) of NH 3 with a low detection limit (246 ppb) and fast response (<1 s). Furthermore, we integrated AFP-FP into a user-friendly smartphone color recognition app, enabling its practical application in visual, real-time daylight monitoring of food spoilage. [ABSTRACT FROM AUTHOR]

Copyright of Restaurator is the property of De Gruyter 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.)

ShyTech is the new automotive interior smart home living‐style oriented design direction. It is a consistent alternative approach to giant display consoles. Key intention is to reduce a potential information overload by providing content only when and where necessary (on‐demand principle). This paper introduces design opportunities, use cases, challenges and technical solutions for premium image quality, natural‐looking and genuine‐feeling surface textures, daylight readability and postcard effect avoidance. [ABSTRACT FROM AUTHOR]

The intensification of global warming has resulted in extremely hot weather in many parts of the world, posing a severe challenge to the health and safety of outdoor workers. Passive daytime radiative cooling (PDRC) textiles with no energy input requirements can effectively achieve temperature management. However, few wearable radiative cooling devices have been successfully prepared. This study demonstrates a radiative cooling paper (RCP) with tunable stiffness for the thermal management of human head by using SiO 2 fibers and fumed SiO 2 as emitters. The as-prepared RCP exhibits high sunlight reflectivity of 0.97, and high emissivity of 0.91 in the atmospheric window. The results demonstrate that the RCP hat can prevent hair from overheating by reducing the temperature by an average of 12.9 °C compared with a white cotton hat under peak daylight conditions. Besides, the RCP exhibits outstanding integrated properties of high mechanical properties, waterproofness, and air permeability. Therefore, it is more suitable than other textiles for the manufacture of radiative cooling hats, and offers a promising solution to solve the problem of head thermal management in outdoor conditions. [Display omitted] • This study designed and prepared a ceramic fiber paper with remarkable passive daytime radiative cooling performance. • The radiative cooling paper (RCP) exhibits good impact strength, superhydrophobicity, and air permeability. • The RCP is suitable for the manufacture of radiative cooling hat to achieve the thermal management of human head. [ABSTRACT FROM AUTHOR]

Undoubtedly, light is a key element for human beings to adapt to their environment and to see the form, the color, and the perspectives of different objects in their immediate surroundings. Almost 80 percent of the information we obtain daily through our senses we obtain through sight. The correct design of the illumination system and building facades should offer optimal conditions for visual comfort. To achieve this aim, a collaboration between architects, lighting designers, and engineers should be established to improve citizens’ quality of life. This paper sought to bridge this knowledge by finding the link between daylighting, the building façades, and visual comfort. Accordingly, the paper conducts a theoretical review to evaluate the existing studies in an attempt to present this linkage focusing on kinetic façades. Then, an analytical review is conducted for 38 eligible records, that are extracted from different scholarly databases to find the assessment methods and tools used to determine the most favorable conditions of daylight for intelligent facades. Ultimately, the outcomes of the research will provide insights for further studies, in addition to that these connections can inform policy development to assist architects to design effective facades and more adaptive capabilities designed for the building envelope. Kinetic facades were found to provide visual comfort in addition to various productivity, economic, and environmental benefits, which in turn enhance the quality of life. [ABSTRACT FROM AUTHOR]

This paper presents an indoor positioning strategy based on Visible Light Communication that relies on LED luminaires as transmitters, whose luminous flux is modulated at different frequencies, and a light sensor as a receiver. Then, a previously trained Artificial Neural Network (ANN) uses the illuminance signal gathered by the receiver as input to estimate the sensor's position. The main contribution of the technique is that the ANN is trained by using an illuminance estimator based on the lighting distribution of the luminaires, which is obtained through the IES file provided by the luminaire's manufacturer, without the need to collect data from the environment. In this work, the designed illuminance estimator is validated by comparing it to the well-known commercial software DIALux and Relux. The algorithm's setting and the performance evaluation of the ANN are explained. Then, the impact of the lighting uniformity and the environment's number of divisions on the accuracy of the results is analyzed. Error analyses are also made by adding uncertainty to the illuminance measurements obtained by the sensor. Finally, the work is compared to several papers in the field. [ABSTRACT FROM AUTHOR]

This paper introduces the results of an experiment on lighting perception and reading speed where data collected in a physical space is compared to that collected in representations of that space simulated through a web survey and three VR Head-Mounted Displays (HMDs). The results build on an experiment, where perceptions of electric lighting conditions in a physical space were compared to those of the same space simulated in a single VR HMD (HTC Vive Pro). This study extends the previous scope to compare three VR HMD groups (cardboard VR, Oculus Quest 2, and HTC Vive Pro) to ratings of the same lighting conditions viewed through 2D-perspective or immersive panoramic images displayed in a web survey. Past research has compared perceptions of daylight and electric lighting scenes between physical and VR environments, but there is a lack of research that compares ratings of lighting conditions between VR HMDs and to other conventional image formats. For the VR HMD groups, the results revealed significant differences in reading speed between the physical space and cardboard VR HMD groups. An analysis of our subjective ratings showed all three VR HMDs producing fewer significantly different ratings from the physical space than either of the web groups, but ratings in the panoramic group outperformed the 2D-perspective group. The findings suggest that the type of VR HMD impacts reading speed in virtual lighting scenes and more immersive images produce less error than 2D-perspective images when compared to ratings in a physical space. [ABSTRACT FROM AUTHOR]

