Architectural Lighting Research Articles

A Hybrid Effectiveness-Implementation Study of a Multi-Component Lighting Intervention for Hospital Shift Workers.

Simple lighting solutions may mitigate the harmful effects of shiftwork. This hybrid effectiveness–implementation study evaluated a multi-component lighting intervention in hospital nurses that included 6500 K architectural lighting in the nurses’ station plus optional behavioral components (a lightbox, blueblocker glasses, eyemasks) with instruction about appropriately timed usage. Selective improvements from baseline were observed in on-shift performance, sleep quality, and caffeine consumption in day workers (all p < 0.05); off-shift sleepiness scores improved for night workers (p < 0.05). Further, self-reported measures of quality of life improved for both groups (p < 0.05). Preliminary implementation data from interviews and questionnaires suggest perceived benefits and high acceptability of the intervention.

Remembrance Light At Memorial Sites

Everyone in Russia has been preparing to the 75th anniversary of the victory in World War Two despite the fact that the state-level commemoration events are being impeded by the global disaster which may be compared to a world war: the COVID‑19 pandemic. Like a war, it will eventually end but the memory about the anniversary must and will live on. Therefore, the subject of the article is topical: commemoration light and memory in light of an eternal flame and artistic and sacral illumination (Tribute in Light, like it was in New York in 2001). Numerous issues of architectural lighting of memorial sites and monuments in different Russian cities are under consideration. Positive and negative examples of light design solutions are described. It is also noted that information on contemporary state of this area is extremely insufficient.

LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography.

Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semiautomatically in clinical routine and is, thus, prone to interobserver and intraobserver variabilities. Recent studies have shown that deep learning has the potential to perform fully automatic segmentation. However, the current best solutions still suffer from a lack of robustness in terms of accuracy and number of outliers. The goal of this work is to introduce a novel network designed to improve the overall segmentation accuracy of left ventricular structures (endocardial and epicardial borders) while enhancing the estimation of the corresponding clinical indices and reducing the number of outliers. This network is based on a multistage framework where both the localization and segmentation steps are optimized jointly through an end-to-end scheme. Results obtained on a large open access data set show that our method outperforms the current best-performing deep learning solution with a lighter architecture and achieved an overall segmentation accuracy lower than the intraobserver variability for the epicardial border (i.e., on average a mean absolute error of 1.5 mm and a Hausdorff distance of 5.1mm) with 11% of outliers. Moreover, we demonstrate that our method can closely reproduce the expert analysis for the end-diastolic and end-systolic left ventricular volumes, with a mean correlation of 0.96 and a mean absolute error of 7.6 ml. Concerning the ejection fraction of the left ventricle, results are more contrasted with a mean correlation coefficient of 0.83 and an absolute mean error of 5.0%, producing scores that are slightly below the intraobserver margin. Based on this observation, areas for improvement are suggested.

Identification of a tool for evaluation of lighting solutions by users on the example of architectural lighting

This article devoted to description of investigation citizens perception the lighting solutions of architectural lighting at the historical centers of Saint-Petersburg and Copenhagen. The main purpose is recognition the factors of lighting solution attractiveness for further implementation in lighting design. The experiment where every respondent should take evaluation of one or the other lighting solutions has been done for research this area. The questions creation and data analysis occurred by using the Mehrabian and Russell psychological model (PAD) also method S-O-R (stimuli, organism, response). As the result such factors of attractiveness as luminance, color, artistry (imagery), contextual correlation have been determined. This research has been conducted within master thesis at CLD ITMO University

On Methodology for Designing Architectural Lighting of Production Site Interior Part 111: Results and Conclusions

This is the final, third part, on the presentation of Chapter 4 and the results of the Vladimir Voronov thesis [1], successfully defended at the Moscow Architectural Institute in 1985 and devoted to the author’s method of designing architectural lighting for industrial interiors with three main upper lantern types of natural daylight and artificial lighting. The method was developed on the basis of longterm analytical calculations and numerous experiments conducted according to all the laws of statistics in natural conditions and in the camera “Mirror-type artificial sky” created by the author using planar and volumetric (on mock-ups) light modelling with careful measurement of lighting parameters characterizing various states, qualities and options for luminance composition, light saturation of the interior space, contrast of lighting, etc. The conclusions of the dissertation give a general picture of the research work performed, the main meaning of which is the belief that the design of lighting in industrial (and in any other) interiors is not limited to providing elementary normalized lighting parameters, but is a complex, sophisticated, and creative task of architectural design where the light – natural and artificial – is the main “actor”, providing functional and aesthetic qualities to the interior.

