Search results for: future design

Authors: Rajkumar Ghosh

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Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.

Keywords: earthquake, out-of-sequence thrust, disaster, human life

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Authors: Jonas Hamann, Siavash Saki, Tobias Hagen

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Discretization of urban areas is a crucial aspect in many spatial analyses. The process of discretization of space into subspaces without overlaps and gaps is called tessellation. It helps understanding spatial space and provides a framework for analyzing geospatial data. Tessellation methods can be divided into two groups: regular tessellations and irregular tessellations. While regular tessellation methods, like squares-grids or hexagons-grids, are suitable for addressing pure geometry problems, they cannot take the unique characteristics of different subareas into account. However, irregular tessellation methods allow the border between the subareas to be defined more realistically based on urban features like a road network or Points of Interest (POI). Even though Python is one of the most used programming languages when it comes to spatial analysis, there is currently no library that combines different tessellation methods to enable users and researchers to compare different techniques. To close this gap, we are proposing TessPy, an open-source Python package, which combines all above-mentioned tessellation methods and makes them easily accessible to everyone. The core functions of TessPy represent the five different tessellation methods: squares, hexagons, adaptive squares, Voronoi polygons, and city blocks. By using regular methods, users can set the resolution of the tessellation which defines the finesse of the discretization and the desired number of tiles. Irregular tessellation methods allow users to define which spatial data to consider (e.g., amenity, building, office) and how fine the tessellation should be. The spatial data used is open-source and provided by OpenStreetMap. This data can be easily extracted and used for further analyses. Besides the methodology of the different techniques, the state-of-the-art, including examples and future work, will be discussed. All dependencies can be installed using conda or pip; however, the former is more recommended.

Keywords: geospatial data science, geospatial data analysis, tessellations, urban studies

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Authors: Nandy Putra, Atrialdipa Duanovsah, Kristofer Haliansyah

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The aim of this research is to design a LHP with low thermal resistance and low condenser temperature. A Self-designed cascade LHP was tested by using biomaterial, sintered copper powder, and aluminum screen mesh as the wick. Using pure water as the working fluid for the first level of the LHP and 96% alcohol as the working fluid for the second level of LHP, the experiments were run with 10W, 20W, and 30W heat input. Experimental result shows that the usage of biomaterial as wick could reduce more temperature at evaporator than by using sintered copper powder and screen mesh up to 22.63% and 37.41% respectively. The lowest thermal resistance occurred during the usage of biomaterial as wick of heat pipe, which is 2.06 ^oC/W. The usage of cascade system could be applied to LHP to reduce the temperature at condenser and reduced thermal resistance up to 17.6%.

Keywords: biomaterial, cascade loop heat pipe, screen mesh, sintered Cu

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Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi

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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.

Keywords: fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

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This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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Authors: Liang Ning, Chung Hau Yin

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Angiogenesis is the process of new blood vessel development. It has been recognized as a therapeutic target for blocking cancer growth four decades ago. Vascular sprouting is initiated by pro-angiogenic factors. Vascular endothelial cell growth factor (VEGF) plays a central role in angiogenic initiation, many patients with cancer or ocular neovascularization have been benefited from anti-VEGF therapy. Emerging approaches impacting in the later stages of vessel remodeling and maturation are expected to improve clinical efficacy. TIE receptor as well as the corresponding angiopoietin ligands, were identified as another endothelial cell specific receptor tyrosine kinase signaling system. Much efforts were made to reduce the activity of angiopoietin-TIE receptor axis. Two eudesmane-type sesquiterpenes from laggera alata, namely, 15-dihydrocostic acid and ilicic acid were found with strong anti-angiogenic properties in zebrafish model. Meanwhile, the mRNA expression levels of VEGFR2 and TIE2 pathway related genes were down-regulated in the sesquiterpenes treated zebrafish embryos. Besides, in human umbilical vein endothelial cells (HUVECs), the sesquiterpenes have the ability to inhibit VEGF-induced HUVECs proliferation and migration at non-toxic concentration. Moreover, angiopoietin-2 induced TIE2 phosphorylation was inhibited by the sesquiterpenes, the inhibitory effect was detected in angiopoietin-1 induced HUVECs proliferation as well. Thus, we hypothesized the anti-angiogenic activity of the compounds may via the inhibition of VEGF and TIE2 related pathways. How the compounds come into play as the pathways inhibitors need to be evaluated in the future.

