Search results for: contractual complexity

Authors: Imme Petersen, Wiebke Sick, Regine Kollek

Abstract:

In systems medicine, high-throughput technologies produce large amounts of data on different biological and pathological processes, including (disturbed) gene expressions, metabolic pathways and signaling. The large volume of data of different types, stored in separate databases and often located at different geographical sites have posed new challenges regarding data handling and processing. Tools based on bioinformatics have been developed to resolve the upcoming problems of systematizing, standardizing and integrating the various data. However, the heterogeneity of data gathered at different levels of biological complexity is still a major challenge in data analysis. To build multilayer disease modules, large and heterogeneous data of disease-related information (e.g., genotype, phenotype, environmental factors) are correlated. Therefore, a great deal of attention in systems medicine has been put on data standardization, primarily to retrieve and combine large, heterogeneous datasets into standardized and incorporated forms and structures. However, this data-centred concept of standardization in systems medicine is contrary to the debate in science and technology studies (STS) on standardization that rather emphasizes the dynamics, contexts and negotiations of standard operating procedures. Based on empirical work on research consortia that explore the molecular profile of diseases to establish systems medical approaches in the clinic in Germany, we trace how standardized data are processed and shaped by bioinformatics tools, how scientists using such data in research perceive such standard operating procedures and which consequences for knowledge production (e.g. modeling) arise from it. Hence, different concepts and meanings of standardization are explored to get a deeper insight into standard operating procedures not only in systems medicine, but also beyond.

Keywords: data, science and technology studies (STS), standardization, systems medicine

Procedia PDF Downloads 340

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

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

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

Procedia PDF Downloads 63

Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

Procedia PDF Downloads 278

Authors: Thelma Mort

Abstract:

This empirical, qualitative research uses interviews of four intermediate phase English language student teachers at one university in South Africa and is an exploration of student teacher learning on their teaching practicum in their penultimate year of the initial teacher education course. The country’s post-apartheid language in education policy provides a context to this study in that children move from mother tongue language of instruction in foundation phase to English as a language of instruction in Intermediate phase. There is another layer of context informing this study which is the school context; the student teachers’ reflections are from their teaching practicum in resource constrained schools, which make up more than 75% of schools in South Africa. The findings were that in these schools, deep biases existed to local languages, that language was being used as a proxy for social class, and that conditions necessary for language acquisition were absent. The student teachers’ attitudes were in contrast to those found in the schools, namely that they had various pragmatic approaches to overcoming obstacles and that they saw language as enabling interdisciplinary work. This study describes language issues, tensions created by policy in South African schools and also supplies a regional account of learning to teach in resource constrained schools in Cape Town, where such language tensions are more inflated. The central findings in this research illuminate attitudes to language and language education in these teaching practicum schools and the complexity of learning to be a language teacher in these contexts. This study is one of the few local empirical studies regarding language teaching in the classroom and language teacher education; as such it offers some background to the country’s poor performance in both international and national literacy assessments.

Keywords: language teaching, narrative, post apartheid, South Africa, student teacher

Procedia PDF Downloads 146

Authors: Omogboyega Abe

Abstract:

This paper examines the relationships between socio-economic inequalities of power, race, wealth engendered by corporate structure, and domination in postcolonial Africa. The paper further considers how land as an epitome of property and power for the locals paved the way for capitalist accumulation and control in the hands of transnational corporations. European colonization of Africa was contingent on settler colonialism, where properties, including land, were re-modified as extractive resources for primitive accumulation. In developing Africa's extractive resources, transnational corporations (TNCs) usurped states' structures and domination over native land. The usurpation/corporate capture that exists to date has led to remonstrations and arguably a counter-productive approach to development projects. In some communities, the mention of extractive companies triggers resentment. The paradigm of state capture and state autonomy is simply inadequate to either describe or resolve the play of forces or actors responsible for severe corporate-induced human rights violations in emerging markets. Moreover, even if the deadly working conditions are conceived as some regulatory failure, it is tough to tell whose failure. The analysis in this paper is that the complexity and ambiguity evidenced by the multiple regimes and political and economic forces shaping production, consumption, and distribution of socio-economic variables are not exceptional in emerging markets. Instead, the varied experience in developing countries provides a window for seeing what we face in understanding and theorizing the structure and operation of the global economic and regulatory order in general.

