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Floorplan energy assessments present a highly efficient method for evaluating the energy efficiency of residential properties without requiring physical presence. By employing computer modelling, an accurate determination of the building's heat loss or gain can be achieved, enabling planners and homeowners to devise energy-efficient renovation or redevelopment plans. However, the creation of an AI model for floorplan element detection necessitates the manual annotation of a substantial collection of floorplans, which poses a daunting task. This paper introduces a novel active learning model designed to detect and annotate the primary elements within floorplan images, aiming to assist energy assessors in automating the analysis of such images–an inherently challenging problem due to the time-intensive nature of the annotation process. Our active learning approach initially trained on a set of 500 annotated images and progressively learned from a larger dataset comprising 4500 unlabelled images. This iterative process resulted in mean average precision score of 0.833, precision score of 0.972, and recall score of 0.950. We make our dataset publicly available under a Creative Commons license. [ABSTRACT FROM AUTHOR]

Floorplanning is a crucial part of very large-scale integration (VLSI) physical design flow. It primarily determines the position of the blocks on a chip by considering the area, the total wirelength, etc., in light of several real-world limitations such as delay, price, and chip performance. Adopting B*-tree representation, this paper proposes a novel dual-population adaptive hybrid memetic algorithm called DPAHMA to handle the VLSI floorplanning problem effectively by optimizing the chip area and the total wirelength. Three main ideas are presented in this paper, including new definitions of crossover and mutation operators based on B*-tree encoding that overcome the shortcomings of the existing method, such as overly complicated operations on binary trees and a lack of diversity; a dynamic self-adjusting objective function, namely WeightDS, which is able to find solutions more suitable for the user-specified weight; and a main-auxiliary population mechanism by which a candidate population is introduced to assist the normal population in the global search phase. To make full use of the information obtained by the local search method, the candidate population keeps its high-quality solutions. The individuals from the candidate population crossover with the individuals from the normal population before the end of each iteration to obtain higher-quality solutions as much as possible. Experimental results for MCNC and GSRC benchmarks show that DPAHMA obtains floorplans effectively with better area and total wirelength than those of the state-of-the-art floorplanners. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) is a novel paradigm that consists of a wide network of machines and intelligent devices with the capability of communication and interaction with each other. One of the significant issues for the IoT is its healthcare applications. The positioning systems based on their environment can be classified into two main categories: Indoor and outdoor. Recently, IoT indoor positioning attracts too much attention among researchers for patient monitoring. Hence, in this paper, a stress‐free floor plan indoor positioning algorithm for patient monitoring is proposed, called THIP. The history of the patient's movement is stored in a trajectory history, and this information is employed to estimate the patient's more accurate position. The proposed THIP algorithm is simulated in MATLAB software. Several experiments are conducted to evaluate the performance of the proposed algorithm. Simulation results show that the proposed THIP algorithm raises patient positioning accuracy and declines the distance error cumulative compared to LiFS by about 4.68% and 60.6 m, respectively. Moreover, it can identify the floor level of the moving user. [ABSTRACT FROM AUTHOR]

Building owners are working on converting their legacy documentation 2D floor plans into digital 3D representations, but the manual process is labor-intensive and time-consuming. In this paper, deep learning is leveraged to automate the process. This automation requires interoperability between artificial neural networks and prevailing 3D modeling software. The system processes 2D floor plans and outputs parameters of recognized walls, single doors, double doors, and columns. The parameters include the start point and end point of the wall and the center point of the door and column. These parameters are input into Revit 2022 through the Revit API 2022 after post-processing. The dimensional parameter integration affordances of object detection and instance segmentation are studied and compared using Faster R-CNN and Mask R-CNN models. Instance segmentation was found to require more time for data labeling but was more capable of informing the modeling of irregularly shaped objects. The mean Average Precision (mAP) of object detection and instance segmentation are 71.7% and 69.3%, respectively. Apart from single doors, the average precision for other categories falls within the range of 74% to 96%. The results provide software developers with guidance on choosing between object detection and instance segmentation strategies for processing legacy building documents. These types of systems are anticipated to be pivotal to the industry's transition from 2D to 3D information modalities and advise practitioners to carefully choose suitable models and consider the recommendations provided in this study to mitigate potential failure cases. [ABSTRACT FROM AUTHOR]

