Search results for: green building rating systems

Authors: Anna Drabczyk, Sonia Kudlacik-Kramarczyk, Dagmara Malina, Bozena Tyliszczak, Agnieszka Sobczak-Kupiec

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Nowadays, nano-size materials are very popular group of materials among scientists. What is more, these materials find an application in a wide range of various areas. Therefore constantly increasing demand for nanomaterials including metallic nanoparticles such as silver of gold ones is observed. Therefore, new routes of their preparation are sought. Considering potential application of nanoparticles, it is important to select an adequate methodology of their preparation because it determines their size and shape. Among the most commonly applied methods of preparation of nanoparticles chemical and electrochemical techniques are leading. However, currently growing attention is directed into the biological or biochemical aspects of syntheses of metallic nanoparticles. This is associated with a trend of developing of new routes of preparation of given compounds according to the principles of green chemistry. These principles involve e.g. the reduction of the use of toxic compounds in the synthesis as well as the reduction of the energy demand or minimization of the generated waste. As a result, a growing popularity of the use of such components as natural plant extracts, infusions or essential oils is observed. Such natural substances may be used both as a reducing agent of metal ions and as a stabilizing agent of formed nanoparticles therefore they can replace synthetic compounds previously used for the reduction of metal ions or for the stabilization of obtained nanoparticles suspension. Methods that proceed in the presence of previously mentioned natural compounds are environmentally friendly and proceed without the application of any toxic reagents. Methodology: Presented research involves preparation of silver nanoparticles using selected plant extracts, e.g. artichoke extract. Extracts of natural origin were used as reducing and stabilizing agents at the same time. Furthermore, syntheses were carried out in the presence of additional polymeric stabilizing agent. Next, such features of obtained suspensions of nanoparticles as total antioxidant activity as well as content of phenolic compounds have been characterized. First of the mentioned studies involved the reaction with DPPH (2,2-Diphenyl-1-picrylhydrazyl) radical. The content of phenolic compounds was determined using Folin-Ciocalteu technique. Furthermore, an essential issue was also the determining of the stability of formed suspensions of nanoparticles. Conclusions: In the research it was demonstrated that metallic nanoparticles may be obtained using plant extracts or infusions as stabilizing or reducing agent. The methodology applied, i.e. a type of plant extract used during the synthesis, had an impact on the content of phenolic compounds as well as on the size and polydispersity of obtained nanoparticles. What is more, it is possible to prepare nano-size particles that will be characterized by properties desirable from the viewpoint of their potential application and such an effect may be achieved with the use of non-toxic reagents of natural origin. Furthermore, proposed methodology stays in line with the principles of green chemistry.

Keywords: green chemistry principles, metallic nanoparticles, plant extracts, stabilization of nanoparticles

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Stefano Sorace, Gloria Terenzi, Giulia Mazzieri, Iacopo Costoli

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The prolonged earthquake sequence that struck several urban agglomerations and villages in Central Italy, starting from 24 August 2016 through January 2017, highlighted once again the seismic vulnerability of pre-normative reinforced concrete (R/C) structures. At the same time, considerable damages were surveyed in recently retrofitted R/C buildings too, one of which also by means of a dissipative bracing system. The solution adopted for the latter did not expressly take into account the performance of non-structural elements, and namely of infills and partitions, confirming the importance of their dynamic interaction with the structural skeleton. Based on this consideration, an alternative supplemental damping-based retrofit solution for this representative building, i.e., a school with an R/C structure situated in the municipality of Norcia, is examined in this paper. It consists of the incorporation of dissipative braces equipped with pressurized silicone fluid viscous (FV) dampers, instead of the BRAD system installed in the building, the delayed activation of which -caused by the high stiffness of the constituting metallic dampers- determined the observed non-structural damages. Indeed, the alternative solution proposed herein, characterized by dissipaters with mainly damping mechanical properties, guarantees an earlier activation of the protective system. A careful assessment analysis, preliminarily carried out to simulate and check the case study building performance in originally BRAD-retrofitted conditions, confirms that the interstorey drift demand related to the Norcia earthquake's mainshock and aftershocks is beyond the response capacity of infills. The verification analyses developed on the R/C structure, including the FV-damped braces, highlight their higher performance, giving rise to a completely undamaged response both of structural and non-structural elements up to the basic design earthquake normative level of seismic action.

