Search results for: energy modeling tools

Authors: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

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In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: wildfire, Mediterranean-climate regions, management, policy

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Authors: Catherine Begin, Jeanne Berthod, Manon Truchon

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In Quebec, there are more than 8,000 community organizations throughout the province, representing more than 72,000 jobs. Working in a community setting involves several particularities (e.g., contact with the suffering of users, feelings of powerlessness, institutional pressure, unstable funding, etc.), which can put workers at risk of fatigue, burnout, and psychological distress. A 2007 study shows that 52% of community workers surveyed have a high psychological distress index. The Ricochet project, founded in 2019, is an initiative aimed at providing various care and services to community workers in the Quebec City region, with a global health approach. Within this program, mindful self-compassion training (MSC) is offered at a low cost. MSC is one of the effective strategies proposed in the literature to help prevent and reduce burnout. Self-compassion is the recognition that suffering, failure, and inadequacies are inherent in the human experience and that everyone, including oneself, deserves compassion. MSC training targets several behavioral, cognitive, and emotional learnings (e.g., motivating oneself with caring, better managing difficult emotions, promoting resilience, etc.). A mixed-method evaluation was conducted with the participants in order to explore the effects of the training on community workers in the Quebec City region. The participants were community workers (management or caregiver). 15 participants completed satisfaction and perceived impact surveys, and 30 participated in structured interviews. Quantitative results showed that participants were generally completely satisfied or satisfied with the training (94%) and perceived that the training allowed them to develop new strategies for dealing with stress (87%). Participants perceived effects on their mood (93%), their contact with others (80%), and their stress level (67%). Some of the barriers raised were scheduling constraints, length of training, and guilt about taking time for oneself. The qualitative results show that individuals experienced long-term benefits, as they were able to apply the tools they received during the training in their daily lives. Some barriers were noted, such as difficulty in getting away from work or problems with the employer, which prevented enrollment. Overall, the results of this evaluation support the use of MSC (mindful self-compassion) training among community workers. Future research could support this evaluation by using a rigorous design and developing innovative ways to overcome the barriers raised.

Keywords: mindful self-compassion, community workers, work stres, burnout, wellbeing at work

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

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Authors: Golshid Gilani, Albert De La Fuente, Ana Blanco

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Sustainability assessment of new and existing buildings has generated a growing interest due to the evident environmental, social and economic impacts during their construction and service life. Façades, as one of the most important exterior elements of a building, may contribute to the building sustainability by reducing the amount of energy consumption and providing thermal comfort for the inhabitants, thus minimizing the environmental impact on both the building and on the environment. Various methods have been used for the sustainability assessment of buildings due to the importance of this issue. However, most of the existing methods mainly concentrate on environmental and economic aspects, disregarding the third pillar of sustainability, which is the social aspect. Besides, there is a little focus on comprehensive sustainability assessment of facades, as an important element of a building. This confirms the need of developing methods for assessing the sustainable performance of building façades as an important step in achieving building sustainability. In this respect, this paper aims at presenting a model for assessing the global sustainability of façade systems. for that purpose, the Integrated Value Model for Sustainable Assessment (MIVES), a Multi-Criteria Decision Making model that integrates the main sustainability requirements (economic, environmental and social) and includes the concept of value functions, used as an assessment tool.

Keywords: façade, MCDM, MIVES, sustainability

Procedia PDF Downloads 349

Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

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Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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Authors: Bunindro Nameirakpam, Sonia Sougrapakam, Shannon B. Olsson, Rajashekar Yallappa

