Search results for: software component and interfaces

Authors: Michael Ngongeh Mombe

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This Paper seeks to investigate an assertion made by some colleagues that there is no need paying a human translator to translate their literary texts, that there are softwares such as Reverso that can be used to do the translation. The main objective of this study is to examine the veracity of this assertion using Reverso to translate a literary text without any post-editing by a human translator. The work is based on two theories: Skopos and Communicative theories of translation. The work is a documentary research where data were collected from published documents in libraries, on the internet and from the translation produced by Reverso. We made a comparative text analyses of both source and target texts in a bid to highlight the weaknesses and strengths of the software. Findings of this work revealed that those who advocate the use of only Machine translation do so in ignorance of the translation mistakes usually made by the software. From the review of all the 268 segments of translation, we found out that the translation produced by Reverso is fraught with errors. We therefore recommend the use of human translators to either do the translation of their literary texts or revise the translation produced by machine to conform to the skopos of the work. This paper is based on Reverso translation. Similar works in the near future will be based on the other translation softwares to determine their weaknesses and strengths.

Keywords: machine translation, human translator, Reverso, literary text

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Authors: Andreas Livera, Spyros Theocharides, Michalis Florides, Charalambos Anastassiou

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A main challenge in the quest for ensuring quality of operation, especially for photovoltaic (PV) systems, is to safeguard the reliability and optimal performance by detecting and diagnosing potential failures and performance losses at early stages or before the occurrence through real-time monitoring, supervision, fault detection, and predictive maintenance. The purpose of this work is to present the functionalities and results related to the development and validation of a software platform for PV assets diagnosis and maintenance. The platform brings together proprietary hardware sensors and software algorithms to enable the early detection and prediction of the most common and critical faults in PV systems. It was validated using field measurements from operating PV systems. The results showed the effectiveness of the platform for detecting faults and losses (e.g., inverter failures, string disconnections, and potential induced degradation) at early stages, forecasting PV power production while also providing recommendations for maintenance actions. Increased PV energy yield production and revenue can be thus achieved while also minimizing operation and maintenance (O&M) costs.

Keywords: failure detection and prediction, operation and maintenance, performance monitoring, photovoltaic, platform, recommendations, predictive maintenance

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Authors: Dwi Arisandi Wijaya, Ernawati Arifin Giri-Rachman, Neni Nurainy

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Typhoid fever disease can be prevented by using a polysaccharide-based vaccine Vi which is a virulence factor of S.typhi. To produce high yield Vi polysaccharide from bacteria, it is important to know the biosynthesis of Vi polysaccharide and the regulators involved. In the In vivo condition, S. typhi faces different osmolarity, and the bacterial two-component system OmpR-EnvZ, regulate by up and down Capsular Vi polysaccharide biosynthesis. A high yielded Vi Polysaccharide strain, S. typhi strain C6524 used to study the effect of media osmolarity on Vi polysaccharide biosynthesis and the osmoregulation pattern of S. typhi strain C6524. The methods were performed by grown S. typhi strain C6524 grown on medium with 50 mM, 100 mM, and 150 mM osmolarity with the batch system. Vi polysaccharide concentration was measured by ELISA method. For further investigation of the osmoregulation pattern of strain C6524, the osmoregulator gene, OmpR, has been isolated and sequenced using the specific primer of the OmpR gene. Nucleotide sequence analysis is done with BLAST and Lallign. Amino Acid sequence analysis is done with Prosite and Multiple Sequence Alignment. The results of cultivation showed the average content of polysaccharide Vi for 50 mM, 100 mM, and 150 mM osmolarities 11.49 μg/mL, 12.06 μg/mL, and 14.53 μg/mL respectively. Analysis using Anova stated that the osmolarity treatment of 150 mM significantly affects Vi content. Analysis of nucleotide sequences shows 100% identity between S. typhi strain C6524 and Ty2. Analysis of amino acid sequences shows that the OmpR response regulator protein of the C6524 strain also has a α4-β5-α5 motif which is important for the regulatory activation system when phosphorylation occurs by domain kinase. This indicates that the regulator osmolarity response of S. typhi strain C6524 has no difference with the response regulator owned by S. typhi strain Ty2. A high Vi response rate in the 150 mM osmolarity treatment requires further research for RcsB-RcsC, another two-component system involved in Vi Biosynthesis.

