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The traditional storage method of fire accident cases is mainly in the form of text, and it is difficult to effectively conduct comprehensive analysis due to the limited ability to display key information and fire knowledge. In this paper, a structured storage form of building fire cases was proposed based on knowledge graph, which can comprehensively describe and visualize the fire causes, the dynamic fire development process and evacuation process. It enables readers to get information and knowledge from building fire cases intuitively, and supports the comprehensive analysis for building fire prevention strategies. The knowledge graphs are constructed for two common building types (residential and public buildings), and have the capacity to reflect the dynamic development law of fires from ignition to spread in different buildings. Meanwhile, as the occupants' evacuation is the first concern when a fire occurs, the knowledge graphs also visualize the relationship among various conditions in the evacuation process. Different application scenarios are displayed in the paper, including case query, root-cause analysis and consequence forecasting, which shows the advantages and applicability of building fire knowledge graph. [ABSTRACT FROM AUTHOR]

In the countryside, where intensive rural development and rising property values have been observed since the late 1970s, the preservation and meaning of traditional dwellings have emerged as crucial considerations in shaping Hong Kong's countryside conservation policy. The focus of this paper is on the conservation of temples, as we are drawn to these structures not only for their architectural merit but also for their role as public buildings within the countryside. Consequently, their cultural significance is heavily influenced by the stakeholders they are associated with, distinguishing them from other types of dwellings. This paper examines the coastal landscape of South Lantau, which includes several villages with distinct traditions that have undergone significant transformations since the 1960s. Located at the southwest edge of Hong Kong, Lantau Island had a rural lifestyle that was relatively undisturbed before WWII because of the difficulty in accessing the island. However, in response to the large people influx from China's mainland after 1949, the Hong Kong government introduced the Lantau Development Plan in 1953, mainly to open up new sources of freshwater resources for Hong Kong Island. The construction of South Lantau Road in 1955 and Shek Pik Reservoir in 1957 gradually led to the decline of agricultural activities in South Lantau and the population exodus of local villagers, resulting in a rupture to regional traditions. In multilineage communities such as the villages on South Lantau, worship of a common deity provides a vital source of social bonding, particularly for an area long beset by typhoons, piracy and banditry. Local people pray for safety and prosperity through collective rituals and celebratory activities. Therefore, temples are not only religious establishments but also embody the sense of social solidarity among villagers on South Lantau. Through the case study of three rural villages on South Lantau, this paper examines how temples play an important role in the continuity of the communal network amid repercussions from the postwar disruption of traditional rural life. Significantly, this pilot study also draws attention to the functions of temples in their historical context. It emphasises the importance of recognising and re-evaluating these buildings for cultural enhancement as part of community engagement. This study provides valuable insights for future conservation efforts for religious buildings in the countryside. [ABSTRACT FROM AUTHOR]

Among all public buildings, on account of their educational purpose, school buildings have a major social responsibility. Therefore energy performance in this type of building is of great importance. The overall purpose of this research is to achieve a functional benchmarking, based on the real operation conditions of school buildings, by the exploitation of the results made public, through an intensive literature survey on energy consumptions in schools. The survey was made to gather data that is relative to energy consumption in school buildings, documented in the most diverse fields and units: global energy consumption values, electrical energy consumption; fuel consumption for heating, energy data consumption of schools expressed in annual cost per unit of heated/cooled surface area ($/m 2 ) or per unit of heated/cooled volume ($/m 3 ) or, finally, as the annual cost per student ($/student). The literature was analyzed to determine if a worldwide comparison among the published data could be established. The results suggest that when attempting to determine an energy benchmark some considerations should not be forgotten: standard indoor environmental conditions (IEC) for classrooms (set-point for indoor operative temperature of 20 °C in winter and 26 °C in summer as suggested in EN 15251:2007), electrical and heating consumption values should be kept separately, different education levels usually require different energy consumption values. A good way to normalize heating energy consumption is going through a climatic adjustment based on Heating Degree Days (HDD). For an impartial data comparison, based either on an operating rating or on a simulation carried out for reference conditions, benchmark reference values should be expressed in terms of billed energy data. [ABSTRACT FROM AUTHOR]

Objectives Comprehensive smokefree laws, as recommended by the WHO Framework Convention of Tobacco Control (WHO FCTC), are the most effective tool to protect the population from secondhand smoke (SHS) and to ensure healthy environments. Studies evaluating how laws govern SHS protection are scarce. This study assessed the level of protection from SHS of laws from countries belonging to the WHO European Region. Methods A new methodology system was developed to evaluate the smokefree legislation according to the principles provided by the WHO guidelines for the correct implementation of Article 8 of the FCTC. For each law, six main sectors and 28 facilities were evaluated. Results Overall 68 laws from 48 countries from the WHO European Region were reviewed. 'Education' and 'Public transport' were the most protected sectors from SHS. Many WHO European laws do not provide protection from SHS across all public sectors. For example, 48.5% of general health facilities and 71.2% of restaurants are unprotected from SHS. The level of protection provided in the 28 facilities studied was low; many WHO European laws still allow smoking under certain conditions, permitting smoking in designated and/or ventilated areas. Conclusions Nine years after the adoption of the WHO FCTC there are still legal formulas in which smoking is allowed in several facilities, through the inclusion of separated areas, ventilated areas and other conditions. Tobacco control efforts still face the challenge of eradicating the legal clauses that prevent 100% smokefree environments. [ABSTRACT FROM AUTHOR]

Since people tend to spend more and more time visiting museums, more accurate requirements are needed for the indoor environmental conditions of these confined spaces where two primary requisites coincide in defining their optimal indoor microclimate: the need for the appropriate artwork preservation and suitable levels of indoor comfort conditions for people visiting the exhibition buildings and/or working there. Regrettably, people and artwork requirements are sometimes characterized by different reference limits of the environmental parameters that, not rarely, could potentially conflict. Another important point to consider is that museums hosted by heritage buildings (particularly in Mediterranean climates, as is often the case in Italy) are often not equipped with climatization systems because of difficulty in installing generally bulky equipment such as HVAC systems. This circumstance represents another important limit for achieving suitable conditions for the two requisites. In addition, the recent pandemic-related occurrences are pushing technicians and designers to rethink the criteria for controlling the microclimate of public buildings, and museums among them. In this paper, this issue is addressed by reviewing current regulations, standards, and handbooks (and by means of a real case example related to the Italian context) in order to ascertain whether such documentation could facilitate the development of effective rules/guidelines for proper management of indoor parameters in museums. [ABSTRACT FROM AUTHOR]