A Novel Approach to Implementation of Lighting Design Using Virtual Reality

Architectural lighting style may be field among design, interior style and electrical engineering that’s involved with the look of light system as well as natural light-weight, electric-light bulb, or each to serve human wants . Lighting design using virtual reality is an innovative approach towards electrical system design. The lighting design process and the current problems associated with them are solved by integrating two different branches of engineering along with electrical engineering. The problems associated with current lighting design such as excess illumination, improper arrangement and non uniformity can lead to several problems. This includes energy loss, cost overruns and eye strain. Implementation of lighting design using virtual reality helps to overcome many of these problems. It enable the identification of problems in the early stage of design itself by creating a 3D model of the proposed building and transforming it to a real time visual experience with the help of virtual reality concept. Hence the proper lighting calculation along with this will improve overall lighting design in terms of energy savings, cost ,and aesthetics.

Spatial representations of melanopic light in architecture

Modes of representation are key elements in communicating the properties of natural and built environments. This research proposes a capture and representation method for daylighting dynamics in interior and exterior spaces for the photopic (daytime vision) and melanopic (biological clock) portions of the electromagnetic spectrum. The proposed representations of physical ambiences situate quantitative physical information in space and can be displayed as immersive representations for better communication between architects and other stakeholders in the building industry. A digital tool was developed for low-cost, automated surveys using lightweight Raspberry Pi microcomputers and associated Camera Modules (RPiCM). The method allows visualizing the qualitative and quantitative aspects of lighting patterns using High Dynamic Range (HDR) images that generate luminance maps, accurately render human perception and subsequently generate photopic/melanopic dominance maps. The resulting spatial representations become communication tools to identify the photopic/melanopic dominance of architectural components and support design initiatives from architects.

A Study of Walking Street Night Lighting Plan on the Aspect of CPTED

The purpose of the study was to apply the architectural lighting for CPTED on the narrow pedestrian roads in old town residential area. CPTED is short for Criminal Prevention Through Environmental Design. Recently, it is being tried as a design for crime prevention in the old city. The narrow pedestrian roads less than 4 m width have vulnerable environment to crime. However, current CPTED plans have no detailed consideration for the environment on narrow roads of old residential area. The narrow pedestrian roads less than 4m width have distinctive characteristics. The environment broadly similar to interior space. Under the environment, it is possible that applying the architectural lighting on the roads less than 4 m. In this paper, the vulnerable environment to crime is reproduced by the different 3D modelings. Then, it applies the architectural lighting on the modelings. On the basis of those 30 images, sensibility estimation is fulfilled. As a result, the light type of indirect distribution and the light type intalled on the wall give people a sense of criminal safety. Also, people prefer warm tone to cool tone. In the preference ranking in the types of architectural lighting, it was in order of cove lighting, balance lighting, flat lighting, troffer lighting, up lighting, foot lighting.

On Methodology for Designing Architectural Lighting of Production Site Interior

The article describes content of original and relevant but virtually forgotten thesis of V.V. Voronov on lighting of production site interiors by means of overhead natural (using three types of skylights) and artificial illumination, in order to elaborate scientific methodology for architectural design of more qualitative luminous environment on the basis of comprehensive approach and enhanced criteria framework of its evaluation using light engineering parameters. The thesis is unique in terms of the scope and quality of field and laboratory observations which are reflected not only in the text but also in the graphical attachments, namely photos, figures, schemes, drawings, charts, nomograms, and diagrams accompanied by specific measured or calculated parameters. The first part of the thesis contains theoretical basics and results of field observations conducted by different methods. This second part is the exposition of chapter 3 of the V.V. Voronov’s candidate thesis (1985). It describes the methodology for and the results of the experiments by means of planar and volumetric light simulation using the architectural lighting simulating assembly (chamber) which were conducted in MARKHI in 1970–1985.