Keywords: dissipative technologies, performance assessment analysis, concrete structures, seismic retrofit

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Authors: Monica Hoeldtke Pietruchinski, Andrey Ricardo Pimentel

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The teaching of computer programming for beginners has been presented to the community as a not simple or trivial task. Several methodologies and research tools have been developed; however, the problem still remains. This paper aims to present multi-agent system architecture to be incorporated to the educational collaborative game software for teaching programming that monitors, evaluates and encourages collaboration by the participants. A literature review has been made on the concepts of Collaborative Learning, Multi-agents systems, collaborative games and techniques to teach programming using these concepts simultaneously.

Keywords: architecture of multi-agent systems, collaborative evaluation, collaboration assessment, gamifying educational software

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Authors: Narash Narasimman, Calvin Leong Jia Jun, Raksha Karthik, Paul Englert

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Background: Project Grit, a 12-week youth resilience program implemented by Impart and Spartans Boxing Club, aimed to help at-risk adolescents develop resilience through psychoeducation and mental health techniques for dealing with everyday stressors and adversity. The programme consists of two parts-1.5 hours of group therapy followed by 1 hour of boxing. Due to the novelty of the study, 6 male participants, aged 13 to 18, were recruited to participate in the study. Aim: This case study aims to examine the effectiveness of Project Grit in building resilience among at-risk adolescents. Methods: A case study design was employed to capture the complexity and uniqueness of the intervention, without oversimplifying or generalizing it. A 15-year-old male participant with a history of behavioural challenges, delinquency and gang involvement was selected for the study. Teacher, parent and child versions of the Strengths and Difficulties Questionnaire (SDQ) were administered to the facilitators, parents and participants respectively before and after the programme. Relevant themes from the qualitative interviews will be discussed. Results: Scores from all raters revealed improvements in most domains of the SDQ. Total difficulties scores across all raters improved from “very high” to “close to average”. High interrater reliability was observed (κ= .81). The participant reported learning methods to effectively deal with his everyday concerns using healthy coping strategies, developing a supportive social network, and building on his self efficacy. Themes from the subject’s report concurred with the improvement in SDQ scores. Conclusions: The findings suggest that Project Grit is a promising intervention for promoting resilience among at-risk adolescents. The teleological behaviourism framework and the combination of sports engagement and future orientation may be particularly effective in fostering resilience among this population. Further studies need to be conducted with a larger sample size to further validate the effectiveness of Project Grit.

Keywords: resilience, project grit, adolescents, at-risk, boxing, future orientation

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Authors: Kirsi Korkealehto

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The purpose of this research was to investigate how the peer evaluation concept was perceived by language teachers developing online language courses. The online language courses in question were developed in language teacher teams within a nationwide KiVAKO-project funded by the Finnish Ministry of Education and Culture. The participants of the project were 86 language teachers of 26 higher education institutions in Finland. The KiVAKO-project aims to strengthen the language capital at higher education institutions by building a nationwide online language course offering on a shared platform. All higher education students can study the courses regardless of their home institutions. The project covers the following languages: Chinese, Estonian, Finnish Sign Language, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish on the levels CEFR A1-C1. The courses were piloted in the autumn term of 2019, and an online peer evaluation session was organised for all project participating teachers in spring 2020. The peer evaluation utilised the quality criteria for online implementation, which was developed earlier within the eAMK-project. The eAMK-project was also funded by the Finnish Ministry of Education and Culture with the aim to improve higher education institution teachers’ digital and pedagogical competences. In the online peer evaluation session, the teachers were divided into Zoom breakout rooms, in each of which two pilot courses were presented by their teachers dialogically. The other language teachers provided feedback on the course on the basis of the quality criteria. Thereafter good practices and ideas were gathered to an online document. The breakout rooms were facilitated by one teacher who was instructed and provided a slide-set prior to the online session. After the online peer evaluation sessions, the language teachers were asked to respond to an online questionnaire for feedback. The questionnaire included three multiple-choice questions using the Likert-scale rating and two open-ended questions. The online questionnaire was answered after the sessions immediately, the questionnaire link and the QR-code to it was on the last slide of the session, and it was responded at the site. The data comprise online questionnaire responses of the peer evaluation session and the researcher’s observations during the sessions. The data were analysed with a qualitative content analysis method with the help of Atlas.ti programme, and the Likert scale answers provided results per se. The observations were used as complementary data to support the primary data. The findings indicate that the working in the breakout rooms was successful, and the workshops proceeded smoothly. The workshops were perceived as beneficial in terms of improving the piloted courses and developing the participants’ own work as teachers. Further, the language teachers stated that the collegial discussions and sharing the ideas were fruitful. The aspects to improve the workshops were to give more time for free discussions and the opportunity to familiarize oneself with the quality criteria and the presented language courses beforehand. The quality criteria were considered to provide a suitable frame for self- and peer evaluations.

