Search results for: cluster model approach

Authors: Ismail Cengiz, Faruk Elaldi

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Within the scope of the study presented in this paper, load carrying capacity and buckling behavior of a stiffened aluminum panel designed by adopting current ‘buckle-resistant’ design application and ‘Post –Buckling’ design approach were investigated experimentally and numerically. The test specimen that is stabilized by Z-type stiffeners and manufactured from aluminum 2024 T3 Clad material was test under compression load. Buckling behavior was observed by means of 3 – dimensional digital image correlation (DIC) and strain gauge pairs. The experimental study was followed by developing an efficient and reliable finite element model whose ability to predict behavior of the stiffened panel used for compression test is verified by compering experimental and numerical results in terms of load – shortening curve, strain-load curves and buckling mode shapes. While finite element model was being constructed, non-linear behaviors associated with material and geometry was considered. Finally, applicability of aluminum stiffened panel in airframe design against to composite structures was evaluated thorough the concept of ‘Structural Efficiency’. This study reveals that considerable amount of weight saving could be gained if the concept of ‘post-buckling design’ is preferred to the already conventionally used ‘buckle resistant design’ concept in aircraft industry without scarifying any of structural integrity under load spectrum.

Keywords: post-buckling, stiffened panel, non-linear finite element method, aluminum, structural efficiency

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Authors: Emmanuel Barrantes Chaves, Ernesto Rivera Alvarado

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This paper presents a method to enable agents for the Terraria game to evaluate algorithms commonly used in general video game artificial intelligence competitions. The usage of the ‘You Only Look Once’ model in the first layer of the process obtains information from the screen, translating this information into a video game description language known as “Video Game Description Language”; the agents take that as input to make decisions. For this, the state-of-the-art algorithms were tested and compared; Monte Carlo Tree Search and Rolling Horizon Evolutionary; in this case, Rolling Horizon Evolutionary shows a better performance. This approach’s main advantage is that a VGDL beforehand is unnecessary. It will be built on the fly and opens the road for using more games as a framework for AI.

Keywords: AI, MCTS, RHEA, Terraria, VGDL, YOLOv5

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Authors: Maninder Singh

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The Chandigarh city is under the strain of exponential growth of car density across various neighborhood. The consumerist nature of society today is to be blamed for this menace because everyone wants to own and ride a car. Car manufacturers are busy selling two or more cars per household. The Regional Transport Offices are busy issuing as many licenses to new vehicles as they can in order to generate revenue in the form of Road Tax. The car traffic in the neighborhoods of Chandigarh has reached a tipping point. There needs to be a more empirical and sustainable model of cars per household, which should be based on specific parameters of livable neighborhoods. Sector 22 in Chandigarh is one of the first residential sectors to be established in the city. There is scope to think, reflect, and work out a method to know how many cars we need to sell our citizens before we lose the argument to traffic problems, parking problems, and road rage. This is where the true challenge of a planner or a designer of the city lies. Currently, in Chandigarh city, there are no clear visible answers to this problem. The way forward is to look at spatial mapping, planning, and design of car parking units to address the problem, rather than suggesting extreme measures of banning cars (short-term) or promoting plans for citywide transport (very long-term). This is a chance to resolve the problem with a pragmatic approach from a citizen’s perspective, instead of an orthodox development planner’s methodology. Since citizens are at the center of how the problem is to be addressed, acceptable solutions are more likely to emerge from the car and traffic problem as defined by the citizens. Thus, the idea and its implementation would be interesting in comparison to the known academic methodologies. The novel and innovative process would lead to a more acceptable and sustainable approach to the issue of number of car parks in the neighborhood of Chandigarh city.

Keywords: cars, Chandigarh, neighborhood, sustainable living, walkability

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Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Chryssantus Kastowo, Theresia Anita Christiani, Anny Retnowati

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Copyright infringement as a form of infringement does not always mean causing harm to the creator. This can be proven with so many copyright violations in society and there is no significant law enforcement effort when compared with the violations that occurred. Copyright law as a form of appreciation from the state to the creator becomes counter productive if there is omission of violations. The problem raised in this article is how is the model of copyright regulation in accordance with the purpose of the law of copyright protection. This article is based on normative legal research focusing on secondary data. The analysis used is a conceptual approach. The analysis shows that the regulation of copyright emphasizes as a subjective right that is wholly within the author's power. This perspective will affect the claim of rights by the creator or allow violations. The creator is obliged to maintain the overall performance of copyright protection, especially in the event of a violation.

