Search results for: hybrid adaptive modeling

Authors: N. H. Hamid, N. M. Mohamed, S. A. Anuar

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Precast residential houses are normally constructed in Malaysia using precast shear-key wall panel and precast wall panel are designed using BS8110 where there is no provision for earthquake. However, the safety of this house under moderate and strong earthquake is still questionable. Consequently, the full-scale of residential house are designed, constructed, tested and analyzed under in-plane lateral cyclic loading. Hysteresis loops are plotted based on the experimental work and compared with modeling of hysteresis loops using HYSTERES in RUAUMOKO 2D program. Modified Takeda hysteresis model is chosen to behave a similar pattern with experimental work. This program will display the earthquake excitations, spectral displacements, pseudo spectral acceleration, and deformation shape of the structure. It can be concluded that this building is suffering severe cracks and damage under moderate and severe earthquake.

Keywords: precast shear-key, hysteresis loops, spectral displacements, deformation shape

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Authors: Sunil Kumar, Vinay Kumar, Mamta Bulla, Rita Dahiya

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Supercapacitors have emerged as a leading energy storage technology, gaining popularity in applications like digital telecommunications, memory backup, and hybrid electric vehicles. Their appeal lies in a long cycle life, high power density, and rapid recharge capabilities. These exceptional traits attract researchers aiming to develop advanced, cost-effective, and high-energy-density electrode materials for next-generation energy storage solutions. Two-dimensional (2D) nanostructures are highly attractive for fabricating nanodevices due to their high surface-to-volume ratio and good compatibility with device design. In the current study, a composite was synthesized by combining MoS2 with reduced graphene oxide (rGO) under optimal conditions and characterized using various techniques, including XRD, FTIR, SEM and XPS. The electrochemical properties of the composite material were assessed through cyclic voltammetry, galvanostatic charging-discharging and electrochemical impedance spectroscopy. The supercapacitor device demonstrated a specific capacitance of 153 F g-1 at a current density of 1 Ag-1, achieving an excellent energy density of 30.5 Wh kg-1 and a power density of 600 W kg-1. Additionally, it maintained excellent cyclic stability over 5000 cycles, establishing it as a promising candidate for efficient and durable energy storage solutions. These findings highlight the dynamic relationship between electrode materials and offer valuable insights for the development and enhancement of high-performance symmetric devices.

Keywords: 2D material, energy density, galvanostatic charge-discharge, hydrothermal reactor, specific capacitance

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Authors: Verónica Díaz

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A Cartesian graph, as a mathematical object, becomes a tool for configuration of change. Its best comprehension is done through everyday life problem-solving associated with its representation. Despite this, the current educational framework favors general graphs, without consideration of their argumentation. Students are required to find the mathematical function without associating it to the development of graphical language. This research describes the use made by students of configurations made prior to Cartesian graphs with regards to an everyday life problem related to a time and distance variation phenomenon. The theoretical framework describes the function conditions of study and their modeling. This is a qualitative, descriptive study involving six undergraduate case studies that were carried out during the first term in 2016 at University of Los Lagos. The research problem concerned the graphic modeling of a real person’s movement phenomenon, and two levels of analysis were identified. The first level aims to identify local and global graph interpretations; a second level describes the iconicity and referentiality degree of an image. According to the results, students were able to draw no figures before the Cartesian graph, highlighting the need for students to represent the context and the movement of which causes the phenomenon change. From this, they managed Cartesian graphs representing changes in position, therefore, achieved an overall view of the graph. However, the local view only indicates specific events in the problem situation, using graphic and verbal expressions to represent movement. This view does not enable us to identify what happens on the graph when the movement characteristics change based on possible paths in the person’s walking speed.

Keywords: cartesian graphs, higher education, movement modeling, problem solving

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Authors: Makenzy Lee Gilbert

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This literature review explores the role of attractor neural networks (ANNs) in modeling psychological processes in artificial and biological systems. By synthesizing research from dynamical systems theory, psychology, and computational neuroscience, the review provides an overview of the current understanding of ANN function in memory formation, reinforcement, retrieval, and forgetting. Key mathematical foundations, including dynamical systems theory and energy functions, are discussed to explain the behavior and stability of these networks. The review also examines empirical applications of ANNs in cognitive processes such as semantic memory and episodic recall, as well as highlighting the hippocampus's role in pattern separation and completion. The review addresses challenges like catastrophic forgetting and noise effects on memory retrieval. By identifying gaps between theoretical models and empirical findings, it highlights the interdisciplinary nature of ANN research and suggests future exploration areas.