КУЛЬТУРА ЗОВНІШНЬОГО ОСВІТЛЕННЯ. ПРОБЛЕМА СВІТОВОГО ЗАБРУДНЕННЯ НАВКОЛИШНЬОГО СЕРЕДОВИЩА

КУЛЬТУРА ЗОВНІШНЬОГО ОСВІТЛЕННЯ. ПРОБЛЕМА СВІТОВОГО ЗАБРУДНЕННЯ НАВКОЛИШНЬОГО СЕРЕДОВИЩА

ARCHITECTURAL LIGHTING

ARCHITECTURAL LIGHTING

Lighting Public Spaces: New Trends and Future Evolutions

The article is devoted to the history and prospects of the development of outdoor lighting in public spaces with new opportunities of rapidly developing lighting technologies and trends in architecture and architectural lighting, taking into account environmental problems.

Light and color in Islamic mysticism and architecture

This paper aims to study the cognitive background of light and color in the culture and art of Islamic mysticism and architecture analytically. Islamic mysticism and architecture are two separate disciplines that pursue a common goal in light and color about the creation of the universe and its emergence in different realms. Architecture tries to express the delicate mystical aspects of this matter in the material world. The mysticism supposes the universe or the light of all lights begins from God, and this light, which is an aspect of existence, will be darker passing to the lower worlds. As the world of reason, the first universe, is white, and the world of the body, which is the last known universe, is black. The findings show that light and color are two fundamental elements of creation and existence, which, by mixing in Islamic mysticism and architecture, have found a new identity and have created a vast global vision toward Allah. This essay is based on an interpretive analytical method, based on Clifford Geertz's interpretations theories and functionalism of Branislaw Malinowski, based on a library and documentary methodology and a qualitative content analysis method that transforms from descriptive to interpretive.

Lighter but Efficient Bit-Depth Expansion Network

With the development of display technology, bit-depth expansion (BDE) has emerged as a basic process to display low-bit-depth image and video resources on high-bit-depth monitors. Most current BDE methods are based on traditional algorithms, and the few existing methods based on deep neural networks still suffer from loss of pixel-level details or from high computational cost. This paper proposes a lightweight but efficient BDE network that can effectively improve the capacity of shallow network by introducing a residual-block-in-residual-block structure. Furthermore, the proposed network adopts residual network architecture and dilated convolution to balance the preservation of pixel-level information and the expansion of the receptive field. Hence, the proposed method can also totally remove significant artifacts from very low-bit-depth images. Experimental results demonstrate that the proposed method can achieve performance comparable to or even better than that of some state-of-the-art methods while having much lighter architecture and fewer parameters.

Optimising Convolutional Neural Networks using a Hybrid Statistically-driven Coral Reef Optimisation algorithm

Convolutional Neural Networks stands at the front of many solutions which deal with computer vision related tasks. The use and the applications of these models are growing unceasingly, as well as the complexity required to deal with bigger and highly complex problems. However, hitting the most suitable model for solving a specific task is not trivial. A very manually intensive and time consuming trial-and-error experimentation is needed in order to find an architecture, hyperparameters and parameters which reach a certain level of performance. Moreover, this process leads to oversized models, diminishing their generalisation capacity. In this paper, we leverage a metaheuristic and a hybridisation process to optimise the reasoning block of CNN models, composed by fully connected and dropout layers, conducting a full reconstruction that leads to lighter models with better performance. Our approach is architecture-independent and operates at the topology, hyperparameters and parameters (connection weights) levels. For that purpose, we have implemented the Hybrid Statistically-driven Coral Reef Optimisation (HSCRO) algorithm as an extension of SCRO, a metaheuristic which does not require to adjust any parameter since they are automatically and dynamically chosen based on the statistical characteristics of the evolution. In addition, a hybridisation process employs the backpropagation algorithm to make a final fine-grained weights adjustment. In the experiments, the VGG-16 model is successfully optimised in two different scenarios (the CIFAR-10 and the CINIC-10 datasets), resulting in a lighter architecture, with an 88% reduction of the connection weights, but without losing its generalisation performance.