Keywords: osmoregulator, OmpR, Salmonella, Vi polysaccharide

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Neha Thakur, Pravin S. More

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The interaction of CO, H2 and LPG with Cu-dosed SnO2 catalysts was studied by means of Fourier transform infrared spectroscopy (FTIR). With increasing Cu loading, pronounced and progressive red shifts of the C–O stretching frequency associated with molecular CO adsorbed on the Cu/SnO2 component were observed. This decrease in n(CO) correlates with enhancement of CO dissociation at higher temperatures on Cu promoted SnO2 catalysts under conditions, where clean Cu is almost ineffective. In the conclusion, the capability of our technique is discussed, and a technique for enhancing the sensitivity in our technique is proposed.

Keywords: FTIR, spectroscopic, dissociation, n(CO)

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Authors: César Coelho, Nikolai Wiegand

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The advancement of nanosatellite technology has opened new avenues for cost-effective and faster space missions. The NanoSat MO Framework (NMF) from the European Space Agency (ESA) provides a modular and simpler approach to the development of flight software and operations of small satellites. This paper presents a methodology using the NMF together with Docker for simulating constellations of satellites. By leveraging Docker containers, the software environment of individual satellites can be easily replicated within a simulated constellation. This containerized approach allows for rapid deployment, isolation, and management of satellite instances, facilitating comprehensive testing and development in a controlled setting. By integrating the NMF lightweight simulator in the container, a comprehensive simulation environment was achieved. A significant advantage of using Docker containers is their inherent scalability, enabling the simulation of hundreds or even thousands of satellites with minimal overhead. Docker's lightweight nature ensures efficient resource utilization, allowing for deployment on a single host or across a cluster of hosts. This capability is crucial for large-scale simulations, such as in the case of mega-constellations, where multiple traditional virtual machines would be impractical due to their higher resource demands. This ability for easy horizontal scaling based on the number of simulated satellites provides tremendous flexibility to different mission scenarios. Our results demonstrate that leveraging Docker containers with the NanoSat MO Framework provides a highly efficient and scalable solution for simulating satellite constellations, offering not only significant benefits in terms of resource utilization and operational flexibility but also enabling testing and validation of ground software for constellations. The findings underscore the importance of taking advantage of already existing technologies in computer science to create new solutions for future satellite constellations in space.

Keywords: containerization, docker containers, NanoSat MO framework, satellite constellation simulation, scalability, small satellites

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Authors: Kylie Henderson

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Adapting mental health interventions is important when providing support to those experiencing difficulties. This analysis aimed to explore and evaluate the effectiveness of various forms of mental health interventions. Literature that has analysed face-to-face (F2F), phone (Telehealth), mobile (mHealth) and online (e-interventions) interferences found all interventions were effective in reducing and treating symptoms of mental health disorders. F2F and Telehealth interventions facilitated greater engagement and client satisfaction. Due to accessibility and privacy, mHealth and e-interventions were the preferred methods of engagement with health services for youth and young adults. Regardless, these interventions still identified several barriers of high dropout, low adherence, and lack of awareness. Additionally, a large proportion of interventions lacked evidence-based foundations. Exploration of interventions that utilise a variety of interfaces, as well as incorporated evidence-based literature and clinician experience, show that they benefit those experiencing mental health difficulties. Applications like YourHealth+ provide a combination of interventions (F2F, mHealth, and e-interventions) to improve the wellbeing of job seekers and employment consults. Individuals that have used the application in conjunction with therapy have reported feeling more empowered and demonstrated improved wellbeing. Practitioners have also described improved confidence in their ability to provide support to clients. Therefore, it can be proposed that utilising a variety of interventions as well as incorporating literature and experience is beneficial to those experiencing mental health difficulties and to health practitioners.