Keywords: colonial, emerging markets, business, human rights, corporation

Procedia PDF Downloads 66

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 112

Authors: Paulson Young Ofenimu Okhawere

Abstract:

Research suggests that the main trait differentiating social entrepreneurs from traditional entrepreneurs is empathy. And although prior research has established the relevance of empathy in predicting social entrepreneurial intentions in different contexts, its usefulness at predicting social entrepreneurial intentions in emerging economy like Nigeria is yet to be well established. Whereas, it is well known that students in tertiary institutions in Nigeria (e.g. Universities, Polytechnics, and Colleges of Education) are given entrepreneurial orientations by being made to offer compulsory courses in entrepreneurship, research focusing on the effect of such students’ entrepreneurial orientation on entrepreneurial intentions is scant. To address this gap in the entrepreneurship literature, this study attempts to enhance our understanding by focusing on students selected from one University of Technology, one Polytechnic, and one College of Education in Niger State of Nigeria. The purpose of this study, therefore, is to examine the mechanism through which students’ institutional level entrepreneurial orientations affect their social entrepreneurial intentions and the role empathy plays in this relationship. Building on complexity theory (Satish & Streufert, 2003, 2001), this study proposes empathy as a proximal antecedent of social entrepreneurial intentions and that it is the mechanism through which the students’ entrepreneurial orientations affect their social entrepreneurial intentions. Data collected from 598 respondents were analyzed using multilevel structural equation modelling with Mplus version 7.3. The findings reveal that (i) although students’ entrepreneurial orientation directly relates to their social entrepreneurial intentions, this relationship differs according to the kind of institution; and (ii) students’ entrepreneurial orientations positively relates to social entrepreneurial intentions indirectly through empathy. Finally, the paper discusses the theoretical and practical implications of the findings, highlights the study’s strengths and limitations, and then maps out some directions for future research.

Keywords: institutional level, entrepreneurial orientation, empathy, social entrepreneurial intentions

Procedia PDF Downloads 151

Authors: Stela Doncheva

Abstract:

Postpartum distress, encompassing depressive symptoms, obsessions, and anxiety, remains a subject of significant scientific interest due to its prevalence among individuals giving birth. This critical and transformative period presents a multitude of factors that impact women's health. On the one hand, variables such as social support, satisfaction in romantic relationships, shared newborn care, and birth satisfaction directly affect the mental well-being of new mothers. On the other hand, the interplay of hormonal changes, personality characteristics, emotional difficulties, and the profound life adjustments experienced by mothers can profoundly influence their self-esteem and overall physical and emotional well-being. This paper extensively explores the factors of alexithymia, social support, partners' support, and birth satisfaction to gain deeper insights into their impact on postpartum distress. Utilizing a qualitative survey consisting of six self-reflective questionnaires, this study collects valuable data regarding the individual postpartum experiences of Bulgarian mothers. The primary objective is to enrich our understanding of the complex factors involved in the development of postpartum distress during this crucial period. The results shed light on the intricate nature of the problem and highlight the significant influence of bio-psycho-social elements. By contributing to the existing knowledge in the field, this research provides valuable implications for the development of interventions and support systems tailored to the unique needs of mothers in the postpartum period. Ultimately, this study aims to improve the overall well-being of new mothers and promote optimal maternal health during the postpartum journey.

Keywords: maternal mental health, postpartum distress, postpartum depression, postnatal mothers

Procedia PDF Downloads 62

Authors: William Feng, Qingyu Gao

Abstract:

Despite the extensive discussions about Hong Kong’s sentiments towards the Chinese Mainland since the sovereignty transfer in 1997, there has been no large-scale empirical analysis of the changing attitudes in the mainstream media, which both reflect and shape sentiments in the society. To address this gap, the present study uses an optimised semantic-based automatic sentiment analysis method to examine a corpus of news about China from 1997 to 2020 in three main Chinese-language newspapers in Hong Kong, namely Apple Daily, Ming Pao, and Oriental Daily News. The analysis shows that although the Hong Kong press had a positive emotional tone toward China in general, the overall trend of sentiment was becoming increasingly negative. Meanwhile, the alignment and antagonism toward China have both increased, providing empirical evidence of attitudinal polarisation in the Hong Kong society. Specifically, Apple Daily’s depictions of China have become increasingly negative, though with some positive turns before 2008, whilst Oriental Daily News has consistently expressed more favourable sentiments. Ming Pao maintained an impartial stance toward China through an increased but balanced representation of positive and negative sentiments, with its subjectivity and sentiment intensity growing to an industry-standard level. The results provide new insights into the complexity of sentiments towards China in the Hong Kong press and media attitudes in general in terms of the “us” and “them” positioning by explicating the cross-newspaper and cross-period variations using an enhanced sentiment analysis method which incorporates sentiment-oriented and semantic role analysis techniques.

