Search results for: hostel building

Authors: Pouya Kaafi, Gholamreza Ghodrati Amiri

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Abnormal loads due to natural events, implementation errors and some other issues can lead to occurrence of progressive collapse in structures. Most of the past researches consist of 2- Dimensional (2D) models of steel frames without consideration of the floor system effects, which reduces the accuracy of the modeling. While employing a 3-Dimensional (3D) model and modeling the concrete slab system for the floors have a crucial role in the progressive collapse evaluation. In this research, a 3D finite element model of a 5-story steel building is modeled by the ABAQUS software once with modeling the slabs, and the next time without considering them. Then, the progressive collapse potential is evaluated. The results of the analyses indicate that the lack of the consideration of the slabs during the analyses, can lead to inaccuracy in assessing the progressive failure potential of the structure.

Keywords: abnormal loads, composite floor system, intermediate steel moment resisting frame system, progressive collapse

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Authors: Ivan Balachin, Geanette Polanco, Jiang Xingliang, Hu Qin

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The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified.

Keywords: field data processing, regression determination, wind turbine performance, wind turbine placing, yaw system losses

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Authors: Cecilia Amponsem-Boateng, Timothy B. Oppong, Haiyan Yang, Guangcai Duan

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The human palm has been identified as one of the richest habitats for human microbial accommodation making hand hygiene essential to primary prevention of infection. Since the hand is in constant contact with fomites which have been proven to be mostly contaminated, building hand hygiene habits is essential for the prevention of infection. This research was conducted to assess the hand hygiene habits of Ghanaian youths in Accra. This study used a survey as a quantitative method of research. The findings of the study revealed that out of the 254 participants who fully answered the questionnaire, 22% had the habit of washing their hands after outings while only 51.6% had the habit of washing their hands after using the bathroom. However, about 60% of the participants said they sometimes ate with their hands while 28.9% had the habit of eating with the hand very often, a situation that put them at risk of infection from their hands since some participants had poor handwashing habits; prompting the need for continuous education on hand hygiene.

Keywords: hand hygiene, hand hygiene habit, hand washing, hand sanitizer use

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Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

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Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

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Authors: Milind Anurag

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This study investigates cutting-edge truss design improvements, which are specifically adapted to satisfy the structural demands and difficulties associated with high-performance facades and roofs in modern architectural environments. With a growing emphasis on sustainability, energy efficiency, and eye-catching architectural aesthetics, the structural components that support these characteristics play an important part in attaining the right balance of form and function. The paper seeks to contribute to the evolution of truss design methods by combining data from these investigations, giving significant insights for architects, engineers, and researchers interested in the creation of high-performance building envelopes. The findings of this study are meant to inform future design standards and practices, promoting the development of structures that seamlessly integrate architectural innovation with structural robustness and environmental responsibility.

Keywords: truss design, high-performance, facades, finite element analysis, structural efficiency

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

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Authors: Aravind J.

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Passive design can be referred to a way of designing buildings that takes advantage of the prevailing climate and natural energy resources. Which will be a key to reduce the increasing energy usage in commercial buildings. Most of the small scale commercial buildings made are merely a thermal mass inbuilt with active systems to bring lively conditions. By bringing the passive design strategies for energy efficiency in commercial buildings will reduce the usage of active systems. Thus the energy usage can be controlled through analysis of daylighting and improved living conditions in the indoor spaces by using passive techniques. And comparative study on different passive design systems and conventional methods will be approached for commercial buildings in hot and humid region. Possible effects of existing risks implied with solution for those problems is also a part of the paper. The result will be carried on with the design programme to prove the workability of the strategies.

