Search results for: settlement architecture cluster

Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: P. Joshna, Souvik Kundu

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Detection of ultraviolet (UV) radiation is very important as it has exhibited a profound influence on humankind and other existences, including military equipment. In this work, a self-powered UV photodetector was reported based on oxides heterojunctions. The thin films of p-type nickel oxide (NiO) and n-type reduced graphene oxide (rGO) were used for the formation of p-n heterojunction. Low-Cost and low-temperature chemical synthesis was utilized to prepare the oxides, and the spin coating technique was employed to deposit those onto indium doped tin oxide (ITO) coated glass substrates. The top electrode platinum was deposited utilizing physical vapor evaporation technique. NiO offers strong UV absorption with high hole mobility, and rGO prevents the recombination rate by separating electrons out from the photogenerated carriers. Several structural characterizations such as x-ray diffraction, atomic force microscope, scanning electron microscope were used to study the materials crystallinity, microstructures, and surface roughness. On one side, the oxides were found to be polycrystalline in nature, and no secondary phases were present. On the other side, surface roughness was found to be low with no pit holes, which depicts the formation of high-quality oxides thin films. Whereas, x-ray photoelectron spectroscopy was employed to study the chemical compositions and oxidation structures. The electrical characterizations such as current-voltage and current response were also performed on the device to determine the responsivity, detectivity, and external quantum efficiency under dark and UV illumination. This p-n heterojunction device offered faster photoresponse and high on-off ratio under 365 nm UV light illumination of zero bias. The device based on the proposed architecture shows the efficacy of the oxides heterojunction for efficient UV photodetection under zero bias, which opens up a new path towards the development of self-powered photodetector for environment and health monitoring sector.

Keywords: chemical synthesis, oxides, photodetectors, spin coating

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Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

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Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

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Authors: Adriana Salgado, Sandra Castaneda, Ivan Perez

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Learning to read and write is a complex process involving several cognitive skills, contextual, and cultural environments. The basis of this development is linguistic skills, such as the ability to name and understand vocabulary, retell a story, phonological awareness, letter knowledge, among others. In children with autism spectrum disorder (ASD), one of the main concerns is related to language disorders. Nevertheless, most of the children with ASD are able to decode written information but have difficulties in reading comprehension. The research of these processes in the Spanish-speaking population is limited. However, the increasing prevalence of this diagnosis (1 in 115 children) in Mexico has implications at different levels. Educational research is an important area of interest in ASD children, such as emergent literacy. Reading and writing expand the possibilities of academic, cultural, and social information access. Taking this information into account, the objective of this research was to identify the relationship between language skills, alphabet knowledge, phonological awareness, and early reading and writing in ASD Spanish-speaking children. The method used for this research was based on tasks that were selected, adapted and in some cases designed to measure initial reading and writing, as well as language skills (naming, receptive vocabulary, and narrative skills), phonological awareness (similar phonological word pairs, beginning sound awareness and spelling) and letter knowledge, in a sample of 45 children (38 boys and 7 girls) with prior diagnosis of ASD. Descriptive analyses, as well as bivariate correlations, cluster analysis, and canonical correspondence, were obtained for the data results. Results showed that variability was large; however, it was possible to characterize the sample in low, medium, and high score groups regarding children performance. The low score group (46.7% of the sample), had a null or deficient performance in language skills and phonological awareness, some could identify up to five letters of the alphabet, showed no early reading skills but they could scribble. The middle score group was characterized by a highly variable performance in different tasks, with better language skills in receptive and naming vocabulary, some narrative, letter knowledge, and phonological awareness (beginning sound awareness) skills. The high score group, (24.4% of the sample) had the best performance in language skills in relation to the sample data, as well as in the rest of the measured skills. Finally, scores were canonically correlated between naming, receptive vocabulary, narrative, phonological awareness, letter knowledge and initial learning of reading and writing skills for the high score group and letter knowledge, naming and receptive vocabulary for the lower score group, which is consistent with previous research in typical and ASD children. In conclusion, the obtained data is consistent with previous studies. Despite large variability, it was possible to identify performance profiles and relations based on linguistic, phonological awareness, and letter knowledge skills. These skills were predictor variables of the initial development of reading and writing. The above has implications for a future program and strategies development that may benefit the acquisition of reading and writing in ASD children.

