Search results for: digital business models

Authors: Jonathan Josephs-Spaulding, Hannah Rettig, Simon Graspeunter, Jan Rupp, Christoph Kaleta

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Background: Recurrent urinary tract infections (rUTIs) are a global cause of emergency room visits and represent a significant burden for public health systems. Therefore, metatranscriptomic approaches to investigate metabolic exchange and crosstalk between uropathogenic Escherichia coli (UPEC), which is responsible for 90% of UTIs, and collaborating pathogens of the urogenital microbiome is necessary to better understand the pathogenetic processes underlying rUTIs. Objectives: This study aims to determine the level in which uropathogens optimize the host urinary metabolic environment to succeed during invasion. By developing patient-specific metabolic models of infection, these observations can be taken advantage of for the precision treatment of human disease. Methods: To date, we have set up an rUTI patient cohort and observed various urine-associated pathogens. From this cohort, we developed patient-specific metabolic models to predict bladder microbiome metabolism during rUTIs. This was done by creating an in silico metabolomic urine environment, which is representative of human urine. Metabolic models of uptake and cross-feeding of rUTI pathogens were created from genomes in relation to the artificial urine environment. Finally, microbial interactions were constrained by metatranscriptomics to indicate patient-specific metabolic requirements of pathogenic communities. Results: Metabolite uptake and cross-feeding are essential for strain growth; therefore, we plan to design patient-specific treatments by adjusting urinary metabolites through nutritional regimens to counteract uropathogens by depleting essential growth metabolites. These methods will provide mechanistic insights into the metabolic components of rUTI pathogenesis to provide an evidence-based tool for infection treatment.

Keywords: recurrent urinary tract infections, human microbiome, uropathogenic Escherichia coli, UPEC, microbial ecology

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Authors: Michal Lysek, Mike Danilovic, Jasmine Lihua Liu

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HMS Industrial Networks AB has been recognized as one of the most innovative companies in the industrial communication industry worldwide. The creation of their Anybus innovation during the 1990s contributed considerably to the company’s success. From inception, HMS’ employees were innovating for the purpose of creating new business (the creation phase). After the Anybus innovation, they began the process of internationalization (the commercialization phase), which in turn led them to concentrate on cost reduction, product quality, delivery precision, operational efficiency, and increasing growth (the growth phase). As a result of this transformation, performing new radical innovations have become more complicated. The purpose of our research was to explore the dynamics of innovation at HMS from the aspect of key actors, activities, and events, over the three phases, in order to understand what led to the creation of their Anybus innovation, and why it has become increasingly challenging for HMS to create new radical innovations for the future. Our research methodology was based on a longitudinal, retrospective study from the inception of HMS in 1988 to 2014, a single case study inspired by the grounded theory approach. We conducted 47 interviews and collected 1 024 historical documents for our research. Our analysis has revealed that HMS’ success in creating the Anybus, and developing a successful business around the innovation, was based on three main capabilities – cultivating customer relations on different managerial and organizational levels, inspiring business relations, and balancing complementary human assets for the purpose of business creation. The success of HMS has turned the management’s attention away from past activities of key actors, of their behavior, and how they influenced and stimulated the creation of radical innovations. Nowadays, they are rhetorically focusing on creativity and innovation. All the while, their real actions put emphasis on growth, cost reduction, product quality, delivery precision, operational efficiency, and moneymaking. In the process of becoming an international company, HMS gradually refocused. In so doing they became profitable and successful, but they also forgot what made them innovative in the first place. Fortunately, HMS’ management has come to realize that this is the case and they are now in search of recapturing innovation once again. Our analysis indicates that HMS’ management is facing several barriers to innovation related path dependency and other lock-in phenomena. HMS’ management has been captured, trapped in their mindset and actions, by the success of the past. But now their future has to be secured, and they have come to realize that moneymaking is not everything. In recent years, HMS’ management have begun to search for innovation once more, in order to recapture their past capabilities for creating radical innovations. In order to unlock their managerial perceptions of customer needs and their counter-innovation driven activities and events, to utilize the full potential of their employees and capture the innovation opportunity for the future.