Keywords: passive design, energy efficiency, commercial buildings, hot and humid climate

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Authors: Mustafa Kara, Yasemin Kilic, Bahattin Murat Demir, Ümit Ustaoglu, Cavit Unal

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This paper reports utilization of different kind of construction and demolition wastes (C&D) in the production of bricks at industrial scale. Plastered brick waste and tile wastes were collected from ISTAÇ Co. Compost and Recovery Plant, Istanbul, Turkey. Plastered brick waste and tile waste are mixed with brick clay in the proportion of 0-30% and fired at 900ºC. The physical and mechanical properties of the produced bricks were determined and evaluated according to IKIZLER Brick Company Production values, Brick Industry Association (BIA) and Turkish Standards (TS). The resulted showed that plastered brick waste and tile waste can be used to produce good quality brick for various engineering applications in construction and building. The replacement of brick clay by plastered brick waste and tile waste at the levels of 30% has good effects on the compressive strength of the bricks.

Keywords: commercial brick, construction and demolition waste, manufacturing, recycling

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Authors: İsmail İnce, Osman Günaydin, Fatma Özer

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Stones used in the construction of historical structures are exposed to various direct or indirect atmospheric effects depending on climatic conditions. Building stones deteriorate partially or fully as a result of this exposure. The historic structures are important symbols of any cultural heritage. Therefore, it is important to protect and restore these historical structures. The aim of this study is to determine the weathering conditions at the Kilistra ancient city. It is located in the southwest of the Konya city, Central Anatolia, and was built by carving into pyroclastic rocks during the Byzantine Era. For this purpose, the petrographic and mechanical properties of the pyroclastic rocks were determined. In the assessment of weathering of structures in the ancient city, in-situ non-destructive testing (i.e., Schmidt hardness rebound value, relative humidity measurement) methods were applied.

Keywords: cultural heritage, Kilistra ancient city, non-destructive techniques, weathering

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Authors: Viktória Sugár, Attila Talamon, András Horkai, Michihiro Kita

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The dense urban fabric of the 7^th district of Budapest -known as the former Jewish Quarter-, contains mainly historical style, multi-story tenement houses with courtyards. The high population density and the unsatisfactory energetic state of the buildings result high energy consumption. As a preliminary survey of a complex rehabilitation plan, the authors aim to determine the energy demand of the area. The energy demand was calculated by analyzing the structure and the energy consumption of each building by using Geographic Information System (GIS) methods. The carbon dioxide emission was also calculated, to assess the potential of reducing the present state value by complex structural and energetic rehabilitation. As a main focus of the survey, an energy intensity map has been created about the area.

Keywords: CO₂, energy intensity map, geographic information system (GIS), Hungary, Jewish quarter, rehabilitation

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Authors: Sarah Faulkner, Patrick Faulkner, Caroline Ellison

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Improved mental and physical health, community connection, and increased life satisfaction has been strongly associated with bike riding for those with and without a disability. However, much evidence suggests that people living with a disability face increased barriers to engaging in cycling compared to members of the general population. People with an intellectual disability often live more sedentary and socially isolated lives that negatively impact their mental and physical health, as well as life satisfaction. This paper is based on preliminary findings from a three-year intervention cycling project funded by the South Australian Government. The cycling project was developed in partnership with community stakeholders that provided weekly instruction, training, and support to individuals living with intellectual disabilities to increase their capacity in cycling. This project aimed to support people living with intellectual disabilities to foster and facilitate improved physical and mental health, confidence, and independence and enhance social networking through their engagement in community cycling. The program applied principles of social role valorisation (SRV) theory as its guiding framework. Preliminary data collected is based on qualitative interviews with over 50 program participants, results from two participant wellness questionnaires, as well as a perceptually regulated exercise test administered throughout the project implementation. Preliminary findings are further supplemented with ethnographic analyses by the researchers who took a phenology of life experience approach. Preliminary findings of the program suggest a variety of social motivations behind participants' desire to learn cycling that acknowledges previous barriers to engagement and cycling’s role to address feelings of loneliness and social isolation. Meaningful health benefits can be achieved as demonstrated by increases in predicted V02 max measures, suggesting that physical intervention can not only improve physical health outcomes but also provide a variety of other social benefits. Initial engagement in the project has demonstrated an increase in participants' sense of confidence, well-being, and physical fitness. Implementation of the project in partnership with a variety of community stakeholders has identified a number of critical factors and processes necessary for future service replication, sustainability, and success. Findings from this intervention study contribute to the development of a knowledge base on how best to support individuals living with an intellectual disability to partake in bike riding and increase positive outcomes associated with their capacity building, social interaction, increased physical activity, physical health, and mental well-being. The initial findings of this study provide critical academic insights into the social and physical benefits of cycling for people living with a disability, as well as practical advice for future human service applications.