Energy efficiency in buildings has a central role to play in reaching the climate neutrality goal set by the European Green Deal. With detailed knowledge of their building stock and the profile of their occupants, regional and local authorities can forge an important link between financiers, industry professionals and homeowners to ensure the successful deployment of financial schemes that support the uptake of energy efficiency upgrades. This paper provides a first assessment of the role of regional and local authorities by reviewing relevant initiatives and programmes on energy efficiency. Based on a questionnaire completed for more than 150 schemes, it explores how European municipalities and regions stimulate energy upgrades in residential, commercial and public buildings through public financial support. It is found that 60% of the examined schemes are offered in the form of grants and subsidies, and 45% of them targeted residential upgrades. The use of EU cohesion policy funds in supporting regional schemes, and promotion of energy efficiency investments at local level through the European Covenant of Mayors initiative are also explored. In spite of possible resource limitations at this level of governance, regional and local authorities are in a good position to utilise European structural or research funds to develop financial schemes, as standalone programmes or blended with national ones, thus providing additional support and funds for deep renovations. The results suggest that energy efficiency in buildings has become an important part of local and regional strategies in several European countries, but could be further enhanced. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the impact of the indoor classroom environment on students' learning efficiency. The research is based on a classroom smart monitoring and a questionnaire about the students' assessment of the comfort conditions and learning efficiency. Multisensor devices are used to measure the indoor temperature, relative humidity, and CO2 concentration at the students' desks. Data analysis concerned an investigation of the spatial and temporal variation of the comfort parameters and their correlation with students' assessment of comfort conditions and learning efficiency. The results show a significant spatial variation in the indoor comfort conditions, particularly for temperature and CO2 concentration. The indoor temperature could exceed by up to 5 °C, the temperature threshold limits value in France's public buildings. At the beginning of the class, the learning efficiency correlates well with the students' assessment of comfort conditions. At the end of the class, the results show a weak correlation with both recorded comfort parameters and the students' assessment of the indoor conditions. The results indicate a decrease in learning efficiency during the class. However, students do not mainly attribute this decrease to the degradation in indoor conditions. [ABSTRACT FROM AUTHOR]

The efficient integration of distributed energy resources (DERs) in buildings is a challenge that can be addressed through the deployment of multienergy microgrids (MGs). In this context, the Interreg SUDOE project IMPROVEMENT was launched at the end of the year 2019 with the aim of developing efficient solutions allowing public buildings with critical loads to be turned into net-zero-energy buildings (nZEBs). The work presented in this paper deals with the development of a predictive energy management system (PEMS) for the management of thermal resources and users' thermal comfort in public buildings. Optimization-based/optimization-free model predictive control (MPC) algorithms are presented and validated in simulations using data collected in a public building equipped with a multienergy MG. Models of the thermal MG components were developed. The strategy currently used in the building relies on proportional–integral–derivative (PID) and rule-based (RB) controllers. The interconnection between the thermal part and the electrical part of the building-integrated MG is managed by taking advantage of the solar photovoltaic (PV) power generation surplus. The optimization-based MPC EMS has the best performance but is rather computationally expensive. The optimization-free MPC EMS is slightly less efficient but has a significantly reduced computational cost, making it the best solution for in situ implementation. [ABSTRACT FROM AUTHOR]

The energy consumption from the building sector accounts for more than 21% of the total in China, where the energy-use intensity of public buildings could reach 3 times that of residential buildings. Energy efficiency improvement (EEI) is considered to be one of the most rapid and cost-effective means for the building sector to achieve carbon neutrality. The Chinese government has carried out a series of policy tool exploration to promote the energy efficiency improvement efforts by public building owners since over a decade ago, but encountered various problems and obstacles. This paper investigated and compared the current status challenges, and problems in the implementation of EEI policy tools in China and developed countries through literature review, field investigations and interviews with experts and stakeholders, and finally also put forward some possible coping strategies for Chinese government. Results indicated that energy grading and labeling, energy benchmarking, carbon-emission trading and energy-consumption quota management were the main 4 EEI policy tools designed based on measured energy consumption data, where the first 3 ones had been widely used over the developed countries but the last one was unique to China. Difficulty in large-scale collection of building energy-consumption data, lack of scientific methods on building energy-use level evaluation, limited data application and feedback, undesirable association between stakeholders, etc., were the main obstacles for achieving the long-term effectiveness of the EEI policy tools. Cooperating with energy supply enterprises to collect data, establishing an effective energy grading system and a closed loop of policy implementation, exploring a new model of building carbon-emission trading and a differential pricing mechanism, combined with innovative financial supports, might be the solutions. The main contribution of this study is that a comprehensive investigation and analysis on the current development status, obstacles, and possible solutions of the public building EEI policy tools in China was carried out, which is expected to provide a reference for the government of China and even the world. [ABSTRACT FROM AUTHOR]

Generally, the central air conditioners are centralized in a refrigeration room in public buildings. The proportion of energy consumption of the refrigeration room is about 40% of entire building. This paper aims to propose an energy plus and self-designed simulator to reduce the energy consumption of a large electronic factory in Zhuhai City, Guangdong province, China. In this paper, the real data collected from the electronic factory in February and the group control method used in the refrigeration room based on the kernel ridge regression algorithm. The correctness of the kernel ridge regression algorithm was verified with the experimental results. Compared to traditional PID control method, the kernel ridge regression algorithm could dynamically adjust those parameters, such as temperature and frequency to match the high efficiency zone of each device. The overall average COP of the system is increased from 4.17 to 7.04. The electricity of the refrigeration room could save 64 MWh with the cooling load forecast error being below 7% in February. The power consumption is expected to reduce by 8.2% and 562.3 MWh in 2022. [ABSTRACT FROM AUTHOR]

According to the latest energy efficiency European directive (EED 2023/1791/EU), the expected energy renovation rate of at least 3% of the buildings' floor area each year towards nearly zero-energy buildings (nZEBs) is extended to include public buildings not only of the central government (as per the first EED 2012/27/EU) but also of regional and local authorities. This poses a great challenge, especially for Municipalities that often manage large building stocks with high energy demands. In response to this challenge, this paper presents the application of the so-called "typology approach" for conducting public buildings' energy renovation plans at the local level. A computational survey is initially introduced to decide the optimal set of building-stock clustering criteria among all possible combinations, involving the minimization of the RMSE index regarding the primary energy consumption of each building. For a representative building from each identified typology, the key performance indicators (KPIs) are computed for alternative energy-upgrading scenarios. Exploiting the IMPULSE Interreg-MED project tools, the KPIs from each representative building are at first extrapolated to all buildings of the examined stock and, finally, a gradual energy renovation plan is automatically produced based on user-defined decision parameters including the required annual renovation rate. The methodology is applied for the case of the Municipality of Hersonissos in Greece. For the specific 44-buildings' stock it was found that the optimal clustering set included four criteria, building use, construction year, heating, and a cooling system, leading to 15 building typologies. Finally, assuming a 7% renovation rate per year, a 12-year gradual renovation (nZEB transformation) plan is obtained foreseeing an 85% CO2 emissions' reduction. [ABSTRACT FROM AUTHOR]