Keywords: barriers to innovation, dynamics of innovation, in search of excellence and innovation, radical innovation

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Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes

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Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.

Keywords: airport ontology, energy management, facility data model, ontology modeling

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Authors: Kanamon Suwantada

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The purpose of this research is to understand customer’s expectations towards homestays and to establish the precise strategies to increase numbers of tourists for homestay business in Amphawa district, Samutsongkram, Thailand. The researcher aims to ensure that each host provides experiences to travelers who are looking for and determining new targets for homestay business in Amphawa as well as creating sustainable homestay using marketing strategies to increase customers. The methods allow interview and questionnaire to gain both overview data from the tourists and qualitative data from the homestay owner’s perspective to create a GAP analysis. The data was collected from 200 tourists, during 15th May - 30th July, 2011 from homestay in Amphawa Community. The questionnaires were divided into three sections: the demographic profile, customer information and influencing on purchasing position, and customer expectation towards homestay. The analysis, in fact, will be divided into two methods which are percentage and correlation analyses. The result of this research revealed that homestay had already provided customers with reasonable prices in good locations. Antithetically, activities that they offered still could not have met the customer’s requirements. Homestay providers should prepare additional activities such as village tour, local attraction tour, village daily life experiences, local ceremony participation, and interactive conversation with local people. Moreover, the results indicated that a price was the most important factor for choosing homestay.

Keywords: ecotourism, homestay, marketing, sufficiency economic philosophy

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Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: R. Setino, I. M. Ambe, J. A Badenhorst-Weiss

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The South African government supply chain management system is not adequately implemented in State Owned Enterprises (SOEs). There are weaknesses in the SOEs SCM enablers, strategies and policies. In addition, top management of SOEs still do not see SCM as strategic enough to deserve their attention, and therefore, there is very little support from top management, thus making it even difficult for SCM practitioners to execute their day to day functions, let alone delivering the letter and spirit of the relevant legislations. Supply chain strategies lack buy in from the top, and as a result senior SCM practitioners has not been involved in the corporate strategy. This has resulted in supply chain and corporate strategies being misaligned. Due to service delivery backlog, high level of corruption and continuous strikes across the country for better services it is inevitable that government leaders be more strategic about how South Africa can use SCM as a tool to improve service delivery. Consequently, there is a need to close the gap between the strategic level dealt by top management and the application of operational SCM concepts: the use of SCM concepts and, therefore, supply chain strategies – should be aligned with the corporate and business strategies in order to ensure the achievement of top level business objectives. This paper aims to explore supply chain practices in State Owned Enterprises (SOEs). The paper based on a conceptual review provides the status, trends and development and suggests a framework for aligning supply chain strategies and organizational strategies in an SOE environment.

Keywords: alignment, strategies, state owned enterprises, supply chain management, South Africa

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Authors: Chen Shuwen, Nunthapin Chantachaimongkol