Keywords: higher education, language learning, online learning, peer-evaluation

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Authors: James Kaweesa

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The Internet of Things (IoT) has become a critical component of modern technology, enabling the connection of numerous devices to the internet. The interconnected nature of IoT devices, along with their heterogeneous and resource-constrained nature, makes them vulnerable to various types of attacks, such as malware, denial-of-service attacks, and network scanning. Intrusion Detection Systems (IDSs) are a key mechanism for protecting IoT networks and from attacks by identifying and alerting administrators to suspicious activities. In this review, the paper will discuss the different types of IDSs available for IoT systems and evaluate their effectiveness in detecting and preventing attacks. Also, examine the various evaluation methods used to assess the performance of IDSs and the challenges associated with evaluating them in IoT environments. The review will highlight the need for effective and efficient IDSs that can cope with the unique characteristics of IoT networks, including their heterogeneity, dynamic topology, and resource constraints. The paper will conclude by indicating where further research is needed to develop IDSs that can address these challenges and effectively protect IoT systems from cyber threats.

Keywords: cyber-threats, iot, intrusion detection system, networks

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: Jin Woong Lee, Kyuman Cho, Taehoon Kim

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The application of constructability is increasingly required not only in the construction phase but also in the whole project stage. In particular, the proper application of construction experience and knowledge during the design phase enables the minimization of inefficiencies such as design changes and improvements in constructability during the construction phase. In order to apply knowledge effectively, engineering technology efforts should be implemented with design progress. Among many engineering technologies, engineering for temporary works, including facilities, equipment, and other related construction methods, is important to improve constructability. Therefore, as basic research, this study investigates the applicability of temporary work engineering during the design phase in the building construction industry. As a result, application of temporary work engineering has a greater impact on construction cost reduction and constructability improvement. In contrast to the existing design-bid-build method, the turn-key and CM (construct management) procurement methods currently being implemented in Korea are expected to have a significant impact on the direction of temporary work engineering. To introduce temporary work engineering, expert/professional organization training is first required, and a lack of client awareness should be preferentially improved. The results of this study are expected to be useful as reference material for the development of more effective temporary work engineering tasks and work processes in the future.

Keywords: Temporary Work Engineering, Design Phase, Constructability, Building Construction

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Authors: Vahid Rashtchi, Ashkan Pirooz

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This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

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Authors: Bulus Kpame, Mukhtar Mohammed Alhaji, Garba Jibril

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In any team sport, the most important variables that should be used to measure performance are physical condition, and technical and tactical performance. In a complex game like football, it is extremely difficult to measure the relative importance of each of these variables. However, physical fitness itself has been shown to consist of several components, like endurance, strength, flexibility, agility, coordination and speed. Each of these components has been shown to consist of several subcomponents. This paper attempts to describe a test battery to assess and evaluate physical performance in football players. This battery comprises a functional, structured training session of about 2.5hrs. it consists of quality rating of the warm-up procedure, tests of flexibility, football skills, power, speed, and endurance. Acceptable values for performance in each of the tests are also presented under each test. It is hoped that this battery of tests will be helpful to the coach in determining the effect of a specific training program. It would also be helpful to train physician and trainer, to monitor progress during rehabilitation after sustaining any injury.