Keywords: copyright, enforcement, law, violation

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Authors: Jalal Eddine Benmansour, Khouane Boulanoir, Nacera Bekhadda, Elhassen Benfriha

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This paper introduces a novel composite control approach that addresses the challenge of stabilizing the three-axis attitude of a flexible satellite in the presence of vibrations caused by flexible appendages. The key contribution of this research lies in the development of a disturbance observer, which effectively observes and estimates the unwanted torques induced by the vibrations. By utilizing the estimated disturbance, the proposed approach enables efficient compensation for the detrimental effects of vibrations on the satellite system. To govern the attitude angles of the spacecraft, a proportional derivative controller (PD) is specifically designed and proposed. The PD controller ensures precise control over all attitude angles, facilitating stable and accurate spacecraft maneuvering. In order to demonstrate the global stability of the system, the Lyapunov method, a well-established technique in control theory, is employed. Through rigorous analysis, the Lyapunov method verifies the convergence of system dynamics, providing strong evidence of system stability. To evaluate the performance and efficacy of the proposed control algorithm, extensive simulations are conducted. The simulation results validate the effectiveness of the combined approach, showcasing significant improvements in the stabilization and control of the satellite's attitude, even in the presence of disruptive vibrations from flexible appendages. This novel composite control approach presented in this paper contributes to the advancement of satellite attitude control techniques, offering a promising solution for achieving enhanced stability and precision in challenging operational environments.

Keywords: attitude control, flexible satellite, vibration control, disturbance observer

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Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in the supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: supply chain management, balanced scorecard, value, structural modeling, stakeholders

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Authors: Rahmat Irawan, Mundhir Hanifsyam Harahap, Andar Ristabet Hesda

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As a public sector organization in Indonesia, Directorate General of State Asset Management (DGSAM) which is a unit under the Ministry of Finance of The Republic of Indonesia, has many constraints in managing its employees. While private organizations are able to conduct a human resource management as the best practice, DGSAM is limited by many regulations, especially about punishment and lay off policy for under-performance employees. Therefore, since 2015, DGSAM tries to implement a new and uncommon approach considering employees’ preference to encourage the motivation and performance of employees. DGSAM’s employees may propose the job places, and DGSAM considers them in deciding employees deployment. This study tries to determine the impact of preference-based approach toward employees’ satisfaction and organizational performance. This study uses quantitative approaches by regression analysis to measure the impact of deployment toward satisfaction of deployed employees and performance change of related units in DGSAM. The result of this study shows that preference-based approach significantly improves employees’ satisfaction and performance of related units as well. Based on the results of this study, it can be suggested that the approach is able to be implemented in the wider scope of the Ministry of Finance of The Republic of Indonesia and whole public sector organization in Indonesia. However, this study only focuses on short term measurement, so it is suggested to do further study to analyze the long-term impact.

Keywords: employee deployment, employee satisfaction, human resource management, organizational performance, preference-based approach

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Authors: Hasan A Al-Asadi, Ali Samir, Afrah Turki Awad, Ali Basem

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Integrating the phase change material (PCM) with photovoltaic (PV) panels is one of the effective techniques to minimize the PV panel temperature and increase their electric output. In order to investigate the impact of the PCM on the electric output of the PV panels for a whole year, a lumped-distributed parameter model for the PV-PCM module has been developed. This development has considered the impact of the PCM density variation between the solid phase and liquid phase. This contribution will increase the assessment accuracy of the electric output of the PV-PCM module. The second contribution is to assess the impact of the expanded composite graphite-PCM on the PV electric output in Milan for a whole year. The novel one-dimensional model has been solved using MATLAB software. The results of this model have been validated against literature experiment work. The weather and the solar radiation data have been collected. The impact of expanded graphite-PCM on the electric output of the PV panel for a whole year has been investigated. The results indicate this impact has an enhancement rate of 2.39% for the electric output of the PV panel in Milan for a whole year.

