Search results for: architecture heritage

Authors: Pranita Shivankar, Arun Suryawanshi, Prabodhachandra Deshmukh, S. V. C. Kameswara Rao

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Many undesirable significant changes in landscapes and the regions in the vicinity of historically important structures occur as impacts due to anthropogenic activities over a period of time. A better understanding of such influences using recently developed satellite remote sensing techniques helps in planning the strategies for minimizing the negative impacts on the existing environment. In 1982, a fossilized hominid skull cap was discovered at a site located along the northern bank of the east-west flowing river Narmada in the village Hathnora. Close to the same site, the presence of Late Acheulian and Middle Palaeolithic tools have been discovered in the immediately overlying pebbly gravel, suggesting that the ‘Narmada skull’ may be from the Middle Pleistocene age. The reviews of recently carried out research studies relevant to hominid remains all over the world from Late Acheulian and Middle Palaeolithic sites suggest succession and contemporaneity of cultures there, enhancing the importance of Hathnora as a rare precious site. In this context, the maximum likelihood classification using digital interpretation techniques was carried out for this study area using the satellite imagery from Landsat ETM+ for the year 2006 and Landsat TM (OLI and TIRS) for the year 2016. The overall accuracy of Land Use Land Cover (LULC) classification of 2016 imagery was around 77.27% based on ground truth data. The significant reduction in the main river course and agricultural activities and increase in the built-up area observed in remote sensing data analysis are undoubtedly the outcome of human encroachments in the vicinity of the eminent heritage site.

Keywords: cultural succession, digital interpretation, Hathnora, Homo Sapiens, Late Acheulian, Middle Palaeolithic

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Authors: Yuhang Zou, Zhu Wang

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Most of the western part of China is mountainous and hilly region, with abundant resources of mountainous space. However, the resources are complex, and the ecological factors are diverse. As urbanization expands rapidly today, the landscape of the mountain residence needs to be changed. This paper, starting with the ecological environment and visual landscape of the mountain living space, analyzes the basic conditions of the Eling Peak, ‘Mirror of the Sky’, in Chongqing, China before its landscape renovation. Then, it analyzes some parts of the project, including the overall planning, ecological coordination, space expansion and local conditions in mountain environment. After that, this paper concludes the intention of designer and 4 methods, appropriate demolition, space reconstruction, landscape modeling and reasonable road system, to transform the master’s mountain residential works. Finally, through the analysis and understanding of the project, it sums up that the most beautiful landscape is not only the outdoor space, but also borrowing scene from the city and the sky, making them a part of the mountainous residential buildings. Only in this way can people, landscape, building, sky, and city become integrated and coexist harmoniously.

Keywords: landscape design, mountainous architecture, renovation, residence

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Authors: Mircan Kaya

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A multi-disciplinary approach is required in any intervention project for historical monuments. Due to the complexity of their geometry, the variable and unpredictable characteristics of original materials used in their creation, heritage structures are peculiar. Their histories are often complex, and they require correct diagnoses to decide on the techniques of intervention. This approach should not only combine technical aspects but also historical research that may help discover phenomena involving structural issues, and acquire a knowledge of the structure on its concept, method of construction, previous interventions, process of damage, and its current state. In addition to the traditional techniques like bed joint reinforcement, the repairing, strengthening and restoration of historical buildings may require several other modern methods which may be described as innovative techniques like pre-stressing and post-tensioning, use of shape memory alloy devices and shock transmission units, shoring, drilling, and the use of stainless steel or titanium. Regardless of the method to be incorporated in the strengthening process, which can be traditional or innovative, it is crucial to recognize that structural strengthening is the process of upgrading the structural system of the existing building with the aim of improving its performance under existing and additional loads like seismic loads. This process is much more complex than dealing with a new construction, owing to the fact that there are several unknown factors associated with the structural system. Material properties, load paths, previous interventions, existing reinforcement are especially important matters to be considered. There are several examples of seismic strengthening with traditional and innovative techniques around the world, which will be discussed in this paper in detail, including their pros and cons. Ultimately, however, the main idea underlying the philosophy of a successful intervention with the most appropriate techniques of strengthening a historic monument should be decided by a proper assessment of the specific needs of the building.