Keywords: autism, autism spectrum disorders, early literacy, emergent literacy

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Authors: Fouzia Khanam, Belal Hossain, Kaosar Afsana, Mahfuzar Rahman

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Aim: Although cardiovascular diseases (CVD) has already been recognized as a major cause of death in developed countries, its prevalence is rising in developing countries as well, and engendering a challenge for the health sector. Bangladesh has experienced an epidemiological transition from communicable to non-communicable diseases over the last few decades. So, the rising prevalence of CVD and its risk factors are imposing a major problem for the country. We aimed to examine the prevalence of CVDs and socioeconomic and lifestyle factors related to it from a population-based survey. Methods: The data used for this study were collected as a part of a large-scale cross-sectional study conducted to explore the overall health status of children, mothers and senior citizens of Bangladesh. Multistage cluster random sampling procedure was applied by considering unions as clusters and households as the primary sampling unit to select a total of 11,428 households for the base survey. Present analysis encompassed 12338 respondents of ≥ 35 years, selected from both rural areas and urban slums of the country. Socio-economic, demographic and lifestyle information were obtained through individual by a face-to-face interview which was noted in ODK platform. And height, weight, blood pressure and glycosuria were measured using standardized methods. Chi-square test, Univariate modified Poisson regression model, and multivariate modified Poisson regression model were done using STATA software (version 13.0) for analysis. Results: Overall, the prevalence of CVD was 4.51%, of which 1.78% had stroke and 3.17% suffered from heart diseases. Male had higher prevalence of stroke (2.20%) than their counterparts (1.37%). Notably, thirty percent of respondents had high blood pressure and 5% population had diabetes and more than half of the population was pre-hypertensive. Additionally, 20% were overweight, 77% were smoker or consumed smokeless tobacco and 28% of respondents were physically inactive. Eighty-two percent of respondents took extra salt while eating and 29% of respondents had deprived sleep. Furthermore, the prevalence of risk factor of CVD varied according to gender. Women had a higher prevalence of overweight, obesity and diabetes. Women were also less physically active compared to men and took more extra salt. Smoking was lower in women compared to men. Moreover, women slept less compared to their counterpart. After adjusting confounders in modified Poisson regression model, age, gender, occupation, wealth quintile, BMI, extra salt intake, daily sleep, tiredness, diabetes, and hypertension remained as risk factors for CVD. Conclusion: The prevalence of CVD is significant in Bangladesh, and there is an evidence of rising trend for its risk factors such as hypertension, diabetes especially in older population, women and high-income groups. Therefore, in this current epidemiological transition, immediate public health intervention is warranted to address the overwhelming CVD risk.

Keywords: cardiovascular diseases, diabetes, hypertension, stroke

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Andrea Corsale

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The historical and geographical regions of Banat and Crişana in Western Romania have long been characterized by a high degree of ethnic diversity. However, this traditionally complex cultural, linguistic, and religious mosaic has undergone a progressive simplification during the past century due to deportations, emigration, and assimilation, and both regions now have a large Romanian-speaking majority population. This contribution focuses on Jewish heritage in the two largest cities of these two regions, Timişoara (Banat) and Oradea (Crişana). The two cities shared some historical events but also went through different experiences, despite their relative geographic proximity. The Jewish community of Timişoara survived the Holocaust basically intact, an almost unique case in Central-Eastern Europe, but largely left the city after the war. Instead, the Jewish community of Oradea was almost completely deported and killed in Auschwitz, and a renewed post-war community gradually emigrated abroad in the following decades. The two Jewish communities are now very small in size but inherited a vast tangible and intangible heritage (synagogues, cemeteries, community buildings, characteristic architecture, memories, local traditions, and histories), partially restored and recovered in recent years. The author’s fieldwork shows that local Jewish stakeholders are aware of the potential of this heritage in terms of cultural and economic benefits, but significant weaknesses and concerns exist, as the small dimension of these communities, and their financial constraints, challenge their future role in the eventual promotion and management of this heritage, which is now basically in the hands of the non-Jewish public and private stakeholders. Projects, experiences, and views related to Jewish heritage conservation and promotion in these two contexts will be portrayed and analysed in order to contribute to a broader discussion on representations and narratives of minority heritage within cultural tourism development dynamics.

Keywords: Jewish heritage, ethnic minorities, heritage tourism, Romania

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Authors: Carmen W. H. Chan, Helen Y. L. Chan, Kai Chow Choi, Ka Ming Chow, Cecilia W. M. Kwan, Nancy H. Y. Ng, Jackie Robinson