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Since the world has moved into a transitional period, known as globalization; the business environment is now more complicated than ever before. Corporate information has become a matter of great importance for stakeholders, in order to understand the current situation. As a result of this, the concept of corporate governance has been broadly introduced to manage and control the affairs of corporations while businesses are required to disclose both financial and non-financial information to public via various communication channels such as the annual report, the financial report, the company’s website, etc. However, currently there are several other issues related to asymmetric information such as moral hazard or adverse selection that still occur intensively in workplaces. To prevent such problems in the business, it is required to have an understanding of what factors strengthen their transparency, accountability, fairness, and responsibility. Under aforementioned arguments, this paper aims to propose a conceptual framework that enables an investigation on how corporate governance mechanism influences disclosure efficiency of listed companies in the Association of Southeast Asia Nations (ASEAN) and the factors that should be considered for further development of good behaviors, particularly in regards to voluntary disclosure practices. To achieve its purpose, extensive reviews of literature are applied as a research methodology. It is divided into three main steps. Firstly, the theories involved with both corporate governance and disclosure practices such as agency theory, contract theory, signaling theory, moral hazard theory, and information asymmetry theory are examined to provide theoretical backgrounds. Secondly, the relevant literatures based on multi- perspectives of corporate governance, its attributions and their roles on business processes, the influences of corporate governance mechanisms on business performance, and the factors determining corporate governance characteristics as well as capability are reviewed to outline the parameters that should be included in the proposed model. Thirdly, the well-known regulatory document OECD principles and previous empirical studies on the corporate disclosure procedures are evaluated to identify the similarities and differentiations with the disclosure patterns in the ASEAN. Following the processes and consequences of the literature review, abundant factors and variables are found. Further to the methodology, additional critical factors that also have an impact on the disclosure behaviors are addressed in two groups. In the first group, the factors which are linked to the national characteristics - the quality of national code, legal origin, culture, the level of economic development, and so forth. Whereas in the second group, the discoveries which refer to the firm’s characteristics - ownership concentration, ownership’s rights, controlling group, and so on. However, because of research limitations, only some literature are chosen and summarized to form part of the conceptual framework that explores the relationship between corporate governance and the disclosure practices of listed companies in ASEAN.

Keywords: corporate governance, disclosure practice, ASEAN, listed company

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Authors: K. Veluraja

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Glycan of glycolipids and glycoproteins is playing a significant role in living systems particularly in molecular recognition processes. Molecular recognition processes are attributed to their occurrence on the surface of the cell, sequential arrangement and type of sugar molecules present in the oligosaccharide structure and glyosidic linkage diversity (glycoinformatics) and conformational diversity (glycoconformatics). Molecular Dynamics Simulation study is a theoretical-cum-computational tool successfully utilized to establish glycoconformatics of glycan. The study on various oligosaccharides of glycan clearly indicates that oligosaccharides do exist in multiple conformational states and these conformational states arise due to the flexibility associated with a glycosidic torsional angle (φ,ψ) . As an example: a single disaccharide structure NeuNacα(2-3) Gal exists in three different conformational states due to the differences in the preferential value of glycosidic torsional angles (φ,ψ). Hence establishing three dimensional structural and conformational models for glycan (cartesian coordinates of every individual atoms of an oligosaccharide structure in a preferred conformation) is quite crucial to understand various molecular recognition processes such as glycan-toxin interaction and glycan-virus interaction. The gycoconformatics models obtained for various glycan through Molecular Dynamics Simulation stored in our 3DSDSCAR (3DSDSCAR.ORG) a public domain database and its utility value in understanding the molecular recognition processes and in drug design venture will be discussed.

Keywords: glycan, glycoconformatics, molecular dynamics simulation, oligosaccharide

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Bahia Braktia, S. Anna Marcela Montenegro, Imene Abdessemed

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Adult education is still considered a crucial area of education. In a developing framework, it is regarded as a practical approach for social inclusion and poverty reduction. They are also perceived as a way to serve adults who did not have the chance to education in their early ages by providing them knowledge, skills and values. Non-formal adult education and trainings are critical means in a society to break poverty and unemployment, and to decrease the social inequality. This paper investigates the perception of women trainees about a series of workshops in natural beauty products, held in Algeria and Costa Rica and organized by a non-profit educational organization, to improve their socio-economic status. This research seeks to explore ways of empowering women by assessing their needs and providing them with skills to start their own business. A questionnaire is administered before the workshops and focus groups are held at the end. A qualitative research method is employed to analyze the data. Preliminary results show that the trainees aspire to create their businesses with the objectives of poverty reduction and social inclusion. The findings also reveal the need for small business funding programs and entrepreneurial training programs.