Keywords: attractor neural networks, connectionism, computational modeling, cognitive neuroscience

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Venkatesh Krishna Murthy

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The era before government-regulated automotive designs gave us some astonishing vehicles that are well worth to keep on the road. The fact that restoring an automobile in 2015 does not mean it will perform like one designed in 2021. This is one of the reasons that manufacturers continue to turn to vintage hardware for future enhancements in their vehicles. Now we need to understand that a modern chassis could possibly allow manufacturers to give vintage performance cars a level of braking capability, compatibility with tires, chassis rigidity, suspension sophistication, and steering response, an experience only racers got until now. However, half a century of advancements in engineering can have a great impact on design in any field, and the automotive realm which holds no exception. In the current situation, a growing number of companies offer chassis and braking components to onboard manufacturers to retrofit contemporary technology for their vintage vehicles to modernize them at the foundation level. The recent question arises on performance on lithium batteries, as opposed to simply bolting upgraded components, for ex. lithium batteries with graphene as superconductive material to enhance performance, an area deeply investigated. Serving as the “bones” of the vehicle, the chassis and frame play a central role in dictating how that automobile will perform. While the desire to maintain originality is alluring for many, the benefits of a modern chassis are vast. In some situations, it also allows builders to put cars back on the road that might otherwise be too far gone. “There’s a couple of different factors at play here – one of them being that these older cars from the ’40s, ’50s, and ’60s have seen a lot of weather and a lot of road miles over the years, more often than not,” says Craig Morrison of Art Morrison Enterprises.

Keywords: hybrid electric vehicles, internet of things, lithium graphene batteries, classic car chassis

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

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Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: early warning system, knowledge management, market prediction, topic modeling.

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Authors: Alessandro Andre Leme

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To analyze three Brazilian think tanks: a) Fernando Henrique Foundation; b) Celso Furtado International Center; c) Millennium Institute and how they dispute interpretations about the type of development and State that should be adopted in Brazil. We will make use of Network and content analysis of the sites. The analyzes show a dispute that goes from a defense of ultraliberalism to developmentalism, going through a hybrid between State and Market voiced in each of the Think Tanks.

Keywords: sociopolitical and economic thinking, development, strategies, intellectuals, state

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Authors: Taehyun Kim, Hyunjoo Park, Taehyun Kim

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Since the rapid economic development, Korea has recently entered a period of low growth due to population decline and aging. Due to the urbanization around the metropolitan area and the hollowing of local cities, the ecological capacity of a city is decreasing while ecological footprints are increasing, requiring a compact space plan for maintaining urban functions. The purpose of this study is to analyze the relationship between urban spatial structure and residents' ecological footprints for sustainable spatial planning. To do this, we try to analyze the relationship between intra-urban spatial structure, such as net/gross density and service accessibility, and resident ecological footprints of food, housing, transportation, goods and services through survey and structural equation modeling. The results of the study will be useful in establishing an implementation plan for sustainable development goals (SDGs), especially for sustainable cities and communities (SDG 11) and responsible consumption and production (SDG 12) in the future.

Keywords: ecological footprint, structural equation modeling, survey, sustainability, urban spatial structure

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Authors: Arun Goel

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Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper, attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly and Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly and Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicates the improvement in the performance of SVM (Poly and Rbf) in comparison to dimensional form of scour.

