Search results for: allocated architecture

Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon

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Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.

Keywords: deep-learning, altimetry, sea surface temperature, forecast

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

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With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Masood Roohi, Amir Taghavipour

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This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.

Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time

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Authors: Nikolaos Mamalis

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The work of the eminent architect and composer has undoubtedly been influenced both by his architecture and collaboration with Le Corbusier and by the conquests of the musical avant-garde of the 20th century (Schoenberg, Messian, Bartock, electroacoustic music). It is known that the golden mean and the Fibonacci sequence played a momentous role in the Architectural Avant-garde (Modulor) and expanded on musical pursuits. Especially in the 50s (serialism), it was a structural tool for composition. Xenakis' architectural and musical work (Sacrifice, Metastasis, Rebonds, etc.) received the influence of the Golden Section, as has been repeatedly demonstrated. However, the idea of this retrospective sequence and the reflection raised by the search for new proportions, both in the architectural and the musical work of Xenakis, was not limited to constituting a step, a workable formula that acted unifyingly with regard to the other parameters of the musical work, or as an aesthetic model that makes sense - philosophically and poetically - an anthropocentric dimension as in other composers (see Luigi Nono) ̇ triggered a qualitative leap, an opening of the composer to the assimilation of mathematical concepts and scientific types in music and the consolidation of new sound horizons of stochastic music.

Keywords: golden ratio, music, space, stochastic music

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Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

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Authors: Isabelle Snyder, Travis Smith

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Microgrid protection presents challenges to conventional protection techniques due to the low-induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected modes. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid-connected or microgrid-connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are labeled as follows: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR).

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection

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Authors: Hasan Farahneh

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Smart asset management along roadsides and in deserted areas is a topic of deprived attention. We find most of the work in emergency reporting services in intelligent transportation systems (ITS) and rural areas but not much in asset reporting. Currently, available asset management mechanisms are based on scheduled maintenance and do not effectively report any emergency situation in a timely manner. This paper is the continuation of our previous work, in which we proposed the usage of Foglets and VLC link between smart vehicles and road side assets. In this paper, we propose a hybrid communication system for asset management and emergency reporting architecture for smart transportation. We incorporate Foglets along with visible light communication (VLC) and radio frequency (RF) communication. We present the channel model and parameters of a hybrid model to support an intelligent transportation system (ITS) system. Simulations show high improvement in the system performance in terms of communication range and received data. We present a comparative analysis of a hybrid ITS system.

Keywords: Internet of Things, Foglets, VLC, RF, smart vehicle, roadside asset management

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Authors: Daniele Abreu e Lima, Chloe Fitzpatrick

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During the 1930s, New Zealand received a wave of refugees feeling from the impeding war and atrocities the Nazi regime was imposing on the German people. Among the hundreds of refugees were highly trained artists, architects and musicians who made a huge contribution to Wellington’s culture and identity. It is unfeasible to chronicle the impact of every Jewish refugee in the development of New Zealand arts scene. But it is possible to choose a number of them and analyse their contribution to NZ culture. This research aims to bring to light the reception and life of five influential Jewish architects; Helmut Einhorn, Ernst Plischke, Frederick Neumann, Henry Kulka, and Maximillian Rosenfeld. Each had a key role in influencing New Zealand architectural landscape and the modernization of the country. Before coming to New Zealand, these five architects lived different lives working all over Europe, from Paris through to Moscow. In common, apart from their ethnicity, they had led cultured lives where they were culturally and politically active. This research looks at how much their individual contributions helped to transform the architectural scene in New Zealand but also in the amount of cultural and religious renunciation they had to endure to be accepted in the country.

Keywords: Jewish Refugee architects, modern architecture, World War 2, New Zealand

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Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

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Authors: Daniel Joseph Whittaker

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This paper examines the broad array of historic sites from which Chicago common brick has emerged, and the methods this brick has been utilized within and around a new hybrid structure recently completed-and periodically opened to the public, as a private art, architecture, design, and social activism gallery space. Various technical aspects regarding the structural and aesthetic reuse methods of salvaged brick within the interior and exterior of this new Tadao Ando-designed building in Lincoln Park, Chicago, are explored. This paper expands specifically upon the multiple possible origins of Chicago common brick, as well as the extant brick currently composing the surrounding alley which is integral to demarcating the southern site boundary of the old apartment building now gallery. Themes encompassing Chicago’s archeological and architectural history, local resource extraction, and labor practices permeate this paper’s investigation into urban, social and architectural history and building construction technology advancements through time.