Keywords: adult education, non-formal education, socio-economic status, women empowerment

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Khadidja Rahmani, Nahla Bouaziz

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Algeria is known for its rich heritage. It owns an immense historical heritage with a universal reputation. Unfortunately, this wealth is withered because of abundance. This research focuses on the Ksourian model, which constitutes a large portion of this wealth. In fact, the Ksourian model is not just a witness to a great part of history or a vernacular culture, but also it includes a panoply of assets in terms of energetic efficiency. In this context, the purpose of our work is to evaluate the performance of the old techniques which are derived from the Ksourian model , and that using the simulation tools. The proposed method is decomposed in two steps; the first consists of isolate and reintroduce each device into a basic model, then run a simulation series on acquired models. And this in order to test the contribution of each of these dialectal processes. In another scale of development, the second step consists of aggregating all these processes in an aboriginal model, then we restart the simulation, to see what it will give this mosaic on the environmental and energetic plan .The model chosen for this study is one of the ksar units of Knadsa city of Bechar (Algeria). This study does not only show the ingenuity of our ancestors in their know-how, and their adapting power to the aridity of the climate, but also proves that their conceptions subscribe in the current concerns of energy efficiency, and respond to the requirements of sustainable development.

Keywords: dialectal processes, energy efficiency, evaluation, Ksourian model, simulation tools

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Authors: Mohammad Bakhshi, Firas Al Janabi

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High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.

Keywords: DiMoN Tool, disaggregation, exceedance probability, Kolmogorov-Smirnov test, rainfall

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Authors: Areej Al-Hamad, Cheryl Forchuk, Abe Oudshoorn, Gerald Patrick Mckinley

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Syrian refugee women face many obstacles when accessing health services in host countries that are influenced by various cultural, structural, and practical factors. This paper is based on critical ethnographic research undertaken in Canada to explore Syrian refugee women's migration experiences. Also, we aim to critically examine how the intersection of gender, trauma, violence and the political and economic conditions of Syrian refugee women shapes their everyday lives and health. The study also investigates the strategies and practices by which Syrian refugee women are currently addressing their healthcare needs and the models of care that are suggested for meeting their physical and mental health needs. Findings show that these women experienced constant worries, hardship, vulnerability, and intrusion of dignity. These experiences and challenges were aggravated by the structure of the Canadian social and health care system. This study offers a better understanding of the impact of migration and trauma on Syrian refugee women's roles, responsibilities, gender dynamics, and interaction with Ontario's healthcare system to improve interaction and outcomes. Health care models should address these challenges among Syrian refugee families in Canada.

Keywords: Syrian refugee women, intersectionality, critical ethnography, migration

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Authors: Abdelmalek Ouannou, Adil Brouri, Laila Kadi, Tarik

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Switched reluctance motor (SRM) has a major interest in a large domain as in electric vehicle driving because of its wide range of speed operation, high performances, low cost, and robustness to run under degraded conditions. The purpose of the paper is to develop a new analytical approach for modeling SRM parameters. Then, an identification scheme is proposed to obtain the SRM parameters. Since the SRM is featured by a highly nonlinear behavior, modeling these devices is difficult. Then, it is convenient to develop an accurate model describing the SRM. Furthermore, it is always operated in the magnetically saturated mode to maximize the energy transfer. Accordingly, it is shown that the SRM can be accurately described by a generalized polynomial Hammerstein model, i.e., the parallel connection of several Hammerstein models having polynomial nonlinearity. Presently an analytical identification method is developed using a chirp excitation signal. Afterward, the parameters of the obtained model have been determined using Finite Element Method analysis. Finally, in order to show the effectiveness of the proposed method, a comparison between the true and estimate models has been performed. The obtained results show that the output responses are very close.

