Search results for: intelligent memory structures

Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: rapid urbanization, traditional street space, space re-construction, bottom-up design

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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Authors: Nasser-Eddine Attari

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After the earthquake many structures were classified as slightly damaged and, being uneconomic to replace them, at least in the short term, suitable means of repairs of the beam column joint area are being studied. Furthermore there exist a large number of buildings that need retrofitting of the joints before the next earthquake. The paper reports the results of the experimental programme, constituted of three beam-column reinforced concrete joints at a scale of one to three (1/3) tested under the effect of a pre-stressed axial load acting over the column. The beams were subjected at their ends to an alternate cyclic loading under displacement control to simulate a seismic action. Strain and cracking fields were monitored with the help a digital recording camera. Following the analysis of the results, a comparison can be made between the performances in terms of ductility, strength and mode of failure of the different strengthening solution considered.

Keywords: fibrereinforced polymers, joints, reinforced concrete, beam columns

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Authors: K. Kaouther, D. Hafedh, A. Ben Cheikh Larbi

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Various structures and compositions thin films were deposited on 100C6 (AISI 52100) steel substrate by PVD magnetron sputtering system. The morphological proprieties were evaluated using an atomic force microscopy (AFM). Vickers microindentation tests were performed with a Shimadzu HMV-2000 hardness testing machine. Hardness measurement was carried out using Jonsson and Hogmark model. The results show that the coatings topography was dominated by domes and craters. Mechanical behavior and failure modes under microindentation were depending of coatings structure and composition. TiAlN multilayer showed exception in the microindentation resistance compared to TiN single layer and TiAlN/TiAlN nanolayer. Piled structure provides an increase of failure resistance and a decrease in cracks propagation.

Keywords: PVD thin films, multilayer, microindentation, cracking, damage mechanisms

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Authors: Muhammad A. Khan, Waseem Shahzad

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Analysis of protein sequences is carried out for the purpose to discover their structural and ancestry relationship. Sequence similarity determines similar protein structures, similar function, and homology detection. Biological sequences composed of amino acid residues or nucleotides provide significant information through sequence alignment. In this paper, we present a new similarity/dissimilarity measure to sequence alignment based on the primary structure of a protein. The approach finds the distance between the two given sequences using the novel sequence alignment algorithm and a mathematical model. The algorithm runs at a time complexity of O(n²). A distance matrix is generated to construct a phylogenetic tree of different species. The new similarity/dissimilarity measure outperforms other existing methods.

Keywords: alignment, distance, homology, mathematical model, phylogenetic tree

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Authors: Jong-Sung Kim, Myung-Jo Jhung

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BFA is one of the reactor internals components in PWR. The BFA has the intended functions to support fuel assembly, to keep structural integrity of upper/lower core support structures, and to secure reactor coolant flow path. Failure of the BFA may give rise to significant effect on reactor safety operation and stop. The BFA is subject to relatively high neutron irradiation dose due to location close to the core. Therefore, IASCC can occur on the BFA due to damage accumulation as operating year increases. In this study, IASCC susceptibility on the BFA was assessed via the FEA considering variations of mechanical material behaviors with neutron irradiation. As a result of the assessment, some points have susceptibility more than 0.2 to IASCC during design lifetime.

Keywords: baffle former assembly, finite element analysis, irradiation aging, nuclear power plant, pressurized water reactor

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: energy consumption, IEEE 802.15.4, IoT security, security cost evaluation

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: L. Freeborn

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This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

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Authors: Mircea I. Pastrav, Cornelia Baera, Florea Dinu

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A different concept for designing and detailing of reinforced concrete precast frame structures is analyzed in this paper. The new detailing of the joints derives from the special hybrid moment frame joints. The special reinforcements of this alternative detailing, named modified special hybrid joint, are bondless with respect to both column and beams. Full scale tests were performed on a plan model, which represents a part of 5 story structure, cropped in the middle of the beams and columns spans. Theoretical approach was developed, based on testing results on twice repaired model, subjected to lateral seismic type loading. Discussion regarding the modified special hybrid joint behavior and further on widening research needed concludes the presentation.