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Natural sources for new pesticidal compounds hold promise in view of their eco-friendly nature, selectivity and mammalian safety. Despite a large number of plants that show insecticidal activity and diversity of natural chemistry with inherent eco-friendly nature, newer classes of insecticides have eluded discovery. Artemisia vulgaris, known as Mugwort, is a universal herb used for folk medicine and religious purposes throughout the ancient world. In India, the essential oils of Artemisia vulgaris are used for its insecticidal, anti parasiticidal and antimicrobial properties. Traditionally, the dried leaves of Artemisia vulgaris are used to repel insects as well as rats in and around the granaries in the North-East India. Artemisia vulgaris collected during November from different ecological sites were studied for the bio-pesticidal utility against the stored grain pests. The insecticidal activities were found in the crude extracts of n-hexane and methanol from the samples collected in Sikkim and Manipur respectively. Using silica gel column chromatography protocol, we have isolated one novel bioactive molecule from the aerial parts of Artemisia vulgaris L based on various physical-chemical and spectroscopic techniques (IR, 1H NMR, 13C NMR and mass). The novel bioactive molecule is highly toxic and very low concentration (4.35 µg/l) is needed to control the stored product insects. In additional experiment results clearly showed the involvement of sodium pumps inhibition in the insecticidal action of purified compound in the Sitophilus oryzae. The knockdown activity of the purified compound is concomitant with the in vivo inhibition of Na+/ K+- ATPase. Further, our study showed insignificant differences in the seed germination of control and the treated grains. The lack of adverse effect of the novel bioactive molecule on the seed germination is highly desirable for seed/grain protectant and showing the potential to be developed as possible natural fumigants for the control of stored grain pests. The novel bioactive molecule is selective insecticide with a high margin of safety to mammals and showed promise as novel biopesticide candidate for grain protection. It is believed that Bio-pesticides can serve as the most important pest management tools as far as global safety is concerned.

Keywords: Indian traditional plant, Artemisia vulgaris, bio-pesticides, Na+/ K+- ATPase, seed germination

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Susanna Vanhamäki, Gabor Schneider, Kati Manskinen

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‘Bioeconomy’ is a complex concept that cuts across many sectors and covers several policy areas. To achieve an overall understanding and support a successful bioeconomy, a cross-sectorial approach is necessary. In practice, due to the concept’s wide scope and varying international approaches, fully understanding bioeconomy is challenging on policy level. This paper provides a background of the topic through an analysis of bioeconomy strategies in the Baltic Sea region. Expert interviews and a small survey were conducted to discover the current and intended focuses of these countries’ bioeconomy sectors. The research shows that supporting sustainability is one of the keys in developing the future bioeconomy. The results highlighted that the bioeconomy has to be sustainable and based on circular economy principles. Currently, traditional bioeconomy sectors like food, wood, fish & waters as well as fuel & energy, which are in the core of national bioeconomy strategies, are best known and are considered more relevant than other bioeconomy industries. However, there is increasing potential for novel sectors, such as textiles and pharmaceuticals. The present research indicates that the opportunities presented by these bioeconomy sectors should be recognised and promoted. Education, research and innovation can play key roles in developing transformative and sustainable improvements in primary production and renewable resources. Furthermore, cooperation between businesses and educators is important.

Keywords: bioeconomy, circular economy, policy, strategy

Procedia PDF Downloads 179

Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Usha N. Murthy, H. B. Rekha, Mahaveer Devoor

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The introduction of more stringent pollution regulations, in relation to financial and social pressures for sustainable development, has pressed toward limiting the volumes of industrial and domestic effluents discharged into the environment-as well as to increase the efforts within research and development of new or more efficient wastewater treatment technologies. Considering both discharge volume and effluent composition, wastewater generated by the textile industry is rated as the most polluting among all industrial sectors. The pollution load is mainly due to spent dye baths, which are composed of unreacted dyes, dispersing agents, surfactants, salts and organics. In the present investigation, the textile dye wastewater was characterized by high colour, chemical oxygen demand (COD), total dissolved solids (TDS) and pH. Electrochemical oxidation process for four plate electrodes was carried out at five different current intensities, out of which 0.14A has achieved maximum percentage removal of COD with 75% and 83% of colour. The COD removal rate in kg COD/h/m2 decreases with increase in the current intensity. The energy consumption increases with increase in the current intensity. Hence, textile dye wastewater can be effectively pre-treated by electrochemical oxidation method where the process limits objectionable colour while leaving the COD associated with organics left for natural degradation thus causing a sustainable reduction in pollution load.