Keywords: face-to-face, e-interventions, mHealth, YourHealth+

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Authors: Aakash Kumar R. G., Anees K. Ahamed, Raj M. Mohan

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Effective engine cooling can improve the engine’s life and efficacy. The design of the fin of the cylinder head and block determines the cooling mechanism of air cooled engine. The heat conduction takes place through the engine parts and convection of heat from the surface of the fins takes place with air as the heat transferring medium. The air surrounding the cooling fins helps in removal of heat built up by the air cooled engine. If the heat removal rate is inadequate, it will result in lower engine efficiency and high thermal stresses in the engine. The main drawback of the air cooled engine is the low heat transfer rate of the cooling fins .This work is based on scrutiny of previous researches that involves enhancing of heat transfer rate of cooling fins. The current research is about augmentation of heat transfer rate of longitudinal rectangular fin profiles by varying the length of the fin and diameter of holes on the fins. Thermal and flow analysis is done for two different models of fins. One is simple fin without holes and the other is perforated (consist of holes). It can be inferred from the research that the fins with holes have a higher fin efficiency than the fins without holes. The geometry of the fin is done in CREO. The heat transfer analysis is done using ANSYS software.

Keywords: fins, heat transfer, perforated fins, thermal analysis, thermal flux

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Authors: Manpreet Kaur, Badaruddoza, Sandeep Kaur Brar

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The increasing prevalence of adolescent obesity is one of the major causes to be hypertensive in adulthood. Various statistical methods have been applied to examine the performance of anthropometric indices for the identification of adverse cardiovascular risk profile. The present work was undertaken to determine the significant traditional risk factors through principal component factor analysis (PCFA) among population based Punjabi adolescents aged 10-18 years. Data was collected among adolescent children from different schools situated in urban areas of Punjab, India. Principal component factor analysis (PCFA) was applied to extract orthogonal components from anthropometric and physiometric variables. Association between components were explained by factor loadings. The PCFA extracted four factors, which explained 84.21%, 84.06% and 83.15% of the total variance of the 14 original quantitative traits among boys, girls and combined subjects respectively. Factor 1 has high loading of the traits that reflect adiposity such as waist circumference, BMI and skinfolds among both sexes. However, waist circumference and body mass index are the indicator of abdominal obesity which increases the risk of cardiovascular diseases. The loadings of these two traits have found maximum in girls adolescents (WC=0.924; BMI=0.905). Therefore, factor 1 is the strong indicator of atherosclerosis in adolescents. Factor 2 is predominantly loaded with blood pressures and related traits (SBP, DBP, MBP and pulse rate) which reflect the risk of essential hypertension in adolescent girls and combined subjects, whereas, factor 2 loaded with obesity related traits in boys (weight and hip circumferences). Comparably, factor 3 is loaded with blood pressures in boys and with height and WHR in girls, while factor 4 contains high loading of pulse pressure among boys, girls and combined group of adolescents.

Keywords: adolescent obesity, cvd, hypertension, punjabi population

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Elena Vinogradova, Aleksei Pleshakov, Aleksei Yakovlev

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During the flight of a supersonic aircraft under various conditions (altitude, Mach, etc.), it becomes necessary to coordinate the operating modes of the air intake and engine. On the supersonic aircraft, it’s been done by changing various control factors (the angle of rotation of the wedge panels and etc.). This paper investigates the possibility of using modern optimization methods to determine the optimal position of the supersonic air intake wedge panels in order to maximize the total pressure recovery coefficient. Modern software allows us to conduct auto-optimization, which determines the optimal position of the control elements of the investigated product to achieve its maximum efficiency. In this work, the flow in the supersonic aircraft inlet has investigated and optimized the operation of the flaps of the supersonic inlet in an aircraft in a 2-D setting. This work has done using ANSYS CFX software. The supersonic aircraft inlet is a flat adjustable external compression inlet. The braking surface is made in the form of a three-stage wedge. The IOSO NM software package was chosen for optimization. Change in the position of the panels of the input device is carried out by changing the angle between the first and second steps of the three-stage wedge. The position of the rest of the panels is changed automatically. Within the framework of the presented work, the position of the moving air intake panel was optimized under fixed flight conditions of the aircraft under a certain engine operating mode. As a result of the numerical modeling, the distribution of total pressure losses was obtained for various cases of the engine operation, depending on the incoming flow velocity and the flight altitude of the aircraft. The results make it possible to obtain the maximum total pressure recovery coefficient under given conditions. Also, the initial geometry was set with a certain angle between the first and second wedge panels. Having performed all the calculations, as well as the subsequent optimization of the aircraft input device, it can be concluded that the initial angle was set sufficiently close to the optimal angle.