Keywords: bed joint reinforcement, historical monuments, post-tensioning, pre-stressing, seismic strengthening, shape memory alloy devices, shock transmitters, tie rods

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Authors: Gholamreza Momenzadeh, Forough Nematolahi

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The Extended Enterprise Resource Planning (ERPII) system usually requires massive amounts of storage space, powerful servers, and large upfront and ongoing investments to purchase and manage the software and the related hardware which are not affordable for organizations. In recent decades, organizations prefer to adapt their business structures with new technologies for remaining competitive in the world economy. Therefore, cloud computing (which is one of the tools of information technology (IT)) is a modern system that reveals the next-generation application architecture. Also, cloud computing has had some advantages that reduce costs in many ways such as: lower upfront costs for all computing infrastructure and lower cost of maintaining and supporting. On the other hand, traditional ERPII is not responding for huge amounts of data and relations between the organizations. In this study, based on a literature study, ERPII is investigated in the context of cloud computing where the organizations operate more efficiently. Also, ERPII conditions have a response to needs of organizations in large amounts of data and relations between the organizations.

Keywords: extended enterprise resource planning, cloud computing, business process, enterprise information integration

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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Authors: Mohamed R. Mhereeg

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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

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Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru

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Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.

Keywords: attendance system, face detection, face recognition, PCA

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Authors: Elena Bellini, Daniele Mugnaini, Michele Boschetto

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People with an Autistic Spectrum Disorder and an Intellectual Disability who need to attend a Hospital Emergency Waiting Room frequently present high levels of discomfort and challenging behaviors due to stress-related hyperarousal, sensory sensitivity, novelty-anxiety, communication and self-regulation difficulties. Increased agitation and acting out also disturb the diagnostic and therapeutic processes, and the emergency room climate. Architectural design disciplines aimed at reducing distress in hospitals or creating autism-friendly environments are called for to find effective answers to this particular need. A growing number of researchers are considering the physical environment as an important point of intervention for people with autism. It has been shown that providing the right setting can help enhance confidence and self-esteem and can have a profound impact on their health and wellbeing. Environmental psychology has evaluated the perceived quality of care, looking at the design of hospital rooms, paths and circulation, waiting rooms, services and devices. Furthermore, many studies have investigated the influence of the hospital environment on patients, in terms of stress-reduction and therapeutic intervention’ speed, but also on health professionals and their work. Several services around the world are organizing autism-friendly hospital environments which involve the architecture and the specific staff training. In Italy, the association Spes contra spem has promoted and published, in 2013, the ‘Chart of disabled people in the hospital’. It stipulates that disabled people should have equal rights to accessible and high-quality care. There are a few Italian examples of therapeutic programmes for autistic people as the Dama project in Milan and the recent experience of Children and Autism Foundation in Pordenone. Careggi’s Emergency Waiting Room in Florence has been built to satisfy this challenge. This project of research comes from a collaboration between the technical staff of Careggi Hospital, the Center for autism PAMAPI and some architects expert in the sensory environment. The methodology of focus group involved architects, psychologists and professionals through a transdisciplinary research, centered on the links between the spatial characteristics and clinical state of people with ASD. The relationship between architectural space and quality of life is studied to pay maximum attention to users’ needs and to support the medical staff in their work by a specific program of training. The result of this research is a sum of criteria used to design the emergency waiting room, that will be illustrated. A protected room, with a clear space design, maximizes comprehension and predictability. The multisensory environment is thought to help sensory integration and relaxation. Visual communication through Ipad allows an anticipated understanding of medical procedures, and a specific technological system supports requests, choices and self-determination in order to fit sensory stimulation to personal preferences, especially for hypo and hypersensitive people. All these characteristics should ensure a better regulation of the arousal, less behavior problems, improving treatment accessibility, safety, and effectiveness. First results about patient-satisfaction levels will be presented.