Automatic light control systems have garnered significant attention for their potential to enhance energy efficiency and user convenience across various settings. This paper provides a comprehensive overview of these systems, elucidating their principles, components, applications, and associated benefits. The primary objective of automatic light control systems is to intelligently regulate lighting levels based on environmental factors such as occupancy, ambient light, and time of day. Various sensors, including Passive Infrared (PIR), ultrasonic, and photoresistors, are commonly employed to detect changes in the surroundings and trigger appropriate lighting adjustments. Advanced control algorithms and communication protocols facilitate seamless integration with building automation systems, enabling centralized management and optimization of lighting across diverse zones. Moreover, the advent of smart lighting solutions leveraging Internet of Things (IoT) platforms enables remote monitoring and control, empowering users to personalize lighting preferences and further optimize energy consumption. The paper critically reviews the key features, benefits, and challenges associated with automatic light control systems, underscoring their pivotal role in promoting sustainability, comfort, and cost-effectiveness in both residential and commercial environments. Additionally, the paper discusses future research directions, highlighting opportunities for innovation in sensor technology, data analytics, and human-centric lighting design to propel the capabilities and adoption of these systems. [ABSTRACT FROM AUTHOR]

Daylighting design is not only dimensioning glazed surfaces to provide sufficient natural light to an occupied space but also a method of analyzing how this can be achieved without unwanted effects, such as gains and losses of heat, glare, and variations in daylighting intensity at various indoor distances and levels. The case study presented in this paper highlights the energy consumed due to a group of windows with a large glazed area in an existing building located in a temperate continental climate area. The energy consumption results from supplementary artificial lighting required to maintain adequate illumination for indoor activities and to counterbalance heat loss during colder periods are evaluated. The analysis performed by modifying the glazed surface led to the identification of an optimum value of window dimensions for minimum energy consumption. The results of the case study highlight the fact that the evolution of the total energy consumption, evaluated as the sum of the energy consumption due to additional heating/cooling and the artificial lighting required to compensate for the reduction in natural light, is strongly influenced by the dimensions of the glazed surfaces, as well as the minimum level of lighting imposed by the regime of activities carried out in the building. Thus, the outcomes obtained in the research show that at lighting values below 500 lx, the total energy consumption is directly proportional to the glazed surface. From values of 500 lx for the illuminance level, the total energy consumption drops from 2730 kWh/year for a window height of 230 cm to 2399 kWh/year for a height of 110 cm, after which it starts to rise again, reaching a value of 2786 kWh/year for a height of 30 cm. This phenomenon is also found at values higher than 500 lx; accordingly, for an imposed lighting of 1000 lx, the minimum total consumption is identified at a window height of 150 cm. The case study presented in this paper clearly highlights a complex relationship between the height of the glazed surface and the energy consumption required to compensate for heating or cooling and the reduction in natural lighting. Lower window heights reduce heat loss or gain but also correspondingly increase the energy consumption of artificial lighting. [ABSTRACT FROM AUTHOR]

This paper reviews how excessive lighting in historical sites can negatively affect the enjoyment of social gatherings. Because light pollution has the potential to affect socialization negatively, we need the appropriate tools to handle these effects. As part of this research, three techniques were used to analyze these effects: a bibliographical examination of relevant concepts, field measurements of illumination levels at historical sites in Cairo, Egypt, as well as questionnaires sent out to users around the world to determine what influences their perceptions of historical sites at night. Based on the results of a systematic review, we developed the concept of toolkits for creating a lively ambiance for evening events. Furthermore, based on the spatial measurements made in the case study, it was determined that the challenge of visual pollution hinders creating a vibrant atmosphere at historical sites. An online survey that investigated the factors influencing the enjoyment of historical sites at night around the world found that positioning the lighting fixtures and illumination is one of the most critical factors. The results of the current study confirm that the urban form of the context provides a pleasant visual and perceptual experience at night as well. The findings of this study have led to three design considerations that can help urban planners and designers when it comes to implementing lighting in public spaces. As a result of these considerations, the historical site in the case study, Al-Hussein Square, Cairo, presents a livelier ambiance at night; hence they can be used by urban designers to enhance the ambiance in similar settings to the present case study. This toolkit provides valuable insights into how local authorities and citizens can work together to reduce lighting pollution by examining the causes of the pollution. [ABSTRACT FROM AUTHOR]

Microgreens have a high nutrient density and are beneficial to human health. Even though this class of vegetables have gaining increasing levels of attention in the last year, scientific research on the growth of microgreens in controlled environments under artificial lighting have not been thoroughly characterized. By describing the scientific outputs focused on the impacts of artificial illumination on microgreens, especially from the first two decades of the 21st century, it is therefore possible to detect advancements and research gaps in this research field. This review is divided in two parts: first, a general overview of the scientific production about microgreens; second, a systematic review of scientific studies exploring artificial lighting on the production of microgreens. The overview of scientific production on microgreens and artificial lighting across the Scopus, Web of Science, and Scielo databases, from 2000 to 2021, respectively, indicated three phases, as before 2011 no paper was found: phase 1 (2012 to 2014), six papers; phase 2 (2015 to 2018), fifteen papers; and phase 3 (2019 to 2021), forty-six papers, respectively. Mustard was the most evaluated crop under all production stages. With regard to the second part of this review, studies on artificial lighting with fluorescent lamps (high-pressure sodium light bulbs—HPS), from the supplementation to the replacement of HPS lighting with light emitting diode (LED) lamps, and plant responses with respect to light properties comprise the main works identified. Studies on the distribution of environmental factors under controlled microgreen cultivation present research gaps. [ABSTRACT FROM AUTHOR]

