Search results for: structural change model

Authors: Jinkoo Kim, Minsung Kim

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This study develops a hybrid seismic energy dissipation device composed of a viscoelastic damper and a steel slit damper connected in parallel. A cyclic loading test is conducted on a test specimen to validate the seismic performance of the hybrid damper. Then a moment-framed model structure is designed without seismic load so that it is retrofitted with the hybrid dampers. The model structure is transformed into an equivalent simplified system to find out optimum story-wise damper distribution pattern using genetic algorithm. The effectiveness of the hybrid damper is investigated by fragility analysis and the life cycle cost evaluation of the structure with and without the dampers. The analysis results show that the model structure has reduced probability of reaching damage states, especially the complete damage state, after seismic retrofit. The expected damage cost and consequently the life cycle cost of the retrofitted structure turn out to be significantly small compared with those of the original structure. Acknowledgement: This research was supported by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R & D program (N043100016).

Keywords: seismic retrofit, slit dampers, friction dampers, hybrid dampers

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Authors: Eve-Andree Laramee

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The aesthetics and ethics of the Nuclear Anthropocene are explored through artists responses to the impact of radioactive materials on ecological systems, global issues, energy policies and ourselves. This presentation tracks and reveals the invisible traces of the nuclear weapons complex and the nuclear energy industry, in relation to environmental justice. Radioactive pollution transgresses international borders, boundaries between land and water, contaminating ecological systems. Radioactive waste is never disposed of; it is dispositioned, placed out of sight and out of mind. These materials leave behind an invisible toxic legacy lasting millions of years. As we are learning post-Fukushima, when climate change occurs and vulnerability spectrums shift, nuclear sites and the life forms surrounding them are at increased risk. By visualizing this contamination through art installations, videos, and social-sculpture interventions, information is shared with the public, raising awareness, and activating community participation in remediation and nonproliferation efforts. The emerging Ecological Art genre proposes paradigms sustainable with the life forms and resources of our planet. It is comprised of artists, scientists, philosophers and activists devoted to these. EcoArt is distinguished by a focus on systems and interrelationships within our environment: the ecological, geographic, political, biological and cultural. This presentation will cover artworks addressing the recent Fukushima meltdowns, weapons proliferation, climate change, radioactive waste disposal and environmental justice. Possibilities for art-and-science collaborations will be discussed as projects that sharpen our ethics and politics in our behaviors and social interactions. The presentation will consist of a PowerPoint talk (paper presentation) accompanied by images and video clips.

Keywords: art, ecology, environment, anthropocene, nuclear

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

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Authors: Nadjah Chergui, Narhimene Boustia

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Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: context, default, exception, vulnerability

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Authors: Maath M. Musleh

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This research aims to study recent trends in the Palestinian feminist movement through the case study of Tal3at. The study uses social network analysis as its primary method to analyze Twitter data. It attempts to interpret results through the lens of network theories and Parson’s AGIL paradigm. The study reveals major structural weaknesses in the Tal3at network. Our findings suggest that the movement will decline soon as sentiments of alienation amongst Palestinian women increases. These findings were validated by a couple of central actors in the network. This study contributes an SNA approach to the understanding of the understudied Palestinian feminism.

Keywords: feminism, Palestine, social network analysis, Tal3at

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Authors: A. Brahma

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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Jae-Yeong Choi, Gyu-Mok Jeon, Jong-Chun Park, Yong-Jin Cho, Seok-Tae Yoon

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When air flow is injected into water, bubbles are formed in various types inside the water pool along with the air flow rate. The bubbles are floated in equilibrium with forces such as buoyancy, surface tension and shear force. Single bubble generated at low flow rate maintains shape, but bubbles with high flow rate break up to make mixing and turbulence. In addition to this phenomenon, as the hot air bubbles are injected into the water, heat affects the interface of phases. Therefore, the main scope of the present work reveals how to proceed heat transfer between water and hot air bubbles injected into water. In the present study, a series of CFD simulation for the heat transfer of hot bubbles injected through a nozzle near the bottom in a cylindrical water column are performed using a commercial CFD software, STAR-CCM+. The governing equations for incompressible and viscous flow are the continuous and the RaNS (Reynolds- averaged Navier-Stokes) equations and discretized by the FVM (Finite Volume Method) manner. For solving multi-phase flow, the Eulerian multiphase model is employed and the interface is defined by VOF (Volume-of-Fluid) technique. As a turbulence model, the SST k-w model considering the buoyancy effects is introduced. For spatial differencing the 3th-order MUSCL scheme is adopted and the 2nd-order implicit scheme for time integration. As the results, the dynamic behavior of the rising hot bubbles with the flow rate injected and regarding heat transfer mechanism are discussed based on the simulation results.