Keywords: masonry construction, history brickmaking, private museums, Chicago Illinois, Tadao Ando

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Authors: Zainal Abidin Akasah, Maizam Alias, Azuin Ramli

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The safety and health performances aspects of a building are the most challenging aspect of facility management. It requires a deep understanding by the building managers on the factors that contribute to health and safety performances. This study attempted to develop an explanatory architectural safety performance model for stratified low-cost housing in Malaysia. The proposed Building Safety and Health Performance (BSHP) model was tested empirically through a survey on 308 construction practitioners using Partial Least Squares (PLS) and Structural Equation Modelling (SEM) tool. Statistical analysis results supports the conclusion that architecture, building services, external environment, management approaches and maintenance management have positive influence on safety and health performance of stratified low-cost housing in Malaysia. The findings provide valuable insights for construction industry to introduce BSHP model in the future where the model could be used as a guideline for training purposes of managers and better planning and implementation of building management.

Keywords: building management, stratified low-cost housing, safety, health model

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Authors: Yavuz Yardım

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The most important criteria for structural engineering is the structure’s ability to carry intended loads safely. The key element of this ability is mathematical modeling of really loadings situation into a simple loads input to use in structure analysis and design. Amongst many different types of loads, the most challenging load is earthquake load. It is possible magnitude is unclear and timing is unknown. Therefore the concept of intended loads and safety have been built on experience of previous earthquake impact on the structures. Understanding and developing these concepts is achieved by investigating performance of the structures after real earthquakes. Damage after an earthquake provide results of thousands of full-scale structure test under a real seismic load. Thus, Earthquakes reveille all the weakness, mistakes and deficiencies of analysis, design rules and practice. This study deals with lesson learnt from earthquake recoded last two decades in Turkey. Results of investigation after several earthquakes exposes many deficiencies in structural detailing, inappropriate design, wrong architecture layout, and mainly mistake in construction practice.

Keywords: earthquake, seismic assessment, RC buildings, building performance

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Authors: Hazem Abuorf

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From the perspective of viewing urban design as the architecture of public spaces, the latter has many advantages; for example, in achieving attractive and vibrant public spaces, ensuring safety and amenity, supporting a strong sense of place and local character. Besides all advantages, such spaces nevertheless trigger numerous dilemmas, how to design urban spaces preserving the quality of life in the long term while equally achieving cohesion between new urban developments and the already existing urban structure without causing a split in history through the cause of functional and aesthetic degradation. Analysis of this article seeks to propose a methodology deemed essential for assessing and stimulating design criteria of the public spaces when rehabilitating urban sites. The method’s utility is shown by analyzing rehabilitation projects in Gaza Strip, whose design of the public spaces has mainly focused on the physical aspect ignoring the place’s local identity, users’ needs, and history. The proposed methodology serves as a guide for municipal authorities and technical teams to deal with interventions that would rework the role of urban design towards making sense of place.

Keywords: urban design, public realm, rehabilitation projects, quality of life

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Authors: Maha Shamseddine, Amjad Nusayr, Wassim Itani

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In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.

Keywords: privacy enforcement, platform-as-a-service privacy awareness, cloud computing privacy

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Authors: Prawal Sinha, Peeyush Singh, Pravir Dutt

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Problems in elastohydrodynamic lubrication have attracted a lot of attention in the last few decades. Solving a two-dimensional problem has always been a big challenge. In this paper, a new discontinuous finite volume method (DVM) for two-dimensional point contact Elastohydrodynamic Lubrication (EHL) problem has been developed and analyzed. A complete algorithm has been presented for solving such a problem. The method presented is robust and easily parallelized in MPI architecture. GMRES technique is implemented to solve the matrix obtained after the formulation. A new approach is followed in which discontinuous piecewise polynomials are used for the trail functions. It is natural to assume that the advantages of using discontinuous functions in finite element methods should also apply to finite volume methods. The nature of the discontinuity of the trail function is such that the elements in the corresponding dual partition have the smallest support as compared with the Classical finite volume methods. Film thickness calculation is done using singular quadrature approach. Results obtained have been presented graphically and discussed. This method is well suited for solving EHL point contact problem and can probably be used as commercial software.

Keywords: elastohydrodynamic, lubrication, discontinuous finite volume method, GMRES technique

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Authors: E. Zarei, M. Bazaei, A. seifi, A. Keshavarzi

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Contextuallism has been always the main component of urban science. It not only has great direct and indirect impact on behaviors, events and interactions, but also is one of the basic factors of an urban values and identity. Nowadays there might be some deficiencies in the cities. In the theories of environment designing, humanistic orientations with the focus on culture and cultural variables would enable us to transfer information. To communicate with the context in which human lives, he needs some common memories, understandable symbols and daily activities in that context. The configuration of a place can impact on human’s behaviors. The goal of this research is to review 7 projects in different parts of the world with various usages and some factors such as ‘sense of place’, ‘sense of belonging’ and ‘social and cultural relations’ will be discussed in these projects. The method used for research in this project is descriptive- analytic. Library information and Internet are the main sources of gathering information and the method of reasoning used in this project is inductive. The consequence of this research will be some data in the form of tables that has been extracted from mentioned projects.