Keywords: electrochemical treatment, COD, colour, environmental engineering

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Authors: Nicolas Giraudo, Peter Thissen

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In this paper we bring up new aspects of the metal proton exchange reaction (MPER, also called early stage hydration): (1) its dependence of the number of protons consumed by the preferential exchanged cations on the pH value applied at the water/wollastonite interface and (2) strong anisotropic characteristics detected in atomic force microscopy (AFM) and low energy ion scattering spectroscopy measurements (LEIS). First we apply density functional theory (DFT) calculations to compare the kinetics of the reaction on different wollastonite surfaces, and combine it with ab initio thermodynamics to set up a model describing (1) the release of Ca in exchange with H coming from the water/wollastonite interface, (2) the dependence of the MPER on the chemical potential of protons. In the second part of the paper we carried out in-situ AFM and inductive coupled plasma atomic emission spectroscopy (ICP-OES) measurements in order to evaluate the predicted values. While a good agreement is found in the basic and neutral regime (pH values from 14-4), an increasing mismatch appears in the acidic regime (pH value lower 4). This is finally explained by non-equilibrium etching, dominating over the MPER in the very acidic regime.

Keywords: anisotropy, calcium silicate, cement, density functional theory, hydration

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

Procedia PDF Downloads 128

Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: Shruti Sakarkar, Jega Jegatheesan, Srinivasan Madapusi

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Photocatalytic membranes have shown great potential for the removal of an organic and inorganic pollutant from wastewater as it combines the degradation and antibacterial properties from photocatalysis and physical separation by the membrane in a single unit. Incorporation of the semiconductor in membrane structure results in enhancing the performance and the properties of the membrane. In this study porous ultrafiltration polyvinylidene fluoride (PVDF) membranes with entrapped TiO₂ nanoparticle were prepared by phase inversion method and further used for the degradation of reactive orange 16 (RO16). Prepared photocatalytic membranes were characterized by the scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), contact angle, and atomic force microscope (AFM). The addition of TiO₂ nanopartparticles improves the strength and thermal stability of the membrane. In particular hydrophilicity and permeability increases with the increase of TiO₂ nanoparticles into the membrane. The photocatalytic membrane achieves 80-85% degrdation of RO16. The impact of different parameters such as pH, concentration of photocatalyst, dye concentration and effect of H₂O₂ were analysed. The best conditions for dye degradation were an initial dye concentration of 50 mg/L, with a membrane containing TiO₂ loading of 2wt%. It was observed that in the presence of H₂O₂, degradation increases with increasing H₂O₂ concentration and reached up to 95-98%. The high quality permeates obtained from the photocatalytic membrane can be reused.

Keywords: photocatalytic membrane, TiO₂, PVDF, nanoparticles

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Authors: Hakan Gungunes, Ismail A. Auwal, Abdulhadi Baykal, Sagar E. Shirsath

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Barium hexaferrite, BaFe₁₂O₁₉, substituted by Bi³⁺ and La³⁺ (BaBiₓLaₓFe₁₂₋₂ₓO₁₉ where 0.0 ≤ x ≤ 0.5) were prepared by solid state synthesis route. The effect of substituted Bi³⁺ and La³⁺ ions on the structure, morphology, magnetic and cation distributions of barium hexaferrite were investigated by X-ray powder diffractometry (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FT-IR) and Mössbauer spectroscopy. XRD powder patterns were refined by the Rietveld analysis method which confirmed the formation of single phase magneto-plumbite structure and the substitution of La³⁺ and Bi³⁺ ions into the lattice of barium ferrite. These results show that both La³⁺ and Bi³⁺ ions completely enter into barium hexaferrite lattice without disturbing the hexagonal ferrite structure. The EDX spectra confirmed the presence of all the constituents in expected elemental percentage. From 57Fe Mössbauer spectroscopy data, the variation in line width, isomer shift, quadrupole splitting and hyperfine magnetic field values on Bi and La substitutions have been determined. Cation distribution in the presently investigated hexaferrite system was estimated using the relative area of Mössbauer spectroscopy.