Keywords: cycling, disability, social inclusion, capacity building

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Authors: Qinglei Liu, Ali Charkhesht, Tiva Sharifi, Ashkan Bahadoran

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Graphene sheets are promising nanoscale building blocks as a support material for the dispersion of nanoparticles. In this work, a solvothermal method employed to directly grow Co1-xZnxFe2O4 ferrite nanospheres on graphene oxide support that is subsequently reduced to graphene. The samples morphology, structure and crystallography were investigated using field-emission scanning electron microscopy (FE-SEM) and powder X-ray diffraction (XRD). The influences of the Zn2+ content on photocatalytic activity, electrical conductivity and magnetic property of the samples are also investigated. The results showed that Co1-x Znx Fe2 O4 nanoparticles are dispersed on graphene sheets and obtained nanocomposites are soft magnetic materials. In addition the samples showed excellent photocatalytic activity under visible light irradiation.

Keywords: reduced graphene oxide, ferrite, magnetic nanocomposite, photocatalytic activity, solvothermal method

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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Authors: M. L. McLain, R. Sreelakshmi, Abhishek, Rajeshwaran, Bhavani Rao, Kamal Bijlani, R. Jayakrishnan

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Technology enhanced learning has brought drastic changes in the field of education in the modern world. In this study we explore a novel way to improve how high school students learn by building a serious game that uses a pedagogical model developed by Robert Gagne. By integrating serious game with principles of Gagne’s learning model can provide engaging and meaningful instructions to students. The game developed in this study is a waste sorting game that can easily and succinctly demonstrate the principles of this learning model. All the tasks in the game that the player has to accomplish correspond to Gagne’s “Nine Events of Learning”. A quiz is incorporated in order to get data on the progress made by the player in understanding the concept and as well as to assess them. Additionally, an experimental study was conducted which demonstrates that game based learning using Gagne’s event is more effective than a traditional classroom setup.

Keywords: game based learning, sorting and recycling of waste, Gagne’s learning model, e-Learning, technology enhanced learning

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Authors: T. A. Mona M. Salem, Ali F. Bakr

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Given the potential devastation associated with future climate change related disasters, it is vital to change the way we build and manage our cities, through new strategies to reconfigure them and their infrastructures in ways that help secure their reproduction. This leads to a kaleidoscopic view of the city that recognizes the interrelationships of energy, water, transportation, and solid waste. These interrelationships apply across sectors and with respect to the built form of the city. The paper aims at a long-term climate resilience of cities and their critical infrastructures, and sets out an argument for including an eco-infrastructure-based approach in strategies to address climate change. As these ecosystems have a critical role to play in building resilience and reducing vulnerabilities in cities, communities and economies at risk, the enhanced protection and management of ecosystems, biological resources and habitats can mitigate impacts and contribute to solutions as nations and cities strive to adapt to climate change.

Keywords: ecology, ecosystem, infrastructure, climate change, urban

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Authors: Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

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Authors: Razyeh Behbahani, Martin L. Plumer, Ivan Saika-Voivod

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Micromagnetic simulations based on the stochastic Landau-Lifshitz-Gilbert equation are used to calculate dynamic magnetic hysteresis loops relevant to magnetic hyperthermia applications. With the goal to effectively simulate room-temperature loops for large iron-oxide based systems at relatively slow sweep rates on the order of 1 Oe/ns or less, a coarse-graining scheme is proposed and tested. The scheme is derived from a previously developed renormalization-group approach. Loops associated with nanorods, used as building blocks for larger nanoparticles that were employed in preclinical trials (Dennis et al., 2009 Nanotechnology 20 395103), serve as the model test system. The scaling algorithm is shown to produce nearly identical loops over several decades in the model grain sizes. Sweep-rate scaling involving the damping constant alpha is also demonstrated.