Keywords: optimal angle, optimization, supersonic air intake, total pressure recovery coefficient

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Authors: Janneth Gonzalez, Marco Avila, George Barreto

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GRP78 participates in multiple functions in the cell during normal and pathological conditions, controlling calcium homeostasis, protein folding and unfolded protein response. GRP78 is located in the endoplasmic reticulum, but it can change its location under stress, hypoxic and apoptotic conditions. NF-κB represents the keystone of the inflammatory process and regulates the transcription of several genes related with apoptosis, differentiation, and cell growth. The possible relationship between GRP78-NF-κB could support and explain several mechanisms that may regulate a variety of cell functions, especially following brain injuries. Although several reports show interactions between NF-κB and heat shock proteins family members, there is a lack of information on how GRP78 may be interacting with NF-κB, and possibly regulating its downstream activation. Therefore, we assessed the computational predictions of the GRP78 (Chain A) and NF-κB complex (IkB alpha and p65) protein-protein interactions. The interaction interface of the docking model showed that the amino acids ASN 47, GLU 215, GLY 403 of GRP78 and THR 54, ASN 182 and HIS 184 of NF-κB are key residues involved in the docking. The electrostatic field between GRP78-NF-κB interfaces and molecular dynamic simulations support the possible interaction between the proteins. In conclusion, this work shed some light in the possible GRP78-NF-κB complex indicating key residues in this crosstalk, which may be used as an input for better drug design strategy targeting NF-κB downstream signaling as a new therapeutic approach following brain injuries.

Keywords: computational biology, protein interactions, Grp78, bioinformatics, molecular dynamics

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Authors: Mohand Kessal, Rachid Boucetta, Mourad Tikobaini, Mohammed Zamoum

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Leakage problem of two-component fluids flow is modeled for a transient one-dimensional homogeneous bubbly flow and developed by taking into account the effect of a leak located at the middle point of the pipeline. The corresponding three conservation equations are numerically resolved by an improved characteristic method. The obtained results are explained and commented in terms of physical impact on the flow parameters.

Keywords: fluid transients, pipelines leaks, method of characteristics, leakage problem

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Authors: Lai-Fen Yang

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In this increasingly visual world, how can we best decipher and understand the many ways that our everyday lives are organized around looking practices and the many images we encounter each day? Indeed, how we interact with and interpret visual images is a basic component of human life. Today, however, we are living in one of the most artificial visual and image-saturated cultures in human history, which makes understanding the complex construction and multiple social functions of visual imagery more important than ever before. Themes regarding our experience of a visually pervasive mediated culture, here, termed visual spectacle.

Keywords: visual culture, contemporary, images, literacy

Procedia PDF Downloads 515

Authors: Kana Matsuyanagi

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Anorexia Nervosa (AN) is a psychiatric disorder characterized by a relentless pursuit of thinness and strict restriction of food. The current therapeutic approaches for AN predominantly revolve around outpatient psychotherapies, which create significant financial barriers for the majority of affected patients, hindering their access to treatment. Nonetheless, AN exhibit one of the highest mortality and relapse rates among psychological disorders, underscoring the urgent need to provide patients with an affordable self-treatment tool, enabling those unable to access conventional medical intervention to address their condition autonomously. To this end, a neurofeedback software, termed RelaxNeuron, was developed with the objective of providing an economical and portable means to aid individuals in self-managing AN. Electroencephalography (EEG) was chosen as the preferred modality for RelaxNeuron, as it aligns with the study's goal of supplying a cost-effective and convenient solution for addressing AN. The primary aim of the software is to ameliorate the negative emotional responses towards food stimuli and the accompanying aberrant eye-tracking patterns observed in AN patient, ultimately alleviating the profound fear towards food an elemental symptom and, conceivably, the fundamental etiology of AN. The core functionality of RelaxNeuron hinges on the acquisition and analysis of EEG signals, alongside an electrocardiogram (ECG) signal, to infer the user's emotional state while viewing dynamic food-related imagery on the screen. Moreover, the software quantifies the user's performance in accurately tracking the moving food image. Subsequently, these two parameters undergo further processing in the subsequent algorithm, informing the delivery of either negative or positive feedback to the user. Preliminary test results have exhibited promising outcomes, suggesting the potential advantages of employing RelaxNeuron in the treatment of AN, as evidenced by its capacity to enhance emotional regulation and attentional processing through repetitive and persistent therapeutic interventions.