As a strong interference source for the all-time optical imaging surveillance of maritime targets, sea surface glare is difficult to mitigate accurately because of its time-varying characteristics due to lighting conditions and seawater fluctuations. In this paper, we propose an adaptive suppression approach to sea surface glare, which establishes a geographic polarization suppression model based on real-time information regarding geographic positioning and the orientation information of the floating platform, and also combines dynamic polarization control and pixel normalization to achieve adaptive suppression of sea surface glare. Experimental results show that this approach can mitigate the influence of rapidly changing glare effectively, and the SSIM indexes between the images without glare and those with glare suppression of the same scenes exceed 0.8, which is suitable for all-time glare suppression on the sea surface under natural lighting conditions. [ABSTRACT FROM AUTHOR]

After the pandemic, as it becomes more feasible to study and work from home, the quality of residential daylighting has attracted increasing attention. With the rapid growth of high-density residential areas, China is confronted with the incoordination between site planning and interior daylight availability across a wide region. Therefore, this paper investigates the applicability of planning regulations for daylight availability in dense residential areas under different climates across China, with the aim of providing data to optimize design strategies. ClimateStudio and ALFA were used to calculate the daylight factor (DF), daylight illuminance, spatial daylight autonomy (sDA), useful daylight illuminance (UDI), and melanopic equivalent daylight illuminance (m-EDI) of living rooms in four practical mixed housing estates in different Chinese daylight climate zones. The results showed that most of the studied units failed to meet current standards of DF and sDA300,50% for residence. However, more than half of these units still had high potential for UDI and met the recommendation of m-EDI by daylight only. The results verified the importance of integrative consideration of the local daylight climate and interior unit design for residential area layout planning. Finally, this paper suggests two topics for further exploration to bridge the gap between area planning and interior daylight availability in dense residential areas. [ABSTRACT FROM AUTHOR]

The images captured by forest nighttime imaging devices are prone to degradation and noise issues due to environmental constraints. This paper proposes a novel framework based on the self‐calibrating illumination framework to improve image quality. The framework consists of four specific steps: (1) addressing non‐uniform degradation by estimating illuminance components through non‐uniform MaxRGB, (2) extracting rich information using multi‐scale inflationary convolution, (3) analyzing the relationship between different input levels and the initial level and progressively adjusting the luminance components using a channel self‐calibration module to achieve continuous improvement in luminance, and (4) designing a reflectance optimization module that enhances illuminance while suppressing noise through a regularization model. To evaluate the proposed method, a dataset comprising 1000 forest night images is constructed using an image simulation strategy. The effectiveness of this method was validated on both synthetic and real datasets, demonstrating its ability to significantly enhance nighttime forest images. When compared to six other algorithms, this method outperformed them in eight evaluation metrics, including a peak signal‐to‐noise ratio metric of 22.839 and a structural similarity metric of 0.909. The experimental results clearly indicate that this method excels in enhancing image quality and fidelity. [ABSTRACT FROM AUTHOR]

In the realm of autonomous systems and smart-city initiatives, accurately detecting and localizing pole-like objects (PLOs) such as electrical poles and traffic signs has become crucial. Despite their significance, the diverse nature of PLOs complicates their accurate recognition. Point cloud data and 3D deep learning models offer a promising approach to PLO localization under varied lighting, addressing issues faced by camera systems. However, the distinct characteristics of different street scenes worldwide require infeasibly extensive training data for satisfactory results because of the nature of deep learning. This prohibitively increases the cost of lidar data capture and annotation. This paper introduces a novel few-shot learning framework for the classification of outdoor point cloud objects, leveraging a minimalistic approach that requires only a single support sample for effective classification. Central to our methodology is the development of Pole-NN, a Non-parametric Network that efficiently distinguishes between various PLOs and other road assets without the need for extensive training datasets traditionally associated with deep learning models. Additionally, we present the Parkville-3D Dataset, an annotated point cloud dataset we have captured and labelled, which addresses the notable scarcity of fine-grained PLO datasets. Our experimental results demonstrate the potential of our approach to utilize the intrinsic spatial relationships within point cloud data, promoting a more efficient and resource-conscious strategy for PLO classification. [ABSTRACT FROM AUTHOR]

In the architecture, engineering, and construction industries, the integration of Building Information Modeling (BIM) has become instrumental in shaping the design and commissioning of smart buildings. At the center of this development is the pursuit of more intelligent, efficient, and sustainable built environments. The emergence of smart buildings equipped with advanced sensor networks and automation systems increasingly requires the implementation of Digital Twins (DT) for the direct coupling of BIM methods for integral building planning, commissioning, and operational monitoring. While simulation tools and methods exist in the design phase of developing advanced controls, their mapping to construction or post-construction models is less well developed. Through systematic, keyword-based literature research on publisher-independent databases, this review paper gives a comprehensive overview of the state of the research on BIM integration of building control systems with a primary focus on combined controls for daylight and artificial lighting systems. The review, supported by a bibliometric literature analysis, highlights major development fields in HVAC controls, failure detection, and fire-detection systems, while the integration of daylight and artificial lighting controls in Digital Twins is still at an early stage of development. In addition to already existing reviews in the context of BIM and Digital planning methods, this review particularly intends to build the necessary knowledge base to further motivate research activities to integrate simulation-based control methods in the BIM planning process and to further close the gap between planning, implementation, and commissioning. [ABSTRACT FROM AUTHOR]