Keywords: assessment, evaluation, performance, programs

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Authors: Zhou Yuwei

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This study used the multidimensional rating scale for disruptive behaviour in preschool children (parent version) to assess changes in the disruptive behaviour (tantrums, disobedience, aggression, and low level of concern for others) of 200 young children in Nanjing, Jiangsu Province, China, before and after living at home during the new crown epidemic, and five additional teachers of young children were selected to conduct interviews on the performance and changes in their disruptive behaviour at school. The following conclusions were drawn from the questionnaires and interviews: (1) 49% of the children showed a decrease in disruptive behaviour compared to the pre-epidemic period; (2) boys were more disruptive than girls due to individual factors; (3) children with a decrease in disruptive behaviour were more likely to have democratic and authoritative parenting styles due to parental education and upbringing; and the higher the level of parental education, the greater the decrease in disruptive behaviour. (4) For parents who worked outside the home during the epidemic and who did not work, disruptive behaviour scores were higher for their children. Meanwhile, disruptive behaviour was more pronounced the longer the child used electronic devices. The longer the parent-child interaction, the less disruptive behaviour was evident.

Keywords: disruptive behaviour, home life, children, COVID-19

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Authors: Adetunji A. Adeyanju., Mathew O. Omeike, Johnson O. Adeniran, Biodun S. Badmus

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In this paper, we discuss certain conditions for uniform asymptotic stability and uniform ultimate boundedness of solutions to some systems of Aizermann-type of differential equations by means of second method of Lyapunov. In achieving our goal, some Lyapunov functions are constructed to serve as basic tools. The stability results in this paper, extend some stability results for some Aizermann-type of differential equations found in literature. Also, we prove some results on uniform boundedness and uniform ultimate boundedness of solutions of systems of equations study.

Keywords: Aizermann, boundedness, first order, Lyapunov function, stability

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Authors: Yen-Jong Chen, Jei-An Su

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Public use facilities provide the basic infrastructure supporting the needs of urban sustainable development. These facilities include roads (streets), parking areas, green spaces, public schools, and city parks. However, how to acquire land with the proper location and size still remains uncertain in a capitalist economy where land is largely privately owned, such as in cities in Taiwan. The issue concerning the proper acquisition of reserved land for local public facilities (RLPF) policies has been continuously debated by the Taiwanese government for more than 30 years. Lately, the government has been re-evaluating projects connected with existing RLPF policies from the viewpoints of the needs of local residents, including the living environments of older adults. This challenging task includes addressing the requests of official bureau administrators, citizens whose property rights and current use status are affected, and other stakeholders, along with the means of development. To simplify the decision to acquire or release public land, we selected only public facilities that are needed for living in the local community, including parks, green spaces, plaza squares, and land for kindergartens, schools, and local stadiums. This study categorized these spaces as the community’s “leisure public facilities” (LPF). By constructing an accessibility index of the services of such multi-function facilities, we computed and produced a GIS map of spatial buffer zones for each LPF. Through these procedures, the service needs provided by each LPF were clearly identified. We then used spatial buffer zone envelope mapping to evaluate these service areas. The results obtained can help decide which RLPF should be acquired or released so that community services can be maximized under a limited budget.

Keywords: urban public facilities, community demand, accessibility, spatial buffer zone, Taiwan

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Authors: Mansur Hamma-Adama, Tahar Kouider