Keywords: Anorexia Nervosa, fear conditioning, neurofeedback, BCI

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Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

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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: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: Dominika Pihikova, Stefan Belicky, Tomas Bertok, Roman Sokol, Petra Kubanikova, Jan Tkac

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Since aberrant glycosylation is frequently accompanied by both physiological and pathological processes in a human body (cancer, AIDS, inflammatory diseases, etc.), the analysis of tumor-associated glycan patterns have a great potential for the development of novel diagnostic approaches. Moreover, altered glycoforms may assist as a suitable tool for the specificity and sensitivity enhancement in early-stage prostate cancer diagnosis. In this paper we discuss the construction and optimization of ultrasensitive sandwich biosensor platform employing lectin as glycan-binding protein. We focus on the immunoassay development, reduction of non-specific interactions and final glycoprofiling of human serum samples including both prostate cancer (PCa) patients and healthy controls. The fabricated biosensor was measured by label-free electrochemical impedance spectroscopy (EIS) with further lectin microarray verification. Furthermore, we analyzed different biosensor interfaces with atomic force microscopy (AFM) in nanomechanical mapping mode showing a significant differences in the altitude. These preliminary results revealing an elevated content of α-2,3 linked sialic acid in PCa patients comparing with healthy controls. All these experiments are important step towards development of point-of-care devices and discovery of novel glyco-biomarkers applicable in cancer diagnosis.

Keywords: biosensor, glycan, lectin, prostate cancer

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Authors: Christopher J. Johnston

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This paper presents the finding of a research study in which novice (first and second year) elementary teachers (grades Kindergarten – six) evaluated various mathematics Virtual Manipulatives, websites, and Applets (tools) for use in mathematics instruction. Participants identified the criteria they used for evaluating these types of resources and provided recommendations for or against five pre-selected tools. During the study, participants participated in three data collection activities: (1) A brief Likert-scale survey which gathered information about their attitudes toward technology use; (2) An identification of criteria for evaluating technology tools; and (3) A review of five pre-selected technology tools in light of their self-identified criteria. Data were analyzed qualitatively using four theoretical categories (codes): Software Features (41%), Mathematics (26%), Learning (22%), and Motivation (11%). These four theoretical categories were then grouped into two broad categories: Content and Instruction (Mathematics and Learning), and Surface Features (Software Features and Motivation). These combined, broad categories suggest novice teachers place roughly the same weight on pedagogical features as they do technological features. Implications for mathematics teacher educators are discussed, and suggestions for future research are provided.

Keywords: mathematics education, novice teachers, technology, virtual manipulatives

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Authors: Nabil A. Ahmed, Nasser A. N. Mhaisen

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The paper presents a solution to enhance the power quality and to reduce the peak load demand in Kuwait electric grid as a solution to the shortage of electricity production. Technical, environmental and economic feasibility study of utilizing integrated grid-connected photovoltaic (PV) system in residential buildings for supplying 7.1% of electrical power consumption in Kuwait is carried out using RETScreen software. A 10 KWp on-grid PV power generation system spread on the rooftop of the residential buildings is adopted and investigated and the complete system performance is simulated using PSIM software. Taking into account the international prices of electricity and natural gas, the proposed solution is investigated and tested for four different types of installation systems in terms of power generation and costs which includes horizontal installation, 25º tilted angle, single axis tracking and dual axis tracking. Results shows that the 25º tilted angle fixed mounted system is the most efficient type. The payback period as a tool of benefit analysis of the proposed system is calculated and it found to be 2.55 years.