Keywords: contextuallism with humanistic approach, sense of place, sense of belonging, social and cultural relations

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Authors: Roland F. Karthaus, Rachel S. O'Brien

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Over the past decade, the authors have undertaken applied research aimed at enabling transformation within the prison service to improve conditions and outcomes for those living, working and visiting in prisons in the UK and the communities they serve. The research has taken place against a context of reducing resources and public discontent at increasing levels of violence, deteriorating conditions and persistently high levels of re-offending. Top-down governmental policies have mainly been ineffectual and in some cases counter-productive. The prison service is characterised by hierarchical organisation, and the research has applied design thinking at multiple levels to challenge and precipitate change: top-down, middle-out and bottom-up. The research employs three distinct but related approaches, system design (top-down): working at the national policy level to analyse the changing policy context, identifying opportunities and challenges; engaging with the Ministry of Justice commissioners and sector organisations to facilitate debate, introducing new evidence and provoking creative thinking, place-based design (middle-out): working with individual prison establishments as pilots to illustrate and test the potential for local empowerment, creative change, and improved architecture within place-specific contexts and organisational hierarchies, everyday design (bottom-up): working with individuals in the system to explore the potential for localised, significant, demonstrator changes; including collaborative design, capacity building and empowerment in skills, employment, communication, training, and other activities. The research spans a series of projects, through which the methodological approach has developed responsively. The projects include a place-based model for the re-purposing of Ministry of Justice land assets for the purposes of rehabilitation; an evidence-based guide to improve prison design for health and well-being; capacity-based employment, skills and self-build project as a template for future open prisons. The overarching research has enabled knowledge to be developed and disseminated through policy and academic networks. Whilst the research remains live and continuing; key findings are emerging as a basis for a new methodological approach to effecting change in the UK prison service. An interdisciplinary approach is necessary to overcome the barriers between distinct areas of the prison service. Sometimes referred to as total environments, prisons encompass entire social and physical environments which themselves are orchestrated by institutional arms of government, resulting in complex systems that cannot be meaningfully engaged through narrow disciplinary lenses. A scalar approach is necessary to connect strategic policies with individual experiences and potential, through the medium of individual prison establishments, operating as discrete entities within the system. A reflexive process is necessary to connect research with action in a responsive mode, learning to adapt as the system itself is changing. The role of individuals in the system, their latent knowledge and experience and their ability to engage and become agents of change are essential. Whilst the specific characteristics of the UK prison system are unique, the approach is internationally applicable.

Keywords: architecture, design, policy, prison, system, transformation

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Authors: K. C. Apil, Keshab Sharma, Bigul Pokharel

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Kathmandu Valley, capital city of Nepal houses numerous historical monuments as well as religious structures which are as old as from the 4th century A.D. The city alone is home to seven UNESCO’s world heritage sites including various public squares and religious sanctums which are often regarded as living heritages by various historians and archeological explorers. Recently on April 25, 2015, the capital city including other nearby locations was struck with Gorkha earthquake of moment magnitude (Mw) 7.8, followed by the strongest aftershock of moment magnitude (Mw) 7.3 on May 12. This study reports structural failures and collapse of heritage structures in Kathmandu Valley during the earthquake and presents preliminary findings as to the causes of failures and collapses. Field reconnaissance was carried immediately after the main shock and the aftershock, in major heritage sites: UNESCO world heritage sites, a number of temples and historic buildings in Kathmandu Durbar Square, Patan Durbar Square, and Bhaktapur Durbar Square. Despite such catastrophe, a significant number of heritage structures stood high, performing very well during the earthquake. Preliminary reports from archeological department suggest that 721 of such structures were severely affected, whereas numbers within the valley only were 444 including 76 structures which were completely collapsed. This study presents recorded accelerograms and geology of Kathmandu Valley. Structural typology and architecture of the heritage structures in Kathmandu Valley are briefly described. Case histories of damaged heritage structures, the patterns, and the failure mechanisms are also discussed in this paper. It was observed that performance of heritage structures was influenced by the multiple factors such as structural and architecture typology, configuration, and structural deficiency, local ground site effects and ground motion characteristics, age and maintenance level, material quality etc. Most of such heritage structures are of masonry type using bricks and earth-mortar as a bonding agent. The walls' resistance is mainly compressive, thus capable of withstanding vertical static gravitational load but not horizontal dynamic seismic load. There was no definitive pattern of damage to heritage structures as most of them behaved as a composite structure. Some structures were extensively damaged in some locations, while structures with similar configuration at nearby location had little or no damage. Out of major heritage structures, Dome, Pagoda (2, 3 or 5 tiered temples) and Shikhara structures were studied with similar variables. Studying varying degrees of damages in such structures, it was found that Shikhara structures were most vulnerable one where Dome structures were found to be the most stable one, followed by Pagoda structures. The seismic performance of the masonry-timber and stone masonry structures were slightly better than that of the masonry structures. Regular maintenance and periodic seismic retrofitting seems to have played pivotal role in strengthening seismic performance of the structure. The study also recommends some key functions to strengthen the seismic performance of such structures through study based on structural analysis, building material behavior and retrofitting details. The result also recognises the importance of documentation of traditional knowledge and its revised transformation in modern technology.

