Search results for: adsorption isotherm models

Authors: Maria Inês Pinho

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Recent literature on issues of Cultural Management (also called Strategic Management for cultural organizations) systematically seeks for models that allow such equipment to adapt to the constant change that occurs in contemporary societies. In the last decade, the world, and in particular Europe has experienced a serious financial problem that has triggered defensive mechanisms, both in the direction of promoting the balance of public accounts and in the sense of the anonymous loss of the democratic and cultural values of each nation. If in the first case emerged the Troika that led to strong cuts in funding for Culture, deeply affecting those organizations; in the second case, the commonplace citizen is seen fighting for the non-closure of cultural equipment. Despite this, the cultural manager argues that there is no single formula capable of solving the need to adapt to change. In another way, it is up to this agent to know the existing scientific models and to adapt them in the best way to the reality of the institution he coordinates. These actions, as a rule, are concerned with the best performance vis-à-vis external audiences or with the financial sustainability of cultural organizations. They forget, therefore, that all this mechanics cannot function without its internal public, without its Human Resources. The employees of the cultural organization must then have an entrepreneurial posture - must be intrapreneurial. This paper intends to break this form of action and lead the cultural manager to understand that his role should be in the sense of creating value for society, through a good organizational performance. This is only possible with a posture of strategic entrepreneurship. In other words, with a link between: Cultural Management, Cultural Entrepreneurship and Cultural Intrapreneurship. In order to prove this assumption, the case study methodology was used with the symbol of the European Capital of Culture (Casa da Música) as well as qualitative and quantitative techniques. The qualitative techniques included the procedure of in-depth interviews to managers, founders and patrons and focus groups to public with and without experience in managing cultural facilities. The quantitative techniques involved the application of a questionnaire to middle management and employees of Casa da Música. After the triangulation of the data, it was proved that contemporary management of cultural organizations must implement among its practices, the concept of Strategic Entrepreneurship and its variables. Also, the topics which characterize the Cultural Intrapreneurship notion (job satisfaction, the quality in organizational performance, the leadership and the employee engagement and autonomy) emerged. The findings show then that to be sustainable, a cultural organization should meet the concerns of both external and internal forum. In other words, it should have an attitude of citizenship to the communities, visible on a social responsibility and a participatory management, only possible with the implementation of the concept of Strategic Entrepreneurship and its variable of Cultural Intrapreneurship.

Keywords: cultural entrepreneurship, cultural intrapreneurship, cultural organizations, strategic management

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Authors: B. Y. Danjuma, A. Archibong-Eso, Aliyu M. Aliyu, H. Yeung

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In this experimental investigation, a new data for slugging frequency for high viscosity oil-gas flow are reported. Scale experiments were carried out using a mixture of air and mineral oil as the liquid phase in a 17 m long horizontal pipe with 0.0762 ID. The data set was acquired using two high-speed Gamma Densitometers at a data acquisition frequency of 250 Hz over a time interval of 30 seconds. For the range of flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence the slug frequency. A comparison of the present data with prediction models available in the literature revealed huge discrepancies. A new correlation incorporating the effect of viscosity on slug frequency has been proposed for the horizontal flow, which represents the main contribution of this work.

Keywords: gamma densitometer, flow pattern, pressure gradient, slug frequency

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Authors: Robert Pellerin, Michel Gamache, Remi Trudeau, Nathalie Perrier

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The context of large engineering projects is particularly favorable to the appearance of engineering changes and contractual modifications. These elements are potential causes for claims. In this paper, we investigate one of the critical components of the claim management process: the calculation of the impacts of changes in terms of losses of productivity due to the need to accelerate some project activities. When project changes are initiated, delays can arise. Indeed, project activities are often executed in fast-tracking in an attempt to respect the completion date. But the acceleration of project execution and the resulting rework can entail important costs as well as induce productivity losses. In the past, numerous methods have been proposed to quantify the duration of delays, the gains achieved by project acceleration, and the loss of productivity. The calculation related to those changes can be divided into two categories: direct cost and indirect cost. The direct cost is easily quantifiable as opposed to indirect costs which are rarely taken into account during the calculation of the cost of an engineering change or contract modification despite several research projects have been made on this subject. However, proposed models have not been accepted by companies yet, nor they have been accepted in court. Those models require extensive data and are often seen as too specific to be used for all projects. These techniques are also ignoring the resource constraints and the interdependencies between the causes of delays and the delays themselves. To resolve this issue, this research proposes a simulation model that mimics how major engineering changes or contract modifications are handled in large construction projects. The model replicates the use of overtime in a reactive scheduling mode in order to simulate the loss of productivity present when a project change occurs. Multiple tests were conducted to compare the results of the proposed simulation model with statistical analysis conducted by other researchers. Different scenarios were also conducted in order to determine the impact the number of activities, the time of occurrence of the change, the availability of resources, and the type of project changes on productivity loss. Our results demonstrate that the number of activities in the project is a critical variable influencing the productivity of a project. When changes occur, the presence of a large number of activities leads to a much lower productivity loss than a small number of activities. The speed of reducing productivity for 30-job projects is about 25 percent faster than the reduction speed for 120-job projects. The moment of occurrence of a change also shows a significant impact on productivity. Indeed, the sooner the change occurs, the lower the productivity of the labor force. The availability of resources also impacts the productivity of a project when a change is implemented. There is a higher loss of productivity when the amount of resources is restricted.