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Introduction: In Hong Kong, a significant number of deaths occur in acute care wards, which requires nurses in these settings to provide end-of-life care and lead ACP implementation. However, nurses in these settings, in fact, have very low-level involvement in ACP discussions because of limited training in ACP conversations. Objective: This study aims to assess the impact of a multi-media experiential ACP (MEACP) training program, which is guided by the experiential learning model and theory of planned behaviour, on nurses' knowledge and confidence in assisting patients with ACP. Methodology: The study utilizes a cluster randomized controlled trial with a 12-week follow-up. Eligible nurses working in acute care hospital wards are randomly assigned at the ward level, in a 1:1 ratio, to either the control group (no ACP education) or the intervention group (4-week MEACP training program). The training programme includes training through a webpage and mobile application, as well as a face-to-face training workshop with enhanced lectures and role play, which is based on the Theory of Planned Behavior and Kolb's Experiential Learning Model. Questionnaires were distributed to assess nurses' knowledge (a 10-item true/false questionnaire) and level of confidence (five-point Likert scale) in ACP at baseline (T0), four weeks after the baseline assessment (T1), and 12 weeks after T1 (T2). In this interim report, data analysis was mainly descriptive in nature. Result: The interim report focuses on the preliminary results of 165 nurses at T0 (Control: 74, Intervention: 91) over a 5-month period, 69 nurses from the control group who completed the 4-week follow-up and 65 nurses from the intervention group who completed the 4-week MEACP training program at T1. The preliminary attrition rate is 6.8% and 28.6% for the control and intervention groups, respectively, as some nurses did not complete the whole set of online modules. At baseline, the two groups were generally homogeneous in terms of their years of nursing practice, weekly working hours, working title, and level of education, as well as ACP knowledge and confidence levels. The proportion of nurses who answered all ten knowledge questions correctly increased from 13.8% (T0) to 66.2% (T1) for the intervention group and from 13% (T0) to 20.3% (T1) for the control group. The nurses in the intervention group answered an average of 7.57 and 9.43 questions correctly at T0 and T1, respectively. They showed a greater improvement in the knowledge assessment at T1 with respect to T0 when compared with their counterparts in the control group (mean difference of change score, Δ=1.22). They also exhibited a greater gain in level of confidence at T1 compared to their colleagues in the control group (Δ=0.91). T2 data is yet available. Conclusion: The prevalence of nurses engaging in ACP and their level of knowledge about ACP in Hong Kong is low. The MEACP training program can enrich nurses by providing them with more knowledge about ACP and increasing their confidence in conducting ACP.

Keywords: advance directive, advance care planning, confidence, knowledge, multi-media experiential, randomised control trial

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Authors: Mahnoor Shoaib

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Sustainable development involves meeting present needs without compromising future generations’ capacity to meet their own while enhancing the quality of life through a healthy and safe environment. In the context of rapid urbanization and globalization, architects and planners bear the responsibility of designing residential buildings that are sustainable and conducive to quality living. Residential buildings serve as multifunctional spaces for personal and family life, making them essential for fostering healthy communities. Therefore, sustainable housing must address not only economic and environmental factors but also social, historical, and cultural dimensions to enhance residents' social lives. This research investigates the socio-cultural aspects of tall residential buildings in Karachi, Pakistan, a developing community characterized by rapid population growth and urbanization. A mixed-methods approach, including qualitative interviews and surveys, was employed to assess residents' perceptions of sustainability in tall buildings, focusing on socio-cultural design constraints and their impact on residential satisfaction. The study finds that socio-cultural elements, such as liveability, social cohesion, and spatial agency, significantly influence residents’ satisfaction with high-rise developments. Moreover, it highlights the need for contextual design solutions that integrate local cultural values into the architecture of tall buildings rather than imposing Western design principles. In conclusion, this research provides valuable insights for architects, designers, and urban planners, emphasizing the importance of understanding community needs and preferences in developing sustainable residential environments. By prioritizing socio-cultural sustainability, we can enhance the overall quality of life for residents in tall buildings, contributing to healthier and more vibrant communities.

Keywords: high-rise residential buildings, quality of life, social cohesion, socio-cultural sustainability

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Authors: Feyzan Tuzkaya, Nihan S. Soylu, Caglar Solak, Mehmet Peker, Hilal Peker, Kemal Ozeralp, Ceren Mete, Ezgi Mehmetoglu, Mehmet Karasu, Cihan Elci, Ece Akca, Melek Goregenli

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Perception, evaluation and representation of the environment have been the subject of many disciplines including psychology, geography and architecture. In environmental and social psychology literature there are several evidences which suggest that cognitive representations about a place consisted of not only geographic items but also social and cultural. Mental representations of residence area or a country is influenced and determined by social-demographics, the physical and social context. Thus, all mental representations of a given place are also social representations. Cognitive maps are the main and common instruments that are used to identify spatial images and the difference between physical and subjective environments. The aim of the current study is investigating the mental and social representations of Turkey in university students’ minds. Data was collected from 249 university students from different departments (i.e. psychology, geography, history, tourism departments) of Ege University. Participants were requested to reflect Turkey in their mind onto the paper drawing sketch maps. According to the results, cognitive maps showed geographic aspects of Turkey as well as the context of symbolic, cultural and political reality of Turkey. That is to say, these maps had many symbolic and verbal items related to critics on social and cultural problems, ongoing ethnic and political conflicts, and actual political agenda of Turkey. Additionally, one of main differentiations in these representations appeared in terms of the East and West side of the Turkey, and the representations of the East and West was varied correspondingly participants’ cultural background, their ethnic values, and where they have born. The results of the study were discussed in environmental and social psychological perspective considering cultural and social values of Turkey and current political circumstances of the country.