Keywords: switched reluctance motor, swept-sine signal, generalized Hammerstein model, nonlinear system

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Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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Authors: Tetsuji Tanaka, Jin Guo

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The extant literature has not succeeded in uncovering the common determinants of price volatility transmissions of agricultural commodities from international to local markets, and further, has rarely investigated the role of self-sufficiency measures in the context of national food security. We analyzed various factors to determine the degree of price volatility transmissions of wheat, rice, and maize between world and domestic markets using GARCH models with dynamic conditional correlation (DCC) specifications and panel-feasible generalized least square models. We found that the grain autarky system has the potential to diminish volatility pass-throughs for three grain commodities. Furthermore, it was discovered that the substitutive commodity consumption behavior between maize and wheat buffers the volatility transmissions of both, but rice does not function as a transmission-relieving element, either for the volatilities of wheat or maize. The effectiveness of grain consumption substitution to insulate the pass-throughs from global markets is greater than that of cereal self-sufficiency. These implications are extremely beneficial for developing governments to protect their domestic food markets from uncertainty in foreign countries and as such, improves food security.

Keywords: food security, GARCH, grain self-sufficiency, volatility transmission

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Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

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Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

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Authors: A. Latif Karimi, M. K. Shrimali

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Seismic design is a critical stage in the process of design and construction of a building. It includes strategies for designing earthquake-resistant buildings to ensure health, safety, and security of the building occupants and assets. Hence, it becomes very important to understand the behavior of structural members precisely, for construction of buildings that can yield a better response to seismic forces. This paper investigates the behavior of a typical structure when subjected to ground motion. The corresponding mode shapes and modal frequencies are studied to interpret the response of an actual structure using different fabricated models and 3D visual models. In this study, three different structural configurations are subjected to horizontal ground motion, and the effect of “stiffness eccentricity” and placement of infill walls are checked to determine how each parameter contributes in a building’s response to dynamic forces. The deformation data from lab experiments and the analysis on SAP2000 software are reviewed to obtain the results. This study revealed that seismic response in a building can be improved by introducing higher deformation capacity in the building. Also, proper design of infill walls and maintaining a symmetrical configuration in a building are the key factors in building stability during the earthquake.

Keywords: eccentricity, seismic response, mode shape, building configuration, building dynamics

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Claire Limoge Schraen, Philippe Gueguen, Cedric Giry, Cedric Desprez, Frédéric Ragueneau

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Mediterranean area is characterized by numerous monumental or vernacular masonry structures illustrating old ways of build and live. Those precious buildings are often poorly documented, present complex shapes and loadings, and are protected by the States, leading to legal constraints. This area also presents a moderate to high seismic activity. Even moderate earthquakes can be magnified by local site effects and cause collapse or significant damage. Moreover the structural resistance of masonry buildings, especially when less famous or located in rural zones has been generally lowered by many factors: poor maintenance, unsuitable restoration, ambient pollution, previous earthquakes. Recent earthquakes prove that any damage to these architectural witnesses to our past is irreversible, leading to the necessity of acting preventively. This means providing preventive assessments for hundreds of structures with no or few documents. In this context we want to propose a general method, based on hierarchized numerical models, to provide preliminary structural diagnoses at a regional scale, indicating whether more precise investigations and models are necessary for each building. To this aim, we adapt different tools, being developed such as photogrammetry or to be created such as a preprocessor starting from pictures to build meshes for a FEM software, in order to allow dynamic studies of the buildings of the panel. We made an inventory of 198 baroque chapels and churches situated in the French Alps. Then their structural characteristics have been determined thanks field surveys and the MicMac photogrammetric software. Using structural criteria, we determined eight types of churches and seven types for chapels. We studied their dynamical behavior thanks to CAST3M, using EC8 spectrum and accelerogramms of the studied zone. This allowed us quantifying the effect of the needed simplifications in the most sensitive zones and choosing the most effective ones. We also proposed threshold criteria based on the observed damages visible in the in situ surveys, old pictures and Italian code. They are relevant in linear models. To validate the structural types, we made a vibratory measures campaign using vibratory ambient noise and velocimeters. It also allowed us validating this method on old masonry and identifying the modal characteristics of 20 churches. Then we proceeded to a dynamic identification between numerical and experimental modes. So we updated the linear models thanks to material and geometrical parameters, often unknown because of the complexity of the structures and materials. The numerically optimized values have been verified thanks to the measures we made on the masonry components in situ and in laboratory. We are now working on non-linear models redistributing the strains. So we validate the damage threshold criteria which we use to compute the vulnerability curves of each defined structural type. Our actual results show a good correlation between experimental and numerical data, validating the final modeling simplifications and the global method. We now plan to use non-linear analysis in the critical zones in order to test reinforcement solutions.