Keywords: PV panel efficiency, PCM, numerical model, solar energy

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Authors: Muhammad Saleem Ullah Khan Sumbal, Eric Tsui, Ricky Cheong, Eric See To

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Organizations are posed to a threat of valuable knowledge loss when employees leave either due to retirement, resignation, job change or because of disabilities e.g. death, etc. Due to changing economic conditions, globalization, and aging workforce, organizations are facing challenges regarding retention of valuable knowledge. On the one hand, large number of employees are going to retire in the organizations whereas on the other hand, younger generation does not want to work in a company for a long time and there is an increasing trend of frequent job change among the new generation. Because of these factors, organizations need to make sure that they capture the knowledge of employee before (s)he walks out of the door. The first step in this process is to know what type of knowledge employee possesses and whether this knowledge is important for the organization. Researchers reveal in the literature that despite the serious consequences of knowledge loss in terms of organizational productivity and competitive advantage, there has not been much work done in the area of knowledge loss assessment of departing employees. An important step in the knowledge retention process is to determine the critical ‘at risk’ knowledge. Thus, knowledge loss risk assessment is a process by which organizations can gauge the importance of knowledge of the departing employee. The purpose of this study is to explore this topic of knowledge loss risk assessment by conducting a qualitative study in oil and gas sector. By engaging in dialogues with managers and executives of the organizations through in-depth interviews and adopting a grounded methodology approach, the research will explore; i) Are there any measures adopted by organizations to assess the risk of knowledge loss from departing employees? ii) Which factors are crucial for knowledge loss assessment in the organizations? iii) How can we prioritize the employees for knowledge retention according to their criticality? Grounded theory approach is used when there is not much knowledge available in the area under research and thus new knowledge is generated about the topic through an in-depth exploration of the topic by using methods such as interviews and using a systematic approach to analyze the data. The outcome of the study will generate a model for the risk of knowledge loss through factors such as the likelihood of knowledge loss, the consequence/impact of knowledge loss and quality of the knowledge loss of departing employees. Initial results show that knowledge loss assessment is quite crucial for the organizations and it helps in determining what types of knowledge employees possess e.g. organizations knowledge, subject matter expertise or relationships knowledge. Based on that, it can be assessed which employee is more important for the organizations and how to prioritize the knowledge retention process for departing employees.

Keywords: knowledge loss, risk assessment, departing employees, Hong Kong organizations

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Authors: Xiaoyun Li, Suoang Longzhou

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This paper derives the analytical solution of stellar distance according to its redshift based on the photon-dominated universe expansion model. Firstly, it calculates stellar separation speed and the farthest distance of observable stars via simulation. Then the analytical solution of stellar distance according to its redshift is derived. It shows that when the redshift is large, the stellar distance (and its separation speed) is not proportional to its redshift due to the relativity effect. It also reveals the relationship between stellar age and its redshift. The correctness of the analytical solution is verified by the latest astronomic observations of Ia supernovas in 2020.

Keywords: redshift, cosmic expansion model, analytical solution, stellar distance

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Authors: Laleh Taheri, Noraini C. Pa, Rusli Abdullah, Salfarina Abdullah

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Knowledge plays an important role to the success of any organization. Software development organizations are highly knowledge-intensive organizations especially in their Requirement Elicitation Process (REP). There are several problems regarding communicating and using the knowledge in REP such as misunderstanding, being out of scope, conflicting information and changes of requirements. All of these problems occurred in transmitting the requirements knowledge during REP. Several researches have been done in REP in order to solve the problem towards requirements. Knowledge Audit (KA) approaches were proposed in order to solve managing knowledge in human resources, financial, and manufacturing. There is lack of study applying the KA in requirements elicitation process. Therefore, this paper proposes a KA model for REP in supporting to acquire good requirements.

Keywords: knowledge audit, requirement elicitation process, KA model, knowledge in requirement elicitation

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Authors: Stefanie Jeanette Huber

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This paper explores the relevance and implications of preferences for housing services on house price fluctuations through the lens of an overlapping generation’s model. The model implies that an economy whose agents have lower preferences for housing services is characterized with lower expenditure shares on housing services and will tend to experience more frequent and more volatile housing bubbles. These model predictions are tested empirically in the companion paper Housing Booms and Busts - Convergences and Divergences across OECD countries. Between 1970 - 2013, countries who spend less on housing services as a share of total income experienced significantly more housing cycles and the associated housing boom-bust cycles were more violent. Finally, the model is used to study the impact of rental subsidies and help-to-buy schemes on rational housing bubbles. Rental subsidies are found to contribute to the control of housing bubbles, whereas help-to- buy scheme makes the economy more bubble-prone.