Keywords: accessibility of care, autism-friendly architecture, personalized therapeutic process, sensory environment

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Mohamed A. Dkhil, Denis Delic, Saleh Al-Quraishy

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Coccidiosis causes considerable economic loss in the poultry industry. The current study aimed to investigate the response of goblet cells as well as the induced tissue damage during Eimeria papilata infection. Mice were infected with sporulated E. papillata oocyts. On day 5 post-infection, the fecal output was determined. Also, the jejunum was prepared for the histological, histochemical and molecular studies. Our results revealed that the intestinal coccidian infection with E. papillata induced a marked goblet cell hypoplasia and depleted mucus secretion. Also, the infection was able to alter the jejuna architecture and increased the apoptotic cells inside the villi. In addition, the real time PCR results indicated that, the inflammatory cytokines TNF-α, iNOS, IFN-y and IL-1β were significantly up-regulated. In contrast, the mRNA expression patterns of IL-6 in response to E. papillata infection did not differ significantly between control and infected mice. Moreover, the mRNA expression of TLR4 was significantly up-regulated, whereas the expression of MUC2 is significantly down-regulated upon infection. Further studies are required to understand the regulatory mechanisms of goblet cells related genes.

Keywords: goblet cells, Eimeria papillata, mice, jejunum

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: S. Masoud Barakati, Mohsen Rahmani Haredasht

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Recently, the use of T-type nested neutral point clamped (T-NNPC) converter has increased in medium voltage applications. However, the T-NNPC converter architecture's reliability and continuous operation are at risk by including semiconductor switches. Semiconductor switches are a prone option for open-circuit faults. As a result, fault-tolerant converters are required to improve the system's reliability and continuous functioning. This study's primary goal is to provide a fault-tolerant T-NNPC converter configuration. In the proposed design utilizing the cold reservation approach, a redundant phase is considered, which replaces the faulty phase once the fault is diagnosed in each phase. The suggested fault-tolerant configuration can be easily implemented in practical applications due to the use of a simple PWM control mechanism. The performance evaluation of the proposed configuration under different scenarios in the MATLAB-Simulink environment proves its efficiency.

Keywords: T-type nested neutral point clamped converter, reliability, continuous operation, open-circuit faults, fault-tolerant converters

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Authors: Fetoon K. Algarawi, Wejdan A. Alslamah, Ahlam A. Alhabib, Afnan S. Alfehaid, Dina M. Ibrahim

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Over the past 20 years, technology was rapidly developed and no one expected what will come next. Advancements in technology open new opportunities for immersive learning environments. There is a need to transmit education to a level that makes it more effective for the student. Augmented reality is one of the most popular technologies these days. This paper is an experience of applying Augmented Reality (AR) technology using a marker-based approach in E-learning system to transmitting virtual objects into the real-world scenes. We present a marker-based approach for transmitting virtual objects into real-world scenes to explain information in a better way after we developed a mobile phone application. The mobile phone application was then tested on students to determine the extent to which it encouraged them to learn and understand the subjects. In this paper, we talk about how the beginnings of AR, the fields using AR, how AR is effective in education, the spread of AR these days and the architecture of our work. Therefore, the aim of this paper is to prove how creating an interactive e-learning system using AR technology will encourage students to learn more.

Keywords: augmented reality, e-learning, marker-based, monitor-based

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Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

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Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

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Authors: Qiang Zhang, Chun Yuan

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Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