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Construction Industry has been evolving since the development of Building Information Modelling (BIM). This technological process is unstoppable; it is out to the market with remarkable case studies of solving the long industry’s history of fragmentation. This industry has been changing over time; United States has recorded the most significant development in construction digitalization, Australia, United Kingdom and some other developed nations are also amongst promoters of BIM process and its development. Recently, a developing country like China and Malaysia are keying into the industry’s digital shift, while very little move is seen in South Africa whose development is considered higher and perhaps leader in the digital transition amongst the African countries. To authors’ best knowledge, Nigerian construction industry has never engaged in BIM discussions hence has no attention at national level. Consequently, Nigeria has no “Noteworthy BIM publications.” Decision makers and key stakeholders need to be informed on the current trend of the industry’s development (BIM in specific) and the opportunities of adopting this digitalization trend in relation to the identified challenges. BIM concept can be traced mostly in Architectural practices than engineering practices in Nigeria. A superficial BIM practice is found to be at organisational level only and operating a model based - “BIM stage 1.” Research to adopting this innovation has received very little attention. This piece of work is literature review based, aimed at exploring BIM in Nigeria and its prospects. The exploration reveals limitations in the literature availability as to extensive research in the development of BIM in the country. Numerous challenges were noticed including building collapse, inefficiencies, cost overrun and late project delivery. BIM has potentials to overcome the above challenges and even beyond. Low level of BIM adoption with reasonable level of awareness is noticed. However, lack of policy and guideline as well as serious lack of experts in the field are amongst the major barriers to BIM adoption. The industry needs to embrace BIM to possibly compete with its global counterpart.

Keywords: adoption, BIM, CAD, construction industry, Nigeria, opportunities

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Authors: Elham Soltani Dehnavi

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In today’s compact cities, bringing daylighting and fresh air to buildings is a significant challenge, but it also presents opportunities to reduce energy consumption in buildings by reducing the need for artificial lighting and mechanical systems. Simple adjustments to building form can contribute to their efficiency. This paper examines how the relationship between the width and depth of the rooms in office buildings affects visual and thermal comfort, and consequently energy savings. Based on these evaluations, we can determine the best location for sedentary areas in a room. We can also propose improvements to occupant experience and minimize the difference between the predicted and measured performance in buildings by changing other design parameters, such as natural ventilation strategies, glazing properties, and shading. This study investigates the condition of spatial daylighting and thermal comfort for a range of room configurations using computer simulations, then it suggests the best depth for optimizing both daylighting and thermal comfort, and consequently energy performance in each room type. The Window-to-Wall Ratio (WWR) is 40% with 0.8m window sill and 0.4m window head. Also, there are some fixed parameters chosen according to building codes and standards, and the simulations are done in Seattle, USA. The simulation results are presented as evaluation grids using the thresholds for different metrics such as Daylight Autonomy (DA), spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), and Daylight Glare Probability (DGP) for visual comfort, and Predicted Mean Vote (PMV), Predicted Percentage of Dissatisfied (PPD), occupied Thermal Comfort Percentage (occTCP), over-heated percent, under-heated percent, and Standard Effective Temperature (SET) for thermal comfort that are extracted from Grasshopper scripts. The simulation tools are Grasshopper plugins such as Ladybug, Honeybee, and EnergyPlus. According to the results, some metrics do not change much along the room depth and some of them change significantly. So, we can overlap these grids in order to determine the comfort zone. The overlapped grids contain 8 metrics, and the pixels that meet all 8 mentioned metrics’ thresholds define the comfort zone. With these overlapped maps, we can determine the comfort zones inside rooms and locate sedentary areas there. Other parts can be used for other tasks that are not used permanently or need lower or higher amounts of daylight and thermal comfort is less critical to user experience. The results can be reflected in a table to be used as a guideline by designers in the early stages of the design process.

Keywords: occupant experience, office buildings, space depth, thermal comfort, visual comfort

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Authors: Abdulkerim Ilgun, Ahmad Javid Zia

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In developing countries, the urban populations are increasing rapidly and with this increment the residential areas are experiencing major problems. Construction of high-rise buildings in confined spaces is one of the most practical solutions for this problem. However, by living in high-rise buildings and sharing common residential areas, residents will face many problems. Irritating sound problem which is known as noise is one of the major problems mentioned above. The second most important problem is the weight of the high-rise buildings which makes the structure more vulnerable to earthquakes. To decrease earthquake loads it’s very important to decrease the weight of the buildings. To solve the problem of noise and keep the building weight at minimum level, experimentally designed soundproof gypsum partition wall which has optimum thickness has been used in high-rise story building and the results have been compared with ordinary brick partition walls. In this compression the effect of weights of soundproof gypsum walls and ordinary brick walls in accordance to structural engineering have been investigated.