Keywords: heritage structures, masonry numerical modeling, seismic vulnerability assessment, vibratory measure

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Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

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Authors: Alberto Mínguez-Martínez, Jesús De Vicente Y Oliva

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It seems that we live in a world in which the trend in industrial environments is the miniaturization of systems and materials and the fabrication of parts at the micro-and nano-scale. The problem arises when manufacturers want to study the quality of their production. This characteristic is becoming crucial due to the evolution of the industry and the development of Industry 4.0. As Industry 4.0 is based on digital models of production and processes, having accurate measurements becomes capital. At this point, the metrology field plays an important role as it is a powerful tool to ensure more stable production to reduce scrap and the cost of non-conformities. The most extended measuring instruments that allow us to carry out accurate measurements at these scales are optical microscopes, whether they are traditional, confocal, focus variation microscopes, profile projectors, or any other similar measurement system. However, the accuracy of measurements is connected to the traceability of them to the SI unit of length (the meter). The fact of providing adequate traceability to 2D and 3D dimensional measurements at micro-and nano-scale in industrial environments is a problem that is being studied, and it does not have a unique answer. In addition, if commercial material standards for micro-and nano-scale are considered, we can find that there are two main problems. On the one hand, those material standards that could be considered complete and very interesting do not give traceability of dimensional measurements and, on the other hand, their calibration is very expensive. This situation implies that these kinds of standards will not succeed in industrial environments and, as a result, they will work in the absence of traceability. To solve this problem in industrial environments, it becomes necessary to have material standards that are easy to use, agile, adaptive to different forms, cheap to manufacture and, of course, traceable to the definition of meter with simple methods. By using these ‘customized standards’, it would be possible to adapt and design measuring procedures for each application and manufacturers will work with some traceability. It is important to note that, despite the fact that this traceability is clearly incomplete, this situation is preferable to working in the absence of it. Recently, it has been demonstrated the versatility and the utility of using laser technology and other AM technologies to manufacture customized material standards. In this paper, the authors propose to manufacture a customized material standard using an ultraviolet laser system and a method to calibrate it. To conclude, the results of the calibration carried out in an accredited dimensional metrology laboratory are presented.

Keywords: industrial environment, material standards, optical measuring instrument, traceability

Procedia PDF Downloads 115

Authors: D. Szinay, O. Perski, A. Jones, T. Chadborn, J. Brown, F. Naughton

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Background: The uptake of health and wellbeing smartphone apps is largely influenced by popularity indicators (e.g., rankings), rather than evidence-based content. Rapid disengagement is common. This study aims to explore how and why potential users 1) select and 2) engage with such apps, and 3) how increased engagement could be promoted. Methods: Semi-structured interviews and a think-aloud approach were used to allow participants to verbalise their thoughts whilst searching for a health or wellbeing app online, followed by a guided search in the UK National Health Service (NHS) 'Apps Library' and Public Health England’s (PHE) 'One You' website. Recruitment took place between June and August 2019. Adults interested in using an app for behaviour change were recruited through social media. Data were analysed using the framework approach. The analysis is both inductive and deductive, with the coding framework being informed by the Theoretical Domains Framework. The results are further mapped onto the COM-B (Capability, Opportunity, Motivation - Behaviour) model. The study protocol is registered on the Open Science Framework (https://osf.io/jrkd3/). Results: The following targets were identified as playing a key role in increasing the uptake of and engagement with health and wellbeing apps: 1) psychological capability (e.g., reduced cognitive load); 2) physical opportunity (e.g., low financial cost); 3) social opportunity (e.g., embedded social media); 4) automatic motivation (e.g., positive feedback). Participants believed that the promotion of evidence-based apps on NHS-related websites could be enhanced through active promotion on social media, adverts on the internet, and in general practitioner practices. Future Implications: These results can inform the development of interventions aiming to promote the uptake of and engagement with evidence-based health and wellbeing apps, a priority within the UK NHS Long Term Plan ('digital first'). The targets identified across the COM-B domains could help organisations that provide platforms for such apps to increase impact through better selection of apps.