Keywords: heat transfer, hot bubble injection, eulerian multiphase model, flow rate, CFD (Computational Fluid Dynamics)

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Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

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Authors: Athulya Jayakumar, M. Manjula

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Though there has been a shift in the understanding of homosexuality from being a sin, crime or pathology in the medical and legal perspectives, the acceptance of homosexuality still remains very scanty in the Indian subcontinent. The present case study is a 24-year-old female who has completed a diploma in polytechnic engineering and residing in the state of Kerala. She initially presented with her husband with complaints of lack of sexual desire and non-cooperation from the index client. After an initial few sessions, the client revealed, in an individual session, about her homosexual orientation which was unknown to her family. She has had multiple short-term relations with females and never had any heterosexual orientation/interest. During her adolescence, she was wondering if she could change herself into a male. However, currently, she accepts her gender. She never wanted a heterosexual marriage; but, had to succumb to the pressure of mother, as a result of a series of unexpected incidents at home and had to agree for the marriage, also with a hope that she may change herself into a bi-sexual. The client was able to bond with the husband emotionally but the multiple attempts at sexual intercourse, at the insistence of the husband, had always been non-pleasurable and induced a sense of disgust. Currently, for several months, there has not been any sexual activity. Also, she actively avoids any chance to have a warm communication with him so that she can avoid chances of him approaching her in a sexual manner. The case study is an attempt to highlight the culture and the struggles of a homosexual individual who comes to therapy for wanting to be a ‘normal wife’ despite having knowledge of legal rights and scenario. There is a scarcity of Indian literature that has systematically investigated issues related to homosexuality. Data on prevalence, emotional problems faced and clinical services available are sparse though it is crucial for increasing understanding of sexual behaviour, orientation and difficulties faced in India.

Keywords: case study, culture, cognitive behavior therapy, female homosexuality

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Authors: Jihene Jlassi, Ahmed Frikha, Wazna Kortli

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The objectives of Nurse-Patient Assignment are the minimization of the overall hospital cost and the maximization of nurses ‘preferences. This paper aims to assess nurses' satisfaction related to the implementation of patient acuity tool-based assignments. So, we used an integer linear program that assigns patients to nurses while balancing nurse workloads. Then, the proposed model is applied to the Paediatrics Department at Kasserine Hospital Tunisia. Where patients need special acuities and high-level nursing skills and care. Hence, numerical results suggested that proposed nurse-patient assignment models can achieve a balanced assignment

Keywords: nurse-patient assignment, mathematical model, logistics, pediatrics department, balanced assignment

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Ravi Kant Anand, Nikkey Keshri

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The Great Barrier Reef of Australia is known for its beautiful landscapes and seascapes with ecological importance. This site was selected as a World Heritage site in 1981 and popularized internationally for tourism, recreational activities and fishing. But the major environmental hazards such as climate change, pollution, overfishing and shipping are making worst the site of marine ecosystem. Climate change is directly hitting on Great Barrier Reef through increasing level of sea, acidification of ocean, increasing in temperature, uneven precipitation, changes in the El Nino and increasing level of cyclones and storms. Apart from that pollution is second biggest factor which vanishing the coral reef ecosystem. Pollution including over increasement of pesticides and chemicals, eutrophication, pollution through mining, sediment runoff, loss of coastal wetland and oil spills. Coral bleaching is the biggest problem because of the environmental threatening agents. Acidification of ocean water reduced the formation of calcium carbonate skeleton. The floral ecosystem (including sea grasses and mangroves) of ocean water is the key source of food for fishes and other faunal organisms but the powerful waves, extreme temperature, destructive storms and river run- off causing the threat for them. If one natural system is under threat, it means the whole marine food web is affected from algae to whale. Poisoning of marine water through different polluting agents have been affecting the production of corals, breeding of fishes, weakening of marine health and increased in death of fishes and corals. In lieu of World Heritage site, tourism sector is directly affected and causing increasement in unemployment. Fishing sector also affected. Fluctuation in the temperature of ocean water affects the production of corals because it needs desolate place, proper sunlight and temperature up to 21 degree centigrade. But storms, El Nino, rise in temperature and sea level are induced for continuous reduction of the coral production. If we do not restrict the environmental problems of Great Barrier Reef than the best known ecological beauty with coral reefs, pelagic environments, algal meadows, coasts and estuaries, mangroves forests and sea grasses, fish species, coral gardens and the one of the best tourist spots will lost in upcoming years. My research will focus on the different environmental threats, its socio-economic impacts and different conservative measures.