Shunt resistance R sh is a critical parameter for photovoltaic cells designed for low light indoor applications because it negatively affects the open circuit voltage, fill factor, and conversion efficiency. Standard CIGS cells are known to have low R sh and are, therefore, unpromising candidates for indoor energy sources. In this paper, we extend the original work of Virtuani et al. by determining the electrical specifications of many CIGS cells with copper contents [Cu]/([Ga]+[In]) as low as 0.33 and gallium contents between 0.28 and 0.81. First, IV data are fitted by a standard single-diode electrical circuit model for each illumination, resulting in light-dependent parameters. Then, we use a procedure based on a single dataset of electrical variables, i.e., independent of light, corrected by the experimental collection function, which captures light-dependent physical mechanisms. In this way, we are able to correctly reproduce the illuminance dependence of the electrical response of the PV cell over three orders of magnitude, in particular with a fixed value of the shunt resistance. The highest R sh is obtained with a low copper composition of 0.5 , regardless of the gallium composition. [ABSTRACT FROM AUTHOR]

Inadequate illumination often causes severe image degradation, such as noise and artifacts. These types of images do not meet the requirements of advanced visual tasks, so low-light image enhancement is currently a flourishing and challenging research topic. To alleviate the problem of low brightness and low contrast, this paper proposes an improved zero-shot Retinex network, named IRNet, which is composed of two parts: a Decom-Net and an Enhance-Net. The Decom-Net is designed to decompose the raw input into two maps, i.e., illuminance and reflection. Afterwards, the subsequent Enhance-Net takes the decomposed illuminance component as its input, enhances the image brightness and features through gamma transformation and a convolutional network, and fuses the enhanced illumination and reflection maps together to obtain the final enhanced result. Due to the use of zero-shot learning, no previous training is required. IRNet depends on the internal optimization of each individual input image, and the network weights are updated by iteratively minimizing a series of designed loss functions, in which noise reduction loss and color constancy loss are introduced to reduce noise and relieve color distortion during the image enhancement process. Experiments conducted on public datasets and the presented practical applications demonstrate that our method outperforms other counterparts in terms of both visual perception and objective metrics. [ABSTRACT FROM AUTHOR]

Copyright of Przeglad Elektrotechniczny is the property of Przeglad Elektrotechniczny 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.)

Aimed at image distortion caused in process of defogging images and interfered by bright objects, a single adaptive image defogging method based on sky segmentation is proposed in this paper. Firstly, the combination of the dark channels and bright channels is used to estimate the atmospheric light. And then the sky region and the accurate atmospheric light are obtained by the information entropy and the dark channel prior. Next, the initial transmittance is estimated by the dark channel prior, and then the fast guiding filter is utilized to estimate the transmittance accurately. Further, an adaptive weight factor and an error amplification compensation factor of bright objects are introduced to optimize the transmittance mapping constraint and to correct the sky region and the non-sky region, respectively. Finally, bright adjustments are performed on the fog-free image obtained from the atmospheric scattering model by a nonlinear mapping method, which causes a clearer and more natural defogging image to be got. The experimental results show that adaptive single image defogging algorithms proposed in this paper has the higher value of peak signal-to-noise ratio, the higher value of structural similarity index measure, the higher value of naturalness image quality evaluator, the higher value of fog aware density evaluator, and the less time consumed, which illustrates that the adaptive single image defogging algorithm proposed in this paper has a better defogging effect on haze images with sky areas and bright objects. [ABSTRACT FROM AUTHOR]

The energy transition requires optimal knowledge of the thermal behaviour of different passive strategies. This paper explores the impact of 28 variables representing 4 shading devices, 5 external wall compositions (Uw), 3 window types (Uw), 4 window-to-wall ratios (WWR), 4 types of climates represented by 4 cities, and 8 orientations. Applying the Latin hypercube sampling method, a campaign of 300 dynamic thermal simulations is performed to assess the impact of the variables selected using the weighted generalised linear regression method for the energy demand for air conditioning, the energy demand for lighting, and the environmental impact expressed in kg of CO2. The model of energy demand for cooling (R² = 0.951) shows that the weather data is the variable that most explains energy demand, followed by the glazing ratio, the thermal characteristics of external walls, and shading devices. The model explaining the energy demand for lighting (R² = 0.945) shows that the WWR and shading devices, the weather data, and the orientation, influence the energy demand for lighting. Finally, the model explaining the embodied carbon footprint (kg of CO2) (R² = 0.989) shows that external walls and window type are the main influencing factors. Finally, the best combination for balancing the cooling-lighting-embodied carbon balance equation is discussed. [ABSTRACT FROM AUTHOR]

The crucial need for perpetual monitoring of photovoltaic (PV) systems, particularly in remote areas where routine inspections are challenging, is of major importance. This paper introduces an advanced approach to optimizing the maximum power point while ensuring real-time PV error handling. The overarching problem of securing continuous monitoring of photovoltaic systems is highlighted, emphasizing the need for reliable performance, especially in remote and inaccessible locations. The proposed methodology employs an innovative genetic algorithm (GA) designed to optimize the maximum power point of photovoltaic systems. This approach takes into account critical PV parameters and constraints. The single-diode PV modeling process, based on environmental variables like outdoor temperature, illuminance, and irradiance, plays a pivotal role in the optimization process. To specifically address the challenge of perpetual monitoring, the paper introduces a technique for handling PV errors in real time using evolutionary-based optimization. The genetic algorithm is utilized to estimate the maximum power point, with the PV voltage and current calculated on the basis of simulated values. A meticulous comparison between the expected electrical output and the actual photovoltaic data is conducted to identify potential errors in the photovoltaic system. A user interface provides a dynamic display of the PV system's real-time status, generating alerts when abnormal PV values are detected. Rigorous testing under real-world conditions, incorporating PV-monitored values and outdoor environmental parameters, demonstrates the remarkable accuracy of the genetic algorithm, surpassing 98% in predicting PV current, voltage, and power. This establishes the proposed algorithm as a potent solution for ensuring the perpetual and secure monitoring of PV systems, particularly in remote and challenging environments. [ABSTRACT FROM AUTHOR]