Keywords: coarse-graining, hyperthermia, hysteresis loops, micromagnetic simulations

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Authors: Sara Fayez Fawzy Mikhael

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Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: Mouhammd Alkasassbeh, Alaa Lasasmeh

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We live in an era of rapid development as a result of significant scientific growth. Like other technologies, wireless sensor networks (WSNs) are playing one of the main roles. Based on WSNs, ZigBee adds many features to devices, such as minimum cost and power consumption, and increasing the range and connect ability of sensor nodes. ZigBee technology has come to be used in various fields, including science, engineering, and networks, and even in medicinal aspects of intelligence building. In this work, we generated two main datasets, the first being based on tree topology and the second on star topology. The datasets were evaluated by three machine learning (ML) algorithms: J48, meta.j48 and multilayer perceptron (MLP). Each topology was classified into normal and abnormal (attack) network traffic. The dataset used in our work contained simulated data from network simulation 2 (NS2). In each database, the Bayesian network meta.j48 classifier achieved the highest accuracy level among other classifiers, of 99.7% and 99.2% respectively.

Keywords: IDS, Machine learning, WSN, ZigBee technology

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Authors: Samwail Fahmi Francis Yacoub

Abstract:

Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, movement skills, motor skills, children, behavior.

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Authors: Mizam Doğan

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In service life; structures can be damaged if they are subjected to dead and live loads which are greater than design values. For preventing this case; possible loads must be correctly calculated, structure must be designed according to determined loads, and structure must not be used out of its function. If loading case of the structure changes when its function changes; it must be reinforced for continuing it is new function. Reinforcement is a process that is made by increasing the existing strengths of structural system elements of the structure as reinforced concrete walls, beams, and slabs. Reinforcement can be done by casting reinforced concrete, placing steel and fiber structural elements. In this paper, reinforcing of columns and slabs of a structure of which function is changed is studied step by step. This reinforcement is made for increasing vertical and lateral load carrying capacity of the building. Not for repairing damaged structural system.

Keywords: strengthening, RC slabs, seismic load, steel beam, structural irregularity

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: Andrea Bikfalvi, Josep Llach, Ferran Lazaro, Bojan Jovanovski

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Due to the continuous need to foster university-business cooperation in both developed and developing countries, some higher education institutions face the challenge of designing, piloting, operating, and consolidating knowledge and technology transfer units. University-business cooperation has different maturity stages worldwide, with some higher education institutions excelling in these practices, but with lots of others that could be qualified as intermediate, or even some situated at the very beginning of their knowledge transfer adventure. These latter face the imminent necessity to formally create the technology transfer unit and to draw its roadmap. The complexity of this operation is due to various aspects that need to align and coordinate, including a major change in mission, vision, structure, priorities, and operations. Qualitative in approach, this study presents 5 case studies, consisting of higher education institutions located in the Western Balkans – 2 in Albania, 2 in Bosnia and Herzegovina, 1 in Montenegro- fully immersed in the entrepreneurial journey of creating their knowledge and technology transfer unit. The empirical evidence is developed in a pan-European project, illustratively called KnowHub (reconnecting universities and enterprises to unleash regional innovation and entrepreneurial activity), which is being implemented in three countries and has resulted in at least 15 pilot cooperation agreements between academia and business. Based on a peer-mentoring approach including more experimented and more mature technology transfer models of European partners located in Spain, Finland, and Austria, a series of initial lessons learned are already available. The findings show that each unit developed its tailor-made approach to engage with internal and external stakeholders, offer value to the academic staff, students, as well as business partners. The latest technology underpinning KnowHub services and institutional commitment are found to be key success factors. Although specific strategies and plans differ, they are based on a general strategy jointly developed and based on common tools and methods of strategic planning and business modelling. The main output consists of providing good practice for designing, piloting, and initial operations of units aiming to fully valorise knowledge and expertise available in academia. Policymakers can also find valuable hints on key aspects considered vital for initial operations. The value of this contribution is its focus on the intersection of three perspectives (service orientation, organisational innovation, business model) since previous research has only relied on a single topic or dual approaches, most frequently in the business context and less frequently in higher education.