Keywords: cellubor, gypsum board, gypsum partition walls, light partition walls, noise, sound

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Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici

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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Mahdi Alsagour, Sam Ramrattan

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This paper was developed to investigate two types of sands from the Kingdom of Saudi Arabia (KSA) for potential use in the global metal casting industry. Four types of sands were selected for study, two of the sand systems investigated are natural sands from the KSA. The third sand sample is a heat processed synthetic sand and the last sample is commercially available US silica sand that is used as a control in the study. The purpose of this study is to define the durability of the four sand systems selected for foundry usage. Additionally, chemical analysis of the sand systems is presented before and after elevated temperature exposure. Results show that Saudi silica sands are durable and can be used in foundry processing.

Keywords: alternative molding media, foundry sand, reclamation, silica sand, specialty sand

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Authors: Mohammadreza Hajialigol, Nargues Falahi Charkhabi, Fatemeh Shahryari, Saadat Sarikhani

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BACKGROUND AND OBJECTIVES Iran is the third producer of Persian walnut worldwide. However, its walnut trees have been under threat from decline during last decade. Walnut canker caused by B. nigrifluens and B. rubrifaciens was recorded in multiple regions of Iran. Furthermore, Brenneria rosae subsp. rosae and Gibbsiella quercinecans were recently recognized as responsible for walnut decline in northwestern Iran. This study aimed to identify the causal agent of walnut decline in Kermanshah and Isfahan. MATERIAL AND METHODS Symptomatic samples were collected from affected walnut trees of Kermanshah and Isfahan provinces. The pathogenicity of strains was proved on immature walnut fruits cv. ‘Hartley’ and young green twigs of two-year-old walnut seedling cv. ‘Chandler’. Pathogenic strains were subjected to conventional phenotypic tests. 16S rRNA, gyrB, and infB genes were partially amplified and sequenced. RESULTS Irregular longitudinal cankers and dark lesions were observed in the outer and inner bark, respectively. Twenty-four strains were isolated on EMB-agar media. Fourteen strains were able to cause necrosis and a dark-colored region in the mesocarp and on young green twigs around the inoculation site 14 and 30 days post-inoculation, respectively. Strains were able to hydrolyze Tween 20, Tween 80, gelatin and esculin, however, did not produce indole or urease. Pairwise comparison, the 16S rRNA gene nucleotide sequences of strain I2 were 100% identical with those of Rahnella victoriana FRB 225T. Moreover, a phylogenetic tree reconstructed based on the concatenated sequences of two housekeeping gene fragments, gyrB (601 bp) and infB (615 bp), revealed that the strains I2, I5, and KE6 were clustered with R. victoriana FRB 225T. CONCLUSION To the best of our knowledge, this is the first report of R. victoriana in association with walnut decline. This result is necessary to find resistant genotypes.

Keywords: emerging pathogens, Iran, juglans regia, MLSA

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Adele Pierre, Nadia Amoroso

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Changing climate patterns are resulting in increased in storm severity, challenging traditional methods of managing stormwater runoff. This research compares a system of bioswales to existing curb and gutter infrastructure in a post-industrial streetscape of Hamilton, Ontario. Using the geodesign process, including rule-based set parameters and an integrated approach combining geospatial information with stakeholder input, a section of Ottawa St. North was modelled to show how green infrastructure can ease the burden on aging, combined sewer systems. Qualitative data was gathered from residents of the neighbourhood through field notes, and quantitative geospatial data through GIS and site analysis. Parametric modelling was used to generate multiple design scenarios, each visualizing resulting impacts on stormwater runoff along with their calculations. The selected design scenarios offered both an aesthetically pleasing urban bioswale street-scape system while minimizing and controlling stormwater runoff. Interactive maps, videos and the 3D model were presented for stakeholder comment via ESRI’s (Environmental System Research Institute) web-scene. The results of the study demonstrate powerful tools that can assist landscape architects in designing, collaborating and communicating stormwater strategies.

