Search results for: mixed method research

Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

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Authors: Dejen Alemu, Murray E. Jennex, Temtim Assefa

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This paper is investigated to understand the design, the use, and the consequence of Knowledge Management System (KMS) for knowledge systems sharing and integration. A KMS for knowledge systems sharing and integration is designed to meet the challenges raised by knowledge management researchers and practitioners: the technical, the human, and social factors. Agricultural KMS involves various members coming from different Communities of Practice (CoPs) who possess their own knowledge of multiple practices which need to be combined in the system development. However, the current development of the technology ignored the indigenous knowledge of the local communities, which is the key success factor for agriculture. This research employed the multi-methodological approach to KMS research in action research perspective which consists of four strategies: theory building, experimentation, observation, and system development. Using the KMS development practice of Ethiopian agricultural transformation agency as a case study, this research employed an interpretive analysis using primary qualitative data acquired through in-depth semi-structured interviews and participant observations. The Orlikowski's structuration model of technology has been used to understand the design, the use, and the consequence of the KMS. As a result, the research identified three basic components for the architecture of the shared KMS, namely, the people, the resources, and the implementation subsystems. The KMS were developed using web 2.0 tools to promote knowledge sharing and integration among diverse groups of users in a distributed environment. The use of a shared KMS allows users to access diverse knowledge from a number of users in different groups of participants, enhances the exchange of different forms of knowledge and experience, and creates high interaction and collaboration among participants. The consequences of a shared KMS on the social system includes, the elimination of hierarchical structure, enhance participation, collaboration, and negotiation among users from different CoPs having common interest, knowledge and skill development, integration of diverse knowledge resources, and the requirement of policy and guideline. The research contributes methodologically for the application of system development action research for understanding a conceptual framework for KMS development and use. The research have also theoretical contribution in extending structuration model of technology for the incorporation of variety of knowledge and practical implications to provide management understanding in developing strategies for the potential of web 2.0 tools for sharing and integration of indigenous knowledge.

Keywords: communities of practice, indigenous knowledge, participation, structuration model of technology, Web 2.0 tools

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Authors: Wega Trisunaryanti, Hesty Kusumastuti, Iip Izul Falah, Muhammad Fajar Marsuki, Rahmad Nuryanto

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Synthesis of Ni supported on mesopore silica-alumina (MSA) for hydrocracking of pyrolyzed α-cellulose had been carried out. The silica and alumina were extracted from Sidoarjo mud. Gelatin from catfish bone was used as a template for the mesopore design. The MSA was synthesized by using hydrothermal method at 100 °C for 24 h and calcined at 550 °C for 4 h then characterized by using X-Ray Diffraction Spectrometer (XRD) and Nitrogen Gas Sorption Analyzer (GAS). The Ni metal was loaded to the MSA by wet impregnation method. The catalytic activity in the hydrocracking reaction of pyrolyzed α-cellulose was carried out at 450 °C for 2 h. The MSA synthesized in this work is an amorphous material with specific surface area, total pore volume, and average pore diameter of 212.29 m²/g, 1.29 cm³/g, and 20.05 nm, respectively. The Ni/MSA catalyst produced 73.02 wt.% of liquid product in hydrocracking of pyrolyzed α-cellulose.

Keywords: catalyst, gelatin, hydrocracking, mesopore silica-alumina, α-cellulose

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Monika Simkute-Bukante

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Teachers significantly influence student achievements, personal development, and academic success. Consequently, they are subject to heightened expectations and scrutiny from governments, school administrations, parents, and even students. Increasing responsibilities and pressures impact teachers’ professional well-being, contributing to a global trend of increased teacher turnover and shortages due to stress and heavy workloads. Given the critical role of teachers in educating young people, it is essential to implement strategies to retain them. School administrations are pivotal in creating an environment conducive to optimal performance. However, there remains a gap in understanding how school administration leadership impacts teachers' professional well-being and its potential for improvement. This research aims to define teacher professional well-being, identify its attributes, and explore the factors influencing it, with a particular focus on the role of school administration. Employing the concept analysis method, this study reviews scholarly publications from 2019 to 2024 to articulate the components of teacher professional well-being. The findings highlight key attributes of teacher well-being, including self-efficacy, work engagement, job satisfaction, relationships with colleagues and students, support from administration, work autonomy, school climate, time pressure, workload, resilience, stress, burnout, and turnover intentions. The analysis demonstrates that school administration leadership directly affects these aspects by providing support in challenging situations, empowering teachers, offering recognition, facilitating open communication, and ensuring autonomy at work. In conclusion, the research shows that teachers' professional well-being is heavily dependent on relationships with school administration, colleagues, and students, as well as the overall school climate. It suggests that by enhancing these elements, school leaders can significantly improve teacher professional well-being. Recommendations are made for developing strategies to support these relationships, thereby fostering an environment that enhances teacher retention and effectiveness.