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Authors: Craig Wight

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Tourism visits to sites associated to varying degrees with death and dying have for some time inspired academic debate and research into what has come to be popularly described as ‘dark tourism’. Research to date has been based on the mobilisation of various social scientific methodologies to understand issues such as the motivations of visitors to consume dark tourism experiences and visitor interpretations of the various narratives that are part of the consumption experience. This thesis offers an alternative conceptual perspective for carrying out research into dark tourism by presenting a discourse analysis of Lithuanian occupation-themed museums using Foucault’s concept of ‘discursive formation’ from ‘Archaeology of Knowledge’. A constructivist methodology is therefore applied to locate the rhetorical representations of Lithuanian and Jewish subject positions and to identify the objects of discourse that are produced in five museums that interpret a historical era defined by occupation, the persecution of people and genocide. The discourses and consequent cultural function of these museums are examined, and the key finding of the research proposes that they authorise a particular Lithuanian individualism which marginalises the Jewish subject position and its related objects of discourse into abstraction. The thesis suggests that these museums create the possibility to undermine the ontological stability of Holocaust and the Jewish-Lithuanian subject which is produced as an anomalous, ‘non-Lithuanian’ cultural reference point. As with any Foucauldian archaeological research, it cannot be offered as something that is ‘complete’ since it captures only a partial field, or snapshot of knowledge, bound to a specific temporal and spatial context. The discourses that have been identified are perhaps part of a more elusive ‘positivity’ which is salient across a number of cultural and political surfaces which are ripe for a similar analytical approach in future. It is hoped that the study will motivate others to follow a discourse-analytical approach to research in order to further understand the critical role of museums in public culture when it comes to shaping knowledge about ‘inconvenient’ pasts.

Keywords: genocide heritage, foucault, Lithuanian tourism, discursive formatoin

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Authors: Seyyed Hossein Alavi, Soudabe Mehri Talarposhti

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Passages urban landscape is made up of various components that the component parts of the whole and vice versa has relationships. In today’s cities, we have not seen a dual relationship and only one side of the equation which is the relationships of the component parts are considered. However, the effect of the component to whole is stronger and also longer. This means that every time the outer shell of the building was constructed instant impact on the viewers while it takes a long time to understand the impact of the building in its environment and basically, it seems city portrait has the sensory and untouchable effect on observer. Today, building facades are designated individually and in isolation from the context. Designers are familiar with the details of the facade, but they are not informed with the science of combination and its impact on portrait. The importance of city and also more important than that, the city portrait haven’t confirmed for those involved in the building and authorities and the construction been changed to a market for more glaring taste of designers and attracting more business and the city and its landscape has been forgotten. This essay is an attempt to collect a part of the principles and definitions needed on perspective issues and portrait, and it is hoped that it will open arena for more research and studies in this field and other related fields.

Keywords: facade, urban housing, urban design, sustainable architecture

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Authors: Baha Hasan, Jan Wikander

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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.

Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology

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Authors: Aswathy Vijayan, Sharath Sunder Rajeev

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Trade has been fundamental in the footprint of human civilization since ancient time. In most of the historic cities, city development was along trading routes, where marketplaces are the major entrance to a city and hence a major element of the urban fabric. Marketplaces are where the commercial activities flourish, people, having a sense of belonging to the place, where they easily fit in. Acknowledging the built environment in and around the market in a way, creating a sense of place is an important factor in the success of public spaces. Local markets are developed in an organic manner, which adds on to the people experience and perception of urban space. With the city development, the commercial needs within the city increase, hence marketplaces flourish, irrespective of the functional segregation within. The work-live culture in the marketplaces diminishes as the commercial expansion washes away the residential patches within it. Real estate flourishes as the newer infills are without considering the carrying capacity of the place. Chalai market is a prominent business center serving the regional level of Thiruvananthapuram city. The transformation trend of marketplaces in city cores are understood from case study on Fatimid Cairo Marketplace. The parameters that led to transformation of marketplaces in a global context is considered for the analysis of the Chalai market. The structure of the marketplace over the years is analyzed in terms of transformation in location, transformation in the land- use, change in commodity, and transformation in movement and activity. The aim of the research is to emphasize the need to understand the transformation trend, in creating a suitable development pattern for the city. The unregulated transformation within the city core has led to tremendous transformation in the user group and user pattern and eventually to the commercial trend. With the change in lifestyle and need for new amenities have led to addition of new infills leading to the degradation of the native commerce. Hence addressing the transformation of marketplaces are crucial to maintaining the locational significance and cultural importance and heritage of the place.