Keywords: modeling, pier scour, regression, prediction, SVM (Poly and Rbf kernels)

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Authors: Dan Geneau, Mary Claire Geneau, Seth Lenetsky, Ming -Chang Tsai, Marc Klimstra

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Introduction— Horizontal force-velocity profiling (HFVP) involves modeling an athletes linear sprint kinematics to estimate valuable maximum force and velocity metrics. This approach to performance modeling has been used in field-based team sports and has recently been introduced to ice-hockey as a forward skating performance assessment. While preliminary data has been collected on ice, distance constraints of the on-ice test restrict the ability of the athletes to reach their maximal velocity which result in limits of the model to effectively estimate athlete performance. This is especially true of more elite athletes. This report explores whether athletes on-ice are able to reach a velocity plateau similar to what has been seen in overground trials. Fourteen male Major Junior ice-hockey players (BW= 83.87 +/- 7.30 kg, height = 188 ± 3.4cm cm, age = 18 ± 1.2 years n = 14) were recruited. For on-ice sprints, participants completed a standardized warm-up consisting of skating and dynamic stretching and a progression of three skating efforts from 50% to 95%. Following the warm-up, participants completed three on ice 45m sprints, with three minutes of rest in between each trial. For overground sprints, participants completed a similar dynamic warm-up to that of on-ice trials. Following the warm-up participants completed three 40m overground sprint trials. For each trial (on-ice and overground), radar was used to collect instantaneous velocity (Stalker ATS II, Texas, USA) aimed at the participant’s waist. Sprint velocities were modelled using custom Python (version 3.2) script using a mono-exponential function, similar to previous work. To determine if on-ice tirals were achieving a maximum velocity (plateau), minimum acceleration values of the modeled data at the end of the sprint were compared (using paired t-test) between on-ice and overground trials. Significant differences (P<0.001) between overground and on-ice minimum accelerations were observed. It was found that on-ice trials consistently reported higher final acceleration values, indicating a maximum maintained velocity (plateau) had not been reached. Based on these preliminary findings, it is suggested that reliable HFVP metrics cannot yet be collected from all ice-hockey populations using current methods. Elite male populations were not able to achieve a velocity plateau similar to what has been seen in overground trials, indicating the absence of a maximum velocity measure. With current velocity and acceleration modeling techniques, including a dependency of a velocity plateau, these results indicate the potential for error in on-ice HFVP measures. Therefore, these findings suggest that a greater on-ice sprint distance may be required or the need for other velocity modeling techniques, where maximal velocity is not required for a complete profile.   

Keywords: ice-hockey, sprint, skating, power

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Authors: Adrian O'Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient

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Authors: Hoang Vo Thi Minh, Duyen Nguyen Thi Phuong, Gerardo Van Halsema

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As one of the deltas which is extremely vulnerable to climate change, the Mekong Delta, Vietnam is facing many challenges that need to be addressed in strategic and holistic ways. In this study scope, a strategic delta planning is recently considered as a new vision of Adaptive Delta Management for the Mekong Delta. In Adaptive Delta Management, Room for the Rivers (RftR) has been formulated as a typical innovation, which is currently in need of careful consideration for implementing in the Mekong Delta’s planning process. This study then attempts to investigate the roles and analyze sociological aspects of the RftR as potential strategic 'soft' measure, in upstream of Hau River in An Phu district, An Giang province, especially in terms of its so-called multifunctions. The study applied social science approach embedded with a few qualitative methods including in-depth interviews and questionnaire distribution and conjoint analysis as a quantitative approach. The former mainly aims at gaining the local community’s perceptions about the RftR solution. The latter tries to gain farmers’ willingness to accept (WTA) with regard to their level of preference towards the three selected solutions which are considered as strategic plans for sustainably developing the MD. Qualitative data analysis shows that, farmers perceive RftR as very useful for their livelihoods due to its multifunctions as well as in terms of water management. The quantitative results illustrated that respondents expressed their WTAs on RftR as 84. 240 thousand VND / year. Amongst the three solutions that are analysed within this study (Floating rice for upper delta, Room for the Rivers for the Middle, and Shrimp-Mangrove integration for the coastal delta), RfrR was ranked as second preference from respondents. This result is not exactly reflecting the real values of these three mentioned solutions but showing a tendency that can be seen as a reference for the decision-makers in delta planning processes.