Keywords: Laggera alata, eudesmane-type sesquiterpene, anti-angiogenesis, VEGF, angiopoietin, TIE2

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Authors: Nitin Ghule, S. G. Taji

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A mathematical model of hot-wall condensers used in refrigerators is presented. The model predicts the heat transfer characteristics of condenser and the effects of various design and operating parameters on condenser tube length and capacity. A finite element approach was used to model the condenser. The condenser tube is divided into elemental units, with each element consisting of adhesive tape, refrigerant tube and outer metal sheet. The heat transfer characteristics of each section are then analyzed by considering the heat transfer through the tube wall, tape and the outer sheet. Variations in inner heat transfer coefficient and pressure drop are considered depending on temperature, fluid phase, type of flow and orientation of tube. Variation in outer heat transfer coefficient is also taken into account. Various materials were analysed for the tube, tape and outer sheet.

Keywords: condenser, domestic refrigerator, heat transfer, mathematical model

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Authors: Septimia Sarbu

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The entropy rate of a stochastic process is a fundamental concept in information theory. It provides a limit to the amount of information that can be transmitted reliably over a communication channel, as stated by Shannon's coding theorems. Recently, researchers have focused on developing new measures of information that generalize Shannon's classical theory. The aim is to design more efficient information encoding and transmission schemes. This paper continues the study of generalized entropy rates, by deriving a closed-form solution to the Sharma-Mittal entropy rate for Gaussian processes. Using the squeeze theorem, we solve the limit in the definition of the entropy rate, for different values of alpha and beta, which are the parameters of the Sharma-Mittal entropy. In the end, we compare it with Shannon and Rényi's entropy rates for Gaussian processes.

Keywords: generalized entropies, Sharma-Mittal entropy rate, Gaussian processes, eigenvalues of the covariance matrix, squeeze theorem

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Authors: Heungwook Son, Sungjoo Lee

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Recently, due to intensifying competition in several industries, the importance of meeting customer requirements has increased. The role that service plays in satisfying customer‘s requirements is key area of focus. Thus, the concept of using product development-research in the service system has been actively practiced. As strategic decision making tool, various types of the technology roadmap were suggested in the product-service system (PSS). However, the technology roadmap was configured a top-down form around the technologies of the elements. The limitation is that it hard for it to indicate a variety of interrelations. In response, this paper suggests using the planning support tool of PSS for a DSM for the technology roadmap; it consists of the relationship of product-service-technology as a bottom-up form. Therefore, nine types of the technology roadmap of PSS exist. The first defines the relationship of product-service-technology. The second phase identifies output when of the technology roadmaps are adapted to the DSM process. Finally, the DSM-based forms of each type of technology roadmap are presented through case studies.

Keywords: DSM, technology roadmap, PSS, product-service system, bottom-up

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Authors: Hansoo Kim, Seunghak Shin

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The differential column shortening in tall buildings can be reduced by improving material and structural characteristics of the structural systems. This paper proposes structural methods to reduce differential column shortening in reinforced concrete tall buildings; connecting columns with rigidly jointed horizontal members, using outriggers, and placing additional reinforcement at the columns. The rigidly connected horizontal members including outriggers reduce the differential shortening between adjacent vertical members. The axial stiffness of columns with greater shortening can be effectively increased by placing additional reinforcement at the columns, thus the differential column shortening can be reduced in the design stage. The optimum distribution of additional reinforcement can be determined by applying a gradient based optimization technique.

Keywords: column shortening, long-term behavior, optimization, tall building

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Authors: Anil Kumar Pandey

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Power plane noise is the most significant source of signal integrity (SI) issues in a high-speed digital design. In this paper, power integrity (PI) analysis of multiple power planes in a power delivery system of a 12-layer high-speed FPGA board is presented. All 10 power planes of HSD board are analyzed separately by using 3D Electromagnetic based PI solver, then the transient simulation is performed on combined PI data of all planes along with voltage regulator modules (VRMs) and 70 current drawing chips to get the board level power noise coupling on different high-speed signals. De-coupling capacitors are placed between power planes and ground to reduce power noise coupling with signals.