Deep neural networks for choice analysis: Architecture design with alternative-specific utility functions

Whereas deep neural network (DNN) is increasingly applied to choice analysis, it is challenging to reconcile domain-specific behavioral knowledge with generic-purpose DNN, to improve DNN’s interpretability and predictive power, and to identify effective regularization methods for specific tasks. To address these challenges, this study demonstrates the use of behavioral knowledge for designing a particular DNN architecture with alternative-specific utility functions (ASU-DNN) and thereby improving both the predictive power and interpretability. Unlike a fully connected DNN (F-DNN), which computes the utility value of an alternative k by using the attributes of all the alternatives, ASU-DNN computes it by using only k’s own attributes. Theoretically, ASU-DNN can substantially reduce the estimation error of F-DNN because of its lighter architecture and sparser connectivity, although the constraint of alternative-specific utility can cause ASU-DNN to exhibit a larger approximation error. Empirically, ASU-DNN has 2–3% higher prediction accuracy than F-DNN over the whole hyperparameter space in a private dataset collected in Singapore and a public dataset available in the R mlogit package. The alternative-specific connectivity is associated with the independence of irrelevant alternative (IIA) constraint, which as a domain-knowledge-based regularization method is more effective than the most popular generic-purpose explicit and implicit regularization methods and architectural hyperparameters. ASU-DNN provides a more regular substitution pattern of travel mode choices than F-DNN does, rendering ASU-DNN more interpretable. The comparison between ASU-DNN and F-DNN also aids in testing behavioral knowledge. Our results reveal that individuals are more likely to compute utility by using an alternative’s own attributes, supporting the long-standing practice in choice modeling. Overall, this study demonstrates that behavioral knowledge can guide the architecture design of DNN, function as an effective domain-knowledge-based regularization method, and improve both the interpretability and predictive power of DNN in choice analysis. Future studies can explore the generalizability of ASU-DNN and other possibilities of using utility theory to design DNN architectures.

Actigraphy for Assessing Light Effects on Sleep and Circadian Activity Rhythm in Alzheimer's Dementia: A Narrative Review.

Alzheimer's Disease (AD) is often accompanied by severe sleep problems and circadian rhythm disturbances which may to some extent be attributed to a dysfunction in the biological clock. The 24-h light/dark cycle is the strongest Zeitgeber for the biological clock. People with AD, however, often live in environments with inappropriate photic Zeitgebers. Timed bright light exposure may help to consolidate sleep- and circadian rest/activity rhythm problems in AD, and may be a low-risk alternative to pharmacological treatment. In the present review, experts from several research disciplines summarized the results of twenty-seven light intervention studies which used wrist actigraphy to measure sleep and circadian activity in AD patients. Taken together, the findings remain inconclusive with regard to beneficial light effects. However, the considered studies varied substantially with respect to the utilized light intervention, study design, and usage of actigraphy. The paper provides a comprehensive critical discussion of these issues. Fusing knowledge across complementary research disciplines has the potential to critically advance our understanding of the biological input of light on health and may contribute to architectural lighting designs in hospitals, as well as our homes and work environments.

국립중앙박물관 아트리움의 빛 변화에 따른 건축조명에 관한 연구

국립중앙박물관 아트리움의 빛 변화에 따른 건축조명에 관한 연구

Identifying supportive daytime lighting characteristics for enhancing individuals’ psychophysiological wellbeing in windowless workplace in tropical Malaysia

Inappropriate architectural lighting exposures in workplaces are causing light-induced health and performance-related problems among healthy, urban individuals. This paper presents part one of an integrated tropical architectural lighting design framework for improving dayshift individuals’ psychophysiological wellbeing in windowless workplace in Malaysia. The paper discusses five architectural lighting factors, namely intensity, spectrum, timing, duration, spatial distribution. The daytime lighting characteristics that influence individuals’ psychophysiological wellbeing indicators (IPWI) were analysed. Findings indicated a dearth of literature in the lighting characteristics to support IPWI in the tropics, as evidence was predominantly from seasonal climate contexts. This motivated a critical discussion on the lighting factors and recommendations of alternative design consideration for a tropical Asian context. Potential daytime architectural lighting characteristics likely to support dayshift IPWI in windowless workplace in tropical Malaysia were also recommended for further investigations. These recommendations in the framework are expected to facilitate healthier windowless workplace design in Malaysia.

Research into Luminance Characteristics of Objects with Architectural Lighting of Central Streets of Tula

The study of luminance distribution over the facades with architectural lighting allows us to estimate the perception of architectural objects, to analyse the quality of light solutions. The relevance of luminance characteristics estimation in night-time urban conditions has been increasing over the years, in particular, for cities where the development direction of lighting environment aims at increase of the number of illuminated objects and where there is no developed strategy of lighting environment development. Using the example of 11 central streets of Tula, the article describes the comprehensive approach to analysis of the quality of architectural lighting. Using a CCD matrix-based luminance meter, the luminance characteristics of facades were estimated.