Keywords: media attitude, sentiment analysis, Hong Kong press, one country two systems

Procedia PDF Downloads 116

Authors: Didier Auroux, Vladimir Groza

Abstract:

This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

Procedia PDF Downloads 315

Authors: Marina Benito-Parejo, Raul Perez-Lopez, Miguel Herraiz, Carolina Guardiola-Albert, Cesar Martinez

Abstract:

Persistency, long-term memory and randomness are intrinsic properties of time-series of earthquakes. The Rescaled Range Analysis (RS-Analysis) was introduced by Hurst in 1956 and modified by Mandelbrot and Wallis in 1964. This method represents a simple and elegant analysis which determines the range of variation of one natural property (the seismic energy released in this case) in a time interval. Despite the simplicity, there is complexity inherent in the property measured. The cumulative curve of the energy released in time is the well-known fractal geometry of a devil’s staircase. This geometry is used for determining the maximum and minimum value of the range, which is normalized by the standard deviation. The rescaled range obtained obeys a power-law with the time, and the exponent is the Hurst value. Depending on this value, time-series can be classified in long-term or short-term memory. Hence, an algorithm has been developed for compiling the RS-Analysis for time series of earthquakes by days. Completeness time distribution and locally stationarity of the time series are required. The interest of this analysis is their application for a complex seismic crisis where different earthquakes take place in clusters in a short period. Therefore, the Hurst exponent has been obtained for the seismic crisis of Alhoceima (Mediterranean Sea) of January-March, 2016, where at least five medium-sized earthquakes were triggered. According to the values obtained from the Hurst exponent for each cluster, a different mechanical origin can be detected, corroborated by the focal mechanisms calculated by the official institutions. Therefore, this type of analysis not only allows an approach to a greater understanding of a seismic series but also makes possible to discern different types of seismic origins.

Keywords: Alhoceima crisis, earthquake time series, Hurst exponent, rescaled range analysis

Procedia PDF Downloads 320

Authors: Andrea ČopíKová

Abstract:

Competency Based Management is a new approach to management, which solves organization’s challenges with complexity and with the aim to find and solve organization’s problems and learn how to avoid these in future. They teach the organizations to create, apart from the state of stability – that is temporary, vital organization, which is permanently able to utilize and profit from internal and external opportunities. The aim of this paper is to propose a process of competency model design, based on which a competency model for a financial department manager in a production company will be created. Competency models are very useful tool in many personnel processes in any organization. They are used for acquiring and selection of employees, designing training and development activities, employees’ evaluation, and they can be used as a guide for a career planning and as a tool for succession planning especially for managerial positions. When creating a competency model the method AHP (Analytic Hierarchy Process) and quantitative pair-wise comparison (Saaty’s method) will be used; these methods belong among the most used methods for the determination of weights, and it is used in the AHP procedure. The introduction part of the paper consists of the research results pertaining to the use of competency model in practice and then the issue of competency and competency models is explained. The application part describes in detail proposed methodology for the creation of competency models, based on which the competency model for the position of financial department manager in a foreign manufacturing company, will be created. In the conclusion of the paper, the final competency model will be shown for above mentioned position. The competency model divides selected competencies into three groups that are managerial, interpersonal and functional. The model describes in detail individual levels of competencies, their target value (required level) and the level of importance.

Keywords: analytic hierarchy process, competency, competency model, quantitative pairwise comparison

Procedia PDF Downloads 240

Authors: Javkhlan Nyamjav, Simona Fischer, Lauren Garner, Veronica McCracken

Abstract:

Current whole building life cycle assessments (LCA) primarily focus on structural and major architectural elements to measure building embodied carbon. Most of the interior finishes and fixtures are available on digital tools (such as Tally); however, furniture is still left unaccounted for. Due to its repeated refreshments and its complexity, furniture embodied carbon can accumulate over time, becoming comparable to structure and envelope numbers. This paper presents a method to calculate the Global Warming Potential (GWP) of furniture elements in commercial buildings. The calculator uses the quantity takeoff method with GWP averages gathered from environmental product declarations (EPD). The data was collected from EPD databases and furniture manufacturers from North America to Europe. A total of 48 GWP numbers were collected, with 16 GWP coming from alternative EPD. The finalized calculator shows the average GWP of typical commercial furniture and helps the decision-making process to reduce embodied carbon. The calculator was tested on MSR Design projects and showed furniture can account for more than half of the interior embodied carbon. The calculator highlights the importance of adding furniture to the overall conversation. However, the data collection process showed a) acquiring furniture EPD is not straightforward as other building materials; b) there are very limited furniture EPD, which can be explained from many perspectives, including the EPD price; c) the EPD themselves vary in terms of units, LCA scopes, and timeframes, which makes it hard to compare the products. Even though there are current limitations, the emerging focus on interior embodied carbon will create more demand for furniture EPD. It will allow manufacturers to represent all their efforts on reducing embodied carbon. In addition, the study concludes with recommendations on how designers can reduce furniture-embodied carbon through reuse and closed-loop systems.