Keywords: power integrity, power-aware signal integrity analysis, electromagnetic simulation, channel simulation

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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Authors: Lishuang Ma

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Charge transfer (CT) complex, also known as Electron donor-acceptor (EDA) complex, has received attentions increasingly in the field of synthetic chemistry community, due to the CT complex can absorb the visible light through the intermolecular charge transfer excited states, various of catalyst-free photochemical transformations under mild visible-light conditions. However, a number of fundamental questions are still ambiguous, such as the origin of visible light absorption, the photochemical and photophysical properties of the CT complex, as well as the detailed mechanism of the radical coupling pathways mediated by CT complex. Since these are critical factors for target-specific design and synthesis of more new-type CT complexes. To this end, theoretical investigations were performed in our group to answer these questions based on multiconfigurational perturbation theory. The photo-induced fluoroalkylation reactions are mediated by CT complexes, which are formed by the association of an acceptor of perfluoroalkyl halides RF−X (X = Br, I) and a suitable donor molecule such as β-naphtholate anion, were chosen as a paradigm example in this work. First, spectrum simulations were carried out by both CASPT2//CASSCF/PCM and TD-DFT/PCM methods. The computational results showed that the broadening spectra in visible light range (360-550nm) of the CT complexes originate from the 1(σπ*) excitation, accompanied by an intermolecular electron transfer, which was also found closely related to the aggregate states of the donor and acceptor. Moreover, from charge translocation analysis, the CT complex that showed larger charge transfer in the round state would exhibit smaller charge transfer in excited stated of 1(σπ*), causing blue shift relatively. Then, the excited-state potential energy surface (PES) was calculated at CASPT2//CASSCF(12,10)/ PCM level of theory to explore the photophysical properties of the CT complexes. The photo-induced C-X (X=I, Br) bond cleavage was found to occur in the triplet state, which is accessible through a fast intersystem crossing (ISC) process that is controlled by the strong spin-orbit coupling resulting from the heavy iodine and bromine atoms. Importantly, this rapid fragmentation process can compete and suppress the backward electron transfer (BET) event, facilitating the subsequent effective photochemical transformations. Finally, the reaction pathways of the radical coupling were also inspected, which showed that the radical chain propagation pathway could easy to accomplish with a small energy barrier no more than 3.0 kcal/mol, which is the key factor that promote the efficiency of the photochemical reactions induced by CT complexes. In conclusion, theoretical investigations were performed to explore the photophysical and photochemical properties of the CT complexes, as well as the mechanism of radical coupling reactions mediated by CT complex. The computational results and findings in this work can provide some critical insights into mechanism-based design for more new-type EDA complexes

Keywords: charge transfer complex, electron transfer, multiconfigurational perturbation theory, radical coupling

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Authors: G. Baraneedaran, Deepak Singh, Kollipara Tejesh

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The wireless sensors network has been an active research area over the y-ear passed. Due to the limited energy and communication ability of sensor nodes, it seems especially important to design a routing protocol for WSNs so that sensing data can be transmitted to the receiver effectively, an energy-balanced routing method based on forward-aware factor (FAF-EBRM) is proposed in this paper. In FAF-EBRM, the next-hop node is selected according to the awareness of link weight and forward energy density. A spontaneous reconstruction mechanism for Local topology is designed additionally. In this experiment, FAF-EBRM is compared with LEACH and EECU, experimental results show that FAF-EBRM outperforms LEACH and EECU, which balances the energy consumption, prolongs the function lifetime and guarantees high Qos of WSN.

Keywords: energy balance, forward-aware factor (FAF), forward energy density, link weight, network performance

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Authors: Yu Du, Jian-Guo Wang

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Green consumption is a key link to develop the ecological economy, and consumers are vital to carry out green consumption. With environmental awareness gradually being aroused, consumers often fail to turn their positive attitude into actual green consumption behavior. According to behavior reasoning theory, reasons for adoption have a direct (positive) influence on consumers’ attitude while reasons against adoption have a direct (negative) influence on consumers’ adoption intentions, the incongruous coexistence of which leads to the attitude-behavior gap of green consumption. Based on behavior reasoning theory, this research integrates reasons for adoption and reasons against adoption into a proposed model, in which reasons both for and against green consumption mediate the relationship between consumer’ values, attitudes, and behavioral intentions. It not only extends the conventional theory of reasoned action but also provides a reference for the government and enterprises to design the repairing strategy of green consumption attitude-behavior gap.