Keywords: climate change, overfishing, acidification, eutrophication

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Mohammed Alhawiti

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Assessment of Learning Management Systems has been of less importance than its due share. This paper investigates the evaluation of learning management systems (LMS) within educational setting as both an online learning system as well as a helpful tool for multidisciplinary learning environment. This study suggests a theoretical e-learning evaluation model, studying a multi-dimensional methods for evaluation through LMS system, service and content quality, learner`s perspective and attitudes of the instructor. A survey was conducted among 105 e-learners. The sample consisted of students at both undergraduate and master’s levels. Content validity, reliability were tested through the instrument, Findings suggested the suitability of the proposed model in evaluation for the satisfaction of learners through LMS. The results of this study would be valuable for both instructors and users of e-learning systems.

Keywords: e-learning, LMS, higher education, management systems

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Said Al Saifi

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This paper proposes a conceptual model for understanding the impact of organisational culture on knowledge management processes and their link with organisational performance. It is suggested that organisational culture should be assessed as a multi-level construct comprising artifacts, espoused beliefs and values, and underlying assumptions. A holistic view of organisational culture and knowledge management processes, and their link with organisational performance, is presented. A comprehensive review of previous literature was undertaken in the development of the conceptual model. Taken together, the literature and the proposed model reveal possible relationships between organisational culture, knowledge management processes, and organisational performance. Potential implications of organisational culture levels for the creation, sharing, and application of knowledge are elaborated. In addition, the paper offers possible new insight into the impact of organisational culture on various knowledge management processes and their link with organisational performance. A number of possible relationships between organisational culture factors, knowledge management processes, and their link with organisational performance were employed to examine such relationships. The research model highlights the multi-level components of organisational culture. These are: the artifacts, the espoused beliefs and values, and the underlying assumptions. Through a conceptualisation of the relationships between organisational culture, knowledge management processes, and organisational performance, the study provides practical guidance for practitioners during the implementation of knowledge management processes. The focus of previous research on knowledge management has been on understanding organisational culture from the limited perspective of promoting knowledge creation and sharing. This paper proposes a more comprehensive approach to understanding organisational culture in that it draws on artifacts, espoused beliefs and values, and underlying assumptions, and reveals their impact on the creation, sharing, and application of knowledge which can affect overall organisational performance.

Keywords: knowledge application, knowledge creation, knowledge management, knowledge sharing, organisational culture, organisational performance

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Authors: Adam Y. Sulaiman, Donal F. Cotter, Ming J. Huang, Neil J. Hewitt

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Decarbonization of the industrial sector in developed countries has become indispensable for addressing climate change. Industrial processes including drying, distillation, and injection molding require a process heat exceeding 180°C, rendering the subcriticalHigh-Temperature heat pump(HTHP) technique unsuitable. A transcritical HTHP utilizing ecologically friendly working fluids is a highly recommended system that incorporates the features of high-energy efficiency, extended operational range, and decarbonizing the industrial sector. This paper delves into the possibility and feasibility of leveraging the HTTP system to provide up to 200°C of heat using R1233zd(E) as a working fluid. Using a steady-state model, various transcritical HTHP cycle configurations aretheoretically compared,analyzed, and evaluatedin this study. The heat transfer characteristics for the evaporator and gas cooler are investigated, as well as the cycle's energy, exergetic, and environmental performance. Using the LMTD method, the gas cooler's heat transfer coefficient, overall length, and heat transfer area were calculated. The findings indicate that the heat sink pressure level, as well as the waste heat temperature provided to the evaporator, have a significant impact on overall cycle performance. The investigation revealed the potential challenges and barriers, including the length of the gas cooler and the lubrication of the compression process. The basic transcritical HTTP cycle with additional IHX was demonstrated to be the most efficient cycle across a variety of heat source temperatures ranging from 70 to 90 °C based on theoretical energetic and exergetic performance.