Keywords: photovoltaics, residential buildings, electrical grid, production capacity, on-grid, power generation

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Authors: Abdulhameed Babatunde Owolabi, Benyoh Emmanuel Kigha Nsafon, Jeung-Soo Huh

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Energy efficiency measures for residential buildings in South Korea is a national issue because most of the apartments built in the last decades were constructed without proper energy efficiency measures making the energy performance of old buildings to be very poor when compared with new buildings. However, the adoption of advanced building technologies and regulatory building codes are effective energy efficiency strategies for new construction. There is a need to retrofits the existing building using energy conservation measures (ECMs) equipment’s in order to conserve energy and reduce GHGs emissions. To achieve this, the Institute for Global Climate Change and Energy (IGCCE), Kyungpook National University (KNU), Daegu, South Korea employed RETScreen Expert software to carry out measurement and verification (M&V) analysis on an existing building in Korea by using six years gas consumption data collected from Daesung Energy Co., Ltd in order to determine the building energy performance after the introduction of ECM. Through the M&V, energy efficiency is attained, and the resident doubt was reduced. From the analysis, a total of 657 Giga Joules (GJ) of liquefied natural gas (LNG) was consumed at the rate of 0.34 GJ/day having a peak in the year 2015, which cost the occupant the sum of $10,821.

Keywords: energy efficiency, measurement and verification, performance analysis, RETScreen experts

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Authors: P. Abhishesh, B. S. Ryuh, Y. S. Oh, H. J. Moon, R. Akanksha

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This paper discusses about the conceptual design and development of the control system software using Programmable logic controller (PLC) for autonomous driving and agricultural operations of Multipurpose Agricultural Robot Platform (MARP). Based on given initial conditions by field analysis and desired agricultural operations, the structural design development of MARP is done using modelling and analysis tool. PLC, being robust and easy to use, has been used to design the autonomous control system of robot platform for desired parameters. The robot is capable of performing autonomous driving and three automatic agricultural operations, viz. hilling, mulching, and sowing of seeds in the respective order. The input received from various sensors on the field is later transmitted to the controller via ZigBee network to make the changes in the control program to get desired field output. The research is conducted to provide assistance to farmers by reducing labor hours for agricultural activities by implementing automation. This study will provide an alternative to the existing systems with machineries attached behind tractors and rigorous manual operations on agricultural field at effective cost.

Keywords: agricultural operations, autonomous driving, MARP, PLC

Procedia PDF Downloads 364

Authors: Gyaltsen Dakpa, K. J. Senthil Kumar, Nai-Wen Tsao, Sheng-Yang Wang

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Context: Coronavirus disease 2019 (COVID-19) is a severe respiratory illness caused by the SARS-CoV-2 virus. One of the hallmarks of COVID-19 is a change in metabolism, which can lead to increased severity and mortality. The mechanism of SARS-CoV-2-mediated perturbations of metabolic pathways has yet to be fully understood. Research Aim: This study aimed to investigate the metabolic alteration caused by SARS-CoV-2 spike protein in Phorbol 12-myristate 13-acetate (PMA)-induced human monocytes (THP-1) and to examine the regulatory effect of natural compounds like Antcins A on SARS-CoV-2 spike protein-induced metabolic alteration. Methodology: The study used a combination of proton nuclear magnetic resonance (1H-NMR) and MetaboAnalyst 5.0 software. THP-1 cells were treated with SARS-CoV-2 spike protein or control, and the metabolomic profiles of the cells were compared. Antcin A was also added to the cells to assess its regulatory effect on SARS-CoV-2 spike protein-induced metabolic alteration. Findings: The study results showed that treatment with SARS-CoV-2 spike protein significantly altered the metabolomic profiles of THP-1 cells. Eight metabolites, including glycerol-phosphocholine, glycine, canadine, sarcosine, phosphoenolpyruvic acid, glutamine, glutamate, and N, N-dimethylglycine, were significantly different between control and spike-protein treatment groups. Antcin A significantly reversed the changes in these metabolites. In addition, treatment with antacid A significantly inhibited SARS-CoV-2 spike protein-mediated up-regulation of TLR-4 and ACE2 receptors. Theoretical Importance The findings of this study suggest that SARS-CoV-2 spike protein can cause significant metabolic alterations in THP-1 cells. Antcin A, a natural compound, has the potential to reverse these metabolic alterations and may be a potential candidate for developing preventive or therapeutic agents for COVID-19. Data Collection: The data for this study was collected from THP-1 cells that were treated with SARS-CoV-2 spike protein or a control. The metabolomic profiles of the cells were then compared using 1H-NMR and MetaboAnalyst 5.0 software. Analysis Procedures: The metabolomic profiles of the THP-1 cells were analyzed using 1H-NMR and MetaboAnalyst 5.0 software. The software was used to identify and quantify the cells' metabolites and compare the control and spike-protein treatment groups. Questions Addressed: The question addressed by this study was whether SARS-CoV-2 spike protein could cause metabolic alterations in THP-1 cells and whether Antcin A can reverse these alterations. Conclusion: The findings of this study suggest that SARS-CoV-2 spike protein can cause significant metabolic alterations in THP-1 cells. Antcin A, a natural compound, has the potential to reverse these metabolic alterations and may be a potential candidate for developing preventive or therapeutic agents for COVID-19.