Keywords: concept analysis, teacher professional well-being, school administration leadership, well-being factors

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

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Authors: Feng Guo

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Human brain organoids, 3D brain tissue cultures derived from human pluripotent stem cells, hold promising potential in modeling neuroinflammation for a variety of neurological diseases. However, challenges remain in generating standardized human brain organoids that can recapitulate key physiological features of a human brain. Here, this study presents a series of organoids-on-a-chip systems to generate better human brain organoids and model neuroinflammation. By employing 3D printing and microfluidic 3D cell culture technologies, the study’s systems enable the reliable, scalable, and reproducible generation of human brain organoids. Compared with conventional protocols, this study’s method increased neural progenitor proliferation and reduced heterogeneity of human brain organoids. As a proof-of-concept application, the study applied this method to model substance use disorders.

Keywords: human brain organoids, microfluidics, organ-on-a-chip, neuroinflammation

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Authors: Panpan Feng

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The concept of green infrastructure originated in Europe and the United States. It aims to ensure smart growth of urban and rural ecosystems and achieve sustainable urban and rural ecological, social, and economic development by combining it with gray infrastructure in traditional planning. Based on the literature review of the theoretical origin, value connotation, and measurement methods of green infrastructure, this study summarizes the research content of green infrastructure at different scales from the three spatial levels of region, city, and block and divides it into functional dimensions, spatial dimension, and strategic dimension. The results show that in the functional dimension, from region-city-block, the research on green infrastructure gradually shifts from ecological function to social function. In the spatial dimension, from region-city-block, the research on the spatial form of green infrastructure has shifted from two-dimensional to three-dimensional, and the spatial structure of green infrastructure has shifted from single ecological elements to multiple composite elements. From a strategic perspective, green infrastructure research is more of a spatial planning tool based on land management, environmental livability and ecological psychology, providing certain decision-making support.

Keywords: green infrastructure, multi-scale, social and ecological functions, spatial strategic decision-making tools

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Authors: Hugo Reis, Isabel Rabiais

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The main purpose of the present study is to understand the nurse’s responsibility in preventing the septic shock in an oncological patient with febrile neutropenia submitted to chemotherapy. In order to do it, an integrative review of literature has been conducted. In the research done in many databases, it was concluded that only 7 out of 5202 articles compiled the entire inclusion standard present in the strict protocol of research, being this made up by all different methodologies. On the research done in the 7 articles it has resulted 8 text macro-units associated to different nursing interventions: ‘Health Education’; ‘Prophylactic Therapy Administration’; ‘Scales Utilization’; ‘Patient Evaluation’; ‘Environment Control’; ‘Performance of Diagnostic Auxiliary Exams’; ‘Protocol Enforcement/Procedure Guidelines’; ‘Antibiotic Therapy Administration’. Concerning the prevalence/result’s division there can be identified many conclusions: the macro-units ‘Patient Evaluation’, ‘Performance of Diagnostic Auxiliary Exams’, and ‘Antibiotic Therapy Administration’ present themselves to be the most prevalent in the research – 6 in 7 occurrences (approximately 85.7%). Next, the macro-unit ‘Protocol Enforcement/Procedure Guidelines’ presents itself as an important expression unit – being part of 5 out of the 7 analyzed studies (approximately 71.4%). The macro-unit ‘Health Education’, seems to be in the same way, an important expression unit – 4 out of the 7 (or approximately 57%). The macro-unit ‘Scales Utilization’, represents a minor part in the research done – it’s in only 2 out of the 7 cases (approximately 28.6%). On the other hand, the macro-units ‘Prophylactic Therapy Administration’ and ‘Environment Control’ are the two categories with fewer results in the research - 1 out of the 7 cases, the same as approximately 14.3% of the research results. Every research done to the macro-unit ‘Antibiotic Therapy Administration’ agreed to refer that the intervention should be strictly done, in a period of time less than one hour after diagnosing the fever, with the purpose of controlling the quick spread of infection – minimizing its seriousness. Identifying these interventions contributes, concluding that, to adopt strategies in order to prevent the phenomenon that represents a daily scenario responsible for the cost´s increase in health institutions, being at the same time responsible for the high morbidity rates and mortality increase associated with this specific group of patients.