Keywords: high-temperature heat pump, transcritical cycle, refrigerants, gas cooler, energy, exergy

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Saeed Al Amoudy

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During the last decade, the rapidly growing prestige of so-called Creative Cities has inspired many other cities seeking to enhance their attractiveness, creativity, and success. However, the concept of a creative city seems to be an elusive one because it reflects a set of distinct ideologies which apply distinct ideas of creativity to physical and economic urban development. The main aim of this study is to investigate the ways in which the theoretical concept of the creative city can be usefully and practically employed to develop the urban services and global identity of Makkah, Saudi Arabia. This is a challenging prospect since no research on creative cities in the Middle East has previously been conducted. The city of Makkah and its holy sites is known as the focus of religious devotion for one and half billion Muslims around the globe, with millions travelling there on annual pilgrimage. The ideas of three of the key authors who have addressed relevant aspects of the concept of the creative city, Landry, Howkins and Florida, were explored in depth for the purpose of identifying the model which would be best suited to Makkah’s identity as a sacred city. Of these, it was the approach of Landry and others whose work was originally focused on finding creative solutions to the problems faced by cities which proved most suitable for the context of Makkah. The development strategies of five case studies of Creative Cities situated in different parts of the world, namely Vancouver, Yokohama, Glasgow, Barcelona, and Sydney, were also examined. Inspired by their diverse experiences, a model, referred to by the acronym CREATIVE, was developed by bringing together the key elements which seemed to ,account for the success of these five creative cities: Concept, Resources, Events, Attractiveness, Technology, Involvement, Vision and Enthusiasm. Expert opinion was sought on the model by presenting this for discussion at five international conferences. This model was used to guide both the process of data collection via interviews, documentation and field notes, and for analysing this, revealing that Makkah has great potential to become a Creative City. The results suggested that implementation of the CREATIVE model in Makkah would help produce creative solutions to address the problems that the city currently faces due to the growing number of pilgrims every year.

Keywords: creative city, city imaging, Makkah, sacred city

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Authors: Qi Lu, Jian Deng, Daishun Huang, Chao Guo

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The lead cooled fast reactor is considered as one of the most potential Generation IV nuclear systems due to the low working pressure, the appreciable neutron economy, and the considerable passive characteristics. Meanwhile, the lead bismuth eutectic (LBE) has the related advantages of lead with the weaker corrosiveness, which has been paid much attention by recent decades. Moreover, the sub-channel code is a necessary analysis tool for the reactor thermal-hydraulic design and safety analysis, which has been developed combined with the accumulation of LBE experimental data and the understanding of physical phenomena. In this study, a sub-channel code available for LBE was developed, and the corresponding geometric characterization method of typical sub-channels was described in detail, especially for for the fuel assembly with wire spacer. As for this sub-channel code, the transversal thermal conduction through gap was taken into account. In addition, the physical properties, the heat transfer model, the flow resistance model and the turbulent mixing model were analyzed. Finally, the thermal-hydraulic experiments of LBE conducted on THEADES (THErmal-hydraulics and Ads DESign) were selected as the evaluation data of this sub-channel code, including 19 rods with wire spacer, and the calculated results were in good agreement with the experimental results.

Keywords: lead bismuth eutectic, sub-channel code, wire spacer, transversal thermal conduction

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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: I. Bouhaf Kharkhachi, A. Attaf

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Tin sulfide thin films on glass substrate were prepared by spray ultrasonic technique, at different experimental conditions. The influence of deposition time (2, 4, 6, 8 and 10 min) on different properties of thin films, such us, (XRD) and (UV) spectroscopy visible spectrum was investigated. X-ray diffraction showing that thin films crystallized in SnS, SnS2, and Sn2S3 phases. The results of (UV) spectroscopy visible spectrum show that films deposited at 4 min are large transmittance 60% in the visible region.