Keywords: strategic delta planning, room for the River, farmers’ perception, willingness-to-accept, local livelihoods

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Authors: Ronit Chakraborty, Sugata Banerji

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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

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Authors: Youb Said, Fourar Ali

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To describe the influence of bottom roughness on the free surface flows by numerical modeling, a two-dimensional model was developed. The equations of continuity and momentum (Naviers Stokes equations) are solved by the finite volume method. We considered a turbulent flow in an open channel with a bottom roughness. For our simulations, the K-ε model was used. After setting the initial and boundary conditions and solve the equations set, we were able to achieve the following results: vortex forming in the hollow causing substantial energy dissipation in the obstacle areas that form the bottom roughness. The comparison of our results with experimental ones shows a good agreement in terms of the results in the rough area. However, in other areas, differences were more or less important. These differences are in areas far from the bottom, especially the free surface area just after the bottom. These disagreements are probably due to experimental constants used by the k-ε model.

Keywords: modeling, free surface flow, turbulence, bottom roughness, finite volume, K-ε model, energy dissipation

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Authors: Adinarayana Badveeti, Mohammad Shafi Mir

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In Srinagar city, in India, road safety is an important aspect that creates ecological balance and social well being. A road accident creates a situation that leaves behind distress, sorrow, and sufferings. Therefore identification of causes of road accidents becomes highly essential for adopting necessary preventive measures against a critical event. The damage created by road accidents to large extent is unrepairable and therefore needs attention to eradicate this continuously increasing trend of awful 'epidemic'. Road accident in India is among the highest in the world, with at least approximately 142.000 people killed each year on the road. Kashmir region is an ecologically sensitive place but lacks necessary facilities and infrastructure regarding road transportation, ultimately resulting in the critical event-road accidents creating a major problem for common people in the region. The objective of this project is to study the safety aspect of Srinagar City and also model the accidents with different aspect that causes accidents and also to suggest the possible remedies for lessening/eliminating the road accidents.

Keywords: road safety, road accident, road infrastructure, accident modeling

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Authors: Mehrdad Azimzadeh, Seyed Mohammadreza Jabbari, Mohammadreza Hosseinzadeh Alherd

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This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.

Keywords: optimization, reinforced concrete, optimization methods, impact load, earthquake

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Seyed Mohammad Mahdi Zamani, Kamran Behdinan

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In this study, a multiscale framework is performed to model the strength of Nextel fibers in presence of an atomistic scale pre-crack at finite temperatures. The bridging cell method (BCM) is the multiscale technique applied in this study, which decomposes the system into the atomistic, bridging and continuum domains; solves the whole system in a finite element framework; and incorporates temperature dependent calculations. Since Nextel is known to be structurally stable and retain 70% of its initial strength up to 1100°C; simulations are conducted at both of the room temperatures, 25°C, and fire temperatures, 1200°C. Two cases are modeled for a pre-crack present in either phases of alumina or mullite of the Nextel structure. The materials’ response is studied with respect to deformation behavior and ultimate tensile strength. Results show different crack growth trends for the two cases, and as the temperature increases, the crack growth resistance and material’s strength decrease.

Keywords: Nextel fibers, multiscale modeling, pre-crack, ultimate tensile strength

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Authors: Karima Qayumi, Alex Norta

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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

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Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

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Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

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Authors: V. Stejskal, K. Lundova, R. Sebesta, T. Vanina, S. Roje