Keywords: bazaar, market centers, marketplaces, traditional city, traditional market, urban fabric

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Authors: Belayneh Matebie, Michael Melese

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The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

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Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

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Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

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This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

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Authors: F. Felipe

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Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Keywords: air defense, effectiveness, system, simulation, decision-support

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Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

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Authors: Ntachobazi bosco

Abstract:

Tourism Development and Planning in Rwanda: Rwanda, a small landlocked country located in the heart of Africa, has experienced significant growth in its tourism industry in recent years. The country’s stunning natural beauty, rich cultural heritage, and warm hospitality have made it an attractive destination for travelers from around the world. However, to ensure sustainable tourism development and planning, the Rwandan government has implemented various strategies and policies to promote responsible tourism practices. Infrastructure Development: To support the growth of the tourism industry, the Rwandan government has invested heavily in infrastructure development. This includes the construction of new hotels, resorts, and lodges, as well as the upgrading of existing facilities. The government has also improved the country’s transportation network, including the construction of new airports and the upgrading of existing ones. Conservation Efforts: Rwanda is home to several national parks and reserves, including the famous Volcanoes National Park, which is known for its mountain gorilla populations. To protect these natural wonders, the Rwandan government has implemented conservation efforts, such as the establishment of protected areas and the development of sustainable tourism practices. Community-Based Tourism: Community-based tourism is a key component of Rwanda’s tourism development strategy. The government has established several community-based tourism programs, which aim to involve local communities in the tourism industry and provide them with economic benefits. These programs include homestays, village tours, and cultural performances. Sustainable Tourism Practices: To promote sustainable tourism practices, the Rwandan government has implemented several initiatives, such as the use of eco-friendly accommodations and the promotion of responsible wildlife viewing practices. The government has also established the Rwanda Tourism Board, which is responsible for promoting and regulating the tourism industry. Challenges and Opportunities: Despite the growth of the tourism industry in Rwanda, several challenges need to be addressed, such as the lack of skilled labor and the need for more infrastructure development. However, there are also several opportunities for the industry, such as the potential for ecotourism and the growth of the meetings, incentives, conventions, and exhibitions (MICE) market.

Keywords: tourism, in rwanda, developent, in africa

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Authors: S. Jabeen

Abstract:

Though Pakistan has a rich cultural history and a diverse population; its global image is tarnished with labels of Muslim ‘fundamentalism’ and ‘extremism.’ Cultural policy is a tool that can be used by the government of Pakistan to ameliorate this image, but instead, this fundamentalist reputation is reinforced in the 2005 draft of Pakistan’s cultural policy. With its stern focus on a homogenized cultural identity, this 2005 draft bases itself largely on forced participation from the largely Muslim public and leaves little or no benefits to them or cultural minorities in Pakistan. The effects of this homogenized ‘Muslim’ identity linger ten years later where the study and celebration of the cultural heritage of Pakistan in schools and educational festivals focus entirely on creating and maintaining a singular ‘Islamic’ cultural identity. The current lack of inclusion has many adverse effects that include the breeding of extremist mindsets through the usurpation of minority rights and lack of safe cultural public spaces. This paper argues that Pakistan can improve social inclusivity and boost its global image through cultural policy. The paper sets the grounds for research by surveying the effectiveness of different cultural policies across nations with differing socioeconomic status. Then, by sampling two public literary festivals in Pakistan as case studies, the National Youth Peace Festival hosted with a nationalistic agenda using public funds and the Lahore Literary Festival (LLF) that aims to boost the cultural literacy scene of Lahore using both private and public efforts, this paper looks at the success of the private, more inclusive LLF. A revision of cultural policy is suggested that combines public and private efforts to host cultural festivals for the sake of cultural celebration and human development, without a set nationalistic agenda. Consequently, this comparison which is grounded in the human capabilities approach, recommends revising the 2005 draft of the Cultural Policy to improve human capabilities in order to support cultural diversity and ultimately contribute to economic growth in Pakistan.