Keywords: Gorkha earthquake, field observation, heritage structure, seismic performance, masonry building

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Embedding Sustainability in technological curricula has become a crucial factor for educating engineers with competences in sustainability. The Technical University of Catalonia UPC, in 2008, designed the Sustainable Technology Excellence Program STEP 2015 in order to assure a successful Sustainability Embedding. This Program takes advantage of the opportunity that the redesign of all Bachelor and Master Degrees in Spain by 2010 under the European Higher Education Area framework offered. The STEP program goals are: to design compulsory courses in each degree; to develop the conceptual base and identify reference models in sustainability for all specialties at UPC; to create an internal interdisciplinary network of faculty from all the schools; to initiate new transdisciplinary research activities in technology-sustainability-education; to spread the know/how attained; to achieve international scientific excellence in technology-sustainability-education and to graduate the first engineers/architects of the new EHEA bachelors with sustainability as a generic competence. Specifically, in this paper authors explain their experience in leading the STEP program, and two examples are presented: Industrial Robotics subject and the curriculum for the School of Architecture.

Keywords: sustainability, curricula improvement, robotics, STEP program

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Authors: Ryunhye Kim

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Despite its relatively short history as an independent state, Qatar has emerged as a highly regarded Gulf state and global power. Since its independence in September 1971, the state has employed deliberate policy initiatives designed to put Qatar on the map and distinguish it from other Gulf states. Because Qatar and its neighbors are resource-poor apart from energy, whoever is first to introduce a unique aspect of branding not only takes the lead but assumes what is often an insurmountable advantage. This study examines three specific modes of branding undertaken by Qatar: (1) energy policies to utilize its natural gas to become a dominant supplier; (2) the deliberate construction of a distinct cultural brand utilizing sports, architecture, museums, and media; and (3) ‘niche diplomacy’ to serve as a mediator in regional and intra-national conflicts, especially as interlocutor between the United States and Arab regimes and Muslim groups. Gleaning data from a range of sources, this study analyzes the effectiveness and significance of Qatar’s place branding on the global stage, as well as potential disadvantages and limits in this branding, including problems encountered before and after the ‘Qatar crisis.’

Keywords: national branding, national-identity, Qatar, soft-power

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Nurdiyana Zainal Abidin, Raja Nafida Raja Shahminan, Fawazul Khair Ibrahim

Abstract:

Timber vernacular houses in Malaysia are unique heritage buildings which can be identified through their designs, structure, architectural elements and ornamentations. Woodcarvings are common forms of ornamentations and decorations in Traditional Malay Houses and they can be found throughout Malaysia including in Negeri Sembilan. As a multi-cultural, multi-racial, and multi-religion state which uniquely practices the matrilineal social system, Negeri Sembilan has a strong connection to its’ history and heritage and in particular the distinctive vernacular architecture. The purpose of this paper is to underline the factors that influence the woodcarvings in Traditional Malay Houses in Negeri Sembilan, Malaysia. The houses studied were from the archives of measured drawings in Center of Built Environment in the Malay World (KALAM), Universiti Teknologi Malaysia (UTM). The findings indicated several factors influencing the woodcarver’s works and also the applications of the woodcarvings such as religious factors, cultural factors and political factors. These factors among several other shows that woodcarvings were predetermined before being carved and that they were not just merely placed without reason but are functioning pieces of aesthetic ornamentation.

Keywords: influences, traditional Malay houses, woodcarvings, multi-cultural

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Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

Abstract:

An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

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Authors: Promise Ekpo Osaine, Daniel Melesse

Abstract:

Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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