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Pure strain of Arctic char (AC) Salvelinus alpinus and hybrid (HB) Salvelinus alpinus vs. Salvelinus fontinalis Mitchill belong to fish, which with great potential for culture in recirculating aquaculture systems (RAS). Aquaculture of these fish currently use flow-through systems (FTS), especially in Nordic countries such as Iceland (biggest producer), Norway, Sweden, and Canada. Four different water saturation regimes included normoxia (NOR), permanent hyperoxia (HYP), intermittent hyperoxia (HYP ± ) and regimes where one day of normoxia was followed by one day of hyperoxia (HYP1/1) were tested during 63 days of experiment in both species in two parallel experiments. Fish were reared in two identical RAS system consisted of 24 plastic round tanks (300 L each), drum filter, biological filter with moving beads and submerged biofilter. The temperature was maintained using flow-through cooler during at level of 13.6 ± 0.8 °C. Different water saturation regimes were achieved by mixing of pure oxygen (O₂) with water in three (one for each hyperoxic regime) mixing tower equipped with flowmeter for regulation of gas inflow. The water in groups HYP, HYP1/1 and HYP± was enriched with oxygen up to saturation of 120-130%. In HYP group was this level kept during whole day. In HYP ± group was hyperoxia kept for daylight phase (08:00-20:00) only and during night time was applied normoxia in this group. The oxygen saturation of 80-90% in NOR group was created using intensive aeration in header tank. The fish were fed with commercial feed to slight excess at 2 h intervals within the light phase of the day. Water quality parameters like pH, temperature and level of oxygen was monitoring three times (7 am, 10 am and 6 pm) per day using handy multimeter. Ammonium, nitrite and nitrate were measured in two day interval using spectrophotometry. Initial body weight (BW) was 40.9 ± 8.7 g and 70.6 ± 14.8 in AC and HB group, respectively. Final survival of AC ranged from 96.3 ± 4.6 (HYP) to 100 ± 0.0% in all other groups without significant differences among these groups. Similarly very high survival was reached in trial with HB with levels from 99.2 ± 1.3 (HYP, HYP1/1 and NOR) to 100 ± 0.0% (HYP ± ). HB fish showed best growth performance in NOR group reached final body weight (BW) 180.4 ± 2.3 g. Fish growth under different hyperoxic regimes was significantly reduced and final BW was 164.4 ± 7.6, 162.1 ± 12.2 and 151.7 ± 6.8 g in groups HY1/1, HYP ± and HYP, respectively. AC showed different preference for hyperoxic regimes as there were no significant difference in BW among NOR, HY1/1 and HYP± group with final values of 72.3 ± 11.3, 68.3 ± 8.4 and 77.1 ± 6.1g. Significantly reduced growth (BW 61.8 ± 6.8 g) was observed in HYP group. It is evident from present study that there are differences between pure bred Arctic char and hybrid in relation to hyperoxic regimes. The study was supported by projects 'CENAKVA' (No. CZ.1.05/2.1.00/01.0024), 'CENAKVA II' (No. LO1205 under the NPU I program), NAZV (QJ1510077) and GAJU (No. 060/2016/Z).

Keywords: recirculating aquaculture systems, Salmonidae, hyperoxia, abiotic factors

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Authors: Ram V. Mohan, John Rivas-Murillo, Ahmed Mohamed, Wayne D. Hodo

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Cementitious materials, an excellent example of highly complex, heterogeneous material systems, are cement-based systems that include cement paste, mortar, and concrete that are heavily used in civil infrastructure; though commonly used are one of the most complex in terms of the material morphology and structure than most materials, for example, crystalline metals. Processes and features occurring at the nanometer sized morphological structures affect the performance, deformation/failure behavior at larger length scales. In addition, cementitious materials undergo chemical and morphological changes gaining strength during the transient hydration process. Hydration in cement is a very complex process creating complex microstructures and the associated molecular structures that vary with hydration. A fundamental understanding can be gained through multi-scale level modeling for the behavior and properties of cementitious materials starting from the material chemistry level atomistic scale to further explore their role and the manifested effects at larger length and engineering scales. This predictive modeling enables the understanding, and studying the influence of material chemistry level changes and nanomaterial additives on the expected resultant material characteristics and deformation behavior. Atomistic-molecular dynamic level modeling is required to couple material science to engineering mechanics. Starting at the molecular level a comprehensive description of the material’s chemistry is required to understand the fundamental properties that govern behavior occurring across each relevant length scale. Material chemistry level models and molecular dynamics modeling and simulations are employed in our work to describe the molecular-level chemistry features of calcium-silicate-hydrate (CSH), one of the key hydrated constituents of cement paste, their associated deformation and failure. The molecular level atomic structure for CSH can be represented by Jennite mineral structure. Jennite has been widely accepted by researchers and is typically used to represent the molecular structure of the CSH gel formed during the hydration of cement clinkers. This paper will focus on our recent work on the shear and compressive deformation and failure behavior of CSH represented by Jennite mineral structure that has been widely accepted by researchers and is typically used to represent the molecular structure of CSH formed during the hydration of cement clinkers. The deformation and failure behavior under shear and compression loading deformation in traditional hydrated CSH; effect of material chemistry changes on the predicted stress-strain behavior, transition from linear to non-linear behavior and identify the on-set of failure based on material chemistry structures of CSH Jennite and changes in its chemistry structure will be discussed.