Keywords: hexaferrite, mössbauer, cation distribution, solid state synthesis

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Authors: Dipti Yadav, Latha Rangan, Pinakeswar Mahanta

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Recent fuel-development strategies to reduce oil dependency, mitigate greenhouse gas emissions, and utilize domestic resources have generated interest in the search for alternative sources of fuel supplies. Bioenergy production from lignocellulosic biomass has a great potential. Cellulose, hemicellulose and Lignin are main constituent of woods or agrowaste. In all the industries there are always left over or waste products mainly lignin, due to the heterogeneous nature of wood and pulp fibers and the heterogeneity that exists between individual fibers, no method is currently available for the quantitative isolation of native or residual lignin without the risk of structural changes during the isolation. The potential benefits from finding alternative uses of lignin are extensive, and with a double effect. Lignin can be used to replace fossil-based raw materials in a wide range of products, from plastics to individual chemical products, activated carbon, motor fuels and carbon fibers. Furthermore, if there is a market for lignin for such value-added products, the mills will also have an additional economic incentive to take measures for higher energy efficiency. In this study residual lignin were isolated from areca nut shells by acid hydrolysis and were analyzed and characterized by Fourier Transform Infrared (FTIR), LCMS and complexity of its structure investigated by NMR.

Keywords: Areca nut, Lignin, wood, bioenergy

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Authors: Soon Young Choi, Chan Hwan Kim, Chan Hong Park, Hyung Rae Kim, Myoung Hoon Lee, Hyeon-Yeong Park

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We performed the marine magnetic, bathymetry and seismic survey at the TA22 seamount (in the Lau basin, SW Pacific) for finding the submarine hydrothermal deposits in October 2009. We acquired magnetic and bathymetry data sets by suing Overhouser Proton Magnetometer SeaSPY (Marine Magnetics Co.), Multi-beam Echo Sounder EM120 (Kongsberg Co.). We conducted the data processing to obtain detailed seabed topography, magnetic anomaly, reduction to the pole (RTP) and magnetization. Based on the magnetic properties result, we analyzed submarine geology structure of TA22 seamount with post-processed seismic profile. The detailed bathymetry of the TA22 seamount showed the left and right crest parts that have caldera features in each crest central part. The magnetic anomaly distribution of the TA22 seamount regionally displayed high magnetic anomalies in northern part and the low magnetic anomalies in southern part around the caldera features. The RTP magnetic anomaly distribution of the TA22 seamount presented commonly high magnetic anomalies in the each caldera central part. Also, it represented strong anomalies at the inside of caldera rather than outside flank of the caldera. The magnetization distribution of the TA22 seamount showed the low magnetization zone in the center of each caldera, high magnetization zone in the southern and northern east part. From analyzed the seismic profile map, The TA22 seamount area is showed for the inferred small mounds inside each caldera central part and it assumes to make possibility of sills by the magma in cases of the right caldera. Taking into account all results of this study (bathymetry, magnetic anomaly, RTP, magnetization, seismic profile) with rock samples at the left caldera area in 2009 survey, we suppose the possibility of hydrothermal deposits at mounds in each caldera central part and at outside flank of the caldera representing the low magnetization zone. We expect to have the better results by combined modeling from this study data with the other geological data (ex. detailed gravity, 3D seismic, petrologic study results and etc).

Keywords: detailed bathymetry, magnetic anomaly, seamounts, seismic profile, SW Pacific

Procedia PDF Downloads 412

Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Wang Haining, Zhang Hong

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In China, rapid urbanization needs more and more buildings constructed for the growing population in cities. With the help of the methodology which contains investigation, contrastive analysis, design based on component with BIM and experiment before real construction, this research based on mobile light structure system, trying to the sustainable problems partly in present China by systematic study. The system cannot replace the permanent heavy structure completely. So the goal is the improvement of the whole building system by the addition of light structure. This house system uses modularized envelopes and standardized connections, which are pre-fabricated and assembled in factories and transported like containers. Aluminum is used as the structural material in this system, and inorganic thermal insulation material used in the envelope, which have high fireproof properties. The relationship between manufactory and construction of the system is progressive hierarchy. They exist as First Industrial, Second Industrial, Third Industrial and Site Assembly Stage. It could maximize the land usage capacity by fully exploit the area where normal permanent architecture can't take advantage of. Not only the building system itself especially the thermal isolated materials used and active solar photovoltaic system equipped can save energy, but also the way of product development is sustainable.