Keywords: furniture, embodied carbon, calculator, tenant improvement, interior design

Procedia PDF Downloads 215

Authors: Vibhore Bakshi

Abstract:

This research paper is a step towards understanding the role of governance in the plan preparation process. It addresses the complexities of the peri-urban, historical constructions, politics and policies of sustainability, and legislative frameworks. The paper reflects on the Delhi NCT as one of the classical cases that have happened to witness different structural changes in the master plan around 1981, 2001, 2021, and Proposed Draft 2041. The Delhi Landsat imageries for 1989 and 2018 show an increase in the built-up areas around the periphery of NCT. The peri-urbanization has been a result of increasing in-migration to peri–urban areas of Delhi. The built-up extraction for years 1981, 1991, 2001, 2011, and 2018 highlights the growing peri-urbanization on scarce land therefore, it becomes equally important to research the history of the land and its legislative measures. It is interesting to understand the streaks of changes that have occurred in the land of Delhi in accordance with the different master plans and land legislative policies. The process of masterplan process in Delhi has experienced a lot of complexities in juxtaposition to other metropolitan regions of the world. The paper identifies the shortcomings in the current master planning process approach in regard to the stage of the planning process, traditional planning approach, and lagging ICT-based interventions. The metropolitan governance systems across the globe and India depict diversity in the organizational setup and varied dissemination of functions. It addresses the complexity of the peri-urban, historical constructions, politics and policies of sustainability, and legislative frameworks.

Keywords: governance, land provisions, built-up areas, in migration, built up extraction, master planning process, legislative policies, metropolitan governance systems

Procedia PDF Downloads 171

Authors: Aliyaa Zaidan, Rayan Bahabri

Abstract:

The twenty-first century revealed an accelerating change and intensifying complexity of communication technology. Online social networking engines have gained astounding recognition worldwide. The influence of those social media platforms on dentistry and dental students is not well established. Therefore, this study aimed to evaluate the impact of using social media on professional and profile level among dental students in Saudi Arabia. A cross-sectional study developed via online questionnaire concerning on social media usage and its effect on professional and profile level of dental students and dental interns from several universities in Saudi Arabia. A total of 296 dental students and dental interns in Saudi Arabia responded to the questionnaire. Ninety-eight percent of the participants usually use the social media on a regular basis. Most social media sites used among the participants were Snapchat, Instagram, and YouTube by 85%, 81%, 77% respectively. Forty-one percent of the participants agreed that using social media in the dental field is a necessity nowadays. Thirty-eight percent of participants agreed that using social media is an easy way to gain a reliable knowledge, while 43% agreed that social media will improve the quality of healthcare. Furthermore, 65% of the students deemed using social media for academic purposes will improve their performance. Fifty-five percent of the respondents often use social media tools to obtain information about subject or procedures related to the dental field. Regarding profile reputation of dental students, 40% of the respondents agreed that their profile information published on social networking websites, could be used by others to judge their level of professionalism. Male and female dental students both agreed that their reputation would be adversely affected by 37%,63%, respectively, if their social networking activity were viewed by members of the public. The discrepancy among student levels reveals that social media profile positively influence the acceptance to postgraduate programs (P= 0.01).

Keywords: dental students, professional, reputation, social media

Procedia PDF Downloads 210

Authors: Pius Marthin, Nihal Ata Tutkun

Abstract:

Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

Procedia PDF Downloads 88

Authors: Renata Kurpiewska-Korbut

Abstract:

Making an assumption that the use and sharing of data generated in humanitarian action constitute a core function of humanitarian organizations, the paper analyzes the position of the largest Polish humanitarian non-governmental organizations in the humanitarian data ecosystem in Ukraine and their approach to non-personal and personal data management since February of 2022. Both expert interviews and document analysis of non-profit organizations providing a direct response in the Ukrainian crisis context, i.e., the Polish Humanitarian Action, Caritas, Polish Medical Mission, Polish Red Cross, and the Polish Center for International Aid and the applicability of theoretical perspective of contingency theory – with its central point that the context or specific set of conditions determining the way of behavior and the choice of methods of action – help to examine the significance of data complexity and adaptive approach to data management by relief organizations in the humanitarian supply chain network. The purpose of this study is to determine how the existence of well-established and accurate internal procedures and good practices of using and sharing data (including safeguards for sensitive data) by the surveyed organizations with comparable human and technological capabilities are implemented and adjusted to Ukrainian humanitarian settings and data infrastructure. The study also poses a fundamental question of whether this crisis experience will have a determining effect on their future performance. The obtained finding indicate that Polish humanitarian organizations in Ukraine, which have their own unique code of conduct and effective managerial data practices determined by contingencies, have limited influence on improving the situational awareness of other assistance providers in the data ecosystem despite their attempts to undertake interagency work in the area of data sharing.