Keywords: cementitious materials, deformation, failure, material chemistry modeling

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Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini

Abstract:

Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.

Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling

Procedia PDF Downloads 92

Authors: Ahmad Shukri Mohd Noor, Emma Ahmad Sirajudin, Rabiei Mamat

Abstract:

Pertaining to a particular Marine interest, the process of data sampling could take years before a study can be concluded. Therefore, the need for a robust backup system for the data is invariably implicit. In recent advancement of Marine applications, more functionalities and tools are integrated to assist the work of the researchers. It is anticipated that this modality will continue as research scope widens and intensifies and at the same to follow suit with current technologies and lifestyles. The convenience to collect and share information these days also applies to the work in Marine research. Therefore, Marine system designers should be aware that high availability is a necessary attribute in Marine repository applications as well as a robust backup system for the data. In this paper, the approach to high availability is related both to hardware and software but the focus is more on software. We consider a NABTIC repository system that is primitively built on a single server and does not have replicated components. First, the system is decomposed into separate modules. The modules are placed on multiple servers to create a distributed system. Redundancy is added by placing the copies of the modules on different servers using Neighbor Caring Environment System(NCES) technique. NCER is utilizing parallel replication components mechanism. A background monitoring is established to check servers’ heartbeats to confirm their aliveness. At the same time, a critical adaptive threshold is maintained to make sure a failure is timely detected using Adaptive Fault Detection (AFD). A confirmed failure will set the recovery mode where a selection process will be done before a fail-over server is instructed. In effect, the Marine repository service is continued as the fail-over masks a recent failure. The performance of the new prototype is tested and is confirmed to be more highly available. Furthermore, the downtime is not noticeable as service is immediately restored automatically. The Marine repository system is said to have achieved fault tolerance.

Keywords: availability, fault detection, replication, fault tolerance, marine application

Procedia PDF Downloads 321

Authors: Lotfi O. Gargab, Ruichong R. Zhang

Abstract:

A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

Procedia PDF Downloads 368

Authors: R. N. Karthik Babu, R. Sarvesh, A. Rajendra Prasad, G. Swaminathan

Abstract:

M42 is a molybdenum-series high-speed alloy steel widely used because of its better hot-hardness and wear resistance. These steels are conventionally heat treated in a salt bath furnace with up to three stages of preheating with predetermined soaking and holding periods. Such methods often involve long periods of processing with a large amount of energy consumed. In this study, the M42 steel samples were heat-treated by rapidly heating the specimens to the austenising temperature of 1260 °C and cooled conventionally by quenching in a neutral salt bath at a temperature of 550 °C with the aid of a hybrid microwave furnace. As metals reflect microwaves, they cannot directly be heated up when placed in a microwave furnace. The technology used herein requires the specimens to be placed in a crucible lined with SiC which is a good absorber of microwaves and the SiC lining heats the metal through radiation which facilitates the volumetric heating of the metal. A sample of similar dimensions was heat treated conventionally and cooled in the same manner. Conventional tempering process was then carried out on both these samples and analysed for various parameters such as micro-hardness, processing time, etc. Microstructure analysis and scanning electron microscopy was also carried out. The objective of the study being that similar or better properties, with substantial time and energy saving and cost cutting are achievable by rapid heat treatment through hybrid microwave furnaces. It is observed that the heat treatment is done with substantial time and energy savings, and also with minute improvement in mechanical properties of the tool steel heat treated.

Keywords: rapid heating, heat treatment, metal processing, microwave heating

Procedia PDF Downloads 285

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 63

Authors: Elhameh Narimani, Mikhail Sorin, Philippe Micheau, Hakim Nesreddine

Abstract:

Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.

Keywords: Coefficient of Performance, COP, Ejector Refrigeration System, ERS, exergy efficiency (ηII), heat exchangers modeling, moving boundary method

Procedia PDF Downloads 199