To build a house, buyers meet with an architect, who analyses the land's built-up area and creates a development blueprint. Customers may have different perspectives on their residence. As a result, in order to save architects' time and provide an appropriate floor plan to the customer, we presented an interactive framework that allows the client to change existing designs and search for similar ones in a repository. To do this, we created a vocabulary of annotations for inserting new items, deleting existing objects, shifting the position of objects, and moving the locations of objects. The proposed framework accepts a digital form of a printed floor plan image with or without hand-drawn annotations as a query, then performs suggested editing operations and converts the image to standard form by identifying annotations. The retrieval model then analyses the processed image and provides further recommendations similar to the query floor plan image. Our contributions include (1) an interactive platform for updating an existing floor plan based on predefined vocabulary of annotations, and (2) a unique structure-based features for retrieving similar floor plans with a 10 % improvement in mAP score. The suggested framework's performance was examined using publicly available datasets, and it obtained 0.85 mAP which edge over existing state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

This paper proposes a robust localization system using complementary information extracted from ceiling and ground plans, particularly applicable to dynamic and complex environments. The ceiling perception provides the robot with stable and time-invariant environmental features independent of the dynamic changes on the ground, whereas the ground perception allows the robot to navigate in the ground plane while avoiding stationary obstacles. We propose an architecture to fuse ground 2D LiDAR scan and ceiling 3D LiDAR scan with our enhanced mapping algorithm associating perception from both sources efficiently. The localization ability and the navigation performance can be promisingly secured even in a harsh environment with our complementary sensed information from the ground and ceiling. The salient feature of our work is that our system can simultaneously map both the ceiling and ground plane efficiently without extra efforts of deploying articulated landmarks and apply such hybrid information effectively, which facilitates the robot to travel through any indoor environment with human crowds without getting lost. [ABSTRACT FROM AUTHOR]

We present a novel vectorized indoor modeling approach that converts point clouds into building information models (BIM) with concise and semantically segmented polygonal meshes. Existing methods detect planar shapes and connect them to complete the scene. Some focus on floor plan reconstruction as a simplified problem to better analyze connectivity between planes of floors and walls. However, the connectivity analysis is still challenging and ill-posed with incomplete point clouds as input. We propose ArrangementNet to estimate scene arrangements from an incomplete point cloud, which we can easily convert into a BIM model. ArrangementNet is a novel graph neural network that consumes noisy over-partitioned initial arrangements extracted through non-learning techniques and outputs high-quality scene arrangement. The core of ArrangementNet is an extended graph convolution that leverages co-linear and co-face relationships in the arrangement and improves the quality of prediction in complex scenes. We apply ArrangementNet to improve floor plan and ceiling arrangements and enrich them with semantic objects as scene arrangements for scene generation. Our approach faithfully models challenging scenes obtained from laser scans or multiview stereo and shows significant improvement in BIM model reconstruction compared to the state-of-the-art. Our code is available at https://github.com/zssjh/ArrangementNet. [ABSTRACT FROM AUTHOR]

This paper presents the formulation of a novel fire spread model to allow the study of traveling fires in large open spaces. The fuel load for an office building, for example, is made up of clusters of workstations that are arranged in a realistic pattern on the floor plan. The fire begins with the assumed ignition of a single workstation. The fire dynamics are modeled using computational fluid dynamics (CFD) software, which allows the user to specify exact compartment parameters, such as the compartment size, wall lining, ventilation conditions, and fuel load distribution. To reduce computational expense, each object (e.g., workstation) is represented by a burner that has a heat release rate equivalent to a complete workstation, as determined by experimental tests. The fire is allowed to spread realistically from object to object through the use of an improved flux-time product ignition model. The improved flux-time product ignition model is derived to predict ignition under time-varying heat flux exposure and only requires well-documented material properties for implementation. The study validates the equivalent burner assumption and the flux-time product fire spread model for large compartments using experimental data from NIST (Hamins A (2005) Experiments and modeling of multiple workstations burning in a compartment. Nist Ncstar.). The proposed fire spread model for large compartments aims to provide more realistic fire behaviors for fire resistant design of structures while balancing accuracy with computational efficiency. [ABSTRACT FROM AUTHOR]

This study investigates the room acoustics of seven chamber music halls of various modern and historical architecture by means of objective room acoustic measures and a subjective listening experiment. The acoustic measurements were performed with heavy cloth covering the audience areas to simulate occupancy in the halls. A loudspeaker quartet was used for auralizations, which were reproduced in a surrounding loudspeaker array. The perceptual differences between the halls were evaluated in terms of envelopment, warmth, clarity, proximity, and preference by using a paired comparison paradigm. The subjective evaluations were conducted in two different laboratories and latent class analysis was used to study the agreement between laboratories and the emergence of different listener groups in the ratings of each attribute. Concerning preference, the emergence of two groups found in the study of large symphony halls was confirmed, where one group prefers rich, enveloping sound and one group prefers high clarity. The perceptual ratings were not clearly associated with a specific hall shape, but rather depended on the distribution of early and late sound energy. Thus, the distinction between rectangular and non-rectangular floor plans previously found for large symphony halls was not observed with these smaller halls. [ABSTRACT FROM AUTHOR]