Keywords: cognitive maps, East, West, politics, social representations, Turkey

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: P. Caimmi, E. Bele, A. Abolfathi

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Lattice materials are cellular structures composed of a periodic network of beams. They offer high weight-specific mechanical properties and lend themselves to numerous weight-sensitive applications. The periodic internal structure responds to external vibrations through characteristic frequency bandgaps, making these materials suitable for the reduction of noise and vibration. However, the deviation from architectural homogeneity, due to, e.g., manufacturing imperfections, has a strong influence on the mechanical properties and vibration response of these materials. In this work, we present results on the influence of geometric imperfections on the vibration response of hexagonal lattices. Three classes of geometrical variables are used: the characteristics of the architecture (relative density, ligament length/cell size ratio), imperfection type (degree of non-periodicity, cracks, hard inclusions) and defect morphology (size, distribution). Test specimens with controlled size and distribution of imperfections are manufactured through selective laser sintering. The Frequency Response Functions (FRFs) in the form of accelerance are measured, and the modal shapes are captured through a high-speed camera. The finite element method is used to provide insights on the extension of these results to semi-infinite lattices. An updating procedure is conducted to increase the reliability of numerical simulation results compared to experimental measurements. This is achieved by updating the boundary conditions and material stiffness. Variations in FRFs of periodic structures due to changes in the relative density of the constituent unit cell are analysed. The effects of geometric imperfections on the dynamic response of periodic structures are investigated. The findings can be used to open up the opportunity for tailoring these lattice materials to achieve optimal amplitude attenuations at specific frequency ranges.

Keywords: lattice architectures, geometric imperfections, vibration attenuation, experimental modal analysis

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Authors: Dalma Varga, Nora Hubayne H.

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Nowadays, among the measures taken to offset the consequences of climate change, water resources management is one of the key tools, which can include excess water management. As a result of climate change’s effects and as a result of the frequent inappropriate landuse, more and more areas are affected by the excess water inundation. Hungary is located in the deepest part of the Pannonian Basin, which is exposed to water damage – especially lowland areas that are endangered by floods or excess waters. The periodical presence of excess water creates specific habitats in a given area, which have ecological, functional, and aesthetic values. Excess water inundation affects approximately 74% of Hungary’s lowland areas, of which about 46% is also under nature protection (such as national parks, protected landscape areas, nature conservation areas, Natura 2000 sites, etc.). These data prove that areas exposed to excess water inundation – which are predominantly characterized by agricultural land uses – have an important ecological role. Other research works have confirmed the presence of numerous rare and endangered plant species in drainage canals, on grasslands exposed to excess water, and on special agricultural fields with mud vegetation. The goal of this research is to define and analyze ecosystem services of areas exposed to excess water inundation. In addition to this, it is also important to determine the quantified indicators of these areas’ natural and landscape values besides the presence of protected species and the naturalness of habitats, so all in all, to analyze the various nature protections related to excess water. As a result, a practice-orientated assessment method has been developed that provides the ecological water demand, assimilates to ecological and habitat aspects, contributes to adaptive excess water management, and last but not least, increases or maintains the share of the green infrastructure network. In this way, it also contributes to reduce and mitigate the negative effects of climate change.

Keywords: ecosystem services, landscape architecture, excess water management, green infrastructure planning

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Authors: Muhammad Shuaibu Birniwa