Excavations at Ashdod‐Yam exposed a fortification system that features a massive mudbrick wall with large earthen ramparts laid on either side. This fortified horseshoe‐shaped enclosure once surrounded what was likely a human‐made harbor and an adjacent acropolis with complex earthen architecture, constructed and active during Iron Age IIB–C (eighth–seventh centuries B.C.E.). These Iron Age public structures are at the center of the current research. In this paper, we present the geoarchaeological analyses of Ashdod‐Yam's earthen architecture. We applied a multidisciplinary methodology to new evidence for mudbrick manufacture with the goal of understanding the relationship between governing bodies and craftsmen. The analyses combine X‐ray fluorescence, loss on ignition, environmental scanning electron microscopy, and thin‐section petrography to investigate raw material procurement, manufacturing choices, and labor organization at Ashdod‐Yam during Iron IIB–C. Construction techniques and the standardization of the mudbrick recipe point to a local enterprise regarding the site's public earthen architecture. Furthermore, the degree of labor organization must have been closely observed and supervised by a central political power. Thus, it is argued here that construction and maintenance of the site was carried out by the kingdom of Ashdod, either as a part of its own local initiative or on behalf of the Neo‐Assyrian empire. [ABSTRACT FROM AUTHOR]

Room usage semantics in models of large indoor environments such as public buildings and business complex are critical in many practical applications, such as health and safety regulations, compliance, and emergency response. Existing models such as IndoorGML have very limited semantic information at room level, and it remains difficult to capture semantic knowledge of rooms in an efficient way. In this paper, we formulate the task of generating rooms usage semantics as a special case of room classification problems. Although methods for room classification tasks have been developed in the field of social robotics studies and indoor maps, they do not deal with room usage and occupancy aspects of semantics, and they ignore the value of furniture objects in understanding room usage. We propose a method for generating room usage semantics based on the spatial configuration of room objects (e.g., furniture, walls, windows, doors). This method uses deep learning architecture to support a room usage classifier that can learn spatial configuration features directly from semantically labelled point cloud (SLPC) data that represent room scenes with furniture objects in place. We experimentally assessed the capacity of our method in classifying rooms in office buildings using the Stanford 3D (S3DIS) dataset. The results showed that our method was able to achieve an overall accuracy of 91% on top-level room categories (e.g., offices, conference rooms, lounges, storage) and above 97% accuracy in recognizing offices and conference rooms. We further show that our classifier can distinguish fine-grained categories of of offices and conference rooms such as shared offices, single-occupancy offices, large conference rooms, and small conference rooms, with comparable intelligence to human coders. In general, our method performs better on rooms with a richer variety of objects than on rooms with few or no furniture objects. [ABSTRACT FROM AUTHOR]

This research provides a comprehensive exploration of energy efficiency dynamics in non-residential public buildings such as schools, swimming pools, hospitals, and museums. Recognizing the distinct energy consumption patterns of each building type, the study accentuates the unique challenges they present, with a particular focus on the continuous and intensive energy demands of hospitals and the unparalleled energy needs of swimming pools. Through an extensive review of various case studies, the research unveils prevailing energy consumption trends, highlighting the role of metrics in assessing energy efficiency and the inherent challenges these metrics face in ensuring uniformity and direct comparability. A core element of this analysis emphasizes the dual nature of technical retrofitting, categorizing interventions into passive and active measures. The research delves into the sustainability imperatives of energy interventions, exploring the economic motivations underpinning retrofit decisions, and the intricate relationship between advanced technological solutions and the behavioral tendencies of building operators and users. Additionally, the study uncovers the influence of external determinants such as climatic factors and government policies in shaping energy consumption in public buildings. In synthesizing these findings, the paper offers insightful recommendations, emphasizing the need for an integrated approach that harmonizes technological innovations with informed operational habits, aiming to optimize energy efficiency in public non-residential buildings. [ABSTRACT FROM AUTHOR]

Air-supported structures are widely used as public buildings. Air-supported structures are soft and most traditional fire-fighting installations cannot be used in them. Existing design specifications only specify the fire resistance of the materials to be used for air-supported structures and there is no fire resistance design method for air-supported structures. The destruction process of air-supported structures can be divided into three stages: pre-fracture, leakage, and collapse. Theorical and numerical models were used to research the time span of all those stages. A framework to estimate the collapse and evacuation time was proposed in this paper. Air-supported structures with different spans were researched in this paper, and we found that the height of a structure has a significant influence on its fire resistance. The evacuation time increased by more than 52 times when the structure's span increased from 20 m to 80 m. The pre-fracture stage contributed to more than 90% of the evacuation time when the span of structure was larger than 80 m. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) can provide important flexibility to the integration of local energy generation in buildings. Although most studies considering the integration of EVs and buildings are focused on residential buildings, the number of publications regarding large buildings, in particular, public buildings (PBs), has increased. However, the quantity of studies regarding the integration of EVs and PBs is still limited. Additionally, there are no review studies approaching the integration of EVs and buildings in one single framework. In this sense, this review aims to address the challenges and trends associated with optimizing the charging of EVs in PBs by conducting a systematic review of the existing literature. As contributions, this work develops a review that approaches the integration of EVs and PBs using multiple strategies and structures, presents an integrated picture of the technical and economic constraints, and addresses the future trends and research perspectives related to the subject. Through the use of an open-access search engine (LENS), a cluster of 743 publications was analyzed using two strings and a timeframe restriction. The most important contributions regarding optimization strategies and their evolution are presented, followed by a comparison of the findings with other review papers. As key findings, technical and economic constraints are identified (uncertainties of driving behavior and local generation, battery degradation, "injection tariffs", etc.), as are future trends and perspectives (local generation legislation, incentives for purchasing EVs, energy communities, etc.). [ABSTRACT FROM AUTHOR]

The Renovation Wave for Europe highlighted the role of the public building stock for which Directive 2012/27/EU has set an annual renewal rate of 3%, which should rise to reach the goal of decarbonization by 2050. In this paper, the energy retrofit of an educational building—at the academic level—in Southern Italy was investigated. The aim was to evaluate the incentive share, which could accelerate the energy efficiency process, to achieve a cost-effective nZEB. The results show that the highest incentive rate is required for interventions on the opaque building envelope, which are also those that allow the least energy savings. An incentive rate of about 45% for the energy efficiency of the transparent envelope is necessary to reduce the payback time by about 7 years. The efficiency of the plants and the installation of a PV system are energetically and economically convenient even without forms of economic incentive. Finally, if the building is brought to high energy standards—a primary energy saving of 46% and energy class A3—an incentive rate of 40% is required to repay the intervention in about 10 years. [ABSTRACT FROM AUTHOR]