Keywords: SnS, thin films, ultrasonic spray, X-ray diffraction, UV spectroscopy visible

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Authors: Özge Selin Çevik, Leyla Şahin, Gülhan Örekeci Temel

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The early postnatal period is critical for the development of cognitive and emotional functions. Maternal separation is a detrimental postnatal influence, whereas environmental enrichment is a therapeutic and protective agent. It is unclear if long-term environmental enrichment can compensate for the effects of maternal separation stress on anxiety behavior. This study was designed to examine how environmental enrichment affects anxiety levels and corticosterone levels in maternally separated rats. There are six main groups in this study: control (C), maternal separation+standard cage (MS), maternal separation+enriched environment (MSE), enriched environment (E), the maternal separation that decapitated at postnatal (PN) 21 (MS21), and standard cage that decapitated at PN21 (STD21). The maternal separation procedure consisted of PN for 21 days (between 09:00 a.m and 12:00 a.m). Enriched (E, MSE) or standard cage environment rats (MS, C) spent PN (22-55) days in either enriched cages or standard cages. Anxiety and locomotor activity were examined with the open field and elevated plus-maze test. Blood corticosterone level was evaluated by the enzyme-linked immunosorbent assay (ELISA) method. Results showed that maternal separation (MS) increased locomotor activity and anxiety. An enriched environment (E) did not change the locomotor activity. MSE group’s anxiety and locomotor activity did not change. Corticosterone levels increased in the maternal separation group that decapitated at the PN 21 days. Maternal separation increases anxiety. Environmental enrichment alone was insufficient to cause alterations in the anxiety level. In addition, environmental enrichment did not ameliorate the anxiety level in maternally separated rats. However, environmental enrichment decreased the locomotor activity in the maternally separated rats.

Keywords: maternal separation, environment enrichment, stress, hippocampus, anxiety, memory, rat

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Authors: Bishal Saha, Musah Ahmed Rufai Muhyedeen, Jubeyer Hossain Joy, Muhammad Muhitur Rahman, Mohammad Shahedur Rahman, Md Arif Hasan, Syed Masiur Rahman

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Greenhouse gas (GHG) emission is one of the critical problems of today’s world. Many countries have been taking many short- and long-term plans to reduce climate change mitigation. However, the potential of behavioral changes in addressing this problem is promising, as reported by many researchers. This paper presents a comprehensive literature review that focuses on ways to influence people’s behavior in their homes, workplace, and transportation to mitigate the emission directly or indirectly. This study will investigate different theories pertinent to planned behavior and the key elements for modifying behavior like biophilia, reinforcement to use optimum energy and recyclable products, proper application of greenhouse tax, modern technology, and sustainable design adaptation, transportation sharing, social and community norms, proper education and information, and financial incentives. There is a number of challenges associated with behavioral changes. Behavioral interventions have different actions varied by their type and need to combine various policy tools and great social marketing. Many interventions can reduce GHG emissions without any compromise with household well-being. This study will develop a landscape of prevailing theories of environmental psychology by identifying and reviewing the key themes and findings of this field of study. It will support especially the developing countries to reduce GHG emissions without significant capital investment. It is also expected that the behavioral changes will lead to the successful adoption of climate-friendly policies easily. This study will also generate new research questions and directions.

Keywords: behavioral changes, climate change mitigation, environmental psychology, greenhouse gas emission

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Authors: Reza Salehi, Peter L. Dold, Yves Comeau

Abstract:

The aim of the present study was to investigate the effect of a total of 6 operating parameters including pH (X1), temperature (X2), stirring speed (X3), chemical oxygen demand (COD) (X4), volatile suspended solids (VSS) (X5) and time (X6) on anaerobic orthophosphate release from enhanced biological phosphorus removal (EBPR) sludge. An 8-run Plackett Burman design was applied and the statistical analysis of the experimental data was performed using Minitab16.2.4 software package. The Analysis of variance (ANOVA) results revealed that temperature, COD, VSS and time had a significant effect with p-values of less than 0.05 whereas pH and stirring speed were identified as non-significant parameters, but influenced orthophosphate release from the EBPR sludge. The mathematic expression obtained by the first-order multiple linear regression model between orthophosphate release from the EBPR sludge (Y) and the operating parameters (X1-X6) was Y=18.59+1.16X1-3.11X2-0.81X3+3.79X4+9.89X5+4.01X6. The model p-value and coefficient of determination (R2) value were 0.026 and of 99.87%, respectively, which indicates the model is significant and the predicted values of orthophosphate release from the EBPR sludge have been excellently correlated with the observed values.