Keywords: housing bubbles, housing booms and busts, preference for housing services, expenditure shares for housing services, rental and purchase subsidies

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Latifa Alenezi, Liz Croot, Janet Harris

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Chronic Low Back Pain (CLBP) is one of the most common and recurrent musculoskeletal problems that causes patients to access health care services frequently. The Bio-psychosocial Model emphasises that psychological, behavioural and social factors contribute to the development and persistence of CLBP. Cognitive behavioural therapy (CBT) is a psychological pain management strategy that can be used by physiotherapists treating chronic low back pain. However, evidence of the effectiveness of CBT for CLBP varies between different studies. The proposed study was preceded by a mixed methods systematic review that found that CBT has a beneficial effect for CLBP patients when compared to waiting list or other treatments; however, there is variation in effectiveness across different settings. Little is known about how CBT is applied by physiotherapists in physiotherapy settings. The interest of this study is directed towards generating an explanation and understanding of why, when, and how some physiotherapists make decisions and choose to apply CBT for CLBP patients, whereas others do not. Also, how and for what type of CLBP patients does CBT work, and for whom might CBT not work? Therefore, the study will take a qualitative approach to explore CLBP patients’, physiotherapists’ and managers’ perceptions of CBT and how it is used in physiotherapy to enable a deeper understanding and richer explanation of CBT effectiveness and help to inform research and practice. The study will use grounded theory approach to generate an explanatory theory of the clinical application of CBT for CLBP in physiotherapy settings. Physiotherapists, patients and managers of physiotherapy services will be interviewed. Grounded theory techniques will be used to analyse the data. The presentation will describe findings from the interviews and the emerging theory. This research will help to further inform RCTs about the effectiveness of CBT for CLBP in physiotherapy.

Keywords: CBT, CLBP, perception, physiotherapy, theory

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Authors: Soudabeh Shemehsavar

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In this paper, we consider the situation under a life test, in which the failure time of the test units are not related deterministically to an observable stochastic time varying covariate. In such a case, the joint distribution of failure time and a marker value would be useful for modeling the step stress life test. The problem of accelerating such an experiment is considered as the main aim of this paper. We present a step stress accelerated model based on a bivariate Wiener process with one component as the latent (unobservable) degradation process, which determines the failure times and the other as a marker process, the degradation values of which are recorded at times of failure. Parametric inference based on the proposed model is discussed and the optimization procedure for obtaining the optimal time for changing the stress level is presented. The optimization criterion is to minimize the approximate variance of the maximum likelihood estimator of a percentile of the products’ lifetime distribution.

Keywords: bivariate normal, Fisher information matrix, inverse Gaussian distribution, Wiener process

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Authors: Muhanad Al-Jubouri

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A local scour is the most important of the several scours impacting bridge performance and security. Even though scour is widespread in bridges, especially during flood seasons, the experimental tests could not be applied to many standard highway bridges. A computational fluid dynamics numerical model was used to solve the problem of calculating local scouring and deposition for non-cohesive silt and clear water conditions near single and double cylindrical piers with the effect of floating debris. When FLOW-3D software is employed with the Rang turbulence model, the Nilsson bed-load transfer equation and fine mesh size are considered. The numerical findings of single cylindrical piers correspond pretty well with the physical model's results. Furthermore, after parameter effectiveness investigates the range of outcomes based on predicted user inputs such as the bed-load equation, mesh cell size, and turbulence model, the final numerical predictions are compared to experimental data. When the findings are compared, the error rate for the deepest point of the scour is equivalent to 3.8% for the single pier example.

Keywords: local scouring, non-cohesive, clear water, computational fluid dynamics, turbulence model, bed-load equation, debris

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Authors: Pablo J. Valverde, Jaime E. Fernandez

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This paper shows under which conditions public corruption can emerge. The theoretical model includes variables such as the public employee wage (w), a control corruption parameter (c), and the group size of interactions (GS) between clusters of public officers and contractors. The system behavior is analyzed using phase diagrams based on combinations of such parameters (c, w, GS). Numerical simulations are implemented in order to contrast analytic results based on Nash equilibria of the theoretical model. Major findings include the functional relationship between wages and network topology, which attempts to reduce the emergence of corrupt behavior.