In collaboration with the Consorzio Villa Reale, the topographic, 3D and aerial photogrammetric surveys of the Visconti Tower of the Monza Park were carried out. The surveys were carried out to obtain an extremely detailed, precise and georeferenced 3D model of the building in order to produce high-level internal and external elevations and floor plans and to obtain a digital twin of the structure. The survey is the result of different survey tools and techniques integrated together. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Architectural Sciences & Applications (JASA) is the property of Journal of Architectural Sciences & Applications 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.)

In interior space planning, the furnishing stage usually entails manual iterative processes, including meeting design objectives, incorporating professional input, and optimizing design performance. Machine learning has the potential to automate and improve interior design processes while maintaining creativity and quality. The aim of this study was to develop a furnishing method that leverages machine learning as a means for enhancing design processes. A secondary aim was to develop a set of evaluation metrics for assessing the quality of the results generated from such methods, enabling comparisons between the performance of different models. To achieve these aims, floor plans were tagged and assembled into a comprehensive dataset that was then employed for training and evaluating three conditional generative adversarial network models (pix2pix, BicycleGAN, and SPADE) to generate furniture layouts within given room boundaries. Post-processing methods for improving the generated results were also developed. Finally, evaluation criteria that combine measures of architectural design with standard computer vision parameters were devised. Visual architectural analyses of the results confirm that the generated rooms adhere to accepted architectural standards. The numerical results indicate that BicycleGAN outperformed the two other models. Moreover, the overall results demonstrate a machine-learning workflow that can be used to augment existing interior design processes. [ABSTRACT FROM AUTHOR]

It is known that when a reinforced concrete building exposed to a horizontal load is subjected to torsional moments around its center of rigidity, additional shear stresses occur in the vertical load-carrying elements, such as the columns and shear walls. Therefore, in order to estimate the additional stresses caused by the torsion, the rigidity center should be calculated precisely. It is known that there are several analytical approaches to calculating the rigidity center location. These approaches do not calculate the rigidity centers close to each other in asymmetric buildings. As significant differences were observed in the calculation of the rigidity center using analytical methods, it was decided to seek verification by conducting an experimental study. In order to calculate and verify the location of the rigidity center, an extensive experimental study was planned. A total of 20 scaled and revised buildings were built, and they were tested in the specially designed test setup. The tested buildings had square, rectangular and irregular floor plans. In addition, vertical load-carrying members were either symmetrically placed on the floor plan or kept asymmetrical to see the effect of their location on the rigidity center. All the buildings were tested under their self-weight, and the corresponding displacements were recorded. Additionally, all the buildings were modeled using ETABS to verify the theoretical background of the rigidity center. From the test results, it was found that the resultant shear force can be calculated by multiplying the displacements of each member of a given story found from the tests on its bending stiffness, and this will give the location of the rigidity center. The rigidity center was found to be identical to the results obtained from the 3D model analysis using ETABS, although it uses a different procedure. As the results from the experiment and 3D model are close to each other, it can be said that the rigidity center of reinforced concrete buildings can be found from simple tests using any material that has almost uniform mechanical properties. [ABSTRACT FROM AUTHOR]

In this paper, I propose the "squares-are-the-key method" as an update of the outdoor freehand-drawing class for architectural design. Let's generate simplified 2D grids of site and floor plans, transform them to isometric grids, and insert essential height edges, taken from simplified elevations and sections, into it, on site. [ABSTRACT FROM AUTHOR]