Keywords: febrile neutropenia, oncology nursing, patient, septic shock

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Authors: Xu Runzhang, Yang Yanbing, Niu Yi, Zhang Mingyou, Liu Yu

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For a class of semilinear parabolic equations with linear dynamical boundary conditions in a bounded domain, we obtain both global solutions and finite time blow-up solutions when the initial data varies in the phase space H1(Ω). Our main tools are the comparison principle, the potential well method and the concavity method. In particular, we discuss the behavior of the solutions with the initial data at critical and high energy level.

Keywords: high energy level, critical energy level, linear dynamical boundary condition, semilinear parabolic equation

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Authors: Silvia Franco, Marcos Sarasola

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The Faculty of Business Administration at the Catholic University of Uruguay is performing an important educational innovation, unique in the country. In preparing future professionals in companies, teamwork competence is very important. However, there is no often a systematic and specific training in the acquisition of this competence in undergraduate students. For this reason, we have designed and implemented an educational innovation through an intervention method to improve teamwork competence for undergraduate students of business studies. Students’ teams are integrated according to the complementary roles of Belbin; changes in teamwork competence during training period are measured with CCSAC tool; classroom methodology in the prio-border teamwork by Team-Based Learning. Methodology also integrates coaching and support team performance during the first two semesters.

Keywords: business students, teamwork, learning, competences

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Authors: Xiaocong He

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Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. Mechanical structures assembled by SPR are expected to possess a high damping capacity. In this study, experimental measurement techniques were proposed for the prediction of vibration behavior of single-lap cantilevered SPR beams. The dynamic test software and the data acquisition hardware were used in the experimental measurement of the dynamic response of the single-lap cantilevered SPR beams. Free and forced vibration behavior of the single-lap cantilevered SPR beams was measured using the LMS CADA-X experimental modal analysis software and the LMS-DIFA Scadas II data acquisition hardware. The frequency response functions of the SPR beams of different rivet number were compared. The main goal of the paper is to provide a basic measuring method for further research on vibration based non-destructive damage detection in single-lap cantilevered SPR beams.

Keywords: self-piercing riveting, dynamic response, experimental measurement, frequency response functions

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Authors: Ewa Rak

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This paper is part of a broader research project on employee development in small enterprises, financed by Polish National Science Centre. The project results will serve as basis for a doctoral dissertation. The paper utilises literature studies and qualitative research conducted in small enterprises operating in the Lower Silesia region of Poland. This paper aims to identify some of the factors that stimulate employee development in small companies operating in Poland. The great variety of business pursuits and applications represented by this sector makes it hard to determine a universal configuration of factors to offer best possible conditions for employee development. Research results suggest that each of the examined companies had one or two of such factors in focus, and serving as the basis for the entire pro-development system. These include: employment security (both for employee and entrepreneur) and extensive knowledge and experience of entrepreneurs, but only if it is combined with a willingness and ability to share it.

Keywords: employee development, factors that stimulate employee development, human resources development, Poland, small enterprises, training

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Authors: Kalpana Singh, Nikita Katiyar

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This research investigates the impact of Raga Bhairavi, a prominent musical scale in Indian classical music, on the mood and basic physiological parameters of research scholars at the University of Lucknow - India. The study focuses on the potential therapeutic effects of listening to Raga Bhairavi during morning hours. A controlled experimental design is employed, utilizing self-reporting tools for mood assessment and monitoring physiological indicators such as heart rate, oxygen saturation levels, body temperature and blood pressure. The hypothesis posits that exposure to Raga Bhairavi will lead to positive mood modulation and a reduction in physiological stress markers among research scholars. Data collection involves pre and post-exposure measurements, providing insights into the immediate and cumulative effects of the musical intervention. The study aims to contribute valuable information to the growing field of music therapy, offering a potential avenue for enhancing the well-being and productivity of individuals engaged in intense cognitive activities. Results may have implications for the integration of music-based interventions in academic and research environments, fostering a conducive atmosphere for intellectual pursuits.