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Automobile Independent Workshop Service Technicians (popularly called roadside mechanics) are technical personals that repairs most of the automobile vehicles in Nigeria. Majority of these mechanics acquired their skills through apprenticeship training. Modern vehicle imported into the country posed greater challenges to the present automobile technicians particularly in the area of carrying out maintenance repairs of these latest automobile vehicles (autotronics vehicle) due to their inability to possessed autotronic skills competency. To source for solution to the above mentioned problems, therefore a research is carried out in North – Western region of Nigeria to produce a suitable maintenance training modules that can be used to train the technicians for them to upgrade/acquire the needed competencies for successful maintenance repair of the autotronic vehicles that were running everyday on the nation’s roads. A cluster sampling technique is used to obtain a sample from the population. The population of the study is all autotronic inclined lecturers, instructors and independent workshop service technicians that are within North – Western region of Nigeria. There are seven states (Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto and Zamfara) in the study area, these serves as clusters in the population. Five (5) states were randomly selected to serve as the sample size. The five states are Jigawa, Kano, Katsina, Kebbi and Zamfara, the entire population of the five states which serves as clusters is (183), lecturers (44), instructors (49) and autotronic independent workshop service technicians (90), all of them were used in the study because of their manageable size. 183 copies of autotronic maintenance training module questionnaires (AMTMQ) with 174 and 149 question items respectively were administered and collected by the researcher with the help of an assistants, they are administered to 44 Polytechnic lecturers in the department of mechanical engineering, 49 instructors in skills acquisition centres/polytechnics and 90 master craftsmen of an independent workshops that are autotronic inclined. Data collected for answering research questions 1, 3, 4 and 5 were analysed using SPSS software version 22, Grand Mean and standard deviation were used to answer the research questions. Analysis of Variance (ANOVA) was used to test null hypotheses one (1) to three (3) and t-test statistical tool is used to analyzed hypotheses four (4) and five (5) all at 0.05 level of significance. The research conducted revealed that; all the objectives, contents/tasks, facilities, delivery systems and evaluation techniques contained in the questionnaire were required for the development of the autotronic maintenance training modules for independent workshop service technicians in the north – western zone of Nigeria. The skills upgrade training conducted by federal government in collaboration with SURE-P, NAC and SMEDEN was not successful because the educational status of the target population was not considered in drafting the needed training modules. The mode of training used does not also take cognizance of the theoretical aspect of the trainees, especially basic science which rendered the programme ineffective and insufficient for the tasks on ground.

Keywords: autotronics, roadside, mechanics, technicians, independent

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Authors: P. Defossez, J. M. Bonnefond, D. Garrigou, P. Trichet, F. Danjon

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Windstorm damage to European forests has ecological, social and economic consequences of major importance. Most trees during storms are uprooted. While a large amount of work has been done over the last decade on understanding the aerial tree response to turbulent wind flow, much less is known about the root-soil interface, and the impact of soil moisture and root-soil system fatiguing on tree uprooting. Anchorage strength is expected to be reduced by water-logging and heavy rain during storms due to soil strength decrease with soil water content. Our paper is focused on the maritime pine cultivated on sandy soil, as a representative species of the Forêt des Landes, the largest cultivated forest in Europe. This study aims at providing knowledge on the effects of soil saturation on root anchorage. Pulling experiments on trees were performed to characterize the resistance to wind by measuring the critical bending moment (Mc). Pulling tests were performed on 12 maritime pines of 13-years old for two unsaturated soil conditions that represent the soil conditions expected in winter when wind storms occur in France (w=11.46 to 23.34 % gg⁻¹). A magnetic field digitizing technique was used to characterize the three-dimensional architecture of root systems. The soil mechanical properties as function of soil water content were characterized by laboratory mechanical measurements as function of soil water content and soil porosity on remolded samples using direct shear tests at low confining pressure ( < 15 kPa). Remarkably Mc did not depend on w but mainly on the root system morphology. We suggested that the importance of soil water conditions on tree anchorage depends on the tree size. This study gives a new insight on young tree anchorage: roots may sustain by themselves anchorage, whereas adhesion between roots and surrounding soil may be negligible in sandy soil.

Keywords: roots, sandy soil, shear strength, tree anchorage, unsaturated soil

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Authors: Robin Ferguson

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The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

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Authors: Mohd Imtiaz S, Saurabh Jain, Pothiraj K.

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In today’s highly competitive passenger vehicle market, comfortable driving experience is one of the key parameters significantly weighed by the customer. Smooth ride and handling of the vehicle with exceptionally reliable wheel end solution is a paramount requirement in passenger Sports Utility Vehicle (SUV) vehicles subjected to challenging terrains and loads with rigid rear drive axle configuration. Traditional wheel-end bearing systems in passenger segment rigid rear drive axle utilizes the semi-floating layout, which imparts vertical bending loads and torsion to the axle shafts. The wheel-end bearing is usually a Single or Double Row Deep-Groove Ball Bearing (DRDGBB) or Double Row Angular Contact Ball Bearing (DRACBB). This solution is cost effective and simple in architecture. However, it lacks effectiveness against the heavy loads subjected to a SUV vehicle, especially the axial trust at high-speed cornering. This paper describes the solution of Double Row Taper Roller Bearing (DRTRB) wheel-end for a SUV vehicle in the rigid rear drive axle and improvement in terms of maximizing its load carrying capacity along with better reliability in terms of axial thrust in high-speed cornering. It describes the advantage of geometry of DRTRB over DRDGBB and DRACBB highlighting contact and load flow. The paper also highlights the vehicle level considerations affecting the B10 life of the bearing system for better selection of the DRTRB wheel-ends systems. This paper also describes real time vehicle level results along with theoretical improvements.