When asked about the proportion of interior design courses in their undergraduate programs, 28% answered that 0% of the curricula included interior design; 41% stated that it was between 1% and 5%; 16% between 6% and 10%; and, 15% noted that 11% to 25% of their curricula comprised interior design coursework. Design Thinking and Interior Design: A Competitive Edge One way that the interior design profession in Colombia could distinguish itself from architecture is through the use of design thinking and human-centered design. Further, this design-thinking knowledge may enhance both architectural and interior design training which is woefully insufficient in terms of interior design education. Keywords: Interior Design; Colombia; Design Thinking; Architecture; Education EN Interior Design Colombia Design Thinking Architecture Education 95 100 6 06/28/23 20230601 NES 230601 Interior design in Colombia is a discipline that, throughout its history, has been directly linked with architecture, up to the point that the collective perception is that an Architect, regardless of their academic and professional background, should be more than capable of conceiving and designing interior spaces as the Colombian CPNAA's (Professional National Council of Architecture and Auxiliary Professions) guidebook suggests: I The applicability of a professional architect's commitment is directly related to designing a new building and the other multiple professional services such as remodeling, extensions, reconstructions, interior design, and similar i ([18], p. 11). [Extracted from the article]

In both traditional and modern Kuwaiti houses, the diwaniya--a "man cave" where men feel comfortable--is central in terms of both space and function. Due to cultural and religious customs, males and females traditionally socialize in separate groups; men gather in the diwaniya, whereas women gather in a reception room in the internal space of the house. Historically, most houses in Kuwait had a diwaniya, and despite differences in layout and furniture, they all emphasized a comfortable environment and a casual attitude to facilitate informal conversation. Due to modernization, the Kuwaiti residence has evolved in terms of design and architecture, and specifically the home interior design that affects the household's daily social lifestyle. This study uses electronic questionnaires to investigate the role of the diwaniya in contemporary house floor plans and family needs. Two hundred Kuwaiti men of various ages, living in all six governorates, answered questions about the importance of diwaniyas, how often they visit them, what type and size they prefer, and whether they intend to build a diwaniya when they design their own home. The results provide a body of knowledge regarding interior design recommendations for new homeowners who are in the process of building new houses. [ABSTRACT FROM AUTHOR]

The invention of reinforced concrete in the second half of the 19th century represented a revolution in building design and construction. Its worldwide spread at the beginning of the last century was the origin of today's globalized way of building and living. The gradual abandonment of local building traditions and the contemporary debate on the sustainability of construction aimed at reconciling the sector's energy and material needs with the preservation of the natural environment date back to this period. From the second decade of the last century until the 1960s, the invention of reinforced concrete also determined the emergence and dissemination of the theoretical principles of the Modern Movement. This movement was joined by numerous architects, each of whom interpreted in an original way the five points of Le Corbusier's rationalism (pilotis, free floor plan, free façade, ribbon windows, roof-garden-flat roof) and created masterpieces of architecture of the last century. This period was rich of cut-edging innovations in the building components. Through the critical study of archives and historical and technical sources, the work focuses on the innovation of the technological elements of façades to control the interaction between sunlight and the building, today referred to as passive energy systems. The study of some famous architectures of the Modern Movement demonstrates that architectural design is a continuous experimentation of materials and new technological solutions. Moreover, the control of the on-site behavior and effectiveness of innovations provides continuous lessons that presuppose the ability to seize opportunities for development and improvement from failed experiments. [ABSTRACT FROM AUTHOR]

In the real-estate industry, floor plans are commonly used to communicate spatial layouts of housing alternatives to house hunters. Using the method of stated preferences, this research investigates whether lay-individuals' preferences for layout attributes differ when floor plans versus text descriptions are used to measure preferences for build-to-rent apartments. The study involved 417 student respondents evaluating four hypothetical apartments twice, with the apartments varying in two focal attributes, layout orientation, and dining space status. Findings from the experiment indicate that floor plan representations of apartments are rated higher overall than text representations; however they also suggest that the effects of the two focal attributes on apartment preferences are larger for text than floor plan formats. Further, effects of the attributes on apartment preference ratings are shown to depend on the participants' user goal and on their level of attribute knowledge. The main contribution of this research is that it demonstrates how representation format influences housing preferences, and further, how lay-individuals' judgements of layout attributes depend on the individual's goals and their knowledge of the attributes. These findings are relevant for future stated preference studies and for real estate agents and property developers when considering what information to provide to prospective buyers and renters of sight-unseen residential property. [ABSTRACT FROM AUTHOR]

BIM (building information modelling) has led to substantial improvements in all design steps. Applied mainly as an information management system in the digital design of structures and buildings, only in recent years has the use of BIM also extended to the construction of road infrastructure. The so-called I-BIM (infrastructure building information modelling) methodology supports the designer in the phases of construction and execution of the design considering all aspects related to the project, including sustainability. Through the software "Roads" of "SierraSoft S.r.l.", in this article, the I-BIM approach has been used to design a 35 km cycle path as sustainable as possible. From an operational point of view, the design of a cycle path section begins with the modelling of the infrastructure in all its aspects: a study of the route, analysis of interference, modelling of the infrastructure (floor plan, profile and sections) and an intersection study. Creating an infrastructure that increases soft mobility vehicles through a comprehensive design, attracting as many users as possible, is the real innovative challenge. [ABSTRACT FROM AUTHOR]