Keywords: bioswale, geodesign, data-driven and rule-based design, geodesign, GIS, stormwater management

Procedia PDF Downloads 168

Authors: Imme Petersen, Wiebke Sick, Regine Kollek

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In systems medicine, high-throughput technologies produce large amounts of data on different biological and pathological processes, including (disturbed) gene expressions, metabolic pathways and signaling. The large volume of data of different types, stored in separate databases and often located at different geographical sites have posed new challenges regarding data handling and processing. Tools based on bioinformatics have been developed to resolve the upcoming problems of systematizing, standardizing and integrating the various data. However, the heterogeneity of data gathered at different levels of biological complexity is still a major challenge in data analysis. To build multilayer disease modules, large and heterogeneous data of disease-related information (e.g., genotype, phenotype, environmental factors) are correlated. Therefore, a great deal of attention in systems medicine has been put on data standardization, primarily to retrieve and combine large, heterogeneous datasets into standardized and incorporated forms and structures. However, this data-centred concept of standardization in systems medicine is contrary to the debate in science and technology studies (STS) on standardization that rather emphasizes the dynamics, contexts and negotiations of standard operating procedures. Based on empirical work on research consortia that explore the molecular profile of diseases to establish systems medical approaches in the clinic in Germany, we trace how standardized data are processed and shaped by bioinformatics tools, how scientists using such data in research perceive such standard operating procedures and which consequences for knowledge production (e.g. modeling) arise from it. Hence, different concepts and meanings of standardization are explored to get a deeper insight into standard operating procedures not only in systems medicine, but also beyond.

Keywords: data, science and technology studies (STS), standardization, systems medicine

Procedia PDF Downloads 324

Authors: Bing Lu, Shuang Li, Hongyuan Zhou

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The steel–concrete hybrid structure has been extensively employed in high–rise buildings and super high–rise buildings. The light gauge steel–concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a new–type steel–concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high–rise buildings with three different concrete hybrid structures were investigated through finite element software, respectively. The three concrete hybrid structures are reinforced concrete column–steel beam (RC‒S) hybrid structure, concrete–filled steel tube column–steel beam (CFST‒S) hybrid structure, and tubed concrete column–steel beam (TC‒S) hybrid structure. The nonlinear time-history analysis of three high–rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high–rise buildings were superior. Under extremely rare earthquakes, the maximum inter–storey drifts of three high–rise buildings are significantly lower than 1/50. The inter–storey drift and floor acceleration of high–rise building with CFST‒S hybrid structure were bigger than those of high–rise buildings with RC‒S hybrid structure, and smaller than those of high–rise building with TC‒S hybrid structure. Then, based on the time–history analysis results, the post-earthquake repair cost ratio and repair time of three high–rise buildings were predicted through an economic performance analysis method proposed in FEMA‒P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC‒S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel–concrete hybrid structure, high–rise building, time–history analysis

Procedia PDF Downloads 162

Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper presents development results of usage of C-OTDR monitoring systems for rail traffic management. The C-OTDR method is based on vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes which take place due to microscopic seismoacoustic impacts on the optical fiber allows to determine seismoacoustic emission source positions and to identify their types. This approach proved successful for rail traffic management (moving block system, weigh- in-motion system etc).

Keywords: C-OTDR systems, moving block-sections, rail traffic management, Rayleigh backscattering, weigh-in-motion

Procedia PDF Downloads 569

Authors: Sitarrine Thongpussawal, Dasarath Jayasuriya, Thanaroj Woraratprasert, Sakawtree Prajamwong