At present, China is in a period of rapid urbanization, and the concept of green structure is getting more and more attention. Green structures can solve asset utilization and ecological problems brought about by rapid urbanization. Therefore, green structure has become the only way for the development of China's construction industry. This paper aims to study the feasibility analysis of new green building technology measures. The related concepts of green building, the analytic hierarchy process, and the meaning of life cycle cost are proposed. The main assessment bottom lines include engineering, environmental, social, and economic bottom lines. From the application examples of green building technology in the starting area of Guangzhou International Financial City, it can be seen that, based on the green building technology proposed in this paper, it is necessary to sort out specific technologies and practices suitable for the actual application of the project in a specific project. Then, the applicability and incremental cost of each technology can be analyzed, and finally, a green building technology system suitable for specific project applications is formed. The experimental results show that compared with residential buildings, the increase of public buildings is 338 million yuan, and the increase of nonassigned parts is about 9.84 million yuan. [ABSTRACT FROM AUTHOR]

Indoor navigation has been studied for many years, but it still has many limitations. In current navigation, pedestrians need to tell navigation systems the destination, because it is one of the preconditions for path planning. However, in some indoor cases, pedestrians cannot specify a destination because they have no information about where it is or even cannot be sure if there is a desired one. We believe that determining a service area is a possible way to handle such cases. For example, a service area that can be reached within a 2-min walk. In this paper, we propose an indoor service area determination approach for pedestrian navigation path planning. We demonstrate this approach in a shopping mall with multi-floors. The results show that it can successfully compute the reachable spaces and thereby helping people to select and arrive at the most appropriate destination. This approach is also useful for other indoor navigation applications within public buildings like offices, airports, theaters, hospitals, and museums where pedestrians would like to make a choice between multiple facilities of the same type, such as printers, registration desks, ATMs, AED, garbage bins, even exits. [ABSTRACT FROM AUTHOR]

Ever since European Directive 2012/27/EU, particular attention has been focused on the improvement of the energy efficiency of the public building stock. According to the directive, local public authorities, regions and municipalities, are expected to develop and implement energy efficiency retrofitting plans for their public building stocks. While conducting such plans, important challenges are raised mainly related to data collection and the manipulation of key performance indicators (KPIs) for many buildings. The present paper deals with the aforementioned challenges through (a) the evaluation of freely available tools developed in the framework of Mediterranean territorial cooperation projects, with respect to the main pillars of energy efficiency planning, and (b) the introduction of a stepwise methodology using selected tools toward a reliable energy efficiency plan extending from the classification of the building stock to the prioritization of projects in terms of a gradual renovation plan based on energy and cost criteria. The methodology is applied for a case study in Greece, which refers to 10 public buildings of the Municipality of Aigialeia in Greece. A reliable renovation plan is developed, taking into account the municipal authority's directions in a specialized decision-making scheme. It is concluded that the suggested methodology is very practical for planning purposes, while for the case studied, a 6-year gradual renovation plan is emerged until a deep retrofit of all buildings, associated with an estimated primary energy saving and CO2 emissions avoidance of more than 1850 MWh and 400 tns, respectively, with a total investment of about EUR 3 million. [ABSTRACT FROM AUTHOR]

This paper presents an overview of emerging research at the Manifest Data Lab a collective of artists and climate scientists who employ climate data experimentally in public settings. We discuss one of our projects The Carbon Chronicles, a reverse-engineered climate data set, projected on prominent public buildings in London during the period of COP26. Our approach examines the potential of climate data visualisations to operate as a public form that surface issues of climate justice and historic responsibilities. We report on the project's methodological framing, production and associated artistic strategies. [ABSTRACT FROM AUTHOR]

For large public buildings, a siphon drainage system facilitates good on building safety and operation. However, conventional siphon drainage systems are designed based on full pipe flow, which is suitable only under specific criteria and cannot assess the detailed flow characteristics from priming to the entire siphon formation process. In this paper, a full-size experimental platform for a single outlet siphon drainage system is proposed to research the flow characteristics of the siphon drainage. Then, a full-scale numerical model of a siphon drainage system is established and the process of the siphon drainage is simulated by the volume of fluid model. The accuracy of the numerical model is verified by comparing its results with the experimental data. Moreover, a sensitivity analysis of different pipeline structure parameters on siphon priming time is presented, which shows that a larger length and diameter of the suspension pipe and a larger riser pipe diameter prolong the siphon formation time. Finally, theoretical formulas are derived to describe the mathematical relationships between the suspension pipe length and maximum displacement and the suspension pipe length and siphon priming time. [ABSTRACT FROM AUTHOR]

The study was carried out on a group of 85 public buildings, which differed in type of use, construction technology and heating systems. From the collected data, a set of qualitative and quantitative variables characterizing them in terms of heat demand was extracted. In this paper, the authors undertook to test the suitability of a model based on rough set theory (RST), which allows the analysis of imprecise, general and uncertain data. To obtain input data for the RST model in quantitative form, the authors used an alternative approach, which is a method based on the thermal properties of buildings. The quality of the predictive model was evaluated based on the following indicators, such as the coefficient of determination (R2), the mean bias error (MBE), the coefficient of variance of the root mean square error (CV RMSE) and the mean absolute percentage error (MAPE), which are accepted as statistical calibration standards by ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers). A quality-acceptable predictive model must meet the calibration conditions: MBE ±5%, CV RMSE < 15% and R2 > 0.75. For the analyzed RST model, the following values of evaluation indicators were obtained: MBE = −1.1%, CV RMSE = 11.8% and R2 = 0.91. The evaluation results obtained gave rise to the conclusion that the method used, which is based on a limited amount of data describing buildings, gives good results in estimating the unit rate of energy demand for heating. [ABSTRACT FROM AUTHOR]

This paper analyses the tensions, contradictions and overlaps between supportive migration infrastructures and the generalised anti‐migrant atmosphere created by the UK government. It utilises infrastructural perspectives to show how the hostile environment has become an everyday reality that forced migrants have to constantly endure and navigate. As an everyday reality, the hostile environment inheres and comes to life in various settings, spaces, infrastructures and affects. Specifically, this paper documents how government buildings, urban landscapes and houses provided to forced migrants are all conduits through which anti‐migrant hostility is encountered and reproduced. It also demonstrates how the hostile environment permeates infrastructures designed to provide support to forced migrants, creating divisions between those providing care and those being cared for, thus recreating affective and interpersonal borders. At the same time, the paper shows how anti‐migrant infrastructures are contested and repurposed by activists, demonstrating the processual and always in‐the‐making nature of infrastructures. [ABSTRACT FROM AUTHOR]