The popularity of online home design and floor plan customization has been steadily increasing. However, the manual conversion of floor plan images from books or paper materials into electronic resources can be a challenging task due to the vast amount of historical data available. By leveraging neural networks to identify and parse floor plans, the process of converting these images into electronic materials can be significantly streamlined. In this paper, we present a novel learning framework for automatically parsing floor plan images. Our key insight is that the room type text is very common and crucial in floor plan images as it identifies the important semantic information of the corresponding room. However, this clue is rarely considered in previous learning-based methods. In contrast, we propose the Row and Column network (RC-Net) for recognizing floor plan elements by integrating the text feature. Specifically, we add the text feature branch in the network to extract text features corresponding to the room type for the guidance of room type predictions. More importantly, we formulate the Row and Column constraint module (RC constraint module) to share and constrain features across the entire row and column of the feature maps to ensure that only one type is predicted in each room as much as possible, making the segmentation boundaries between different rooms more regular and cleaner. Extensive experiments on three benchmark datasets validate that our framework substantially outperforms other state-of-the-art approaches in terms of the metrics of FWIoU, mACC and mIoU. [ABSTRACT FROM AUTHOR]

The generative spatial layout design process can generate and optimize a wide range of design responses by complying with all desired requirements and criteria and evaluating them based on one or more specific functions. Considering the complexities and diversity of spatial layout responses, it is important to know the various mechanisms of the product design process related to them. Based on this, the aim of this research is to provide a mechanism for designing a generative spatial layout (GSL) based on a housing design problem. The method of this research with a quantitative approach is the simulation and placement of spaces through coding in Grasshopper and Python software under the Grasshopper platform. The main variables of the research are the dimensions of the spaces of the residential unit, the proximity matrix, and the spatial relationships of the residential unit. With the restrictions made, 440 spatial layout responses were produced in four general shapes, including an incomplete square, a rectangle with a one-to-two ratio, an incomplete rectangle with an incomplete one-to-two ratio, and L-shape. The geometrical data of production plans have been subjected to correlation and linear regression tests in the SPSS software. Two models have been developed based on the perimeter of the plan and the area of its peripheral rectangle. Based on the obtained results, GSL design will be able to provide more favorable solutions. The results indicate that, by providing the design constraints in all the results, the area-oriented approach to the productive design of housing configurations can serve as an assistant mechanism for the designer in providing a variety of floor plans in terms of area for the designer. [ABSTRACT FROM AUTHOR]

A significant number of young people live in temporary homes, which are designed to fulfil basic needs and provide space for normal activities. However, it is unclear what those basic activities are. Moreover, the indoor environmental quality is often left out of the meaning of home, although activities and objects can affect its experienced quality. We therefore verbally and visually explored how young temporary dwellers appropriate and experience their homes, including the indoor environmental quality. Fourteen young adults took part in semi-structured interviews and photographed their most used as well as their favourite place. The interviews were transcribed and analysed following an interpretative phenomenological analysis. The experiences of appropriation in the home were connected to the physical environment through an analysis of the photos and floor plans (sketched by the researcher) using an architectural analysis from the user perspective. The outcome showed that the young adults appropriated their home in three ways: by familiarising the place with objects and "normal" activities, organising where things are and when they happen, and managing the indoor environmental quality through activities and objects. It is concluded that qualitative and visual analyses can assist with making recommendations to improve the design of temporary housing. [ABSTRACT FROM AUTHOR]

The inscriptions on Middle Babylonian kudurru monuments contain references to a certain type of Vorlage, wooden wax-covered writing boards. The kudurru monuments were erected in temples as (legal) proof of a royal land grant. In this article I explore three ways in which wooden wax-covered writing boards may have functioned as a Vorlage for kudurru inscriptions. Wooden wax-covered writing boards may have served as a Vorlage for literary passages, as a draft for the kudurru inscription or as a writing material for land survey documents (possibly the Middle Babylonian ammatu documents). Firstly, parallels between the colophons of kudurru inscriptions and first millennium literary and scholarly texts imply a shared scholarly practice in a temple context, in which wooden wax-covered writing boards were used as a Vorlage. Secondly, the use of wooden wax-covered writing boards to draft monumental inscriptions is well attested in the 1st millennium BC. Thirdly, I propose that writing boards may have been used to record the land survey necessary for the royal land grant, since land surveys and ground plans were traditionally recorded on writing boards in Mesopotamia. Wooden wax-covered writing boards and wooden writing materials became more widespread in the Middle Babylonian period. The Middle Babylonian land survey document was called ammatu document. Further, in this article I demonstrate that the equation of the Middle Babylonian ammatu document with the Old Babylonian ṭuppi ummātim, a term for title deeds written on clay tablets, is problematic. [ABSTRACT FROM AUTHOR]