Solid-state lighting systems can vary widely in the degree of temporal light modulation (TLM) of their light output. TLM is known to have visual, cognitive, and behavioral effects but there are few recommendations for limits on the acceptable TLM in everyday lighting systems and there is little information concerning individual differences in sensitivity. This paper is a re-analysis of previously presented data, focusing on two subgroups in a larger sample: those scoring low or high on the Wilkins Pattern Glare Sensitivity (PGS) test, which is a validated test that identifies people at high risk of visual stress. The results show that the PGS groups differed in their sensitivity to TLM conditions, despite short exposures and a restricted field of view. [ABSTRACT FROM AUTHOR]

This paper investigates the determinants and prospects of household lighting choices in rural Tanzania using a Multinomial Logit Regression Model. The analysis is based on data from 4671 households, focusing on three lighting options: electricity, solar energy, and candle lighting. The results reveal significant factors influencing these choices, including household head characteristics, household size, marital status, education, employment status, number of rooms, and income. Key findings indicate that the age of the household head negatively influences the likelihood of choosing grid-electricity, while having a male head of household significantly reduces the probability of opting for any lighting option. Larger household size is negatively associated with choosing electricity and candle lighting. Marital status shows that married households are more likely to use candle lighting. Employment status positively impacts the likelihood of adopting all three lighting options, with employed household heads being more likely to choose modern lighting solutions. Income levels are crucial, as higher income significantly increases the probability of selecting electricity and candle lighting, but not solar energy. These findings provide valuable insights for policymakers and stakeholders aiming to enhance sustainable energy access in rural Tanzania. It highlights the importance of addressing socio-economic factors to promote the adoption of modern and sustainable lighting technologies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a digital model to run an evacuation simulation that reflects the road network blockage caused by the landslide and river flooding damage in Marumori-machi, Miyagi Prefecture, which was severely damaged by Typhoon No. 19 in 2019. In particular, we propose an evacuation agent simulation model that can be extended in the future to scenarios related to disaster response decisions, education, and awareness on the part of residents and can reproduce the evacuation agent situation of a real disaster. The method adjusts a set of parameters of vehicles and pedestrian agents to reproduce the evacuation situation. Then, using the parameter set, we perform the agent simulations under different scenarios varying the time of disaster occurrence and evacuation. Finally, we evaluate the changes in the number of people who have completed their evacuation, the number of victims, etc. The results of the scenarios with different disaster occurrence times showed that the final evacuation rate situation improved by at least 1% (about 170 people who completed evacuation) during daylight time compared to nighttime. The relationship between sunset time and the start of evacuation was qualitatively and quantitatively demonstrated to be supported. It was also confirmed that the evacuation situation did not change much with the time of the evacuation announcement. These results show trends limited to the present study's disasters and scenarios and do not necessarily provide generalized findings for disaster response. However, the results indicate that applying the proposed methodology to a greater number of disasters and scenario conditions could lead to better analysis and optimization of disaster response. Interviews with government disaster management officials in the target areas suggest that confirming the effectiveness of disaster response while visualizing the distribution of disaster risk in the areas from a bird's eye view, as in this study, could enhance existing response plans. This approach may also present information comprehensibly for staff and residents who did not experience the disaster firsthand, simulating the experience for better understanding. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) windows have received more and more attention in recent years since their active energysaving advantages. Considering the surface covered with solar cell modules, the indoor daylight environment of PV windows is obviously different with clear glass windows. However, despite many scholars have studied the indoor daylight environment of PV windows, there few investigations study it from the perspective of human subjective visual perception. In this paper, the indoor daylight environment and human visual comfort of building with Cadmium Telluride Photovoltaic (CdTe-PV) window were investigated. Firstly, the parameters of indoor daylight environment and subjective questionnaires in rooms with CdTe-PV window and clear glass window were analyzed respectively. On the basis of this, combined with indoor working surface illuminance and results of subjective questionnaires, the daylight illuminance threshold of human visual comfort was investigated by the method of Mean Bias Degree (MBD). Finally, an evaluation model for indoor daylight environment of buildings with CdTe-PV window was developed by Fuzzy Comprehensive Evaluation Method. The results showed that the working surface illuminance of CdTe-PV window was lower than that of clear glass room, the CCT of different windows room had a minor gap and the CdTe-PV window room was closer to the recommended range that was 3300-5000K. As for CRI, both the CdTe-PV window room and the clear glass room could meet the visual comfort requirements of office staff. Furthermore, it was found that the requirement of human visual comfort was met when indoor working surface illuminance varies between 500-2200lx in the room with CdTe-PV window. At last, according to the comprehensive evaluation model proposed in this paper, it was found that the indoor daylight environment of buildings with CdTe-PV window was excellent in the present experiment. [ABSTRACT FROM AUTHOR]