Keywords: SARS-CoV-2-spike, ¹H-NMR, metabolomics, antcin-A, taiwanofungus camphoratus

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Authors: Masoud Mahdavi

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The use of sloping lands is increasing due to the reduction of suitable lands for the construction of buildings. In the design and construction of buildings on sloping lands, the foundation has special loading conditions that require the designer and executor to use the slopped foundation. The creation of underground cavities, including urban and subway tunnels, sewers, urban facilities, etc., inside the ground, causes the behavior of the foundation to be unknown. In the present study, using Abacus software, a 45-degree stepped foundation on the ground is designed. The foundations are placed on the ground in a cohesive (no-hole) manner with circular cavities that show the effect of increasing the cross-sectional area of ​​the underground cavities on the foundation's performance. The Kobe earthquake struck the foundation and ground for two seconds. The underground cavities have a circular cross-sectional area with a radius of 5 m, which is located at a depth of 22.54 m above the ground. The results showed that as the number of underground cavities increased, von Mises stress (in the vertical direction) increased. With the increase in the number of underground cavities, the plastic strain on the ground has increased. Also, with the increase in the number of underground cavities, the change in location and speed in the foundation has increased.

Keywords: stepped foundation, sloping ground, Kobe earthquake, Abaqus software, underground excavations

Procedia PDF Downloads 156

Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

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Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

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Authors: Naira Poghosyan

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In knowledge society the content of the studies, the methods used and the requirements for an educator’s professionalism regularly undergo certain changes. It follows that in knowledge society the aim of education is not only to educate professionals for a certain field but also to help students to be aware of cultural values, form human mutual relationship, collaborate, be open, adapt to the new situation, creatively express their ideas, accept responsibility and challenge. In this viewpoint, the development of communicative language competence requires a through coordinated approach to ensure proper comprehension and memorization of subject-specific words starting from high school level. On the other hand, ESP (English for Specific Purposes) teachers and practitioners are increasingly faced with the task of developing and exploiting new ways of assessing their learners’ literacy while learning and teaching ESP. The presentation will highlight the latest achievements in this field. The author will present some practical methodological issues and principles associated with learning, teaching and assessing ESP skills of the learners, using the two software programs of EXE 2.0 and Hot Potatoes 6. On the one hand the author will display the advantages of the two programs as self-learning and self-assessment interactive tools in the course of academic study and professional development of the CLIL learners, on the other hand, she will comprehensively shed light upon some methodological aspects of working out appropriate ways of selection, introduction, consolidation of subject specific materials via EXE 2.0 and Hot Potatoes 6. Then the author will go further to distinguish ESP courses by the general nature of the learners’ specialty identifying three large categories of EST (English for Science and Technology), EBE (English for Business and Economics) and ESS (English for the Social Sciences). The cornerstone of the presentation will be the introduction of the subject titled “The methodology of teaching ESP in non-linguistic institutions”, where a unique case of teaching ESP on Architecture and Construction via EXE 2.0 and Hot Potatoes 6 will be introduced, exemplifying how the introduction, consolidation and assessment can be used as a basis for feedback to the ESP learners in a particular professional field.