Keywords: humanitarian data ecosystem, humanitarian data management, polish NGOs, Ukraine

Procedia PDF Downloads 92

Authors: Soroosh Torabi, Brad Berron, Ren Xu, Christine Trinkle

Abstract:

Microfluidics integrated with 3D cell culture is a powerful technology to mimic cellular environment, and can be used to study cell activities such as proliferation, migration and response to drugs. This technology has gained more attention in cancer studies over the past years, and many organ-on-a-chip systems have been developed to study cancer cell behaviors in an ex-vivo tumor microenvironment. However, there are still some barriers to adoption which include low throughput, complexity in 3D cell culture integration and limitations on non-optical analysis of cells. In this study, a user-friendly microfluidic multi-well plate was developed to mimic the in vivo tumor microenvironment. The microfluidic platform feeds multiple 3D cell culture sites at the same time which enhances the throughput of the system. The platform uses hydrophobic Cassie-Baxter surfaces created by microchannels to enable convenient loading of hydrogel/cell suspensions into the device, while providing barrier free placement of the hydrogel and cells adjacent to the fluidic path. The microchannels support convective flow and diffusion of nutrients to the cells and a removable lid is used to enable further chemical and physiological analysis on the cells. Different breast cancer cell lines were cultured in the device and then monitored to characterize nutrient delivery to the cells as well as cell invasion and proliferation. In addition, the drug response of breast cancer cell lines cultured in the device was compared to the response in xenograft models to the same drugs to analyze relevance of this platform for use in future drug-response studies.

Keywords: microfluidics, multi-well 3d cell culture, tumor microenvironment, tumor-on-a-chip

Procedia PDF Downloads 262

Authors: Sajed A. Habib

Abstract:

Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: automation, industry 4.0, model-based design training, problem-based learning

Procedia PDF Downloads 132

Authors: Sara Fioretti

Abstract:

In the 2nd millennium BCE, maritime networks became essential to the Mediterranean lifestyle, creating an interconnected world. This phenomenon of interconnected cultures has often been misinterpreted as an “effect” of the Mycenaean “influence” without considering the complexity and role of regional and cross-cultural exchanges. This paper explores the socio-economic relationships, in both cross-cultural and potentially inter-regional settings, present within the archaeological repertoire of the southern Italian Late Bronze Age (LBA 1600 -1140 BCE). The emergence of economic relations within the connectivity of the regional settlements is explored through ceramic contexts found in the case studies Punta di Zambrone, Broglio di Trebisacce, and Nuraghe Antigori. This work-in-progress research is situated in the shifting theoretical views of the last ten years that discuss the Late Bronze Age’s connectivity through Social Networks, Entanglement, and Assertive Objects combined with a comparative statistical study of ceramic frequency distribution. Applying these theoretical frameworks with a quantitative approach demonstrates the specific regional economic relationships that shaped the cultural interactions of the Late Bronze Age. Through this intersection of theory and statistical analysis, the case studies establish a small percentage of pottery as imported, whilst assertive productions have a relatively higher quantity. Overall, the majority still adheres to regional Italian traditions. Therefore, we can dissect the rhizomatic relationships cultivated by the Italian coasts and Mycenaeans and their roles within their networks through the intersection of theoretical and statistical analysis. This research offers a new perspective on the connectivity of the Late Bronze Age relational structures.

Keywords: late bronze age, mediterranean archaeology, exchanges and trade, frequency distribution of ceramic assemblages

Procedia PDF Downloads 39

Authors: Lusia Ndahafa Nghitotelwa

Abstract:

India is a home to many languages, cultures, traditions, castes and religions. This diversity, when observed in education, appears to be challenging and difficult to manage with respect to including everyone in the educational system. But in order to achieve this, attempts to understand the complexity of the issue and find some solutions for including everyone in education has been made in India since independence, regardless of the students’ background. Despite that, the challenge is still topical. Plenty of students are left out of the system due to the lack of awareness and appropriate management of these diversities. Therefore, the present paper makes an attempt to study the awareness and management of diversity in Indian schools. Existing studies on diversity in Indian schools, along with how measures and which measures have been taken to accommodate and retain everyone in school, have been looked at, and a thorough critical analysis of findings has been narrated. It was found that a lot of efforts have been conjugated to include and educate children of all castes, religions, and linguistic backgrounds. Furthermore, the awareness of inclusive education among teachers and society members is moderate, but teachers lack the necessary skills and knowledge on how to deal with students with special educational needs in regular classes. Also, the management is aware of inclusive education, but the management does not include teachers in decision-making. Moreover, it was found that the poor management of inclusion services and retention of special needs students in Indian schools results in their poor effective integration into the workforce. Finally, the management was found to have stringent admission criteria, which has the effect of hindering some students from entering the educational system. Based on the results of the study, it is clear that the implementation of inclusive education is still a challenge in India. However, there are promising results in tackling the issue. All children should be given an opportunity to learn together with other children in order to broaden their interest and challenge their potential.