Through their consumption behavior, households are responsible for more than 70% of total global greenhouse gas emissions. Therefore, the GHG emission reduction potential due to the household behavior is very high. Energy consumption is the main source of the GHG emission in households. There are two main ways to reduce GHG emissions in households: use of renewable energy, energy efficiency improvement, and energy conservation due to changes in the energy use patterns. The highest energy saving potential in households is linked with building renovation, followed by the use of energy efficient appliances (including lighting). Renewable energy microgeneration technologies in households also provide opportunities for GHG emission reduction. Although there have been many policies developed to reduce GHG emissions from energy consumption in households, they still need to be more effective. This paper aims to assess willingness of Lithuanian households to reduce GHG emissions from energy consumption in households by embarking on energy renovation of buildings, use of energy efficient appliances and use of renewable energy technologies. The willingness to pay for these GHG emission reduction measures allows to compare household preferences with respect to available support measures and assess the adequacy of such measures. The paper also discusses household attitudes toward the main policies and measures for GHG emission reduction. The results show the highest willingness to pay for energy efficient appliances, followed by renewable energy technologies. The willingness to pay for energy renovation is the lowest one and such s measure requires significant state support. [ABSTRACT FROM AUTHOR]

With the rapid development of the city, the city's intelligent lighting control system has gradually replaced the traditional lighting control system. But at present, there are still some problems in urban street lamp lighting control, such as a low level of intelligence, a huge waste of electric energy, improper maintenance, and so on. Firstly, aiming at the problem of untimely detection of street lamp faults, this paper adds GIS technology to the intelligent lighting system and uses GIS to locate the faulty street lamp. To improve the accuracy of intelligent dimming, an improved intelligent dimming algorithm based on a support vector machine is proposed. To verify the effectiveness of the proposed algorithm, an intelligent lighting control system based on an improved algorithm and GIS technology is designed in this paper. It can control the street light switch in real-time and monitor the working condition of the street light in real-time. The performance of the improved system is verified by experiments. The experimental results show that the system achieves automatic dimming function through an improved dimming algorithm; the system can alarm and locate the fault lamp position quickly; the system can achieve a greater energy-saving effect. [ABSTRACT FROM AUTHOR]

Street lighting is very important now-days especially at dangerous areas and highways but it consume a lot of power and it became challenging for many researchers in the past few years. Enormous efforts have been placed on the issue of reducing power consumption in illuminating cities and streets, researchers had various approaches and methods in tackling this challenging matter, till now there is no ideal system that has been developed to reduce the electricity usage. In this paper intelligent controller based on deep learning proposed to control the light at the street from sunset to sunrise, the system will decrease the light used to illuminate the streets in the absence of movements, the network trained based on deep learning with several image of different objects to help the system detecting any moving objects in the street to provide the street with the exact amount of light needed in order to reduce the waste of electrical energy resulting from street lighting and to help reduce accidents hence high percentage of criminal activity and life threatening conditions occur in the absence of light. The system was trained with a vast and diverse dataset to assure the accuracy and efficiency of the proposed system, the trained system showed a result of 90 precision of detecting moving objects, the proposed system was tested with a new dataset to assure the reliability and dependency of the system and reducing the errors to the minimum, the system shows promising results in detecting movements and objects, after the detection being complete, the system will send a pulse width modulation causing a 20 % light dimming, leading to enormous reduction in the power consumption, adding to that the proposed system is easy to use [ABSTRACT FROM AUTHOR]

Pigments with special effects are nowadays utilized in the graphic engineering and design to achieve an added value of the final product. Daylight-invisible, UV-visible fluorescent pigments can be used as markings, sensors, as well as special design or security feature. Red and green UV-visible fluorescent pigments used in this experiment were mixed in the transparent base and screen-printed using the 60 l/cm mesh on the white uncoated paper, by applying different number of printed ink layers: one, two and three. Prints were then subjected to the accelerated ageing in a weathering chamber. Ink layer thickness and colorimetric properties of the unaged and aged prints were analyzed. Microscopic and macroscopic images of the prints were taken before and after the ageing process do assess the subjective visual difference between the unaged and aged samples. Results of this research have shown that one printed layer of the ink had inadequate visual response of fluorescence because of the effect of the optical brighteners in the paper. Higher number of the ink layers on print displayed better fluorescence effect and improved light fastness compared to the print obtained by applying only one ink layer. Results of the colorimetric measurements, as well as microscopic and macroscopic images, displayed the objective and subjective differences in the color appearance of the unaged and aged prints. Thereby, results of this research provided the guidelines for usage of the special-effect UV-visible fluorescent inks in applied graphic design. [ABSTRACT FROM AUTHOR]

Light pollution has a detrimental effect on astronomy. Artificial light emitted from outdoor lighting increases the brightness of the night sky, making it difficult to observe astronomical objects. The spectral power distribution of artificial light sources is one of the key factors determining how much the night sky is deteriorated by light pollution. The ongoing replacement of discharge lamps with LED sources may have a major impact on astronomy because LED spectra usually cover the entire visible radiation range. This paper provides an analysis of the impact of LED sources with correlated color temperature in the range from 1000 K to approximately 10 000 K on visual and instrumental astronomical observations. For each analyzed artificial source, the Starlight Contamination Degree (SCD) index, i.e. a quantity that allows for quick evaluation of the impact of the sources on the night sky, is calculated. The reflection of artificial light from different ground surfaces and its scattering in the atmosphere was included in the calculation of the SCD index. LED lamps with very low values of correlated color temperature (CCT) and color rendering index (CRI) were found to possibly have a similar or even smaller impact on astronomical observations than sodium discharge lamps. Moreover, professional astronomical observations are more affected by LED lamps than visual observations, even for lamps with the lowest CCT and CRI. Thus, additional measures (e.g. reducing lumen output) should be applied to protect observational conditions. The results of the study help to assess which LED lamps can be used, and which should be avoided in the protection zones around astronomical observing sites. [ABSTRACT FROM AUTHOR]