• ANN, CART, and RF regression trees have shown the potential in modeling energy cost. • Three different strategies regarding variable selection were tested and compared. • Machine learning and Boruta method have produced the highest accuracy of prediction. • The model has extracted heating and occupational data as the most important. • The created model could be used to assess the concept of smart buildings and cities. The paper deals with modeling the cost of energy consumed in public buildings by leveraging three machine learning methods: artificial neural networks, CART, and random forest regression trees. Energy consumption is one of the major issues in global and national policies, therefore scientific efforts in creating prediction models of energy consumption and cost are highly important. One of the largest energy consumers in every state is its public sector, consisting of educational, health, public administration, military, and other types of public buildings. Recent technologies based on sensor networks and Big data platforms enable collection of large amounts of data that could be used to analyze energy consumption and cost. A real data from Croatian public sector is used in this paper including a large number of constructional, energetic, occupational, climate and other attributes. The algorithms for data pre-processing and modeling by optimizing parameters are suggested. Three strategies were tested: (1) with all available variables, (2) with a filter-based variable selection, and (3) with a wrapper-based variable selection which integrates Boruta algorithm and random forest. Prediction models of energy cost are created using two approaches: (a) comparative usage of artificial neural networks and two types of regression trees, CART and random forest, and (b) integration of RF-Boruta variable selection and machine learning methods for prediction. A cross-validation procedure was used to optimize the artificial neural network and regression tree topology, as well to select the most appropriate activation function. Along with creating a prediction model, the aim of the paper was also to extract the relevant predictors of energy cost in public buildings which are important in planning the construction or renovation of buildings. The results have shown that the second approach which integrates machine learning with Boruta method, where the random forest algorithm is used for both variable reduction and prediction modeling, has produced a higher accuracy of prediction than the individual usage of three machine learning methods. Such findings confirm the potential of hybrid machine learning methods which are suggested in previous research, but in favor of random forest method over CART and artificial neural networks. Regarding the variable selection, the model has extracted heating and occupational data as the most important, followed by constructional, cooling, electricity, and lighting attributes. The model could be implemented in public buildings information systems and their IoT networks within the concept of smart buildings and smart cities. [ABSTRACT FROM AUTHOR]

Data‐based improvement of energy consumption and indoor climate in public buildings – Literature study with focus on the success of approaches Reducing the energy consumption of public buildings is particularly important for achieving climate targets because of the exemplary role they play. A comfortable indoor climate and clean indoor air are crucial for the well‐being and health of building users. Rapid developments in sensors as well as in the fields of data analysis and simulation have led to increasing attempts to achieve improvements in energy consumption and indoor climate using data‐based approaches. The momentum has increased so much that it is becoming increasingly difficult to keep track of which approaches are applied in which situations and with what success. This paper presents a literature study that addresses this issue. For the study, 91 peer‐reviewed articles published between 2014 and 2022 were examined. It was found that the importance of indoor climate in data‐based approaches is increasing compared to that of energy consumption, building‐model‐based simulations are used with increasing frequency, articles deal with very specific issues, and an end‐to‐end consideration that also takes building users into account is usually omitted. [ABSTRACT FROM AUTHOR]

• A pre-1919 primary school with single glazing in Edinburgh has an oversizing of its space heating system of 32 % at design conditions. • Supply temperature can be operated below 70 °C all year round. • Supply temperatures can be reduced below 55 °C all year-round during daytime. As part of the decarbonization of its existing building stock the UK needs to replace gas boilers with heat pumps and low-temperature heat networks. Both technologies are efficient at supply temperatures of 55 °C, with a maximum of 70 °C for heat networks, when existing systems have been designed to operate at 82 °C. Most space heating systems are expected oversized and operate most of the year in part-load, which facilitate the temperature reduction, but little is known about the degree of oversizing. This paper uses the case study of a pre-1919 school in Edinburgh to evaluate the true oversizing of its heating system and its consequences on minimum supply temperatures. This building is still equipped with single glazing and is therefore a worst-case scenario. An oversizing of 32 % was estimated which enables the use of a supply temperature below 70 °C all year round. Moreover, the supply temperature can be kept below 55 °C all year round during daytime due to internal heat gains. In conclusion, this building shows a nascent readiness for low-temperature heat. It would benefit from energy efficiency measures such as double-glazed windows, but this is not pre-requisite. Those results are important for the heat network industry when sizing their systems, but also energy and asset managers when they schedule renovation programmes to have their buildings low-temperature-ready. [ABSTRACT FROM AUTHOR]

As the major power consumer in buildings, Heating, ventilation and air conditioning (HVAC) systems can significantly contribute to the economical operation of the power system during the peak periods in summer or winter, by flexibly responding to the grid demands. Indoor air temperature set-point resetting is a typical passive demand response (DR) control strategy that have potentials to be widely implemented by inverter air conditioners in residential buildings. However, in the existing small and medium-size public buildings, the compressor motor of HVAC systems mostly does not allow for stepless speed changes. This means that the indoor temperature set-point resetting strategy may results in frequent on/off switching of the chiller plant, leading to a compromised lifespan. Although rooftop photovoltaic systems (PVs) are expected to be widely adopted in new buildings, their potential for peak load shaving or valley load filling has received limited investigation. This study proposes a grey-box model-based demand side management (DSM) method for variable air volume systems (VAVs) and rooftop PVs in public buildings. The DSM method utilizes the particle swarm optimization (PSO) algorithm to determine optimal indoor air temperature and/or evaporator outlet water temperature set-point schedules for the VAVs, as well as optimal charging/discharging schedules for the storage battery of rooftop PVs. This approach aims to reduce the peak power demands of the integrated system without causing severe thermal discomfort, increasing chiller mechanical costs (refers to frequent on/off switching of the chiller plant in this paper), or overcharging/over-discharging of storage batteries. The results of case studies demonstrate that the strategy of co-resetting indoor air temperature – evaporator outlet water temperature set-points outperforms the indoor air temperature set-point resetting strategy in terms of both peak power demands reduction and mechanical cost saving when applied to the VAVs in low performance buildings. In comparison, for the VAVs installed in normal buildings, both the strategies yield significant decreases in peak power demands and mechanical cost by fully utilizing the thermal capacity of the building internal thermal mass. Furthermore, by implementing the DSM method for rooftop PVs, the integrated system can achieve zero or near-zero net power demands during the DR periods. The proposed DSM method can also be utilized in valley load filling programs to facilitate the accommodation of renewable energy. • A grey-box model of VAVs is developed and integrated with the building RC model. • A grey-box model-based DSM method is proposed for VAVs and rooftop PVs in buildings. • Impact of internal mass on peak shaving is quantified using the integrated model. • PSO is used to optimize the operating schedules of VAVs and rooftop PVs. • Tradeoff among peak shaving, thermal comfort and mechanical cost saving is realized. [ABSTRACT FROM AUTHOR]

Kindergartens are probably the very first public buildings we actively use in our lives. Therefore, they can be considered as the physical structures that are providing for the very important educational and social function. Additionally, they can also be considered as the specific learning tool for future generations where they can encounter the ideas of green and energy-efficient buildings. One of the results of the research project "Energy efficiency in public buildings" has been formulated through the development of Serbian National Typology of Kindergartens which was conceived as a specific tool that can be used for improving this portion of building stock. The paper presents the methodology for identification of typical kindergarten buildings, covering various construction periods, building sizes and illustrates the type of analysis performed for model representatives. The potential for energy upgrades covering physical structure, installed technological systems, as well as expected impact on energy performance, has been estimated. The study presents results based on the analysis of the data derived from the National Typology, stressing out that energy retrofits of large and medium-sized kindergartens built during the 1970s and 1980s should be the primary focus of refurbishment activities. Accounting for almost 60% of total buildings and 69.59% of heated area, they are responsible for 75.97% of energy demands. Estimated energy savings of more than 60% indicate the effectiveness of their retrofit. The paper also presents the potential uses of National Typology as a retrofit tool on various scales, from single-building considerations to a strategic approach at the national level. [ABSTRACT FROM AUTHOR]