Keywords: modified hybrid joint, repair, seismic loading type, acceptance criteria

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

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We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

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Authors: F. Asadi, M. M. Zerafat, S. Sabbaghi

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Among water pollutants, volatile organic compounds can cause severe long lasting effects not only on biotic organism but also on human health. As a result, this material group has attracted more attention in recent years. Adsorption is one of the common processes for remediation of aromatic compounds. In this study, porous clay hetrostructers (PCHs) are synthesized through gallery template approach and cetyltrimethylammonium bromide and dodecylamine used as template and co-template, respectively. Porous clay is characterized by XRD and FTIR. Batch adsorption experiments were carried out to investigate the effect of various adsorption parameters like adsorbent dosage, pH, initial concentration and contact time. It was found that by increasing adsorbent dosage from 0.5gr/lit to 4gr/lit, toluene removal is increased from 34% to 88.1%. Increasing contact time and decreasing the pH of aqueous solution increases toluene removal efficiency.

Keywords: adsorption, clay, nano-porous, toluene

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Authors: Mohammed Raza Mehdi, Kamran Ahmed

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Mega-city Karachi has numerous unplanned slum areas and squatter settlements with irregular growth of building structures. Due to weak development policy and lack of development control, such settlements are increasing at a rapid pace. Mapping such areas for planning and infrastructure development requires an integrated approach of socio-spatial and technological tools. Therefore in this study, an attempt is made to create GIS information layers on complex inbound built-up areas of slums at the coastal belt of Karachi by using a stereo pair of satellite images. The outcome expected is technological application to aid planning institutions for crisis management and infrastructure development in irregularly developed slum areas of Karachi, Pakistan.

Keywords: slum, satellite imageries, GIS, Karachi, Pakistan

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Authors: Gabriella Dravecz, László Péter, Zsolt Kis

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Abstract— The growth of optical LiNbO3 single crystal and its physical and chemical properties are well known on the macroscopic scale. Nowadays the rare-earth doped single crystals became important for coherent quantum optical experiments: electromagnetically induced transparency, slow down of light pulses, coherent quantum memory. The expansion of applications is increasingly requiring the production of nano scaled LiNbO3 particles. For example, rare-earth doped nanoscaled particles of lithium niobate can be act like single photon source which can be the bases of a coding system of the quantum computer providing complete inaccessibility to strangers. The polyol method is a chemical synthesis where oxide formation occurs instead of hydroxide because of the high temperature. Moreover the polyol medium limits the growth and agglomeration of the grains producing particles with the diameter of 30-200 nm. In this work nano scaled LiNbO3 was prepared by the polyol method. The starting materials (niobium oxalate and LiOH) were diluted in H2O2. Then it was suspended in ethylene glycol and heated up to about the boiling point of the mixture with intensive stirring. After the thermal equilibrium was reached, the mixture was kept in this temperature for 4 hours. The suspension was cooled overnight. The mixture was centrifuged and the particles were filtered. Dynamic Light Scattering (DLS) measurement was carried out and the size of the particles were found to be 80-100 nms. This was confirmed by Scanning Electron Microscope (SEM) investigations. The element analysis of SEM showed large amount of Nb in the sample. The production of LiNbO3 nano particles were succesful by the polyol method. The agglomeration of the particles were avoided and the size of 80-100nm could be reached.