The role of the transparent envelope in energy savings is crucial as it accounts for a significant proportion of the total energy loss (between 30 and 40%). This paper focuses on the identification of reasonable parameters for the transparent envelope in different climatic regions. To achieve this goal, typical urban office buildings from four different climatic regions are used as research objects. A total of 1600 scenarios were simulated to investigate the variation of energy use intensity, including transparent envelope parameters, meteorological parameters and different types of glazing. The results show that for south-facing transparent envelope facades, type D glazing is the most energy efficient in severe cold regions, type C in colder regions and type B in the other two climatic regions. No solar shading is required in the very cold region. Horizontal shading can be an effective method for saving energy in colder climates, while comprehensive shading can be beneficial in other regions. Deep shading is particularly energy efficient if it meets lighting requirements. For example, in Guangzhou, energy savings of 13.46%, 15.47%, 7.01% and 7.02% can be achieved in the east, west, south and north directions, respectively, using B-type glazing and a comprehensive shading depth of 900 mm. [ABSTRACT FROM AUTHOR]

The paper presents a study of decentralized control for a satellite formation flying mission that uses differential lift and drag to enforce the relative positioning requirements. All spacecraft are equipped with large sunlight reflectors so that, given the appropriate lighting conditions, the formation as a whole can be made visible from the Earth as a configurable pixel image in the sky. The paper analyzes the possibility of achieving a pre-defined lineup of the formation by implementing decentralized aerodynamic-based control through the orientation of sunlight reflectors relative to the incoming airflow. The required relative trajectories are so-called projected circular orbits which ensure the rotation of the image with the orbital period. The choice of the reference trajectory for each satellite is obtained by minimizing the total sum of relative trajectory residuals. The control law is based on the linear-quadratic regulator with the decentralized objective function of reducing the mean deviation of each satellite's trajectory relative to the other satellites. The accuracy of the required image construction and convergence time depending on the initial conditions and orbit altitude are studied in the paper. [ABSTRACT FROM AUTHOR]

Purpose: Employee satisfaction is critical in any workplace. Research suggests that the environment that people work in can contribute greatly to levels of satisfaction as well as productivity. Limited research exists, however, on how the aesthetics of a workplace impact both employee satisfaction and well-being. This paper aims to identify whether the aesthetics in a workplace environment at one university influences employee satisfaction and well-being. Design/methodology/approach: This paper shares data from a survey that determined whether the workplace environment at one university in Queensland, Australia supports its workers' job satisfaction and well-being. The survey was distributed amongst all staff at three campuses with a total of 73 usable responses. Findings: Findings showed that there is a strong need for an aesthetically pleasing workplace and its positive impacts on employees. In addition, an aesthetically pleasing workplace was perceived to have a positive impact on the respondents' likelihood of spending more time at work, hence, a greater sense of satisfaction. The respondents indicated a moderate level of satisfaction with the aesthetics of their workspace and environment including feeling safe. Research limitations/implications: Implications show that further improvements could be attained in the workplace through the addition of natural lighting, plants and artwork. The employees also indicated they would like more control over the aesthetics of the work environment. Originality/value: This research is original as it was not known whether aesthetics in the workplace influenced worker satisfaction and/or well-being. [ABSTRACT FROM AUTHOR]

Lanzhou City is located in the semi-arid region of northwest China, which experiences serious desertification. Moreover, the high intensity of land development, with the accelerated industrialization and urbanization, causes increasingly aggravated conflict between humans and the environment. Exploring the response of the ecological environment quality to the natural environment and anthropogenic activities is important to protect the sustainable development of urban economic construction and the environment. Based on the Google Earth Engine (GEE) platform, this paper constructed a modified Remote Sensing Ecological Index (MRSEI) model which could reflect the ecological environment quality by integrating the desertification index (DI) into the Remote Sensing Ecological index (RSEI) model. This paper explores the spatiotemporal variation in the environmental quality from 2000 to 2020 in Lanzhou, China, and analyzes the natural and anthropogenic factors affecting the environment quality in terms of temperature, precipitation, gross domestic product (GDP), land use, night lighting, and population. The results showed that the mean value of MRSEI ranged from 0.254 to 0.400. The area undergoing fast growth in ecological quality was in the northwestern part of Lanzhou, and the area of decrease was in the central part. Various factors have different degrees of influence on the ecosystem, with temperature, precipitation, and land use having a greater impact, and GDP and population having a limited impact. Precipitation and temperature showed a strong impact when interacting with other factors, demonstrating that precipitation and temperature were also key factors affecting MRSEI. Overall, climate change and the implementation of ecological restoration projects have led to an improvement in the quality of the ecological environment in Lanzhou. This study provides a reference for understanding the spatiotemporal changes in the ecological environment in semi-arid Lanzhou and is conducive to formulating proper protection strategies. [ABSTRACT FROM AUTHOR]

In response to the pressing global challenges around climate change and the imperative of transitioning the energy market towards sustainability, this paper presents a comprehensive review starting from the late 18th century. The study examines the pivotal role of Transmission System Operators (TSOs) and Distribution System Operators (DSOs) in shaping the evolving energy landscape, with a specific emphasis on the C+++ Framework. This framework emphasizes coordination, cooperation, and collaboration between TSOs and DSOs to achieve sustainable energy systems through the integration of renewable energy technologies, storage systems, and efficient energy demand management. In addition, the review provides a historical overview of global warming from 1800 to the present, highlighting key events and developments related to greenhouse gas emissions. Furthermore, the paper delves into the significance of international agreements such as the Paris Agreement and the importance of reducing greenhouse gas emissions for a sustainable future. Recognizing the vital role of the C+++ Framework, the paper concludes with a discussion of future hybrid sustainable technologies incorporating various storage and efficient lighting technologies that can optimize energy management and reduce carbon emissions. This research aims to contribute valuable insights to inform energy policy and decision-making processes for a reliable, efficient, and sustainable energy delivery system. [ABSTRACT FROM AUTHOR]