Keywords: behaviour change, COM-B model, digital health, mhealth

Procedia PDF Downloads 154

Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: S. M. Ali, A. Salam Khan, A. U. Khan, M. Tariq, M. S. Hussain, B. A. Abbasi, I. Hussain, U. Farid

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Environment and surrounding plays a pivotal rule in structuring life-style of the consumers. Living standards intern effect the energy consumption of the consumers. In smart grid paradigm, climate drifts, weather parameter and green environmental directly relates to the energy profiles of the various consumers, such as residential, commercial and industrial. Considering above factors helps policy in shaping utility load curves and optimal management of demand and supply. Thus, there is a pressing need to develop correlation models of load and weather parameters and critical analysis of the factors effecting energy profiles of smart grid consumers. In this paper, we elaborated various environment and weather parameter factors effecting demand of consumers. Moreover, we developed correlation models, such as Pearson, Spearman, and Kendall, an inter-relation between dependent (load) parameter and independent (weather) parameters. Furthermore, we validated our discussion with real-time data of Texas State. The numerical simulations proved the effective relation of climatic drifts with energy consumption of smart grid consumers.

Keywords: climatic drifts, correlation analysis, energy consumption, smart grid, weather parameter

Procedia PDF Downloads 365

Authors: Samira Hamiditehrani

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Automated vehicles (AVs) are emerging technologies that could potentially offer a wide range of opportunities and challenges for the transportation sector. The advent of AV technology has also resulted in new business models in shared mobility services where many ride hailing and car sharing companies are developing on-demand AVs including shared automated vehicles (SAVs) and pooled automated vehicles (Pooled AVs). SAVs and Pooled AVs could provide alternative shared mobility services which encourage sustainable transport systems, mitigate traffic congestion, and reduce automobile dependency. However, the success of on-demand AVs in addressing major transportation policy issues depends on whether and how the public adopts them as regular travel modes. To identify conditions under which individuals may adopt on-demand AVs, previous studies have applied human behavior and technology acceptance theories, where Theory of Planned Behavior (TPB) has been validated and is among the most tested in on-demand AV research. In this respect, this study has three objectives: (a) to propose and validate a theoretical model for behavioral intention to use SAVs and Pooled AVs by extending the original TPB model; (b) to identify the characteristics of early adopters of SAVs, who prefer to have a shorter and private ride, versus prospective users of Pooled AVs, who choose more affordable but longer and shared trips; and (c) to investigate Canadians’ intentions to adopt on-demand AVs for regular trips. Toward this end, this study uses data from an online survey (n = 3,622) of workers or adult students (18 to 75 years old) conducted in October and November 2021 for six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa, Montreal, Calgary, and Hamilton. To accomplish the goals of this study, a base bivariate ordered probit model, in which both SAV and Pooled AV adoptions are estimated as ordered dependent variables, alongside a full structural equation modeling (SEM) system are estimated. The findings of this study indicate that affective motivations such as attitude towards AV technology, perceived privacy, and subjective norms, matter more than sociodemographic and travel behavior characteristic in adopting on-demand AVs. Also, the results of second objective provide evidence that although there are a few affective motivations, such as subjective norms and having ample knowledge, that are common between early adopters of SAVs and PooledAVs, many examined motivations differ among SAV and Pooled AV adoption factors. In other words, motivations influencing intention to use on-demand AVs differ among the service types. Likewise, depending on the types of on-demand AVs, the sociodemographic characteristics of early adopters differ significantly. In general, findings paint a complex picture with respect to the application of constructs from common technology adoption models to the study of on-demand AVs. Findings from the final objective suggest that policymakers, planners, the vehicle and technology industries, and the public at large should moderate their expectations that on-demand AVs may suddenly transform the entire transportation sector. Instead, this study suggests that SAVs and Pooled AVs (when they entire the Canadian market) are likely to be adopted as supplementary mobility tools rather than substitutions for current travel modes