Keywords: lithium-niobate, nanoparticles, polyol, SEM

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Authors: K. M. Etmimi, A. A. Sghayer, A. M. Gsiea, A. M. Abutruma

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Relatively few chemical species can be incorporated into diamond during CVD growth, and until recently the uptake of oxygen was thought to be low perhaps as a consequence of a short surface residence time. Within the literature, there is speculation regarding spectroscopic evidence for O in diamond, but no direct evidence. For example, the N3 and OK1 EPR centres have been tentatively assigned models made up from complexes of substitutional N and substitutional oxygen. In this study, we report density-functional calculations regarding the stability, electronic structures, geometry and hyperfine interaction of substitutional oxygen in diamond and show that the C2v, S=1 configuration very slightly lower in energy than the other configurations (C3v, Td, and C2v with S=0). The electronic structure of O in diamond generally gives rise to two defect-related energy states in the band gap one a non-degenerate a1 state lying near the middle of the energy gap and the other a threefold-degenerate t2 state located close to the conduction band edges. The anti-bonding a1 and t2 states will be occupied by one to three electrons for O+, O and O− respectively.

Keywords: DFT, oxygen, diamond, hyperfine

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Authors: H. Naderpour, R. C. Barros, S. M. Khatami

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Seismic excitation is naturally caused large horizontal relative displacements, which is able to provide collisions between two adjacent buildings due to insufficient separation distance and severe damages are occurred due to impact especially in tall buildings. In this paper, an impact is numerically simulated and two needed parameters are calculated, including impact force and energy absorption. In order to calculate mentioned parameters, mathematical study needs to model an unreal link element, which is logically assumed to be spring and dashpot to determine lateral displacement and damping ratio of impact. For the determination of dynamic response of impact, a new equation of motion is theoretically suggested to evaluate impact force and energy dissipation. In order to confirm the rendered equation, a series of parametric study are performed and the accuracy of formula is confirmed.

Keywords: pounding, impact, dissipated energy, coefficient of restitution

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Authors: Munir Tasdemir

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Polymer/clay composites have received great attention in the past three decades owing to their light weight coupled with significantly better mechanical and barrier properties than the corresponding neat polymer resins. An investigation was carried out on the effects of red mud powder size and ratio on the mechanical and thermal properties of polypropylene /red mud polymer composites. Red mud, in four different concentrations (0, 10, 20 and 30 wt %) and three different powder size (180, 63 and 38 micron) were added to PP to produce composites. The mechanical properties, including the elasticity modulus, tensile & yield strength, % elongation, hardness, Izod impact strength and the thermal properties including the melt flow index, heat deflection temperature and vicat softening point of the composites were investigated. The structures of the composites were investigated by scanning electron microscopy and compared to mechanical and thermal properties as a function of red mud powder content and size.

Keywords: polypropylene, powder, red mud, mechanical properties

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Authors: Bruna C. Brasileiro, José Alberto S. Sá, Brigida R. P. Rocha

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The Amazon region development was related to large-scale projects associated with economic cycles. Economic cycles were originated from policies implemented by successive governments that exploited the resources and have not yet been able to improve the local population's quality of life. These implanted development strategies were based on vertical planning centered on State that didn’t know and showed no interest in know the local needs and potentialities. The future of this region is a challenge that depends on a model of development based on human progress associated to intelligent, selective and environmentally safe exploitation of natural resources settled in renewable and no-polluting energy generation sources – a differential factor of attraction of new investments in a context of global energy and environmental crisis. In this process the planning and support of Brazilian State, local government, and selective international partnership are essential. Residual biomass utilization allows the sustainable development by the integration of production chain and energy generation process which could improve employment condition and income of riversides. Therefore, this research discourses how the use of local residual biomass (açaí lumps) could be an important instrument of sustainable development for isolated communities located at Alcobaça Sustainable Development Reserve (SDR), Tucuruí, Pará State, since in this region the energy source more accessible for who can pay are the fossil fuels that reaches about 54% of final energy consumption by the integration between the açaí productive chain and the use of renewable energy source besides it can promote less environmental impact and decrease the use of fossil fuels and carbon dioxide emissions.