People spend more than 90% of their time indoors, and, as such, improving indoor lighting quality can enhance their quality of life by positively influencing both physiological and psychological aspects. Numerous studies suggest that perceptions of a space vary depending on a number of lighting attributes present. Significant effort has been made across various fields to identify the spatial lighting conditions and attributes that impact human perception, although we lack studies that explore the impact of these conditions in tandem. This paper investigates how interior lighting conditions influence human impressions of room ambiance. The study examines 16 different interior scenes, considering factors such as sky condition (sunny vs. overcast), shading blinds position (open vs. closed), presence or absence of electric light (on vs. off), and Correlated Color Temperature (CCT) (2700 K, 4000 K, and 6500 K). The evaluation is conducted within an office environment at Carnegie Mellon University, using a combination of objective lighting metrics and subjective assessments. In total, 26 participants, consisting of 11 females, 14 males, and one undisclosed, aged between 18 and 50, evaluated the office ambiance under various lighting conditions using semantic differential scales. The analysis showed that the variation of blinds and CCT levels significantly influenced the participants' impression of light. The study also identified statistically significant interactions between "blinds and CCT" and "blinds and sky" conditions, highlighting the combined influence of these variables on shaping indoor light impressions. This research offers valuable insights into the complex interplay of different lighting factors in shaping human perceptions, and underscores the importance of optimizing indoor lighting conditions for creating healthy and sustainable indoor environments. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of LED short-circuit fault detection in signaling and lighting systems in the automotive industry. The conventional diagnostic method commonly implemented in newer vehicles relies on measuring the voltage drop across different LED branches and comparing it with threshold values indicating faults caused by open circuits or LED short circuits. With this algorithm, detecting cases of a few LEDs short-circuited within a branch, particularly a single malfunctioning LED, is particularly challenging. In this work, two easily implementable algorithms are proposed to address this issue within the vehicle's control unit. One is based on a mathematical prediction model, while the other utilizes a neural network. The results obtained offer a 100% LED short-circuit fault detection rate in the majority of analyzed cases, representing a significant improvement over the conventional method, even in scenarios involving a single malfunctioning LED within a branch. Additionally, the neural network-based model can accurately predict the number of failed LEDs. [ABSTRACT FROM AUTHOR]

Cloud-induced atmospheric extinction and occlusion significantly affect the effectiveness and quality of telescope observations. Real-time cloud-cover distribution and long-term statistical data are essential for astronomical siting and telescope operations. Visual inspection is currently the primary approach for analyzing cloud distribution at ground-based astronomical sites. However, the main disadvantages of manual observation methods are human subjectivity, heavy workloads, and poor real-time performance. Therefore, a real-time automatic cloud image classification method is desperately needed. This paper presents a novel cloud identification method named the PSO+XGBoost model, which combines eXtreme Gradient Boosting (XGBoost) with particle-swarm optimization (PSO). The entire cloud image is divided into 37 sub-regions to identify the distribution of the clouds more precisely. Nineteen features, including the sky background, star density, lighting conditions, and subregion grayscale values, are extracted. The experimental results have shown that the overall classification accuracy is 96.91%, and our model can outperform several state-of-the-art baseline methods. Our approach achieves high accuracy in comparison with the manual observation methods. Moreover, this method meets telescope real-time scheduling requirements. [ABSTRACT FROM AUTHOR]

Alternating current can result in flickering—or pulsing—in the brightness of light emitted by luminaires. Lighting flicker typically occurs in the range of 100 to 140 cycles per second (Hz), which is too fast for visual perception by most organisms. However, evidence indicates that many organisms perceive flicker with non-visual photoreceptors present on the retinas. Exposure to flickering lights at night disrupts the circadian rhythm of organisms, leading to symptoms similar to blue light exposure at night. The traditional method for detecting flickering is with a flickermeter held near a single light. In this paper, we explore the use of high-speed camera data in the collection of temporal profiles for groups of luminaires simultaneously at distances ranging from several meters to several kilometers. Temporal profiles are extracted for individual lighting features and the full scene. The identification of luminaire types is based on their spectral signatures. With the camera data, it is possible to identify flickering and non-flickering lights, to determine the flicker frequency, to calculate percent flicker and the flicker index, and to identify groups of lights whose flickers are synchronized. Both flickering and non-flickering luminaires can be found for LED, metal halide, fluorescent, and compact fluorescent lights. To date, flickering has been detected in all of the incandescent, high-pressure sodium, and low-pressure sodium luminaires that we measured. We found that flicker synchronization is often present for lights installed within a single facility and also for strings of streetlights. We also found that flicker exposure can come from the light reflected off of the earth's surface. Luminaires designed to illuminate large areas often saturate high-speed camera data collection. This saturation can be reduced or eliminated using neutral density filters on the camera. Published experimental data on the impacts of flicker on organisms remains sparse. Many studies have drawn inferences on the impacts of spectral and lighting brightness on organisms without controlling for flicker. Our conclusion is that lighting flicker is a type of light pollution. The use of high-speed camera data makes it easier to include flicker as a variable in studies regarding the impacts of lighting on organisms. [ABSTRACT FROM AUTHOR]