Keywords: bio-musicology, classical music, mood assessment, music therapy, physiology, Raga Bhairavi

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Reza Ehsani, Hawa Ze Jaffar, Ishak Aris

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Ripeness estimation of oil palm fresh fruit is important processes that affect the profitableness and salability of oil palm fruits. The adulthood or ripeness of the oil palm fruits influences the quality of oil palm. Conventional procedure includes physical grading of Fresh Fruit Bunches (FFB) maturity by calculating the number of loose fruits per bunch. This physical classification of oil palm FFB is costly, time consuming and the results may have human error. Hence, many researchers try to develop the methods for ascertaining the maturity of oil palm fruits and thereby, deviously the oil content of distinct palm fruits without the need for exhausting oil extraction and analysis. This research investigates the potential of infrared images (Thermal Images) as a predictor to classify the oil palm FFB ripeness. A total of 270 oil palm fresh fruit bunches from most common cultivar of oil palm bunches Nigresens according to three maturity categories: under ripe, ripe and over ripe were collected. Each sample was scanned by the thermal imaging cameras FLIR E60 and FLIR T440. The average temperature of each bunches were calculated by using image processing in FLIR Tools and FLIR ThermaCAM researcher pro 2.10 environment software. The results show that temperature content decreased from immature to over mature oil palm FFBs. An overall analysis-of-variance (ANOVA) test was proved that this predictor gave significant difference between underripe, ripe and overripe maturity categories. This shows that the temperature as predictors can be good indicators to classify oil palm FFB. Classification analysis was performed by using the temperature of the FFB as predictors through Linear Discriminant Analysis (LDA), Mahalanobis Discriminant Analysis (MDA), Artificial Neural Network (ANN) and K- Nearest Neighbor (KNN) methods. The highest overall classification accuracy was 88.2% by using Artificial Neural Network. This research proves that thermal imaging and neural network method can be used as predictors of oil palm maturity classification.

Keywords: artificial neural network, maturity classification, oil palm FFB, thermal imaging

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Authors: Elisabeth Desiana Mayasari, Laurensia Aptik Evanjeli, Brigitta Erlita Tri Anggadewi

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The condition of the COVID-19 pandemic demands adaptation in various aspects of human life, including in the field of education. Teachers are expected to do distance learning or Learning From Home (LFH). The teacher said that he experienced stress, anxiety, feeling depressed, and afraid based on the interview. Learning adaptations and pandemic situations can impact the mental health of teachers, so the purpose of this study is to determine the mental health of teachers while teaching online. This research was conducted with a quantitative approach using a survey method. The subjects in this study were 330 elementary school teachers under the auspices of a foundation in Yogyakarta. Teachers' mental health was measured using the Indonesian version of The Mental Health Inventory (MHI-38), which has a reliability of 0.888. The results showed that the teachers generally had a good mental health condition marked by a lower negative aspect score than the positive aspect. In addition, the overall mental health aspect shows that some teachers have better mental health when compared to the average score, as well as higher positive aspect scores in all sub-aspects.

Keywords: mental health, teacher, COVID-19 pandemic, MHI-38

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Authors: Cristina da Silva Torres, José Luis Duarte Ribeiro, Maria Auxiliadora Cannarozzo Tinoco

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As a result of the rapid growth of the Brazilian Air Transport, many airports are at the limit of their capacities and have a reduction in the quality of services provided. Thus, there is a need of models for assessing the quality of airport services. Because of this, the main objective of this work is to propose a model for the evaluation of quality attributes in airport services. To this end, we used the method composed by literature review and interview. Structured a working method composed by 5 steps, which resulted in a model to evaluate the quality of airport services, consisting of 8 dimensions and 45 attributes. Was used as base for model definition the process mapping of boarding and landing processes of passengers and luggage. As a contribution of this work is the integration of management process with structuring models to assess the quality of services in airport environments.