Keywords: axial thrust, b10 life, deep-groove ball bearing, taper roller bearing, semi-floating layout.

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Noor Abdelhamid, Donovan Nelson, Cara Prosser

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The architectural design process could be mapped out as a dialogue between designer and user that is constructed across multiple phases with the overarching goal of aligning design outcomes with user needs. Traditionally, this dialogue is bounded within a preliminary phase of determining factors that will direct the design intent, and a completion phase, of handing off the project to the client. Pre- and post-occupancy evaluations (P/POE’s) could provide an alternative process by extending this dialogue on both ends of the design process. The purpose of this research is to study the influence of systematic pre-occupancy data collection in achieving design goals by conducting post-occupancy evaluations of two case studies. In the context of this study, systematic pre-occupancy data collection is defined as the preliminary documentation of the existing conditions that helps portray stakeholders’ needs. When implemented, pre-occupancy occurs during the early phases of the architectural design process, utilizing the information to shape the design intent. Investigative POE’s are performed on two case studies with distinct early design approaches to understand how the current space is impacting user needs, establish design outcomes, and inform future strategies. The first case study underwent systematic pre-occupancy data collection and synthesis, while the other represents the traditional, uncoordinated practice of informally collecting data during an early design phase. POE’s target the dynamics between the building and its occupants by studying how spaces are serving the needs of the users. Data collection for this study consists of user surveys, audiovisual materials, and observations during regular site visits. Mixed methods of qualitative and quantitative analyses are synthesized to identify patterns in the data. The paper concludes by positioning value on both sides of the architectural design process: the integration of systematic pre-occupancy methods in the early phases and the reinforcement of a continued dialogue between building and design team after building completion.

Keywords: architecture, design process, pre-occupancy data, post-occupancy evaluation

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Authors: Maryam Radan, Fereshteh Nejad Dehbashi, Vahid Bayati, Mahin Dianat, Seyyed Ali Mard, Zahra Mansouri

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Pulmonary emphysema is a pathological respiratory condition identified by alveolar destruction which leads to limitation of airflow and diminished lung function. A substantial body of evidence suggests that mesenchymal stem cells (MSCs) have the ability to induce tissue repair primarily through a paracrine effect. In this study, we aimed to determine the efficacy of Intratracheal adipose-derived mesenchymal stem cells (ADSCs) therapy in comparison to this approach with that of Intravenous (Systemic) therapy. Fifty adult male Sprague–Dawley rats weighing between 180 and 200 g were used in this experiment. The animals were randomized to Control groups (Intratracheal or Intravenous vehicle), Elastase group (intratracheal administration of porcine pancreatic elastase; 25 U/kg on day 0 and day 10th), Elastase+Intratracheal ADSCs therapy (1x107 Cells, on day 28) and Elastase+Systemic ADSCs therapy (1x107 Cells, on day 28). The rats which not subjected to any treatment, considered as the control. All rats were sacrificed 3 weeks later. Morphometric findings in lung tissues (Mean linear intercept) confirmed the establishment of the emphysema model via alveolar disruption. Contrarily, ADSCs administration partially restored alveolar architecture. These results were associated with improving arterial oxygenation, reducing lung edema, and decreasing lung inflammation with higher significant effects in the Intratracheal therapy route. These results documented that the efficacy of intratracheal ADSCs was comparable with intravenous ADSCs therapy. Accordingly, the obtained data suggested that intratracheal delivery of ADSCs would enhance lung repair in pulmonary emphysema. Moreover, this method provides benefits over a systemic administration, such as the reduction of cell number and the low risk to engraft other organs.