Airflow in a multi-zone building can be a major cause of pollutant transfer, excessive energy consumption, and occupants discomfort. The key to monitoring airflows and mitigating related problems is to obtain a comprehensive understanding of pressure relationships within the buildings. This study proposes a visualization method for representing pressure distribution within a multi-zone building by using a novel pressure-sensing system. The system consists of a Master device and a couple of Slave devices that are connected with each other by a wireless sensor network. A 4-story office building and a 49-story residential building were installed with the system to detect pressure variations. The spatial and numerical mapping relationships of each zone were further determined through grid-forming and coordinate-establishing processes for the building floor plan. Lastly, 2D and 3D visualized pressure mappings of each floor were generated, illustrating the pressure difference and spatial relationship between adjacent zones. It is expected that the pressure mappings derived from this study will allow building operators to intuitively perceive the pressure variations and the spatial layouts of the zones. These mappings also make it possible for operators to diagnose the differences in pressure conditions between adjacent zones and plan a control scheme for the HVAC system more efficiently. [ABSTRACT FROM AUTHOR]

On-chip electrostatic discharge (ESD) protection is required for all integrated circuits (ICs). Conventional on-chip ESD protection relies on in-Si PN junction-based device structures for ESD. However, such in-Si PN-based ESD protection solutions pose significant challenges related to ESD protection design overhead, including parasitic capacitance, leakage current, and noises, as well as large chip area consumption and difficulty in IC layout floor planning. The design overhead effects of ESD protection devices are becoming unacceptable to modern ICs as IC technologies continuously advance, which is an emerging design-for-reliability challenge for advanced ICs. In this paper, we review the concept development of disruptive graphene-based on-chip ESD protection comprising a novel graphene nanoelectromechanical system (gNEMS) ESD switch and graphene ESD interconnects. This review discusses the simulation, design, and measurements of the gNEMS ESD protection structures and graphene ESD protection interconnects. The review aims to inspire non-traditional thinking for future on-chip ESD protection. [ABSTRACT FROM AUTHOR]

Wireless localization or positioning is essential for delivering location-based services for designing location tracking systems. Traditional indoor floor planning system employs wireless signals for accurate position estimation. But these positioning schemes failed to perform position estimation effectively and accurately through many obstacles or objects. The novel technique called Linear Features Projective Geometric Damped Convolutional Deep Belief Network (LFPGDCDBN) is introduced to improve the position estimation accuracy with minimum error. The proposed LFPGDCDBN technique includes two major processes namely dimensionality reduction and position estimation. First, the dimensionality reduction process is performed by projecting the principle features using Linear Helmert–Wolf blocked Sammon projection. After the feature selection, Geometric Levenberg–Marquardt Convolutional deep belief network is employed to estimate the position of the devices with higher accuracy and minimum error. The Convolutional deep belief network uses the triangulation geometric method to identify the position of the device in an indoor positioning system. Then the Levenberg–Marquardt function is a Damped least square method to minimize the squares of the deviations between the expected and observed results at the output unit. As a result, the LFPGDCDBN increases the positioning accuracy and minimizes the error rate. Experimental MATLAB assessment is carried out with various factors such as computational time, Computational space, positioning accuracy, and positing error. The experimental results and discussion indicate that the proposed LFPGDCDBN provides improved performance in terms of achieving higher positioning accuracy and minimum error as well as computational time when compared to the existing methods. The experimental results and discussion indicate that the proposed LFPGDCDBN increases the positioning accuracy by 47% and computational time, computational complexity, and reduces the positioning error by 45%, 29%, and 74% as compared to state-of-the-art works. [ABSTRACT FROM AUTHOR]