Keywords: public corruption, game theory, complex systems, Nash equilibrium.

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Authors: Ellen Patricia, Marilou Hyson

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Coaching has been showing great potential to strengthen the impact of brief group trainings and help early childhood teachers solve specific problems at work with the goal of raising the quality of early childhood services. However, there have been some doubts about the benefits that village teachers can receive from coaching. It is perceived that village teachers may struggle with the thinking skills needed to make coaching beneficial. Furthermore, there are reservations about whether principals and supervisors in villages are open to coaching’s facilitative approach, as opposed to the directive approach they have been using. As such, the use of coaching to develop the professionalism of early childhood teachers in the villages needs to be examined. The Coaching Pilot for early childhood teachers in Indonesia villages provides insights for the above issues. The Coaching Pilot is part of the ECED Frontline Pilot, which is a collaboration project between the Government of Indonesia and the World Bank with the support from the Australian Government (DFAT). The Pilot started with coordinated efforts with the local government in two districts to select principals and supervisors who have been equipped with basic knowledge about early childhood education to take part in 2-days coaching training. Afterwards, the participants were asked to collect 25 hours of coaching early childhood teachers who have participated in the Enhanced Basic Training for village teachers. The participants who completed this requirement were then invited to come for an assessment of their coaching skills. Following that, a qualitative evaluation was conducted using in-depth interviews and Focus Group Discussion techniques. The evaluation focuses on the impact of the coaching pilot in helping the village teachers to develop in their professionalism, as well as on the sustainability of the intervention. Results from the evaluation indicated that although their low education may limit their thinking skills, village teachers benefited from the coaching that they received. Moreover, the evaluation results also suggested that with enough training and support, principals and supervisors in the villages were able to provide an adequate coaching service for the teachers. On top of that, beyond this small start, interest is growing, both within the pilot districts and even beyond, due to word of mouth of the benefits that the Coaching Pilot has created. The districts where coaching was piloted have planned to continue the coaching program, since a number of early childhood teachers have requested to be coached, and a number of principals and supervisors have also requested to be trained as a coach. Furthermore, the Association for Early Childhood Educators in Indonesia has started to adopt coaching into their program. Although further research is needed, the Coaching Pilot suggests that coaching can positively impact early childhood teachers in villages, and village principals and supervisors can become a promising source of future coaches. As such, coaching has a significant potential to become a sustainable model for a continuous professional development program for early childhood teachers in villages.

Keywords: coaching, coaching pilot, early childhood teachers, principals and supervisors, village teachers

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Authors: Thomas Gerstner, Bastian von Harrach, Daniel Roth

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The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is the one-step survival idea of Glasserman and Staum. Although this technique yields to new terms per observation, while differentiating, the algorithm is still efficient. As an application, we use the results for a two-dimensional calibration of a Coco-Bond, which we model with different types of discretely monitored barrier options.

Keywords: Monte Carlo, discretely monitored barrier options, pathwise sensitivities, Coco-Bond

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Pooja Mishra, Chris Pollett

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This paper explores efficient ways to implement various media-updating features like news aggregation, video conversion, and bulk email handling. All of these jobs share the property that they are periodic in nature, and they all benefit from being handled in a distributed fashion. The data for these jobs also often comes from a social or collaborative source. We isolate the class of periodic, one round map reduce jobs as a useful setting to describe and handle media updating tasks. As such tasks are simpler than general map reduce jobs, programming them in a general map reduce platform could easily become tedious. This paper presents a MediaUpdater module of the Yioop Open Source Search Engine Web Portal designed to handle such jobs via an extension of a PHP class. We describe how to implement various media-updating tasks in our system as well as experiments carried out using these implementations on an Amazon Web Services cluster.