Nowadays everyone should be aware of the importance of reducing CO2 emissions which produce the greenhouse effect. In the field of construction, several options are proposed to reach nearly-Zero Energy Building (nZEB) standards. Obviously, before undertaking a modification in any part of a building focused on improving the energy performance, it is generally better to carry out simulations to evaluate its effectiveness. Using Artificial Neural Networks (ANNs) allows a digital twin of the building to be obtained for specific characteristics without using very expensive software. This can simulate the effect of a single or combined intervention on a particular floor or an event on the remaining floors. In this paper, an example has been developed based on ANN. The results show a reasonable correlation between the real data of the Operative Temperature with the Energy Consumption and their estimates obtained through an ANN model, trained using an hourly basis, on each of the floors of an office building. This model confirms it is possible to obtain simulations in existing public buildings with an acceptable degree of precision and without laborious modelling, which would make it easier to achieve the nZEB target, especially in existing public office buildings. [ABSTRACT FROM AUTHOR]

The clinical significance of this paper is the finding of occupational trichloramine and endotoxin exposure in air in swimming pool facilities in relation to adverse health effects. This is of particular importance in adventure swimming pools where trichloramine exposure is expected to be high, to further emphasize the importance of occupational exposure limits to protect workers' health. Objective: To study occupational exposure totrichloramine and endotoxins in air at adventure and rehabilitation swimming pool facilities from an adverse health effects perspective. Methods: Air concentrations of trichloramine and endotoxins were measured in five adventure and 10 rehabilitation facilities. Respiratory and ocular symptoms were self-reported, and spirometry and fraction of exhaled nitric oxide (FE no ) were measured. Results: Compared to rehabilitation facilities, the mean trichloramine concentrations in the adventure facilities were higher, both personal (80 μg/m3 (n   =  41) vs 19 μg/m3 (n  = 21)) and stationary (183 μg/m3 (n  = 51) vs 23 μg/m3 (n  = 32)), with higher frequency of ocular and respiratory symptoms. Low stationary endotoxin levels (<0.64 to 25 EU/m3) were found, compared to the reference value (90 EU/m3). Conclusions: Higher trichloramine concentrations in air and more ocular and respiratory symptoms in adventure facilities call for adequate occupational exposure limits. [ABSTRACT FROM AUTHOR]

Real time prediction of energy consumption is the basis of energy conservation and emission reduction. Aiming at the problems of large prediction error and poor effect, a real-time prediction method of energy consumption of geothermal system of public buildings based on wavelet neural network is proposed. Firstly, the energy consumption of geothermal system in public buildings is analyzed, the wavelet neural network is designed, the neural network is optimized and solved by genetic algorithm, and the necessity of constructing the real-time prediction model of energy consumption based on wavelet neural network is established. Then it introduces the basic principle of model establishment, wavelet analysis, and shows the role of wavelet analysis in prediction model. Finally, based on the distribution structure of public buildings, this paper analyzes the energy consumption system of geothermal system, constructs the energy consumption prediction method, analyzes the overall temperature regulation energy consumption prediction principle of building geothermal system, and realizes the real-time prediction of energy consumption of geothermal system of public buildings. The experimental results show that the energy consumption real-time prediction results of the designed method are basically similar to the actual prediction values, and the prediction efficiency is high, which can effectively reduce the energy consumption of the geothermal system of public buildings. [ABSTRACT FROM AUTHOR]

This paper presents a scalable IoT architecture based on the edge–fog–cloud paradigm for monitoring the Indoor Environmental Quality (IEQ) parameters in public buildings. Nowadays, IEQ monitoring systems are becoming important for several reasons: (1) to ensure that temperature and humidity conditions are adequate, improving the comfort and productivity of the occupants; (2) to introduce actions to reduce energy consumption, contributing to achieving the Sustainable Development Goals (SDG); and (3) to guarantee the quality of the air—a key concern due to the COVID-19 worldwide pandemic. Two kinds of nodes compose the proposed architecture; these are the so-called: (1) smart IEQ sensor nodes, responsible for acquiring indoor environmental measures locally, and (2) the IEQ concentrators, responsible for collecting the data from smart sensor nodes distributed along the facilities. The IEQ concentrators are also responsible for configuring the acquisition system locally, logging the acquired local data, analyzing the information, and connecting to cloud applications. The presented architecture has been designed using low-cost open-source hardware and software—specifically, single board computers and microcontrollers such as Raspberry Pis and Arduino boards. WiFi and TCP/IP communication technologies were selected, since they are typically available in corporative buildings, benefiting from already available communication infrastructures. The application layer was implemented with MQTT. A prototype was built and deployed at the Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), using the existing network infrastructure. This prototype allowed for collecting data within different academic scenarios. Finally, a smart sensor node was designed including low-cost sensors to measure temperature, humidity, eCO2, and VOC. [ABSTRACT FROM AUTHOR]

The vision-aided pedestrian dead reckoning (PDR) systems have become increasingly popular, thanks to the ubiquitous mobile phone embedded with several sensors. This is particularly important for indoor use, where other indoor positioning technologies require additional installation or body attachment of specific sensors. This paper proposes and develops a novel 3-D passive vision-aided PDR system that uses multiple surveillance cameras and smartphone-based PDR. The proposed system can continuously track users’ movement on different floors by integrating results of inertial navigation and Faster Region-Based Convolutional Neutral Network (Faster R-CNN)-based real-time pedestrian detection, while utilizing existing camera locations and embedded barometers to provide floor/height information to identify user positions in 3-D space. This novel system provides a relatively low-cost and user-friendly solution, which requires no modifications to currently available mobile devices and also the existing indoor infrastructures at many public buildings for the purpose of 3-D indoor positioning. This paper shows the case of testing the prototype in a four-floor building, where it can provide the horizontal accuracy of 0.16 m and the vertical accuracy of 0.5 m. This level of accuracy is even better than required accuracy targeted by several emergency services, including the Federal Communications Commission (FCC). This system is developed for both Android and iOS-running devices. [ABSTRACT FROM AUTHOR]