Indoor mobile robot (IMR) motion control for e-SLAM techniques with limited sensors, i.e., only LiDAR, is proposed in this research. The path was initially generated from simple floor plans constructed by the IMR exploration. The path planning starts from the vertices which can be traveled through, proceeds to the velocity planning on both cornering and linear motion, and reaches the interpolated discrete points joining the vertices. The IMR recognizes its location and environment gradually from the LiDAR data. The study imposes the upper rings of the LiDAR image to perform localization while the lower rings are for obstacle detection. The IMR must travel through a series of featured vertices and perform the path planning further generating an integrated LiDAR image. A considerable challenge is that the LiDAR data are the only source to be compared with the path planned according to the floor map. Certain changes still need to be adapted into, for example, the distance precision with relevance to the floor map and the IMR deviation in order to avoid obstacles on the path. The LiDAR setting and IMR speed regulation account for a critical issue. The study contributed to integrating a step-by-step procedure of implementing path planning and motion control using solely the LiDAR data along with the integration of various pieces of software. The control strategy is thus improved while experimenting with various proportional control gains for position, orientation, and velocity of the LiDAR in the IMR. [ABSTRACT FROM AUTHOR]

In the study of machine learning, multi-source domain adaptation (MSDA) handles multiple datasets which are collected from different distributions by using domain-invariant knowledge extraction. However, the current studies mainly employ features and raw labels on the joint space to perform domain alignment, neglecting the intrinsic structure of label distribution that can harm the performance of adaptation. Therefore, to make better use of label information when aligning joint feature-label distribution, we propose a rebalancing scheme, class-rebalanced Wasserstein distance (CRWD), for unsupervised MSDA under class-wise imbalance and data correlation. Based on the optimal transport for domain adaptation (OTDA) framework, CRWD mitigates the impact of the biased label structure by rectifying the Wasserstein mapping from source to target space. Technically, the class proportions are utilized to encourage distributional transportation between minor classes and principal components, which reweigh the optimal transport plan and reinforce the ground metric of Mahalanobis distance to better metricise the differences among domains. In addition, the scheme measures both inter-domain and intra-source discrepancies to enhance adaptation. Extensive experiments are conducted on various benchmarks, and the results prove that CRWD has competitive advantages. [ABSTRACT FROM AUTHOR]

With the increasing number of augmented reality apps for houses in recent years, home modeling is essential to complete a 3D reconstruction via identifying the primary features of the house based on a 2D floorplan. Due to the dispersed wall arrangement in 2D floor layouts and the abundant interference information surrounding varied thicknesses, existing segmentation methods mainly rely on image morphology or use deep learning models in other fields like Unet. However, these schemes do not solve poor robust performance problems. In this paper, we propose an Reflect Strip Pooling Unet (RSP-Unet) to enhance the segmentation capabilities of the network for strip features. Specifically, we utilize reflect strip pooling to replace the maximum pooling step and reduce feature loss during the downsampling in the Unet network. More importantly, the proposed module is also integrated with the SE (Squeeze-and- Excitation) mechanism to interact with input from several channels, lessen model overfitting, and increase model robustness. Finally, our extensive experience shows that the results on the self-built floorplan dataset demonstrate that the mean Intersection Over Union(mIOU) is increased by 8.34% and the Dice coefficient is increased by 8.78% compared with the original Unet model. [ABSTRACT FROM AUTHOR]

In object-oriented historical research the need to combine hypotheses and textual arguments with the critical analysis based on sources – such as floor plans, sections, perspectives, and photographs – has considerably benefited from the developments in Digital Humanities (Münster, 2022). The use of digital 3D models has overcome many limitations inherent to two-dimensional records. Since the early 1990s hypothetical 3D reconstructions have therefore increasingly become routine research tools and essential means of representation capable of offering new methods of investigation, enabling new insights into the object-related research. In terms of a holistic approach to the analysis and case studies, i.e. the enhanced ability to examine and explore (Favro, 2012) serious challenges remain regarding documentation, interoperability and long-term access to 3D-based research outputs.In this context, numerous initiatives and research projects have emerged with the common objective of systematising and rationalising the various problems identified by scholars. Such projects still tend to remain isolated, lacking a significant impact on the community of potential users. 3D research outputs are not widely applicable, due to the complex prototypes of the software architecture, difficult to apply in a broad sense. Furthermore, the 'old' problems still exist, i.e. the traditional approaches - which do not consider a 3D model as a scholarly result, but only an investigative tool - and the reluctance to share these results and the associated procedures. Therefore, an attempt is being made to define the development and evaluation of an applicable methodology for the hypothetical 3D historical reconstruction, based on a shared theoretical approach.The working method presented here reflects many years of engagement with source-based hypothetical 3D reconstruction of no longer extant or unrealised architecture for teaching and research. Our focus is therefore on a low-threshold, application-oriented method of the Scientific Reference Model (SRM) as a documented and published basic model. The structured SRM represents an important working and knowledge state, which clarifies the essential information about the object, its components, its credibility or extent of hypothesis and copyright. Such SRM is made available for further research, edits and refinement, as well as further derivatives (special applications). Thus SRM represents a findable referential result of a scholarly investigation of a material object that physically no longer exists. [ABSTRACT FROM AUTHOR]