Keywords: awareness, management, inclusive education, students

Procedia PDF Downloads 229

Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

Abstract:

Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

Procedia PDF Downloads 123

Authors: Mohamed H. Kosba, Heba A. Ibrahim, H. Rozita

Abstract:

Statement of the Problem: The life expectancy for transfusion-dependent thalassemia patients has increased dramatically with iron-chelation therapy and other modern management modalities. In these patients, the most dominant maxillofacial manifestations are protrusion of zygomatic bones and premaxilla due to the hyperplasia of bone marrow. The purpose of this study is to determine the prevalence of malocclusion and orthodontic treatment needs according to the Dental Aesthetic Index (DAI) among Malay transfusion-dependent thalassemia patients. Orientation: This is a cross-sectional study consist of 43 Malay transfusion-dependent thalassemia patients, 22 males, and 19 females with the mean age of 15.9 years old (SD 3.58). The subjects were selected randomly from patients attending Paediatrics and Internal Medicine Clinic at Hospital USM and Hospital Sultana Bahiyah. The subjects were assessed for malocclusion according to Angle’s classification, and orthodontic treatment needs using DAI. The results show that 22 of the subjects (51.1%) have class II malocclusion, 12 subjects (28%) have class І, while 9 subjects (20.9%) have class Ⅲ. The assessment of orthodontic treatment needs to reveal 22 cases (51.1%) fall in the normal/minor needs category, 12 subjects (28%) fall in the severe and very severe category, while 9 subjects (20.9%) fall in the definite category. Conclusion & Significance: Half of Malay transfusion-dependent thalassemia patients have Class Ⅱmalocclusion. About 28% had malocclusion and required orthodontic treatment. This research shows that Malay transfusion-dependent thalassemia may require orthodontic management; earlier intervention to reduce the complexity of the treatment later, suggesting functional appliance as a suitable treatment option for them, a twin block appliance together with headgear to restrict maxillary growth suggested for management. The current protocol implemented by the Malaysian Ministry of Health for the management of these patients seems to be sufficient since the result shows that about 28% require orthodontic treatment need, according to DAI.

Keywords: prevalence, DAI, thalassaemia, angle classification

Procedia PDF Downloads 142

Authors: Renato Roda

Abstract:

With the emergence of the so-called 'Knowledge Society', the implementation of policies to attract, grow and retain talents, in an academic context as well, has become critical –both in the perspective of didactics and research and as far as administration and institutional management are concerned. At the same time, the contemporary philanthropic entities/organizations, which are evolving from traditional types of social support towards new styles of aid, envisaged to go beyond mere monetary donations, face the challenge of brand-new forms of complexity in supporting such specific dynamics of the global human capital market. In this sense, it becomes unavoidable for the philanthropic foundation, while carrying out their daily charitable tasks, to resort to innovative ways to facilitate the acquisition and the promotion of talents by academic and research institutions. In order to deepen such a specific perspective, this paper features the case of Turin, former 'factory city' of Italy’s North West, headquarters -and main reference territory- of Italy’s largest and richest private formerly bank-based philanthropic foundation, the Fondazione Compagnia di San Paolo. While it was assessed and classified as 'medium' in the city Global Talent Competitiveness Index (GTCI) of 2020, Turin has nevertheless acquired over the past months status of impact laboratory for a whole series of innovation strategies in the competition for the acquisition of excellence human capital. Leading actors of this new city vision are the foundations with their specifically adjusted financial engagement and a consistent role of stimulus towards innovation for research and education institutions.

Keywords: human capital, post-Fordism, private foundation, war on talents

Procedia PDF Downloads 170

Authors: Leora Branfield Day, Stephanie Saunders, Leah Steinberg, Shiphra Ginsburg, Christine Soong

Abstract:

Introduction: Discordance between patients expressed and documented preferences at the end of life is common. Although junior trainees frequently lead goals of care (GOC) conversations, lack of training can result in poor communication. Based on a needs assessment, we developed an interactive electronic learning module (eModule) for conducting patient-centred GOC discussions. The purpose of this study was to evaluate the impact of the eModule on residents’ attitudes towards GOC conversations. Methods: First-year internal medicine residents (n=11) from the University of Toronto selected using purposive sampling underwent semi-structured interviews before and after completing a GOC eModule. Interviews were anonymized, transcribed and open-coded using NVivo. Using a constructivist grounded theory approach, we developed a framework to understand the attitudes of residents to GOC conversations before and after viewing the module. Results: Before the module, participants described limited training and negative emotions towards GOC conversations. Many focused on code status and procedure choices (e.g., ventilation) instead of eliciting patient-centered values. Pressure to “get the DNR" led to conflicting feelings and distress. After the module, participants’ approached conversations with a greater focus on patient values and process. They felt more prepared and comfortable, recognizing the complexity of conversations and the importance of patient-centeredness. Conclusions: A novel GOC eModule allowed residents to develop a patient-centered and standardized approach to GOC conversations while improving confidence and preparedness. This resource could be an effective strategy toward attaining a critical communication competency among learners with the potential to enhance accurate GOC documentation.

Keywords: goals of care conversations, communication skills, emodule, medical education

Procedia PDF Downloads 135

Authors: Jungbin Lim, Bohee Kang, Heelim Lee, Sunjin Kim, GeumHee Choi, Jae-Suk Jung, Suk Ji

Abstract:

Nonsurgical periodontal therapies have, for several decades, been the basis of periodontal treatment concepts. The aim of this paper is to investigate the effectiveness of non-surgical periodontal therapy according to the severity of periodontitis disease. Methods: Retrospective data of patients who visited Department of periodontics in Ajou University Medical Center from 2016 to 2022 were collected. Among the patients, those who took full mouth examination of clinical parameters and non-surgical periodontal therapy were chosen for this study. Selected patients were divided into initial, moderate, and severe periodontitis based on severity and complexity of management (2018 World Workshop EFP/AAP consensus). Recall visits with clinical periodontal examination were scheduled for 1,2,3 months or 1,3,6 months after the treatment. The results were evaluated by recordings of mean probing pocket depth (mean PD), mean clinical attachment levels (mean CAL), bleeding on probing (BOP%), mean gingival index (mean GI), mean regression, mean sulcus bleeding index (mean SBI), mean plaque scores (mean PI). All statistical analyses were performed with R software, version 4.3.0. A level of significance, P<0.05, was considered to be statistically significant. Results: A total of 92 patients were included in this study. 15 patients were diagnosed as initial periodontitis, 14 moderate periodontitis, and 63 severe periodontitis. The all parameters except for mean recession decreased over time in all groups. The amount of mean PD decreased were the greatest in severe periodontitis group followed by moderate and initial, which was found to be statistically significant. The changes of mean PD were 0.15±0.05 mm, 0.37±0.06 mm, and 1.01±0.07 mm (initial, moderate, and severe, respectively, P<0.001). When comparing before and after treatment, the reductions in BOP(%), mean GI, mean SBI, and mean PI were statistically significant. Conclusion: All patients who received non-surgical periodontal therapy showed periodontal healing in terms of improvements in clinical parameters, and it was greater in the severe group.

Keywords: periodontology, clinical periodontology, oral treatment, comprehensive preventive dentistry, non-surgical periodontal therapy

Procedia PDF Downloads 75

Authors: Zhibo Zhao, Horst Hahn, Robert Kruk, Abhisheck Sarkar

Abstract:

High entropy oxides (HEOs), based on the incorporation of multiple-principal cations into the crystal lattice, offer the possibility to explore previously inaccessible oxide compositions and unconventional properties. Here it is demonstrated that despite the chemical complexity of HEOs external stimuli, such as epitaxial strain, can selectively stabilize certain magneto-electronic states. Epitaxial (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄-HEO thin films are grown in three different strain states: tensile, compressive, and relaxed. A unique coexistence of rocksalt and spinel-HEO phases, which are fully coherent with no detectable chemical segregation, is revealed by transmission electron microscopy. This dual-phase coexistence appears as a universal phenomenon in (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄ epitaxial films. Prominent changes in the magnetic anisotropy and domain structure highlight the strain-induced bidirectional control of magnetic properties in HEOs. When the films are relaxed, their magnetization behavior is isotropic, similar to that of bulk materials. However, under tensile strain, the hardness of the out-of-plane (OOP) axis increases significantly. On the other hand, compressive straining results in an easy OOP magnetization and a maze-like magnetic domain structure, indicating perpendicular magnetic anisotropy. Generally, this study emphasizes the adaptability of the high entropy design strategy, which, when combined with coherent strain engineering, opens additional prospects for fine-tuning properties in oxides.