Keywords: anaerobic, operating parameters, orthophosphate release, Plackett-Burman design

Procedia PDF Downloads 268

Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

Abstract:

We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

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Authors: Yan-Ting Lin, Wei-Nian Su

Abstract:

The purpose of this paper is to demonstrate the design of 5kW vertical axis wind turbine (VAWT) using DOE method. The NACA0015 airfoil was implemented for the design and 3D simulation. The critical design parameters are chord length, tip speed ratio (TSR), aspect ratio (AR) and pitch angle in this investigation. The RNG k-ε turbulent model and the sliding mesh method are adopted in the CFD simulation. The results show that the model with zero pitch, 0.3 m in chord length, TSR of 3, and AR of 10 demonstrated the optimum aerodynamic power under the uniform 10m/s inlet velocity. The aerodynamic power is 3.61kW and 3.89kW under TSR of 3 and 4 respectively. The aerodynamic power decreased dramatically while TSR increased to 5.

Keywords: vertical axis wind turbine, CFD, DOE, VAWT

Procedia PDF Downloads 426

Authors: Ebenezer Amoquandoh, Daniel Bruce Sarpong, Godfred K. Ofosu-Budu, Andreas Fliessbach

Abstract:

Soil quality is at stake globally, but under tropical conditions, the loss of soil fertility may be existential. The current rates of soil nutrient depletion, erosion and environmental degradation in most of Africa’s farmland urgently require methods for soil fertility restoration through affordable agricultural management techniques. The study assessed the effects of locally available organic resources to improve soil fertility, crop yield and profitability compared to business as usual on farms in the Eastern and Greater Accra regions of Ghana. Apart from this, we analyzed the change of farmers’ perceptions and knowledge upon the experience with the new techniques; the effect of using locally available organic resource on farmers’ yield and determined the factors influencing the profitability of farming. Using the Difference in Mean Score and Proportion to estimate the extent to which farmers’ perceptions, knowledge and practices have changed, the study showed that farmers’ perception, knowledge and practice on the use of locally available organic resources have changed significantly. This paves way for the sustainable use of locally available organic resource for soil fertility improvement. The Propensity Score Matching technique and Endogenous Switching Regression model used showed that using locally available organic resources have the potential to increase crop yield. It was also observed that using the Profit Margin, Net Farm Income and Return on Investment analysis, it is more profitable to use locally available organic resources than other soil fertility amendments techniques studied. The results further showed that socioeconomic, farm characteristics and institutional factors are significant in influencing farmers’ decision to use locally available organic resources and profitability.

Keywords: soil fertility, locally available organic resources, perception, profitability, sustainability

Procedia PDF Downloads 134

Authors: Syed W. Hasan, Zhiqun Tian

Abstract:

Wet spinning provides a facile and economic route to fabricate graphene nanofibers (GFs) on mass scale. Nevertheless, the pristine GFs exhibit significantly low electrical and mechanical properties owing to stacked graphene sheets and weak inter-atomic bonding. In this report, we present highly conductive Ag-decorated-GFs (Ag/GFs). The SEM micrographs show Ag nanoparticles (NPs) (dia ~10 nm) are homogeneously distributed throughout the cross-section of the fiber. The Ag NPs provide a conductive network for the electrons flow raising the conductivity to 1.8(10^4) S/m which is 4 times higher than the pristine GFs. Our results surpass the conductivities of graphene fibers doped with CNTs, Nanocarbon, fullerene, and Cu. The chemical and structural attributes of Ag/GFs are further elucidated through XPS, AFM and Raman spectroscopy.

Keywords: Ag nanoparticles, Conductive fibers, Graphene, Wet spinning

Procedia PDF Downloads 126