The seismic assessment of the vulnerability of existing public structures, especially school buildings, is a crucial issue in seismic prone countries. Recently, several national and regional programs and activities have focussed on the mitigation of Italian public buildings. They promote the scheduling of public buildings' structural safety assessment and, when needed, the design and execution of strengthening interventions. Nevertheless, the three strong earthquakes that occurred in the last decade in Italy, Abruzzo (2009), Emilia (2012), and Central Italy (2016), confirmed the vulnerability of school buildings and the social importance of their quick re-opening after a damaging earthquake. In the present paper, the activities carried out on 1514 school building structures in the aftermath of the 2016 Central Italy earthquake sequence are reported and analysed. According to survey data collected by post-earthquake usability inspections, the paper analyses the school buildings characteristics, damage level and extent to structural and non-structural components as well as the correlation between seismic intensity and observed damage. [ABSTRACT FROM AUTHOR]

This paper proposes a method to assess the financial attractiveness provided by adding a Battery Energy Storage System (BESS) in distributed photovoltaic (PV) generation on public buildings in Brazil. The method is applicable to prosumer units (PU) connected on the medium voltage grid operating under time-based electricity tariffs. The BESS primary objective was to achieve optimal reductions in electric energy expenses through effective energy arbitrage mechanisms. The procedural steps of the methodology begin with an analysis encompassing assessment of solar resource, PU consumption profile, and BESS sizing and operation. Subsequently, steps entail contracted power optimization, PU net-metering analysis, and evaluation of BESS impacts on electric energy expenses. Lastly, a regulatory and economic analysis is conducted incorporation considerations on BESS taxation, behind-the-meter regulations, and a sensitivity assessment extending to the 2030 outlook. By 2050, it is anticipated that PV generation will surpass hydropower, becoming the predominant component of Brazil's energy mix. This shift is expected to create an increased need for solutions, notably storage systems, capable of meeting flexibility requirements and maintaining grid resilience. The results suggest that the financial viability of incorporating BESS becomes favourable when the battery cost is below 365 $/kWh. In approximately 50% of the Brazilian territory, prevailing economic conditions support the adoption of BESS. Nationwide feasibility of integration is anticipated for the year 2027. It was observed that government policies to exempt BESS taxation, even if temporary, would be extremely interesting to promote the widespread adoption of this technology. The 2030 outlook of the transition to these benign renewable energy technologies is already in place, and will dominate the energy mix. [ABSTRACT FROM AUTHOR]

Indoor localization is essential for robotic navigation by using different sensors on board. Specifically, visual localization with a single camera is a great challenge in highly symmetric environments (e.g. offices, hospitals or residences), where appearance patterns are repetitive and captures from different locations provide very similar images. To overcome this issue, in this paper, we present a method that integrates multisensory information from an RGB-D camera, a LiDAR and motor encoders. Our approach simultaneously utilizes spatial consistency from a reference topological map and temporal consistency from time-series observations. Inspired by human cognitive perception, we define a two layered topological architecture that encompasses both coarse information of object distributions and structural information with some metric references. Categories of common objects in the environments, such as fire extinguishers or doors, are used as natural beacons. We evaluated our approach in two real-world buildings based on a multi-aisle structure with corridors of very similar appearance. Results demonstrated accurate localization despite the high level of symmetry of the scenario, and how ambiguity was significantly reduced as the agent progressed along its trajectory. • A structure with multisensory integration describes symmetrical environments. • An analytic model is presented for global indoor localization applied to robotics. • A custom visual detector allows to use characteristic objects as natural beacons. • Spatial and temporal consistency allows to discriminate very similar routes. • The system has proven its robustness in two large-scale public buildings. [ABSTRACT FROM AUTHOR]

The paper explains the need for energy renovation of public and other buildings and the regulatory framework (regulations and program procedures) through which this is sought. Important parameters of energy renovation of 48 school buildings in Osijek-Baranja County were processed and analyzed in more detail within the projects contracted in 2017 and 2018 (co-financed from the European Structural and Investment Funds within the Operational Program "Competitiveness and Cohesion" 2014-2020). The content of energy renovation works and their frequency in buildings and the expected energy savings were presented. The representation of existing energy classes and their improvement after reconstruction, regarding the construction period were analysed. The costs of renovation in relation to the age and area of buildings were considered as well. These data were compared to the results from the previous cycle of family houses' renovation in the same county (2015-2016), while the owners were co-financed, without the required minimum of improvement. The problems of the energy renewal process were highlighted and recommendations for better efficiency were given. [ABSTRACT FROM AUTHOR]

At 03:56 local time on November 26, 2019, an earthquake with a Mw = 6.4 struck western part of Albania. The duration of the tremor lasted less than 50 s and was felt largely also in Albania's capital Tirana, and in places as far away more than 300 km northeast of the epicenter. It caused damage to many public and residential buildings in districts of Durres, Tirana, Lezha, Shkodra, Diver, Berat and surrounding areas. This paper describes rapid visual assessment of the damaged buildings (169 in total) in affected areas by IZIIS teams' inspection of damaged buildings. Severe damages were identified in structural and non-structural elements as a result of inconsistent application of recent knowledge in design, construction and quality control of earthquake resistant structures. Structural errors in design and construction as well as inappropriate quality of built-in materials have been observed. Such results from the rapid damage assessment leads to the necessity of taking specific measures as detailed engineering inspection of vital structures as a basis of definition corresponding technical solutions for repair and strengthening with aim of restoring their operational mode. Last but not least, the biggest effect of earthquake damage was observed in non-structural elements which made the structures not-usable for citizens of the earthquake region. [ABSTRACT FROM AUTHOR]

Recently, the application of building information modeling (BIM) in building energy efficiency design programs has been emphasized in research. In China, faced with requirements in building energy efficiency design standards and specifications, researchers have been using BIM as a platform for breaking up bottlenecks in energy simulation and design software, and BIM is considered the key to improve the efficiency of building energy efficiency design. Firstly, based on the trade-off energy consumption judgment method proposed in the 'Public Building Energy Efficiency Design Standard (GB50189-2015)', this study combines the BIM platform with an orthogonal simulation design adopting an experimental building construction project in a cold region of China, to thereby study the influences of different envelope structural parameters on cooling and heating loads. Then, this study analyzes the continuity and consistency of data exchange between different BIM-related software, through the modeling software Revit and the sustainable analysis software Ecotect. Finally, through the experiment, the critical factors of the optimized design of the building envelope are investigated and applied for the optimized design of the building thermal system. In addition, this study uses BIM to complete an energy efficiency design for a laboratory heating, ventilation and air conditioning (HVAC) system. According to the experimental results, the following conclusions can be drawn: this study proposes a BIM-based optimized design method of building thermal system, which complies with various Chinese building energy efficiency standards and polices and can be used as a reference for Chinese designers. Also, the issues and challenges in building consumption simulation based on BIM technology and the application of BIM technology in the design of building thermal HVAC systems are discussed, and the development trends of BIM technology in China are analyzed. Building thermal system and HVAC system design are the key points of building efficiency design. The optimized design method proposed in this paper is of great significance to this system design. The optimized design method can improve the design efficiency of designers while complying with China's standards and policies. Therefore, it can save costs, improve the economic benefits of the projects and, at the same time, obtain an ideal building efficiency design. [ABSTRACT FROM AUTHOR]