Keywords: green product, attitude-behavior gap, behavior reasoning theory, green consumption, SEM

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Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

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The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

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Authors: Garg Ramneesh, Uppal Sanjeev, Mittal Rajinder, Shah Sheerin, Jain Vikas, Singla Bhupinder

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Introduction: Despite advances in trauma care, a classification system for soft tissue injuries of the face still needs to be objectively defined. Aim: To develop a classification system for soft tissue injuries of the face; that is objective, easy to remember, reproducible, universally applicable, aids in surgical management and helps to develop a structured data that can be used for future use. Material and Methods: This classification system includes those patients that need surgical management of facial injuries. Associated underlying bony fractures have been intentionally excluded. Depending upon the severity of soft tissue injury, these can be graded from 0 to IV (O-Abrasions, I-lacerations, II-Avulsion injuries with no skin loss, III-Avulsion injuries with skin loss that would need graft or flap cover, and IV-complex injuries). Anatomically, the face has been divided into three zones (Zone 1/2/3), as per aesthetic subunits. Zone 1e stands for injury of eyebrows; Zones 2 a/b/c stand for nose, upper eyelid and lower eyelid respectively; Zones 3 a/b/c stand for upper lip, lower lip and cheek respectively. Suffices R and L stand for right or left involved side, B for presence of foreign body like glass or pellets, C for extensive contamination and D for depth which can be graded as D 1/2/3 if depth is still fat, muscle or bone respectively. I is for damage to facial nerve or parotid duct. Results and conclusions: This classification system is easy to remember, clinically applicable and would help in standardization of surgical management of soft tissue injuries of face. Certain inherent limitations of this classification system are inability to classify sutured wounds, hematomas and injuries along or against Langer’s lines.

Keywords: soft tissue injuries, face, avulsion, classification

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Authors: Rajrupa Ghosh, Abhijit Mitra

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Future use of animal protein sources in prawn feeds is expected to be considerably reduced as a consequence of increasing economical, environmental and safety issues. Of main concern has been the use of expensive marine protein sources, such as fish meal which often results in fouling of water quality and disease outbreak in cultured species. To determine prawn capacity to use practical feeds with plant proteins as replacement ingredients to animal protein sources, 8-months growth trial was conducted in two sets of ponds using juvenile (0.02 gm) Macrobrachium rosenbergii. Among the two sets, one set (comprising of three ponds) is experimental pond included formulated feed prepared with 30% Porteresia coarctata dust along with other general ingredients and another set (comprising of another three ponds) is control pond with commercial feed. Mean final weight, percent weight gain, final net yield, feed conversion ratio and survival were evaluated. Higher condition index values, survival rate and gain in prawn weight were observed in experimental pond compared to control pond. Low FCR values were observed in the experimental pond than the control pond. Evaluation of production parameters at the end of the study demonstrated significant differences (P ≥ 0.05) among two ponds. The variation may be attributed to specially formulated plant based feed that not only boosted up the growth of prawns, but also upgraded the ambient aquatic health. These results indicate that fish meal can be replaced with algal protein sources in diets without affecting prawn growth and production.

Keywords: macrobrachium rosenbergii, porteresia coarctata, Indian sundarbans, feed

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Mohammad Shokoohi-Yekta, Hamid Mirebrahim

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A body of research has been devoted to investigating the preferences of computer programmers. These researches used various questionnaires to find out what programming language is most popular among programmers. The problem with such research is that the programmers are usually familiar with only a few languages; therefore, disregarding a number of other languages which might have characteristics that match their preferences more closely. To overcome such a problem, we decided to investigate the preferences of programmers in regards to the characteristics of languages, which help us to discover the languages that include the most characteristics preferred by the users. We conducted a user study to measure the preferences of programmers on different characteristics of programming languages and then tried to compare existing languages in the areas of application, Web and system programming. Overall, the results of our study indicated that the Ruby programming language has the highest preference score in the two areas of application and Web, and C++ has the highest score in the system area. The results of our study can also help programming language designers know the characteristics they should consider when developing new programming languages in order to attract more programmers.