Keywords: aluminum house, light Structure, rapid assembly, repeat construction

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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Link-to-column connection in eccentrically braced frames (EBF) has been a critical problem since the link flange connected to the column fractured prior to the required link rotation. Even though the problem in link-to-column connection still exist, the use of an eccentrically braced frame (EBF) is increasing day by day as EBF have high elastic stiffness, stable inelastic response under repeated lateral loading, and excellent ductility and energy dissipation capacity. In order to address this problem, a reduced web and flange link section is proposed and evaluated in this study. Reducing the web with holes makes the link to control the failure at the edge of holes introduced. Reducing the flange allows the link to control the location at which the plastic hinge is formed. Thus, the failure supposed to occur in the link flange connected at the connection move to the web and to the reduced link flange. Nonlinear FE analysis and experimental investigations have been done on the developed links, and the result shows that the link satisfies the plastic rotation limit recommended in AICS-360-10. Design equations that define the behavior of the proposed link have been recommended, and the equations were verified through the experimental and FE analysis results.

Keywords: EBFs, earthquake disaster, link-to-column connection, reduced link section

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Authors: Shivani Yadav

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The Study of terrorism lends itself to the constructivist framework as constructivism focuses on the importance of ideas and norms in shaping interests and identities. Constructivism is pertinent to understand the phenomenon of a terrorist organization like the Islamic State (IS), which opportunistically utilizes radical ideas and norms to shape its ‘politics of identity’. This ‘identity’, which is at the helm of preferences and interests of actors, in turn, shapes actions. The paper argues that an effective counter-terrorism policy must recognize the importance of ideas in order to counter the threat arising from acts of radicalism and terrorism. Traditional theories of international relations, with an emphasis on state-centric security problematic, exhibit several limitations and problems in interpreting the phenomena of terrorism. With the changing global order, these theories have failed to adapt to the changing dimensions of terrorism, especially ‘newer’ actors like the Islamic State (IS). The paper observes that IS distinguishes itself from other terrorist organizations in the way that it recruits and spreads its propaganda. Not only are its methods different, but also its tools (like social media) are new. Traditionally, too, force alone has rarely been sufficient to counter terrorism, but it seems especially impossible to completely root out an organization like IS. Time is ripe to change the discourse around terrorism and counter-terrorism strategies. The counter-terrorism measures adopted by states, which primarily focus on mitigating threats to the national security of the state, are preoccupied with statist objectives of the continuance of state institutions and maintenance of order. This limitation prevents these theories from addressing the questions of justice and the ‘human’ aspects of ideas and identity. These counter-terrorism strategies adopt a problem-solving approach that attempts to treat the symptoms without diagnosing the disease. Hence, these restrictive strategies fail to look beyond calculated retaliation against violent actions in order to address the underlying causes of discontent pertaining to ‘why’ actors turn violent in the first place. What traditional theories also overlook is that overt acts of violence may have several causal factors behind them, some of which are rooted in the structural state system. Exploring these root causes through the constructivist framework helps to decipher the process of ‘construction of terror’ and to move beyond the ‘what’ in theorization in order to describe ‘why’, ‘how’ and ‘when’ terrorism occurs. Study of terrorism would much benefit from a constructivist analysis in order to explore non-military options while countering the ideology propagated by the IS.

Keywords: constructivism, counter terrorism, Islamic State, politics of identity

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Authors: Wizna, Helmi Muis, Hafil Abbas