Keywords: distributed jobs framework, news aggregation, video conversion, email

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Authors: Duncan Oteki, Andebut Yeneneh, Daba Gedafa, Nabil Suleiman

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Most agencies lack the equipment required to measure the dynamic modulus (|E*|) of asphalt mixtures, necessitating the need to use predictive models. This study compared measured |E*| values for nine North Dakota asphalt mixes using the original Witczak, modified Witczak, and Hirsch models. The influence of temperature on the |E*| models was investigated, and Pavement ME simulations were conducted using measured |E*| and predictions from the most accurate |E*| model. The results revealed that the original Witczak model yielded the lowest Se/Sy and highest R² values, indicating the lowest bias and highest accuracy, while the poorest overall performance was exhibited by the Hirsch model. Using predicted |E*| as inputs in the Pavement ME generated conservative distress predictions compared to using measured |E*|. The original Witczak model was recommended for predicting |E*| for low-reliability pavements in North Dakota.

Keywords: asphalt mixture, binder, dynamic modulus, MEPDG, pavement ME, performance, prediction

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Authors: Itulelo Matiyabu Imaja, Manoj Maharaj, Patrick Ndayizigamiye

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Lack of transparency in public funds management is observed in many African countries. The DR Congo is among the most corrupted countries in Africa, and this is due mainly to lack of transparency and accountability in public funds management. Corruption has a negative effect on the welfare of the country’s citizens and the national economic growth. Public funds collection and allocation are the major areas whereby malpractices such as bribe, extortion, embezzlement, nepotism and other practices related to corruption are prevalent. Hence, there is a need to implement strong mechanisms to enforce transparency in public funds management. Many researchers have suggested some control mechanisms in curbing corruption in public funds management focusing mainly on law enforcement and administrative reforms with little or no insight on the role that ICT can play in preventing and curbing the corrupt behaviour. In the Democratic Republic of Congo (DRC), there are slight indications that the government of the DR Congo is integrating ICT to fight corruption in public funds collection and allocation. However, such government initiatives are at an infancy stage, with no tangible evidence on how ICT could be used effectively to address the issue of corruption in the context of the country. Hence, this research assesses the role that ICT can play for transparency in public funds management and suggest a framework for its adoption in the Democratic Republic of Congo. This research uses the revised Capability model (Capability, Empowerment, Sustainability model) as the guiding theoretical framework. The study uses the exploratory design methodology coupled with a qualitative approach to data collection and purposive sampling as sampling strategy.

Keywords: corruption, DR congo, ICT, management, public funds, transparency

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Authors: A. Ascenso, C. Silveira, B. Augusto, S. Rafael, S. Coelho, J. Ferreira, A. Monteiro, P. Roebeling, A. I. Miranda

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Innovative nature-based solutions (NBSs) can provide answers to the challenges that urban areas are currently facing due to urban densification and extreme weather conditions. The effects of NBSs are recognized and include improved quality of life, mental and physical health and improvement of air quality, among others. Part of the work developed in the scope of the UNaLab project, which aims to guide cities in developing and implementing their own co-creative NBSs, intends to assess the impacts of NBSs on air quality, using Eindhoven city as a case study. The state-of-the-art online air quality modelling system WRF-CHEM was applied to simulate meteorological and concentration fields over the study area with a spatial resolution of 1 km2 for the year 2015. The baseline simulation (without NBSs) was validated by comparing the model results with monitored data retrieved from the Eindhoven air quality database, showing an adequate model performance. In addition, land use changes were applied in a set of simulations to assess the effects of different types of NBSs. Finally, these simulations were compared with the baseline scenario and the impacts of the NBSs were assessed. Reductions on pollutant concentrations, namely for NOx and PM, were found after the application of the NBSs in the Eindhoven study area. The present work is particularly important to support public planners and decision makers in understanding the effects of their actions and planning more sustainable cities for the future.

Keywords: air quality, modelling approach, nature based solutions, urban area

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Authors: Vojtěch Svěrák

Abstract:

Climate change ethics have recently shifted away from individualistic paradigms towards concepts of shared or collective responsibility. Despite this evolving trend, a noticeable gap remains: a lack of research exclusively addressing the moral responsibility of specific unorganized social groups. The primary objective of the article is to fill this gap. The article employs the structuralist methodological approach proposed by some feminist philosophers, utilizing structural analysis to explain the existence of social groups. The argument is made for the integration of this framework with the so-called forward-looking Social Connection Model (SCM) of responsibility, which ascribes responsibilities to individuals based on their participation in social structures. The article offers an extension of this model to justify the responsibility of unorganized social groups. The major finding of the study is that although members of unorganized groups are loosely connected, collectively they instantiate specific external social structures, share social positioning, and the notion of responsibility could be based on that. Specifically, if the structure produces harm or perpetuates injustices, and the group both benefits from and possesses the capacity to significantly influence the structure, a greater degree of responsibility should be attributed to the group as a whole. This thesis is applied and justified within the context of climate change, based on the asymmetrical positioning of different social groups. Climate change creates a triple inequality: in contribution, vulnerability, and mitigation. The study posits that different degrees of group responsibility could be drawn from these inequalities. Two social groups serve as a case study for the article: first, the Pakistan lower class, consisting of people living below the national poverty line, with a low greenhouse gas emissions rate, severe climate change-related vulnerability due to the lack of adaptation measures, and with very limited options to participate in the mitigation of climate change. Second, the so-called polluter elite, defined by members' investments in polluting companies and high-carbon lifestyles, thus with an interest in the continuation of structures leading to climate change. The first identified group cannot be held responsible for climate change, but their group interest lies in structural change and should be collectively maintained. On the other hand, the responsibility of the second identified group is significant and can be fulfilled by a justified demand for some political changes. The proposed approach of group responsibility is suggested to help navigate climate justice discourse and environmental policies, thus helping with the sustainability transition.

Keywords: collective responsibility, climate justice, climate change ethics, group responsibility, social ontology, structural analysis

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Authors: Azizul Baten, Kamrul Hossain, Abdullah-Al-Zabir

Abstract:

The objective of this study is to develop an appropriate stochastic frontier secondary schools efficiency model by ICT Intervention and to examine the impact of ICT challenges on secondary schools efficiency in the Sylhet division in Bangladesh using stochastic frontier analysis. The Translog stochastic frontier model was found an appropriate than the Cobb-Douglas model in secondary schools efficiency by ICT Intervention. Based on the results of the Cobb-Douglas model, it is found that the coefficient of the number of teachers, the number of students, and teaching ability had a positive effect on increasing the level of efficiency. It indicated that these are related to technical efficiency. In the case of inefficiency effects for both Cobb-Douglas and Translog models, the coefficient of the ICT lab decreased secondary school inefficiency, but the online class in school was found to increase the level of inefficiency. The coefficients of teacher’s preference for ICT tools like multimedia projectors played a contributor role in decreasing the secondary school inefficiency in the Sylhet division of Bangladesh. The interaction effects of the number of teachers and the classrooms, and the number of students and the number of classrooms, the number of students and teaching ability, and the classrooms and teaching ability of the teachers were recorded with the positive values and these have a positive impact on increasing the secondary school efficiency. The overall mean efficiency of urban secondary schools was found at 84.66% for the Translog model, while it was 83.63% for the Cobb-Douglas model. The overall mean efficiency of rural secondary schools was found at 80.98% for the Translog model, while it was 81.24% for the Cobb-Douglas model. So, the urban secondary schools performed better than the rural secondary schools in the Sylhet division. It is observed from the results of the Tobit model that the teacher-student ratio had a positive influence on secondary school efficiency. The teaching experiences of those who have 1 to 5 years and 10 years above, MPO type school, conventional teaching method have had a negative and significant influence on secondary school efficiency. The estimated value of σ-square (0.0625) was different from Zero, indicating a good fit. The value of γ (0.9872) was recorded as positive and it can be interpreted as follows: 98.72 percent of random variation around in secondary school outcomes due to inefficiency.

Keywords: efficiency, secondary schools, ICT, stochastic frontier analysis

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Authors: Manik Sharma, Ganapathy Krishnamurthi

Abstract:

The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Jakub Kraus, Vladimír Plos, Peter Vittek

Abstract:

This article deals with a new approach to the airport emergency plans, which are the basic documents and manuals for dealing with events with impact on safety or security. The article describes the identified parts in which the current airport emergency plans do not fulfill their role and which should therefore be considered in the creation of corrective measures. All these issues have been identified at airports in the Czech Republic and confirmed at airports in neighboring countries.

Keywords: airport emergency plan, aviation safety, aviation security, comprehensive management system

Procedia PDF Downloads 491