Keywords: object orientation, programming language design, programmers' preferences, characteristic

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Authors: Samarpreet Singh, Gerald Giesbrecht

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Both c-section and antibiotic exposure are linked to gut microbiota imbalance in infants. Such disturbance is associated with the Hypothalamic-Pituitary-Adrenal (HPA) axis function. However, the literature only has contradicting evidence for the association between c-sections and the HPA axis. Therefore, this study aims to test if the mode of delivery and antibiotics exposure is associated with the HPA axis. Also, whether exposure to both interacts with the HPA-axis. It was hypothesized that associations and interactions would be observed. Secondary data analysis was used for this co-relational study. Data for the mode of delivery and antibiotics exposure variables were documented from hospital records or self-questionnaires. In addition, cortisol levels (Area under the curve with respect to increasing (AUCi) and Area under the curve with respect to ground (AUCg)) were based on saliva collected from three months old during the infant’s visit to the lab and after drawing blood. One-way and between-subject ANOVA analyses were run on data. No significant association between delivery mode and infant cortisol level was found, AUCi and AUCg, p > .05. Only the infant’s AUCg was found to be significantly higher if there were antibiotics exposure at delivery (p = .001) or their mothers were exposed during pregnancy (p < .05). Infants born by c-section and exposed to antibiotics at three months had higher AUCi than those born vaginally, p < .02. These results imply that antibiotic exposure before three months is associated with an infant’s stress response. The association might increase if antibiotic exposure occurs three months after a c-section birth. However, more robust and causal evidence in future studies is needed, given a variable group’s statistically weak sample size. Nevertheless, the results of this study still highlight the unintended consequences of antibiotic exposure during delivery and pregnancy.

Keywords: HPA-axis, antibiotics, c-section, gut-microbiota, development, stress

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Authors: Caroline M. B. De Araujo, Helenise A. Do Nascimento, Claudia J. Da S. Cavalcanti, Mauricio A. Da Motta Sobrinho, Maria F. Pimentel

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Oil production is often followed by the joint production of water and gas. During the journey up to the surface, due to severe conditions of temperature and pressure, the mixing between these three components normally occurs. Thus, the three phases separation process must be one of the first steps to be performed after crude oil extraction, where the water-oil separation is the most complex and important step, since the presence of water into the process line can increase corrosion and hydrates formation. A wide range of methods can be applied in order to proceed with oil-water separation, being more commonly used: flotation, hydrocyclones, as well as the three phase separator vessels. Facing what has been presented so far, it is the aim of this paper to study a system consisting of a three-phase separator, evaluating the influence of three variables: temperature, working pressure and separator type, for two types of oil (light and heavy), by performing two factorial design plans 23, in order to find the best operating condition. In this case, the purpose is to obtain the greatest oil flow rate in the product stream (m3/h) as well as the lowest percentage of water in the oil stream. The simulation of the three-phase separator was performed using Aspen Hysys®2006 simulation software in stationary mode, and the evaluation of the factorial experimental designs was performed using the software Statistica®. From the general analysis of the four normal probability plots of effects obtained, it was observed that interaction effects of two and three factors did not show statistical significance at 95% confidence, since all the values were very close to zero. Similarly, the main effect "separator type" did not show significant statistical influence in any situation. As in this case, it has been assumed that the volumetric flow of water, oil and gas were equal in the inlet stream, the effect separator type, in fact, may not be significant for the proposed system. Nevertheless, the main effect “temperature” was significant for both responses (oil flow rate and mass fraction of water in the oil stream), considering both light and heavy oil, so that the best operation condition occurs with the temperature at its lowest level (30oC), since the higher the temperature, the liquid oil components pass into the vapor phase, going to the gas stream. Furthermore, the higher the temperature, the higher the formation water vapor, so that ends up going into the lighter stream (oil stream), making the separation process more difficult. Regarding the “working pressure”, this effect showed to be significant only for the oil flow rate, so that the best operation condition occurs with the pressure at its highest level (9bar), since a higher operating pressure, in this case, indicated a lower pressure drop inside the vessel, generating lower level of turbulence inside the separator. In conclusion, the best-operating condition obtained for the proposed system, at the studied range, occurs for temperature is at its lowest level and the working pressure is at its highest level.