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An experiment was conducted to improve the nutrient value of sago pith (Metroxylon sago Rottb) supplemented with Zn, Sulfur and urea through fermentation by using cellulolytic bacteria (Bacillus amyloliquefaciens) as inoculums. The experiment was determination of the optimum dose combination (dosage of Zn, S and urea) for sago pith fermentation based on nutrient quality and quantity of these fermented products. The study was conducted in experimental method, using the completely randomized design in factorial with 3 treatments consist of: factor A (Dose of urea: A1 = 2.0%, A2 = 3.0%), factor B (Dose of S: B1 = 0.2%, B2 = 0.4%) and factor C (Dose of Zn: C1 = 0.0025%, C2 = 0.005%). Results of study showed that optimum condition for fermentation process of sago pith with B. amyloliquefaciens caused a change of nutrient content was obtained at urea (3%), S (0,2%), and Zn (0,0025%). This fermentation process was able to increase amino acid average, reduce crude fiber content by 67% and increase crude protein by 433%, which made the nutritional value of the product based on dry matter was 18.22% crude protein, 12.42% crude fiber, 2525 Kcal/kg metabolic energy and 65.73% nitrogen retention.

Keywords: fermentation, sago pith, sulfur, Zn, urea, Bacillus amyloliquefaciens

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Authors: M. R. Gholizadeh, N. Bhuiyan, M. Salari

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In the near future, companies will be increasingly forced to shift their activities along a new road in order to decrease the harmful effects of their design, production and after-life on our environment. Products must meet environmental standards to not only prevent penalties but to consider the sustainability for future generations. However, the most important factor that companies will face is selecting a reasonable strategy to maximize their profit. Thus, companies need to have precise forecast from their profit after design stage through Trade-off analysis. This paper is an attempt to introduce a mathematical model that considers effective factors that impact the total profit when products are designed for resource and energy efficiency or recyclability. The modification is according to different strategies based on a Cost-Volume-Profit model. Here, the cost structure consists of Recycling cost, Development cost, Ramp-up cost, Production cost, and Pollution cost. Also, the model shows the effect of implementation of design for recyclable on revenue structure through revenue of used parts and revenue of recycled materials. A numerical example is used to evaluate the proposed model. Results show that fulfillment of Green Product Development not only can reduce the environmental impact of products but also it will increase profit of company in long term.

Keywords: green product, design for environment, C-V-P model, trade-off analysis

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Authors: Valencia Fernandes, Dharmendra Kumar Khatri, Shashi Bala Singh

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Background and Aim: Epigenetics are the inaudible signatures of several pathological processes in the brain. This study understands the influence of DNA methylation, a major epigenetic modification, in the prefrontal cortex and hippocampus of the diabetic brain and its notable effect on the cellular chaperones and synaptic proteins. Method: Chronic high fat diet and STZ-induced diabetic mice were studied for cognitive dysfunction, and global DNA methylation, as well as DNA methyltransferase (DNMT) activity, were assessed. Further, the cellular chaperones and synaptic proteins were examined using DNMT inhibitor, 5-aza-2′-deoxycytidine (5-aza-dC)-via intracerebroventricular injection. Moreover, % methylation of these synaptic proteins were also studied so as to correlate its epigenetic involvement. Computationally, its interaction with the DNMT enzyme were also studied using bioinformatic tools. Histological studies for morphological alterations and neuronal degeneration were also studied. Neurogenesis, a characteristic marker for new learning and memory formation, was also assessed via the BrdU staining. Finally, the most important behavioral studies, including the Morris water maze, Y maze, passive avoidance, and Novel object recognition test, were performed to study its cognitive functions. Results: Altered global DNA methylation and increased levels of DNMTs within the nucleus were confirmed in the cortex and hippocampus of the diseased mice, suggesting hypermethylation at a genetic level. Treatment with AzadC, a global DNA demethylating agent, ameliorated the protein and gene expression of the cellular chaperones and synaptic fidelity. Furthermore, the methylation analysis profile showed hypermethylation of the hsf1 protein, a master regulator for chaperones and thus, confirmed the epigenetic involvement in the diseased brain. Morphological improvements and decreased neurodegeneration, along with enhanced neurogenesis in the treatment group, suggest that epigenetic modulations do participate in learning and memory. This is supported by the improved behavioral test battery seen in the treatment group. Conclusion: DNA methylation could possibly accord in dysregulating the memory-associated proteins at chronic stages in type 2 diabetes. This could suggest a substantial contribution to the underlying pathophysiology of several metabolic syndromes like insulin resistance, obesity and also participate in transitioning this damage centrally, such as cognitive dysfunction.