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Thailand grapples with recurrent floods causing substantial repercussions on its economy, society, and environment. In 2021, the economic toll of these floods amounted to an estimated 53,282 million baht, primarily impacting the agricultural sector. The existing flood monitoring system in Thailand suffers from inaccuracies and insufficient information, resulting in delayed warnings and ineffective communication to the public. The Office of the National Water Resources (OWNR) is tasked with developing and integrating data and information systems for efficient water resources management, yet faces challenges in monitoring accuracy, forecasting, and timely warnings. This study endeavors to evaluate the viability of enhancing Thailand's Flood Forecasting and Warning (FFW) systems. Additionally, it aims to formulate a comprehensive work package grounded in international best practices to enhance the country's FFW systems. Employing qualitative research methodologies, the study conducted in-depth interviews and focus groups with pertinent agencies. Data analysis involved techniques like note-taking and document analysis. The study substantiates the feasibility of developing and enhancing FFW systems in Thailand. Implementation of international best practices can augment the precision of flood forecasting and warning systems, empowering local agencies and residents in high-risk areas to prepare proactively, thereby minimizing the adverse impact of floods on lives and property. This research underscores that Thailand can feasibly advance its FFW systems by adopting international best practices, enhancing accuracy, and improving preparedness. Consequently, the study enriches the theoretical understanding of flood forecasting and warning systems and furnishes valuable recommendations for their enhancement in Thailand.

Keywords: flooding, forecasting, warning, monitoring, communication, Thailand

Procedia PDF Downloads 45

Authors: Dušan Bojović, Wei Huang, Zdravko Stojanović, Jovan Ilić

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In an era of ever-growing electricity generation from renewable energy sources, namely wind and solar, a need for reliable energy storage and intensive balancing of the electric power system gains significance. For decades, pump storage hydroelectric power plants have proven to be an important asset regarding the storage of generated electricity. However, with the increasing overall share of wind and solar in electric systems at large, the importance of electric grid stability keeps growing. A large pump storage project, the Bistrica Pump Storage Plant (PSP), is currently under development in Serbia. The Bistrica PSP will be designed as a 600+ MW power plant, which is envisaged as a significant contributor to the Serbian power grid stability as more and more renewable energy sources are implemented over time. PSP Bistrica is seen as a strategically important project on the green agenda path of the Electric Power Industry of Serbia as a necessary pre-condition for the safe implementation of other renewable energy sources. The importance of such a plant would also play an important role in reducing the electricity production from coal, i.e., thermoelectric power plants. During the project’s development, various techniques and technologies are evaluated for the purpose of determining the optimum (the most profitable) solution. Over the course of this paper, these technologies – such as frequency-regulated pump turbines and ternary sets will be presented, with a detailed explanation of their possible application within the Bistrica PSP project and their relative advantages/disadvantages in this particular case.

Keywords: hydraulic turbines, pumped storage, renewable energy, competing technologies

Procedia PDF Downloads 74

Authors: Mohamed El-Sayed Mosaad

Abstract:

An analytic approach is obtained for the steady heat transfer problem of two fluid systems, in thermal communication via heat conduction across a solid wall separating them. The two free convection layers created on wall sides are assumed to be in parallel flow. Fluid-solid interface temperature on wall sides is not prescribed in analysis in advance; rather, determined from conjugate solution among other unknown parameters. The analysis highlights the main conjugation parameters controlling thermal interaction process of involved heat transfer modes. Heat transfer results of engineering importance are obtained.

Keywords: conjugate heat transfer, boundary layer, convection, thermal systems

Procedia PDF Downloads 368

Authors: Emine Laarouchi, Daniela Cancila, Laurent Soulier, Hakima Chaouchi

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Cyber-Physical Systems as drones proved their efficiency for supporting emergency applications. For these particular applications, travel time and autonomous navigation algorithms are of paramount importance, especially when missions are performed in urban environments with high obstacle density. In this context, however, safety properties are not properly addressed. Our ambition is to optimize the system safety level under autonomous navigation systems, by preserving performance of the CPS. At this aim, we introduce genetic algorithms in the autonomous navigation process of the drone to better infer its trajectory considering the possible obstacles. We first model the wished safety requirements through a cost function and then seek to optimize it though genetics algorithms (GA). The main advantage in the use of GA is to consider different parameters together, for example, the level of battery for navigation system selection. Our tests show that the GA introduction in the autonomous navigation systems minimize the risk of safety lossless. Finally, although our simulation has been tested for autonomous drones, our approach and results could be extended for other autonomous navigation systems such as autonomous cars, robots, etc.

Keywords: safety, unmanned aerial vehicles , CPS, ACPS, drones, path planning, genetic algorithms

Procedia PDF Downloads 170