Keywords: factorial experimental design, oil production, simulation, three-phase separator

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Authors: Irfan Ahmad Afip

Abstract:

This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

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Authors: Nadine Maier, Martin Mensinger, Enea Tallushi

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In general, today, two types of launching bearings are used in the construction of large steel and steel concrete composite bridges. These are sliding rockers and systems with hydraulic bearings. The advantages and disadvantages of the respective systems are under discussion. During incremental launching, the center of the webs of the superstructure is not perfectly in line with the center of the launching bearings due to unavoidable tolerances, which may have an influence on the buckling behavior of the web plates. These imperfections are not considered in the current design against plate buckling, according to DIN EN 1993-1-5. It is therefore investigated whether the design rules have to take into account any eccentricities which occur during incremental launching and also if this depends on the respective launching bearing. Therefore, at the Technical University Munich, large-scale buckling tests were carried out on longitudinally stiffened plates under biaxial stresses with the two different types of launching bearings and eccentric load introduction. Based on the experimental results, a numerical model was validated. Currently, we are evaluating different parameters for both types of launching bearings, such as load introduction length, load eccentricity, the distance between longitudinal stiffeners, the position of the rotation point of the spherical bearing, which are used within the hydraulic bearings, web, and flange thickness and imperfections. The imperfection depends on the geometry of the buckling field and whether local or global buckling occurs. This and also the size of the meshing is taken into account in the numerical calculations of the parametric study. As a geometric imperfection, the scaled first buckling mode is applied. A bilinear material curve is used so that a GMNIA analysis is performed to determine the load capacity. Stresses and displacements are evaluated in different directions, and specific stress ratios are determined at the critical points of the plate at the time of the converging load step. To evaluate the load introduction of the transverse load, the transverse stress concentration is plotted on a defined longitudinal section on the web. In the same way, the rotation of the flange is evaluated in order to show the influence of the different degrees of freedom of the launching bearings under eccentric load introduction and to be able to make an assessment for the case, which is relevant in practice. The input and the output are automatized and depend on the given parameters. Thus we are able to adapt our model to different geometric dimensions and load conditions. The programming is done with the help of APDL and a Python code. This allows us to evaluate and compare more parameters faster. Input and output errors are also avoided. It is, therefore, possible to evaluate a large spectrum of parameters in a short time, which allows a practical evaluation of different parameters for buckling behavior. This paper presents the results of the tests as well as the validation and parameterization of the numerical model and shows the first influences on the buckling behavior under eccentric and multi-axial load introduction.

Keywords: buckling behavior, eccentric load introduction, incremental launching, large scale buckling tests, multi axial stress states, parametric numerical modelling

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Authors: H. Zedira, M. T. Hannachi, H. Djebaili, B. Daheche

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The rapid pace of technology development and strong competition in the market, prompted us to consider the field of manufacturing of steel pipes by a process complies fully with the requirements of industrial induction welding is high frequency (HF), this technique is better known today in Algeria, more precisely for the manufacture of tubes diameters Single Annabib TG Tebessa. The aim of our study is based on the characterization of processes controlling the mechanical behavior of steel pipes (type E24-2), welded by high frequency induction, considering the different tests and among the most destructive known test internal pressure. The internal pressure test is performed according to the application area of welded pipes, or as leak test, either as a test of strength (bursting). All tubes are subjected to a hydraulic test pressure of 50 bar kept at room temperature for a period of 6 seconds. This study provides information that helps optimize the design and implementation to predict the behavior of the tubes during operation.

Keywords: castem, pressure, stress, tubes, thickness

Procedia PDF Downloads 320

Authors: Elke Mackensen

Abstract:

Systems Engineering plays a key role during industrial product development of complex technical systems. The need for systems engineers in industry is growing. However, there is a gap between the industrial need and the academic education. Normally the academic education is focused on the domain specific design, implementation and testing of technical systems. Necessary systems engineering expertise like knowledge about requirements analysis, product cost estimation, management or social skills are poorly taught. Thus, there is the need of new academic concepts for teaching systems engineering skills. This paper presents a project-orientated training concept to prepare students from different technical degree programs for systems engineering activities. The training concept has been initially implemented and applied in the industrial engineering master program of the University of Applied Sciences Offenburg.