Keywords: epigenetics, cognition, chaperones, DNA methylation

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Authors: Abdelbary Prince, Said Moussa, Hyungkyu Kim, Eman Gouda, Jin Han

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We compared the dynamic alterations of mitochondrial proteome of control, ischemia-reperfusion (IR) and ischemic preconditioned (IPC) rabbit hearts. Using 2-DE, we identified 29 mitochondrial proteins that were differentially expressed in the IR heart compared with the control and IPC hearts. For two of the spots, the expression patterns were confirmed by Western blotting analysis. These proteins included succinate dehydrogenase complex, Acyl-CoA dehydrogenase, carnitine acetyltransferase, dihydrolipoamide dehydrogenase, Atpase, ATP synthase, dihydrolipoamide succinyltransferase, ubiquinol-cytochrome c reductase, translation elongation factor, acyl-CoA dehydrogenase, actin alpha, succinyl-CoA Ligase, dihydrolipoamide S-succinyltransferase, citrate synthase, acetyl-Coenzyme A dehydrogenase, creatine kinase, isocitrate dehydrogenase, pyruvate dehydrogenase, prohibitin, NADH dehydrogenase (ubiquinone) Fe-S protein, enoyl Coenzyme A hydratase, superoxide dismutase [Mn], and 24-kDa subunit of complex I. Interestingly, most of these proteins are associated with the mitochondrial respiratory chain, antioxidant enzyme system, and energy metabolism. The results provide clues as to the cardioprotective mechanism of ischemic preconditioning at the protein level and may serve as potential biomarkers for detection of ischemia-induced cardiac injury.

Keywords: ischemic preconditioning, mitochondria, proteome, cardioprotection

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Authors: Manju Lata Sharma

Abstract:

Damage to cells caused by free radicals is believed to play a central role in the ageing process and in disease progression. Withania somnifera is widely used in ayurvedic medicine, and it is one of the ingredients in many formulations to increase energy, improve overall health and longevity and prevent disease. Withania somnifera possesses antioxidative properties. The antioxdant activity of Withania somnifera consisting of an equimolar concentration of active principles of sitoindoside VII-X and withaferin A. The antioxidant effect of Withania somnifera extract was investigated on lipid peroxidation (LPO), superoxide dismutase (SOD) and catalase (CAT) activity in mice. Aim: To study the antioxidant activity of an extract of Withania somnifera leaf against a mice model of chronic stress. Healthy swiss albino mice (3-4 months old) selected from an inbred colony were divided in to 6 groups. Biochemical estimation revealed that stress induced a significant change in SOD, LPO, CAT AND GPX. These stress induced perturbations were attenuated Withania somnifera (50 and 100 mg/kg BW). Result: Withania somnifera tended to normalize the augmented SOD and LPO activities and enhanced the activities of CAT and GPX. The result indicates that treatment with an alcoholic extract of Withania somnifera produced a significant decrease in LPO ,and an increase in both SOD and CAT in brain mice. This indicates that Withania somnifera extract possesses free radical scavenging activity .

Keywords: Withania somnifera, antioxidant, lipid peroxidation, brain

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Authors: Alexey Abilov

Abstract:

The article highlights the experience of training master's and doctoral students at Satbayev University by preparing their course works for disciplines "Principles of Sustainable Architecture", "Energy Efficiency in Urban planning", "Urban planning analysis, "Social foundations of Architecture". The purpose of these works is the acquisition by students of practical skills necessary in their future professional activities, which are achieved through comprehensive assessment of individual sections of the Almaty urban environment. The methodology of student’s researches carried out under the guidance of the author of this publication is based on an expert assessment of the territory through its full-scale survey, analysis of project documents and statistical data, as well as on a social assessment of the territory based on the results of a questionnaire survey of residents. A comprehensive qualitative and quantitative assessment of the selected sites according to the criteria of the quality of the living environment also allows to formulate specific recommendations for designers who carry out a pre-project analysis of the city territory in the process of preparing draft master plans and detailed planning projects.

Keywords: urban environment, expert/social assessment of the territory, questionnaire survey, comprehensive approach

Procedia PDF Downloads 79