By introducing two famous works of Mr. Zhang Kaiji in his later years, the reconstruction plan of Beijing Planetarium and the Museum of Chinese Revolution and the Museum of Chinese History, the paper analyzes the "courtyard.yard" space he once imagined in the modern city and large public buildings, and expounds the value and significance of his conception. The author believes that the expansion and transformation of important works should be based on historical research and centered on the spirit of space, and the intangible space outside of tangible entities should be carefully treated, so as to better complete the transmission of modern Chinese space experience. [ABSTRACT FROM AUTHOR]

Gridshells have been widely used in various public buildings, and many of them are defined over complex free-form surfaces with complex boundaries. This emphasizes the importance of general grid generation and optimization methods in the initial design stage to achieve visually sound and easy-to-manufacture structure. In this paper, a framework is presented to generate uniform, well-shaped and fluency triangular grids for structural design over free-form surfaces, especially those with complex boundaries. The framework employs force-based algorithms and a connectivity-regularization algorithm to optimize grid quality. First, an appropriate distribution of internal points is randomly generated on the surface. Secondly, a bubble-packing method is employed to increase the uniformity of the initial point distribution, and the points are connected using Delaunay-based triangularization to produce an initial grid with rods of balanced length. Thirdly, the grid connectivity is optimized using a range of edge-operations including edge-flip, collapse and split. The optimization process features a grid relaxation objective which includes the degree of the vertices, leading to improved regularity. As a final step, the grid is relaxed to improve fluency using a net-like method. As part of its contribution, this paper, therefore, proposes a metric for fluency, which can be used to quantitatively evaluate the suitability of a given grid for architectural and structural expression. Two case-study examples are presented to demonstrate the effective execution of the grid generation and optimization framework. It is shown that by using the proposed framework, the fluency index of the grid can be improved by up to 157%. • Framework presented for automatic triangular grid generation over free-form surfaces with complex boundaries. • Force-based technique developed to generate and smooth the grid to obtain uniform grids. • Edge-operations including edge-flip, collapse and split employed to optimize connectivity. • New quality index proposed to evaluate the fluency of resulted grids. • Fluency of the grid improved by up to 157% using the framework. [ABSTRACT FROM AUTHOR]

The origins of Malay architecture is typically linked to its vernacular past and vocabulary, primarily expressed in its residential timber traditions and arising from its detailed timber artisanship and constructions. Its constructional ingenuities had evolved a rich diverse language and grammar with its own localised aesthetics. Localized skills of the indigenous translate into structural and constructional marvels. This paper however, attempts to reframe a theory of origin of Malay architecture, extending from this basis and into the public realm of the Malay world. The roots of form of its traditional palaces and mosques represents the architectural and urban core of the regional past and thus can constitute a resource of expanding an 'urban' language. This paper reports on the mapping these palaces, using visual resources and reconstructions of surviving 17th century to the 1800s, to align these "early classicalised" and compact structures of different regions of Malay world, with shared expressions in their elevations and ornaments. Using these as departure points, the paper conceptualises an evolutionary 'tree' or geneanology which can account for the multiple and varied ethnocentric origins of the Malay world, argued as three main streams that had synthesised and mixed across time. The diverse public forms at different sites are linked to common archetypes in an attempt to re-enact a theory of origin. A qualitative approach taken in this research, focusing on aligning past ethnographic and anthropological findings of other researchers; including ethnolinguistic classifications and evolutions from different regionsargues to find geneanological roots and variants that explain the diversity. Using existing drawings, sketches on site visit, photography and literature reviewa, the paper selecta key regions as case studies, and the configurations of the public buildings are mapped in order to reframe into a theoretical taxonomy of origins. The taxonomy suggests a probable genealogical 'tree' of Malay architecture, from which its narrative can be reconstructed. Data in terms of elevational design, suggest five formal archetypes, which are the linear axial, layout configuration, deep plan projection, binuclear form, central and peristyle forms; and three 'strands' of ornamental character and stylisation. It proposes that a Classicalised language of Malay architecture, is possible which can mirror its ethnolinguistic and socio-political 'urban' origins, rather than stagnate into the hegemony of the 'indigineous'; into a universal theory of beginning. [ABSTRACT FROM AUTHOR]

The destruction caused by the earthquake can be widespread causing damage to telecommunication & power infrastructure, bridges & roads, water & sanitation facilities, and other services. Similarly, local administration during earthquake becomes mostly impaired especially after the destruction of majority of government buildings. The major earthquakes of Pakistan include Quetta Earthquake 1935, Kashmir - Khyber Pakhtunkhwa Earthquake 2005, Ziarat Earthquake 2008 and Awaran - Balochistan Earthquake 2013 which emphasized for the need of public and institutional preparedness at large scale. The objective of this paper is to assess the people and government earthquake preparedness in district Mansehra and recommend measures for its improvement. Historically, two high risks tehsils of district Mansehra (Balakot and Mansehra) were selected for this paper. A survey questionnaire was conducted using random sampling technique. The data was collected from six government departments and 498 local respondents. The results of the study reveal that government organizations have learnt lessons from the experience of past earthquake and thus increased their level of preparedness including emergency response system, early warning system, protection of assets and property, care for the human resources, addressing health issues, provision of shelter and logistics etc. Similarly, people are now well aware about the affects of earthquake disaster. The public preparedness level includes adequate knowledge about earthquake disaster, mitigation measures, alternative shelter arrangements and protection of resources. Based on the results of collected data and findings, the research study has proposed certain measures for further improving the public and institutional earthquake preparedness. [ABSTRACT FROM AUTHOR]

Long-span, single-layer spatial grid structures are widely used in public buildings. The progressive collapse of such structures could cause great losses of property and human life. To accurately capture the performance of a structure in progressive collapse, an efficient dynamic behavior analysis should be conducted. In this paper, a multi-degree-of-freedom simplified model was established to represent the progressive-collapse dynamic behavior of single-layer spatial grid structures. Based on the simplified model, two dynamic behavior modes were identified: ordinary and specific dynamic behaviors. In ordinary dynamic behavior, the dynamic effect caused by local failure cannot be transmitted, and the displacement responses of the joints in the failure area are symmetrically distributed based on the final equilibrium states, with the gradual attenuation of the dynamic effect. For the specific dynamic behavior, the dynamic effect is transmitted and a disorganized response of single-layer spatial grid structures occurs. Furthermore, the dynamic progressive-collapse behaviors of six full-scale typical domes were analyzed with a verified numerical simulation. The results indicate that a multi-degree-of-freedom system is necessary for accurately reflecting the dynamic behavior of single-layer spatial grid structures. The middle position between vertex and supports can be defined as the important area of reticulated domes, where a member's failure would have a significant effect on structural performance. If a specific dynamic behavior plays a dominant role in the overall structure, the progressive-collapse resistance may be improved for a single-layer spatial grid structure. [ABSTRACT FROM AUTHOR]