Keywords: educational systems engineering training, requirements analysis, system modelling, SysML

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Authors: Mercy Chepkirui, Reuben Omondi, Paul Orina, Albert Getabu, Lewis Sitoki, Jonathan Munguti

Abstract:

Globally, the decline in capture fisheries as a result of the growing population and increasing awareness of the nutritional benefits of white meat has led to the development of aquaculture. This is anticipated to meet the increasing call for more food for the human population, which is likely to increase further by 2050. Statistics showed that more than 50% of the global future fish diet will come from aquaculture. Aquaculture began commercializing some decades ago; this is accredited to technological advancement from traditional to modern cultural systems, including cage farming. Cage farming technology has been rapidly growing since its inception in Lake Victoria, Kenya. Currently, over 6,000 cages have been set up in Kenyan waters, and this offers an excellent opportunity for recognition of Kenya’s government tactic to eliminate food insecurity and malnutrition, create employment and promote a Blue Economy. However, being an open farming enterprise is likely to emit large bulk of waste hence altering the ecosystem integrity of the lake. This is through increased chlorophyll-a pigments, alteration of the plankton community, macroinvertebrates, fish genetic pollution, transmission of fish diseases and pathogens. Cage farming further increases the nutrient loads leading to the production of harmful algal blooms, thus negatively affecting aquatic and human life. Despite the ecological transformation, cage farming provides a platform for the achievement of the Sustainable Development Goals of 2030, especially the achievement of food security and nutrition. Therefore, there is a need for Integrated Multitrophic Aquaculture as part of Blue Transformation for ecosystem monitoring.

Keywords: aquaculture, ecosystem, blue economy, food security

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Authors: Shilpi Tripathi

Abstract:

After independence, Bangladesh had to learn to survive on its own without any economic crutches (aid). Foreign direct investment (FDI) became a crucial economic tool for the country to become economically independent. The government started removing restrictions to encourage foreign investment, economic growth, international trade, and the environment. FDI is considered as a way to bridge the saving-investment gap, reduce poverty, balance trade, create jobs for its vast labour force, increase foreign exchange earnings and acquire new modern technology and management skills in the country. At the same time, spillovers of foreign investments in Bangladesh, such as low wages (compared to laborers of developed countries), poor working conditions and unbridled exploitation of the domestic resources, environmental externalities, etc., cannot be ignored. The most important adverse implications of FDI inflows noticed are the environmental problems, which are further impacting the health and society of the country. This paper empirically studies the relationship between FDI, economic growth, international trade (exports and Imports), and the environment since 1996. The first part of the paper focuses on the background and trends of FDI, GDP, trade, and environment (CO₂). The second part focuses on the literature review on the relationship between all the variables. The last part of the paper examines the results of empirical analysis like co-integration and Granger causality. The findings of the paper reveal that a uni-directional relationship exists between FDI, CO₂, and international trade (exports and imports). The direction of the causality reveals that FDI inflow is one of the major contributors to high-volume international trade. At the same time, FDI and international trade both are contributing to carbon emissions in Bangladesh. The paper concludes with the policy recommendations that will ensure environmentally friendly trade, investment, and growth in Bangladesh for the future.

Keywords: foreign direct investment, GDP, international trade, CO₂, Granger causality, environment

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Authors: Clare Victoria Martin

Abstract:

With reports of increased mental health problems and a lack of proactive, consistent well-being initiatives, well-being is a topical issue in the workplace, as well as a wider public health concern. Additionally, workplace well-being is closely linked to performance, both from a business perspective and in psychological research. Businesses are therefore becoming increasingly motivated to promote well-being, yet there are still barriers, including a lack of evidence-based workplace interventions, issues with measuring effectiveness and problems creating lasting cultural change. This review aimed to collate workplace well-being research to propose a comprehensive new model for delivering evidence-based workplace well-being training with a real potential for lasting impact. Method: A narrative review was conducted to meta-synthesise relevant research. Thematic analysis was then adopted as a systematic method of identifying key themes from the review to lead to practical recommendations. Interventions focusing on strengths, psychological capital, mindfulness and positivity (SPMP) dominated the research in this area, suggesting benefits of incorporating all four into training. However, to avoid a ‘quick fix’ mentality, the concept of training ‘well-being ambassadors’ as a preventative counterpart to mental health ‘first aiders’ was proposed alongside a new ‘REST and RISE’ model: well-being interventions should be ‘relatable’, ‘enjoyable’, ‘sociable’ and ‘trackable’ (REST) in order to increase ‘resilience’, ‘innovation’, ‘strengths’ and ‘engagement’ (RISE). If the REST principles are applied to interventions focusing on SPMP, research suggests individuals will RISE. Future research should empirically test this new well-being ambassador programme and REST/RISE model in an applied setting.

Keywords: performance, positive psychology, thriving, workplace well-being

Procedia PDF Downloads 112