Introduction: Operating suites are multidisciplinary units par excellence, and mostly they are the most expensive units in hospitals. Interdisciplinary workflow and efficiency are therefore crucial, which is influenced by floor plans varying from hospital to hospital. Most operating rooms are equipped with adjacent induction rooms, allowing preparation and anesthesia induction of the next patient, while the previous patient is still in the operating room. Parallelizing the working steps is thought to improve turn-over time, thus increasing throughput, number of cases and finally revenue. However, this assumption has never been challenged. Methods: We analyzed workflow during regular working hours in an operating suite equipped with a mixture of operating rooms (OR) with next door induction rooms and operating rooms without induction rooms. This allows a direct comparison of both structural elements for efficiency using utilization data over a 24-months period. Both settings were used for gynecological operations. Results: Key result is that induction rooms do not improve perioperative workflow including turn-over time. Instead, ORs without adjacent induction rooms have a significantly shorter turn-over time and OR occupancy duration per case, although surgical time and staffing were similar. Discussion: Adjacent induction rooms require extra space, funding, and high maintenance costs, but they do not speed up peri-operative processes. Modern anesthetic techniques allow for fast induction of and emergence from anesthesia. Induction rooms adjacent to the OR are no longer needed if general anesthesia without extended monitoring is used for the majority of cases. [ABSTRACT FROM AUTHOR]

This work describes a framework that allows children and domestic users to create architectural structures like mazes, houses etc., and navigate them in virtual reality (VR). The user can draw a 2D map of a maze etc. using a simple paper, pen and ruler. The application works by taking as input such a hand drawn image via gallery or camera, and then building a 3D model in VR using Unity3D. The 3D model completely follows the design of the floor plan including the placement of doors and windows. Detecting and then constructing walls, doors and windows on the fly in VR is a challenge. The user can also customize walls, windows, doors and floors. This is done by looking at the object and using the VR controller to select various options. The purpose of the framework is purely entertainment and is specifically designed for children and domestic users. From hand-drawn images on a paper to ready-to-navigate 3-D model in VR in just one click is the novelty of our work. User is completely isolated from the complexities and intricacies of programming and usage of different tools and platforms. We also extend our work from hand drawn designs to professional home blueprints and floor plans. We used fully convolutional network to extract walls from the professional floor plans with mean pixel accuracy of 97.3%. For hand-drawn designs, we were able to detect doors and windows with MAE of 0. Our wall segmentation method reported an MAE of only 1.2. [ABSTRACT FROM AUTHOR]

In Istanbul, which is one of the cities with the highest population growth in Turkey, changes have occurred in socio-economic conditions, public space requirements and supply-demand balance due to this increase. In the last 20 years, Shopping Malls and Life Centers (AVM) that provide socialization, culture-art activities and shopping opportunities are the most functional spaces that meet the public indoor space requirements on an urban scale in Istanbul to a certain extent. However, the recent construction of shopping mall investments, especially in a way that will create a surplus of demand regionally, has caused some shopping malls to turn into structures that lose their function and cannot meet the changing requirements. These idle buildings, which lost their function but continued their structural life, brought the concept of "Dead Shopping Mall" to the architectural literature. This study aims to get investors and decision-makers to think about the re-functioning of dead shopping malls in the public interest. The structural functions of dead AVMs that they are compatible with in terms of functional transformation due to reasons such as their location, structural and physical properties, dimensions are limited. According to the research carried out within the scope of this study, it has been determined that the number of examples of many dead shopping malls converted by foundation universities is gradually increasing. Although there are publications in the existing domestic literature on the transformation of dead shopping malls into various commercial functions, there have been no sources examining their transformation for universities. The study interprets this transformation with the method of a foundation university that pioneers the public transformation of dead shopping malls, the flow chart of original design steps with designer experiences, stain studies of floor plans of old and new functions, comparison of old-new interior and exterior building visuals and aims to contribute to the domestic literature in this sense. [ABSTRACT FROM AUTHOR]