Keywords: business model, capacity building, entrepreneurial education, knowledge transfer

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Authors: Aeslina Binti Abdul Kadir, Ahmad Shayuti Bin Abdul Rahim

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Brick is one of the most common masonry units used as building material. Due to the demand, different types of waste have been investigated to be incorporated into the bricks. Many types of sludge have been incorporated in fired clay brick for example marble sludge, stone sludge, water sludge, sewage sludge, and ceramic sludge. The utilization of these waste materials in fired clay bricks usually has positive effects on the properties such as lightweight bricks with improved shrinkage, porosity, and strength. This paper reviews on utilization of different types of sludge wastes into fired clay bricks. Previous investigations have demonstrated positive effects on the physical and mechanical properties as well as less impact towards the environment. Thus, the utilizations of sludge waste could produce a good quality of brick and could be one of alternative disposal methods for the sludge wastes.

Keywords: fired clay brick, sludge waste, compressive strength, shrinkage, water absorption

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Authors: Chi-Rung Jiang, Chun-Chung Chen, Sheng-Yuan Shiao, Fang-Yao Yeh

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Transmission lines are essential for power systems which play a significant role in a city for the development of infrastructures. Once a tower on the transmission line is damaged or becomes unstable, small-scale transmission tower damage might cause a large-scale electric power failure, and consequently, the enormous economic losses will occur. This paper assesses the structural safety and considers the impact of earthquakes and winds, presents a preliminary study of transmission tower with high-low legs by building structural analysis models of towers. The result shows that the high-low legs towers do have some structural characteristics need to be considered, such as the length of the difference of high legs and low legs should be restricted and the deployment direction of legs must be carefully planned during the design of transmission towers. The outcome of this study is beneficial to power systems authorities.

Keywords: power transition tower, structural analysis, high-low legs, safety assessment

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Authors: Claire M. Hollocou, Denise Johnson

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As racism permeates the foundation of America's educational system, educators hold a level of responsibility to address racism and the power of white privilege in the classroom by implementing anti-racist practices. This study aims to discuss the practices of anti-racist education across two predominantly affluent white schools. It offers our perspectives as white and black female teachers committed to implementing and reflecting on our antiracist work. Through communities of practice and the critical dialogue framework, we will provide an environment for one another to share our experiences implementing anti-racist education. We will spend a couple of months engaging in dialogue together to support our praxis. With critical reflection, we will look for themes that emerge through the conversations as well as develop a protocol for building an antiracist community of practice. This study is a work in progress.

Keywords: anti-racism, critical dialogue, race and racism, teacher education

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Authors: Hakim Benoumelghar

Abstract:

The launch in 1999 of the open access Initiative (OAI) and the protocol for sharing metadata, OAI-PMH, in parallel with the provision of deposit platforms, open-source software, such as DSpace in 2002, which allow libraries to develop digital repositories and play a leading role in the open access movement, and by building institutional open archives alongside the theme. This study focuses on Algerian universities and their projects and platforms for digital repositories of theses and scientific papers and the possibilities of access to the university community to develop research and access to archives of scientific digital content offered by the scientific community. This contribution attempts to compare Algerian and foreign institutional deposits in developed countries in order to have development and perspectives to facilitate scientific research and give more possibilities to the scientific community in documentary matters.

Keywords: digital repository, repository software, university, algeria

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