Keywords: quality airport services, model for identification of attributes quality, air transport, passenger

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Authors: Mamani Acurio Alex, Aguilar Alonso Igor

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The lack of interest and the lack of motivation are related. The lack of both in school generates serious problems such as school dropout or a low level of learning. Augmented reality has been very useful in different areas, and in this research, it was implemented in the area of education. Information necessary for the correct development of this mobile application with augmented reality was searched using six different research repositories. It was concluded that the application must be immersive, attractive, and fun for students, and the necessary technologies for its construction were defined.

Keywords: augmented reality, Vuforia, school interest, learning

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Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

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Authors: Fatima Naz, Ayesha Tariq

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In view of growing of the internet users for e-commerce and taking into account, the emergent impact of word of mouth phenomenon this research has different aims. The aims of this study were built following dissimilar discussion with teachers and colleagues enlightening that word of mouth information for online purchasing do not have the same effect for everybody. Then they were born following dissimilar researchers together with what was already done in previous researches and what was completed. As a result different aims were drawn; the initial aim of this research is to study the attention of the customers in the word of mouth to power their online purchasing activities. The next aim is to analyze the people influenced by the interest of word of mouth. The following aim is to examine the marketing behavior bearing in mind the internet progress and word of mouth, their consideration for word of mouth marketing. In the form of research questions the aims of the study are: 1) How community utilizes and multiplies word of mouth information about online purchasing experience? 2) How communities perceive the word of mouth marketing? 3) How marketers take the word of mouth phenomenon and how they handle it?

Keywords: belief, power, inspiration, self-expression, positive attitude to online marketing, forwarding of contents, purchasing decision, standard marketing

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Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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Authors: Mohd Salmi Md Noorani, Ghada Al-Mahbashi, Sakhinah Abu Bakar

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This paper investigates projective lag synchronization (PLS) behavior in drive response dynamical networks (DRDNs) model with identical nodes. A hybrid feedback control method is designed to achieve the PLS with mismatch and without mismatch terms. The stability of the error dynamics is proven theoretically using the Lyapunov stability theory. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Moreover, the numerical simulations results demonstrate the validity of the proposed method.

Keywords: drive-response dynamical network, projective lag synchronization, hybrid feedback control, stability theory

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

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Authors: Prakash Chand, Anurag Gaur, Ashavani Kumar

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In the present study, we have synthesized Cr and Fe doped zinc oxide (ZnO) nano-structures (Zn1-δCraFebO; where δ= a + b=20%, a = 5, 6, 8 & 10% and b=15, 14, 12 & 10%) via sol-gel method at different doping concentrations. The synthesized samples were characterized for structural properties by X-ray diffractometer and field emission scanning electron microscope and the optical properties were carried out through photoluminescence and UV-visible spectroscopy. The particle size calculated through field emission scanning electron microscope varies from 41 to 96 nm for the samples synthesized at different doping concentrations. The optical band gaps calculated through UV-visible spectroscopy are found to be decreasing from 3.27 to 3.02 eV as the doping concentration of Cr increases and Fe decreases.

Keywords: nano-structures, optical properties, sol-gel method, zinc oxide

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Authors: Anna Krukowska, Tomasz Klimczuk, Adriana Zaleska-Medynska