Keywords: high entropy oxides, thin film, strain tuning, perpendicular magnetic anistropy

Procedia PDF Downloads 45

Authors: Siddharatha Sharma

Abstract:

With the advent of technology and machines, the role of biometrics in society is taking an important place for secured living. Security issues are the major concern in today’s world and continue to grow in intensity and complexity. Biometrics based recognition, which involves precise measurement of the characteristics of living beings, is not a new method. Fingerprints are being used for several years by law enforcement and forensic agencies to identify the culprits and apprehend them. Biometrics is based on four basic principles i.e. (i) uniqueness, (ii) accuracy, (iii) permanency and (iv) peculiarity. In today’s world fingerprints are the most popular and unique biometrics method claiming a social benefit in the government sponsored programs. A remarkable example of the same is UIDAI (Unique Identification Authority of India) in India. In case of fingerprint biometrics the matching accuracy is very high. It has been observed empirically that even the identical twins also do not have similar prints. With the passage of time there has been an immense progress in the techniques of sensing computational speed, operating environment and the storage capabilities and it has become more user convenient. Only a small fraction of the population may be unsuitable for automatic identification because of genetic factors, aging, environmental or occupational reasons for example workers who have cuts and bruises on their hands which keep fingerprints changing. Fingerprints are limited to human beings only because of the presence of volar skin with corrugated ridges which are unique to this species. Fingerprint biometrics has proved to be a high level authentication system for identification of the human beings. Though it has limitations, for example it may be inefficient and ineffective if ridges of finger(s) or palm are moist authentication becomes difficult. This paper would focus on uniqueness of fingerprints to the human beings in comparison to other living beings and review the advancement in emerging technologies and their limitations.

Keywords: fingerprinting, biometrics, human beings, authentication

Procedia PDF Downloads 324

Authors: Sara Fioretti

Abstract:

During the Middle Bronze Age, southern Italy underwent a reorganisation of social structures where local cultures, such as the sub-Apennine and Nuragic, flourished and participated in maritime trade. This paper explores the socio-economic relationships, in both cross-cultural and potentially inter-regional settings, present within the archaeological repertoire of the southern Italian Late Bronze Age (LBA 1600 -1050 BCE). The emergence of economic relations within the connectivity of the regional settlements is explored through ceramic contexts found in the case studies Punta di Zambrone, Broglio di Trebisacce, and Nuraghe Antigori. This paper discusses the findings of a statistical and theoretical approach from an ongoing study in relation to the Mediterranean’s characterisation as a period dominated by Mycenaean influence. This study engages with a theoretical bricolage of Social Networks Entanglement, and Assertive Objects Theory to address the selective and assertive dynamics evident in the cross-cultural trade exchanges as well as consider inter-regional dynamics. Through this intersection of theory and statistical analysis, the case studies establish a small percentage of pottery as imported, whilst assertive productions have a relatively higher quantity. Overall, the majority still adheres to regional Italian traditions. Therefore, we can dissect the rhizomatic relationships cultivated by the Italian coasts and Mycenaeans and their roles within their networks through the intersection of theoretical and statistical analysis. This research offers a new perspective on the complex nature of the Late Bronze Age relational structures.

Keywords: late bronze age, mediterranean archaeology, exchanges and trade, frequency distribution of ceramic assemblages, social network theory, rhizomatic exchanges

Procedia PDF Downloads 46

Authors: Karolis Leonavičius, Dalius Kučiauskas, Dangiras Lukošius, Arnoldas Jasiūnas, Kostas Zdanys, Rokas Stanislovas, Emilis Gegevičius, Žana Kapustina, Juozas Nainys

Abstract:

Screening throughput is a common bottleneck in many research areas, including functional genomics, drug discovery, and directed evolution. High-throughput screening techniques can be classified into two main categories: (i) affinity-based screening and (ii) functional screening. The first one relies on binding assays that provide information about the affinity of a test molecule for a target binding site. Binding assays are relatively easy to establish; however, they reveal no functional activity. In contrast, functional assays show an effect triggered by the interaction of a ligand at a target binding site. Functional assays might be based on a broad range of readouts, such as cell proliferation, reporter gene expression, downstream signaling, and other effects that are a consequence of ligand binding. Screening of large cell or gene libraries based on direct activity rather than binding affinity is now a preferred strategy in many areas of research as functional assays more closely resemble the context where entities of interest are anticipated to act. Droplet sorting is the basis of high-throughput functional biological screening, yet its applicability is limited due to the technical complexity of integrating high-performance droplet analysis and manipulation systems. As a solution, the Droplet Genomics Styx platform enables custom droplet sorting workflows, which are necessary for the development of early-stage or complex biological therapeutics or industrially important biocatalysts. The poster will focus on the technical design considerations of Styx in the context of its application spectra.

Keywords: functional screening, droplet microfluidics, droplet sorting, dielectrophoresis

Procedia PDF Downloads 133