Keywords: ESP competences, ESP skill assessment/ self-assessment tool, eXe 2.0 / HotPotatoes software program, ESP teaching strategies and techniques

Procedia PDF Downloads 378

Authors: Arturo Daag

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The Philippine Institute of Volcanology and Seismology (PHIVOLCS) is enhancing its liquefaction hazard map towards a detailed probabilistic approach using SDS and geophysical data. Target sites for liquefaction assessment are public schools in Metro Manila. Since target sites are in highly urbanized-setting, the objective of the project is to conduct both non-destructive geotechnical studies using Screw Driving Testing (SDFS) combined with geophysical data such as refraction microtremor array (ReMi), 3 component microtremor Horizontal to Vertical Spectral Ratio (HVSR), and ground penetrating RADAR (GPR). Initial test data was conducted in liquefaction impacted areas from the Mw 6.1 earthquake in Central Luzon last April 22, 2019 Province of Pampanga. Numerous accounts of liquefaction events were documented areas underlain by quaternary alluvium and mostly covered by recent lahar deposits. SDS estimated values showed a good correlation to actual SPT values obtained from available borehole data. Thus, confirming that SDS can be an alternative tool for liquefaction assessment and more efficient in terms of cost and time compared to SPT and CPT. Conducting borehole may limit its access in highly urbanized areas. In order to extend or extrapolate the SPT borehole data, non-destructive geophysical equipment was used. A 3-component microtremor obtains a subsurface velocity model in 1-D seismic shear wave velocity of the upper 30 meters of the profile (Vs30). For the ReMi, 12 geophone array with 6 to 8-meter spacing surveys were conducted. Microtremor data were computed through the Factor of Safety, which is the quotient of Cyclic Resistance Ratio (CRR) and Cyclic Stress Ratio (CSR). Complementary GPR was used to study the subsurface structure and used to inferred subsurface structures and groundwater conditions.

Keywords: screw drive testing, microtremor, ground penetrating RADAR, liquefaction

Procedia PDF Downloads 203

Authors: Oiane Ruiz de Azua, Salvador Borros, Nuria Agullo, Jordi Arbusa

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Tackiness is described as the ability to spontaneously form a bond to another material under light pressures within a short application time. During the first few minutes of the adhesive's curing, it is necessary to have enough tack to keep the substrates together while cohesion is increasing within the adhesive. This property plays a key role in the manufacturing process of pieces. Epoxy adhesives, unlike other adhesives, usually present low tackiness before curing; however, there is very little literature about the use of tackifiers in epoxy adhesives, except for the high molecular weight epoxy additives. In the present work, a tetrafunctional epoxy resin based on Bisphenol-A and Sulfanilamide has been synthesized in order to be used as a tackifier. This additive offers improved specific adhesion to two-component (2K) epoxy adhesives. The dosage of the tackifier has to be done carefully not to alter the mechanical and rheological properties of the adhesive. The synthetized product has been analyzed by FTIR and ¹H-NMR analysis, and the effect of the addition of 1 wt % of the tackifier on rheological properties, viscoelastic behavior, and mechanical properties has been studied. On one hand, the addition of the product in the epoxy resin part showed a significant increase in tackiness regarding the neat epoxy resin. On the other hand, tackiness of the whole formulation was also increased. Curing time of the adhesive has not undergone any relevant changes with the tackifier addition. Regarding viscoelastic properties, Storage Modulus (G') and Loss Modulus (G'') remain also unchanged at ambient temperature. Probably, in case higher tackifier concentration would be added, differences in viscoelastic properties would be observed. The study of mechanical properties shows that hardness and tensile strength also keep their values unchanged regarding neat two component adhesive. In conclusion, the addition of 1 wt % of sulfanilamide/epoxy enhanced the tackiness of the epoxy resin part, improves tack without modifying significantly either the rheological, the mechanical, or the viscoelastic properties of the product. Thus, the sulfanilamide presented could be a good candidate to be used as an additive to the 2k epoxy formulation for the manufacturing process of pieces.

Keywords: epoxy adhesive, manufacturing process of pieces, sulfanilamide, tackifiers

Procedia PDF Downloads 187