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Photoactive materials have attracted attention due to their potential application in the degradation of environmental pollutants to non-hazardous compounds in an eco-friendly route. Among semiconductor photocatalysts, tantalates such as potassium tantalate (KTaO3) is one of the excellent functional photomaterial. However, tantalates-based materials are less active under visible-light irradiation, the enhancement in photoactivity could be improved with the modification of opto-eletronic properties of KTaO3 by doping rare earth metal (Er) and further photodeposition of noble metal nanoparticles (Pt). Inclusion of rare earth element in orthorhombic structure of tantalate can generate one high-energy photon by absorbing two or more incident low-energy photons, which convert visible-light and infrared-light into the ultraviolet-light to satisfy the requirement of KTaO3 photocatalysts. On the other hand, depositions of noble metal nanoparticles on the surface of semiconductor strongly absorb visible-light due to their surface plasmon resonance, in which their conducting electrons undergo a collective oscillation induced by electric field of visible-light. Furthermore, the high dispersion of Pt nanoparticles, which will be obtained by photodeposition process is additional important factor to improve the photocatalytic activity. The present work is aimed to study the effect of photocatalytic process of the prepared Er-doped KTaO3 and further incorporation of Pt nanoparticles by photodeposition. Moreover, the research is also studied correlations between photocatalytic activity and physico-chemical properties of obtained Pt/Er-KTaO3 samples. The Er-doped KTaO3 microcomposites were synthesized by a hydrothermal method. Then photodeposition method was used for Pt loading over Er-KTaO3. The structural and optical properties of Pt/Er-KTaO3 photocatalytic were characterized using scanning electron microscope (SEM), X-ray diffraction (XRD), volumetric adsorption method (BET), UV-Vis absorption measurement, Raman spectroscopy and luminescence spectroscopy. The photocatalytic properties of Pt/Er-KTaO3 microcomposites were investigated by degradation of phenol in aqueous phase as model pollutant under visible and ultraviolet-light irradiation. Results of this work show that all the prepared photocatalysis exhibit low BET surface area, although doping of the bare KTaO3 with rare earth element (Er) presents a slight increase in this value. The crystalline structure of Pt/Er-KTaO3 powders exhibited nearly identical positions for the main peak at about 22,8o and the XRD pattern could be assigned to an orthorhombic distorted perovskite structure. The Raman spectra of obtained semiconductors confirmed demonstrating perovskite-like structure. The optical absorption spectra of Pt nanoparticles exhibited plasmon absorption band for main peaks at about 216 and 264 nm. The addition of Pt nanoparticles increased photoactivity compared to Er-KTaO3 and pure KTaO3. Summary optical properties of KTaO3 change with its doping Er-element and further photodeposition of Pt nanoparticles.

Keywords: heterogeneous photocatalytic, KTaO3 photocatalysts, Er3+ ion doping, Pt photodeposition

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Authors: Tanit Pruktara

Abstract:

The research aimed to study the students’ learning achievement and awareness level on electrical energy consumption and conservation and also to investigate the students’ attitude on the developed multimedia supplemented instructional unit for learning household electrical energy consumption and conservation in grade 10 Thailand student. This study used a quantitative method using MCQ for pre and post-achievement tests and Likert scales for awareness and attitude survey questionnaires. The results from this were employed to improve the multimedia to be appropriate for the classroom and with real life situations in the second phase, the main study. The experimental results showed that the developed learning unit significantly improved the students’ learning achievement as well as their awareness of electric energy conservation. Additional we found the student will enjoy participating in class activities when the lessons are taught using multimedia and helps them to develop the relevance between the course and real world situations.

Keywords: lesson plan, media and animations, training course, vocational school in Thailand

Procedia PDF Downloads 164

Authors: Weber-Lewerenz Bianca

Abstract:

Digitization is developing fast and has become a powerful tool for digital planning, construction, and operations. Its transformation bears high potentials for companies, is critical for success, and thus, requires responsible handling. This study provides an assessment of calls made in the sustainable development goals by the United Nations (SDGs), White Papers on AI by international institutions, EU-Commission and German Government requesting for the consideration and protection of values and fundamental rights, the careful demarcation between machine (artificial) and human intelligence and the careful use of such technologies. The study discusses digitization and the impacts of artificial intelligence (AI) in construction engineering from an ethical perspective by generating data via conducting case studies and interviewing experts as part of the qualitative method. This research evaluates critically opportunities and risks revolving around corporate digital responsibility (CDR) in the construction industry. To the author's knowledge, no study has set out to investigate how CDR in construction could be conceptualized, especially in relation to the digitization and AI, to mitigate digital transformation both in large, medium-sized, and small companies. No study addressed the key research question: Where can CDR be allocated, how shall its adequate ethical framework be designed to support digital innovations in order to make full use of the potentials of digitization and AI? Now is the right timing for constructive approaches and apply ethics-by-design in order to develop and implement a safe and efficient AI. This represents the first study in construction engineering applying a holistic, interdisciplinary, inclusive approach to provide guidelines for orientation, examine benefits of AI and define ethical principles as the key driver for success, resources-cost-time efficiency, and sustainability using digital technologies and AI in construction engineering to enhance digital transformation. Innovative corporate organizations starting new business models are more likely to succeed than those dominated by conservative, traditional attitudes.

Keywords: construction engineering, digitization, digital transformation, artificial intelligence, ethics, corporate digital responsibility, digital innovation

Procedia PDF Downloads 221

Authors: N. Guo, C. Xu, Z. C. Yang

Abstract:

In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

Procedia PDF Downloads 143