Keywords: automated vehicles, Canadian perception, theory of planned behavior, on-demand AVs

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Authors: Svetlana Strinyuk, Viacheslav Lanin

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Academic English has become lingua franca for international scientific community which stimulates universities to introduce English for Specific Purposes (EAP) courses into curriculum. Teaching L2 EAP students might be fulfilled with corpus technologies and digital stylistics. A special software developed to reach the manifold task of teaching, assessing and researching academic writing of L2 students on basis of digital stylistics and multidimensional analysis was created. A set of annotations (style markers) – grammar, lexical and syntactic features most significant of academic writing was built. Contrastive comparison of two corpora “model corpus”, subject domain limited papers published by competent writers in leading academic journals, and “students’ corpus”, subject domain limited papers written by last year students allows to receive data about the features of academic writing underused or overused by L2 EAP student. Both corpora are tagged with a special software created in GATE Developer. Style markers within the framework of research might be replaced depending on the relevance and validity of the result which is achieved from research corpora. Thus, selecting relevant (high frequency) style markers and excluding less relevant, i.e. less frequent annotations, high validity of the model is achieved. Software allows to compare the data received from processing model corpus to students’ corpus and get reports which can be used in teaching and assessment. The less deviation from the model corpus students demonstrates in their writing the higher is academic writing skill acquisition. The research showed that several style markers (hedging devices) were underused by L2 EAP students whereas lexical linking devices were used excessively. A special software implemented into teaching of EAP courses serves as a successful visual aid, makes assessment more valid; it is indicative of the degree of writing skill acquisition, and provides data for further research.

Keywords: corpus technologies in EAP teaching, multidimensional analysis, GATE Developer, corpus stylistics

Procedia PDF Downloads 188

Authors: Asraful Islam

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Extended dependency graph (EDG) is a state-of-the-art isomorphic graph to represent normal logic programs (NLPs) that can characterize the consistency of NLPs by graph analysis. To construct the vertices and arcs of an EDG, additional renaming atoms and rules besides those the given program provides are used, resulting in higher space complexity compared to the corresponding traditional dependency graph (TDG). In this article, we propose an extended labeled dependency graph (ELDG) to represent an NLP that shares an equal number of nodes and arcs with TDG and prove that it is isomorphic to the domain program. The number of nodes and arcs used in the underlying dependency graphs are formulated to compare the space complexity. Results show that ELDG uses less memory to store nodes, arcs, and cycles compared to EDG. To exhibit the desirability of ELDG, firstly, the stable models of the kernel form of NLP are characterized by the admissible coloring of ELDG; secondly, a relation of the stable models of a kernel program with the handles of the minimal, odd cycles appearing in the corresponding ELDG has been established; thirdly, to our best knowledge, for the first time an inverse transformation from a dependency graph to the representing NLP w.r.t. ELDG has been defined that enables transferring analytical results from the graph to the program straightforwardly.

Keywords: normal logic program, isomorphism of graph, extended labelled dependency graph, inverse graph transforma-tion, graph colouring

Procedia PDF Downloads 205