Keywords: mesenchymal stem cell, emphysema, Intratracheal, systemic

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Authors: Yousef Reda

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Pancreatic cancer has an overall dismal prognosis. CT, MRI and Endoscopic Ultrasound are most often used to establish the diagnosis. We present a case of a patient found on abdominal CT and MRI to have an 8 mm cystic lesion within the head of the pancreas which was thought to be a benign intraductal papillary mucinous neoplasm (IPMN). Further evaluation by EUS demonstrated a 1 cm predominantly solid mass that was proven to be an adenocarcinoma by EUS-guided FNA. The patient underwent a Whipple procedure. The final pathology confirmed a 1 cm pT1 N0 pancreatic ductal adenocarcinoma. Case: A 63-year-old male presented with left upper quadrant pain and an abdominal CT demonstrated an 8 mm lesion within the head of the pancreas that was thought to represent a side branch IPMN. An MRI also showed similar findings. Four months later due to ongoing symptoms an EUS was performed to re-evaluate the pancreatic lesion. EUS revealed a predominantly solid hypoechoic, homogeneous mass measuring 12 mm x 9 mm. EUS-guided FNA was performed and was positive for adenocarcinoma. The patient underwent a Whipple procedure that confirmed it to be a ductal adenocarcinoma, pT1N0. The solid mass was noted to be adjacent to a cystic dilation with no papillary architecture and scant epithelium. The differential diagnosis resided between cystic degeneration of a primary pancreatic adenocarcinoma versus malignant degeneration within a side-branch IPMN. Discussion: The reported sensitivity of CT for pancreatic cancer is approximately 90%. For pancreatic tumors, less than 3 cm the sensitivity of CT is reduced ranging from 67-77%. MRI does not significantly improve overall detection rates compared to CT. EUS, however is superior to CT in the detection of pancreatic cancer, in particular among lesions smaller than 3 cm. EUS also outperforms CT and MRI in distinguishing neoplastic from non-neoplastic cysts. In this case, both MRI and CT failed to detect a small pancreatic adenocarcinoma. The addition of EUS and FNA to abdominal imaging can increase overall accuracy for the diagnosis of neoplastic pancreatic lesions. It may be prudent that when small lesions although appearing as a benign IPMN should further be evaluated by EUS as this would lead to potentially identifying earlier stage pancreatic cancers and improve survival in a disease which has a dismal prognosis.

Keywords: IPMN, MRI, EUS, CT

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Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

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Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

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Authors: Daniel Gidey, Kunwar Siddarth Dadhwal

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By evaluating India's aid systems and ongoing development initiatives, this conference paper offers light on India's role as a source of developmental assistance in Africa. This research attempts to provide insights into the developing landscape of foreign aid and development cooperation by focusing on understanding India's motivations and strategy. In recent years, India's connection with Africa has grown significantly, driven by economic, political, and strategic reasons. This conference paper covers India's many forms of aid, including financial, capacity building efforts, technical assistance, and infrastructure development projects, via a thorough investigation. The article seeks to establish India's priorities and highlight the possible impacts of its development assistance in Africa by examining the industries and locations of concentration. Using secondary data sources, the investigation delves into the underlying goals of India's aid policy in Africa. It investigates whether India's development assistance is consistent with its broader geopolitical aims, such as access to resources, competing with regional rivals, or strengthening diplomatic ties. Furthermore, the article investigates how India's aid policy combines the ideals of South-South cooperation and mutual development, as well as the ramifications for recipient countries. Furthermore, the paper assesses the efficacy and sustainability of India's aid operations in Africa. It takes into account the elements that influence their success, the problems they face, and the amount to which they contribute to local development goals, community empowerment, and poverty alleviation. The study also focuses on the accountability systems, transparency, and knowledge transfer aspects of India's development assistance. By providing a detailed examination of India's aid endeavors in Africa, the paper adds to the current literature on international development cooperation. By offering fresh insights into the motives, strategies, and impacts of India's assistance programs, it seeks to enhance understanding of the emerging patterns in South-South cooperation and the complex dynamics of contemporary international aid architecture.

Keywords: India, Africa, developmental assistance, aid projects and South-South cooperation

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: Theodore Panton

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As cities in the United States experience critical housing shortages, mass timber presents the opportunity to address this crisis in housing supply while taking advantage of the carbon-positive benefits of sustainably forested wood fiber. Mass timber, however, currently has a low level of adoption in residential multifamily structures due to the risk-averse nature of change within the construction financing, Architecture / Engineering / Contracting (AEC) communities, as well as various agency approval challenges. This study demonstrates how mass timber can be used within the cost and feasibility parameters of a typical multistory residential structure and ultimately address the need for dense urban housing. This study will utilize The Garden District, a mixed-use market-rate housing project in Woodinville, Washington, as a case study to illuminate the potential of mass timber in this application. The Garden District is currently in final stages of permit approval and will commence construction in 2023. It will be the tallest dowel-laminated timber (DLT) residential structure in the United States when completed. This case study includes economic, technical, and design reference points to demonstrate the relevance of the use of this system and its ability to deliver “triple bottom line” results. In terms of results, the study establishes scalable and repeatable approaches to project design and delivery of mass timber in multifamily residential uses and includes economic data, technical solutions, and a summary of end-user advantages. This study discusses the third party tested systems for satisfying acoustical requirements within dwelling units, a key to resolving the use of mass timber within multistory residential use. Lastly, the study will also compare the mass timber solution with a comparable cold formed steel (CFS) system with a similar program, which indicates a net carbon savings of over three million tons over the life cycle of the building.