Keywords: cultural policy, festivals, human capabilities, Pakistan

Procedia PDF Downloads 134

Authors: Debasis Sarkar

Abstract:

Building Information Modeling (BIM) is a holistic documentation process for operational visualization, design coordination, estimation and project scheduling. BIM software defines objects parametrically and it is a tool for virtual reality. Primary advantage of implementing BIM is the visual coordination of the building structure and systems such as Mechanical, Electrical and Plumbing (MEP) and it also identifies the possible conflicts between the building systems. This paper is an attempt to develop a risk based BIM model which would highlight the primary advantages of application of BIM pertaining to urban infrastructure transportation project. It has been observed that about 40% of the Architecture, Engineering and Construction (AEC) companies use BIM but primarily for their outsourced projects. Also, 65% of the respondents agree that BIM would be used quiet strongly for future construction projects in India. The 3D models developed with Revit 2015 software would reduce co-ordination problems amongst the architects, structural engineers, contractors and building service providers (MEP). Integration of risk management along with BIM would provide enhanced co-ordination, collaboration and high probability of successful completion of the complex infrastructure transportation project within stipulated time and cost frame.

Keywords: building information modeling (BIM), infrastructure transportation, project risk management, underground metro rail

Procedia PDF Downloads 305

Authors: Vigen Arakelian

Abstract:

The balancing of mechanisms is a well-known problem in the field of mechanical engineering because the variable dynamic loads cause vibrations, as well as noise, wear and fatigue of the machines. A mechanical system with unbalance shaking force and shaking moment transmits substantial vibration to the frame. Therefore, the objective of the balancing is to cancel or reduce the variable dynamic reactions transmitted to the frame. The resolution of this problem consists in the balancing of the shaking force and shaking moment. It can be fully or partially, by internal mass redistribution via adding counterweights or by modification of the mechanism's architecture via adding auxiliary structures. The balancing problems are of continue interest to researchers. Several laboratories around the world are very active in this area and new results are published regularly. However, despite its ancient history, mechanism balancing theory continues to be developed and new approaches and solutions are constantly being reported. Various surveys have been published that disclose particularities of balancing methods. The author believes that this is an appropriate moment to present a state of the art of the shaking force balancing studies completed by new research results. This paper presents an overview of methods devoted to the shaking force balancing of mechanisms, as well as the historical aspects of the origins and the evolution of the balancing theory of mechanisms.

Keywords: inertial forces, shaking forces, balancing, dynamics, mechanism design

Procedia PDF Downloads 121

Authors: Burak Köken, Hatice D. Arslan, Bilgehan Y. Çakmak

Abstract:

Analyzing the relation networks between the hospital buildings which have complex structure and distinctive spatial relationships is quite difficult. The hospital buildings which require specialty in spatial relationship solutions during design and self-innovation through the developing technology should survive and keep giving service even after the disasters such as earthquakes. In this study, a hospital building where the load-bearing system was strengthened because of the insufficient earthquake performance and the construction of an additional building was required to meet the increasing need for space was discussed and a comparative spatial evaluation of the hospital building was made with regard to its status before the change and after the change. For this reason, spatial organizations of the building before change and after the change were analyzed by means of Space Syntax method and the effects of the change on space organization parameters were searched by applying an analytical procedure. Using Depthmap UCL software, connectivity, visual mean depth, beta and visual integration analyses were conducted. Based on the data obtained after the analyses, it was seen that the relationships between spaces of the building increased after the change and the building has become more explicit and understandable for the occupants. Furthermore, it was determined according to findings of the analysis that the increase in depth causes difficulty in perceiving the spaces and the changes considering this problem generally ease spatial use.

Keywords: architecture, hospital building, space syntax, strengthening

Procedia PDF Downloads 516

Authors: Nishank Raisinghani

Abstract:

Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

Procedia PDF Downloads 144