Keywords: Amazon, biomass, renewable energy, sustainability

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Authors: Junita Batubara

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Children with special needs, especially those with disability in mental, physical or social/emotional interactions, are marginalized. Many people still view them as troublesome, inconvenience, having learning difficulties, unproductive and burdensome to society. This study intends to investigate; how musical drama can develop the ability to control the coordination of mental functions; how musical dramas can assist children to work together; how musical dramas can assist to maintain the child's emotional and physical health; how musical dramas can improve children creativity. The objectives of the research are: To know whether musical drama can control the coordination of mental function of children; to know whether musical drama can improve communication ability and expression of children; to know whether musical drama can help children work with people around them; to find out if musical dramas can develop the child's emotional and physical health; to find out if musical drama can improve children's creativity. The study employed a qualitative research approach. Data was collecting by listening, observing in depth through public hearings that select the key informants who were teachers and principals, parents and children. The data obtained from each public hearing was then processed (reduced), conclusion drawing/verification, presentation of data (data display). Furthermore, the model obtained was implementing for musical performance, where the benefits of the show are: musical drama can improve language skills; musical dramas are capable of developing memory and storage of information; developing communication skills and express themselves; helping children work together; assisting emotional and physical health; enhancing creativity.

Keywords: children Down syndrome, music, drama script, performance

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Authors: Boudjelthia Radhwane

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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. The shrinkage of concrete is the main cause of cracking in bridge decks. Bridge decks tend to be restrained from shrinkage, and this restraint along with other factors causes the bridge to crack. The characteristics of SCC under restrained shrinkage are important to understand in order to predict the cracking behavior in actual structures. Restrained shrinkage testing is done in accordance to AASHTO testing protocol. The free shrinkage performance and cracking behavior were reported and compared when changing the sand to aggregate ratio and the water to cement ratio. The results of free shrinkage show that when a mix design has higher free shrinkage, it will crack in restrained shrinkage earlier than a mix with lower free shrinkage.

Keywords: concrete mix, cracking behavior, restrained shrinkage, self compacting concrete

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Authors: Ahmad Almohana

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Technology has led to rapid changes in the world, and most importantly to education, particularly in the 21st century. Technology has enhanced teachers’ potential and has resulted in the provision of greater interaction and choices for learners. In addition, technology is helping to improve individuals’ learning experiences and building their capacity to read, listen, speak, search, analyse, memorise and encode languages, as well as bringing learners together and creating a sense of greater involvement. This paper has been organised in the following way: the first section provides a review of the literature related to the implementation of CALL (computer assisted learning language), and it explains CALL and its phases, as well as attempting to highlight and analyse Warschauer’s article. The second section is an attempt to describe the move from CALL to mobilised systems of edutainment, which challenge existing forms of teaching and learning. It also addresses the role of the teacher and the curriculum content, and how this is affected by the computerisation of learning that is taking place. Finally, an empirical study has been conducted to collect data from teachers in Saudi Arabia using quantitive and qualitative method tools. Connections are made between the area of study and the personal experience of the researcher carrying out the study with a methodological reflection on the challenges faced by the teachers of this same system. The major findings were that it is worth spelling out here that despite the circumstances in which students and lecturers are currently working, the participants revealed themselves to be highly intelligent and articulate individuals who were constrained from revealing this criticality and creativity by the system of learning and teaching operant in most schools.

Keywords: CALL, computer assisted learning language, EFL, English as a foreign language, ELT, English language teaching, ETL, enhanced technology learning, MALL, mobile assisted learning language

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Authors: C. S. Paglia, E. Pesenti, A. Krattiger

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Commercially available methacrylate and acrylamide-based acrylic resins for injection in concrete systems have been tested with respect to the sealing performance and the rebar corrosion. Among the different resins, a methacrylate-based type of acrylic resin significantly inhibited the rebar corrosion. This was mainly caused by the relatively high pH of the resin and the resin aqueous solution. This resin also exhibited a relatively high sealing performance, in particular after exposing the resin to durability tests. The corrosion inhibition behaviour and the sealing properties after the exposition to durability tests were maintained up to one year. The other resins either promoted the corrosion of the rebar and/or exhibited relatively low sealing properties.