Keywords: DLT, dowell laminated timber, mass timber, market rate multifamily

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Authors: O. Wright, N. Perkins, M. Donn, M. Halstead

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This research responded to anecdotal evidence that suggested inefficiencies within the Architect and Acoustician relationship may lead to ineffective acoustic design decisions.  The acoustician spoken to believed that he was approached too late in the design phase. The approached architect valued acoustical qualities, yet, struggled to interpret common measurement parameters. The preliminary investigation of these opinions indicated a gap in the current New Zealand Architectural discourse and currently informs the creation of a 2016 Master of Architecture (Prof) thesis research. Little meaningful information about acoustic intervention in the early design phase could be found from past literature. In the information that was sourced, authors focus on software as an incorporation tool without investigating why the flaws in the relationship originally exist. To further explore this relationship, a survey was designed. It underwent three phases to ensure its consistency, and was delivered to a group of 51 acousticians from one international Acoustics company. The results were then separated between New Zealand and off-shore to identify trends. The survey results suggest that 75% of acousticians meet the architect less than 5 times per project. Instead of regular contact, a mediated method is adopted though a mix of telecommunication and written reports. Acousticians tend to be introduced later into New Zealand building project than the corresponding off-shore building. This delay corresponds to an increase in remedial action for each of the building types in the survey except Auditoria and Office Buildings. 31 participants have had their specifications challenged by an architect. Furthermore, 71% of the acousticians believe that architects do not have the knowledge to understand why the acoustic specifications are in place. The issues raised in this investigation align to the colloquial evidence expressed by the two consultants. It identifies a larger gap in the industry were acoustics is remedially treated rather than identified as a possible design driver. Further research through design is suggested to understand the role of acoustics within architectural design and potential tools for its inclusion during, not after, the design process.

Keywords: architectural acoustics, early-design, interdisciplinary communication, remedial response

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Authors: Elif D. Oguz Erkal, David Krackhardt, Erica Cochran-Hameen

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Even though social network analysis (SNA) is an abundantly studied concept for many organizations and industries, a clear SNA approach to the project teams has not yet been adopted by the construction industry. The main challenges for performing SNA in construction and the apparent reason for this gap is the unique and complex structure of each construction project, the comparatively high circulation of project team members/contributing parties and the variety of authentic problems for each project. Additionally, there are stakeholders from a variety of professional backgrounds collaborating in a high-stress environment fueled by time and cost constraints. Within this case study on Project RE, a design & build project performed at the Urban Design Build Studio of Carnegie Mellon University, social network analysis of the project design team will be performed with the main goal of applying social network theory to construction project environments. The research objective is to determine a correlation between the network of how individuals relate to each other on one’s perception of their own professional strengths and weaknesses and the communication patterns within the team and the group dynamics. Data is collected through a survey performed over four rounds conducted monthly, detailed follow-up interviews and constant observations to assess the natural alteration in the network with the effect of time. The data collected is processed by the means of network analytics and in the light of the qualitative data collected with observations and individual interviews. This paper presents the full ethnography of this construction design team of fourteen architecture students based on an elaborate social network data analysis over time. This study is expected to be used as an initial step to perform a refined, targeted and large-scale social network data collection in construction projects in order to deduce the impacts of social networks on project performance and suggest better collaboration structures for construction project teams henceforth.

Keywords: construction design teams, construction project management, social network analysis, team collaboration, network analytics

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Authors: Roya Morad, W. Eirik Heintz

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The identity of a neighborhood is inevitably shaped by the architecture and the people of that place. Conventionally the streets within each neighborhood served as a semi-public-private extension of the private living spaces. The street as a design element formed a hybrid condition that was neither totally public nor private, and it encouraged social interactions. Thus through creating a sense of community, one of the most basic human needs of belonging was achieved. Similar to major global cities, Tehran has undergone serious urbanization. Developing into a capital city of high rises has resulted in an increase in urban density. Although allocating more residential units in each neighborhood was a critical response to the population boom and the limited land area of the city, it also created a crisis in terms of social communication and place attachment. District 10 in Tehran is a neighborhood that has undergone the most urban transformation among the other 22 districts in the capital and currently has the highest population density. This paper will explore how the active streets in district 10 have changed into their current condition of high rises with a lack of meaningful social interactions amongst its inhabitants. A residential building can be thought of as a large group of people. One would think that as the number of people increases, the opportunities for social communications would increase as well. However, according to the survey, there is an indirect relationship between the two. As the number of people of a residential building increases, the quality of each acquaintance reduces, and the depth of relationships between people tends to decrease. This comes from the anonymity of being part of a crowd and the lack of social spaces characterized by most high-rise apartment buildings. Without a sense of community, the attachment to a neighborhood is decreased. This paper further explores how the neighborhood participates to fulfill ones need for social interaction and focuses on the qualitative aspects of alternative spaces that can redevelop the sense of place attachment within the community.

Keywords: high density, place attachment, social communication, street life, urban transformation

Procedia PDF Downloads 127