Keywords: acrylic resin, sealing performance, rebar corrosion, materials

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

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Authors: Jade Bitomsky

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We all consume films on a daily basis. Yet, we frequently fail to recognize that these narratives shape our social, political, cultural, and economic values and attitudes. Narratives influence our perception; specifically, for this research, our perception of women within the genre of film noir. This creative research project examines to what extent film noir has perpetuated the male gaze and how noir’s representation of women has scripted female gender identity through perpetuated performative acts of femininity. Evolving from this research will be a deconstruction and (re)presentation of the femininity in noir. It will go beyond reiterated examinations, which developed awareness of Hollywood’s oppressive cinematic structures, to subvert the usual phallic diegesis and construct a female gaze in neo-noir screenplay, The Lonely Drive.

Keywords: femme fatale, film noir (classic), male gaze, neo-noir (contemporary), scopophilia

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Authors: Walter Rafael Ramos Villanueva

Abstract:

The overwhelming majority of scholarship on David Chariandy’s novel Soucouyant focuses on how Adele’s dementia represents the preservation of “cultural memory” and the perniciousness of “historical trauma.” However, by metaphorizing Adele’s mental condition, these critics risk treating her dementia as mostly figurative, and they thus elide a more detailed discussion of the literal ramifications of her dementia diagnosis. To move beyond these readings, then, my paper will approach Adele’s disorder as a literal medical condition and explore how her caregiving needs affect not only her but also those around her. Soucouyant subverts traditional caregiving narratives by depicting the difficult and typically invisible labour of informal caregiving that is undertaken by the families and friends of those who are ill or otherwise disabled. Because Adele’s family is unable to access proper public healthcare resources within the community, the burden of care falls upon the protagonist and his brother, who become “parentified children.” Parentified children, according to Nancy D. Chase, are “parents to their parents, and fulfill this role at the expense of their own developmentally appropriate needs and pursuits.” The novel provides a depiction of informal caregiving that is multi-faceted and asks us to question why is it exactly that we place the burden of care on those who are not equipped to handle such pressures instead of putting the onus on the government and the public healthcare system to take care of its most vulnerable members. Ageing Studies scholar Larry Polvika notes that although policymakers often offer “pious expressions of appreciation” and acknowledge that informal caregiving is “the backbone of our long-term care system,” governmental support for these caregivers remains inadequate. It is my belief that, by showcasing the struggles of informal caregivers, Chariandy’s text combats this dangerous and empty political rhetoric.

Keywords: caregiving, dementia, literature, parentified children

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Authors: Hossam Hegazi

Abstract:

Global culture museums play a pivotal role in fostering cross-cultural connections, enhancing mutual understanding, and safeguarding the rich tapestry of cultural heritage. These institutions serve as dynamic bridges, facilitating the exchange of ideas and values among diverse societies. One of the primary functions of global culture museums is to connect people from different backgrounds. By showcasing the artistic expressions, traditions, and historical artifacts of various civilizations, these museums create a shared space for dialogue. Visitors are afforded the opportunity to explore and appreciate the nuances of cultures different from their own, promoting a sense of global interconnectedness. Moreover, these museums contribute significantly to mutual understanding. Through interactive exhibits, innovative technologies, and educational programs, they offer immersive experiences that transcend linguistic and geographical barriers. Visitors gain insights into the customs, beliefs, and lifestyles of others, fostering empathy and appreciation for cultural diversity. Preserving cultural heritage stands as another key objective of global culture museums. By housing and curating artifacts, artworks, and historical items, these institutions play a crucial role in safeguarding the collective memory of humanity. This preservation effort ensures that future generations have access to the cultural legacies that have shaped societies across the globe. In conclusion, global culture museums serve as dynamic hubs that bring people together, promote understanding, and safeguard the wealth of human cultural heritage. Their impact extends beyond the walls of exhibition halls, contributing to a more interconnected and culturally enriched world.

Keywords: global culture museums, cross-cultural connections, mutual understanding, societal dialogue

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Authors: Rahul Paul, Kedar Nath Das

Abstract:

The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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