Keywords: engineering changes, indirect costs overtime, productivity, scheduling, simulation

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Authors: F. Pagliara, F. Mauriello

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The objective of this paper is to investigate the relationship between the increase of accessibility brought by high speed rail (HSR) systems and the tourism market in Italy. The impacts of HSR projects on tourism can be quantified in different ways. In this manuscript, an empirical analysis has been carried out with the aid of a dataset containing information both on tourism and transport for 99 Italian provinces during the 2006-2016 period. Panel data regression models have been considered, since they allow modelling a wide variety of correlation patterns. Results show that HSR has an impact on the choice of a given destination for Italian tourists while the presence of a second level hub mainly affects foreign tourists. Attraction variables are also significant for both categories and the variables concerning security, such as number of crimes registered in a given destination, have a negative impact on the choice of a destination.

Keywords: tourists, overnights, high speed rail, attractions, security

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

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Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

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Authors: M-M. Mohamed Ahmed, Nacer K. M’Sirdi, Aziz Naamane

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In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.

Keywords: autonomous vehicles, convoy, non-linear control, non-linear observer, sliding mode

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: Wei-Zhao, Yannian-Bao, Xing-Fan, Lei-Cao

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An isostatic pressing working cylinder automatic exhaust valve is designed. The finite element models of valve core and valve body under ultra-high pressure work environment are built to study the influence of interact of valve core and valve body to sealing performance. The contact stresses of metal sealing surface with different sizes are calculated and the automatic exhaust valve is optimized. The result of simulation and experiment shows that the sealing of optimized exhaust valve is more reliable and the service life is greatly improved. The optimized exhaust valve has been used in the warm isostatic pressing equipment.

Keywords: exhaust valve, sealing, ultra-high pressure, isostatic pressing

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Authors: Teboho J. Mosikari, Johannes T. Tsoku, Diteboho L. Xaba

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The increase of capital mobility across emerging economies has become an interesting topic for many economic policy makers. The current study tests the validity of Feldstein–Horioka puzzle for 5 BRICS countries. The sample period of the study runs from 2001 to 2014. The study uses the following parameter estimates well known as the Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS). The results of the study show that investment and savings are cointegrated in the long run. The parameters estimated using FMOLS and DOLS are 0.85 and 0.74, respectively. These results imply that policy makers within BRICS countries have to consider flexible monetary and fiscal policy instruments to influence the mobility of capital with the bloc.

Keywords: Feldstein and Horioka puzzle, saving and investment, panel models, BRICS countries

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Authors: Burak Yildirim, Muhsin Tunay Gencoglu

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This publication shows the effects of Microgrid (MG) integration on the power systems oscillating stability. Generated MG model power systems were applied to the IEEE 14 bus test system which is widely used in stability studies. Stability studies were carried out with the help of eigenvalue analysis over linearized system models. In addition, Hopf bifurcation point detection was performed to show the effect of MGs on the system loadability margin. In the study results, it is seen that MGs affect system stability positively by increasing system loadability margin and has a damper effect on the critical modes of the system and the electromechanical local modes, but they make the damping amount of the electromechanical interarea modes reduce.

Keywords: Eigenvalue analysis, microgrid, Hopf bifurcation, oscillatory stability

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Authors: Reza Bazargan lari, Mohammad H. Fattahi

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Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for pre-processing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based pre-processing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: Mesias Alfeus, Kirsty Fitzhenry, Alessia Lederer

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The present paper provides empirical studies to estimate defaultable bonds in the South African financial market. The main goal is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. Multi-dimensional Cox-Ingersoll-Ross (CIR)-type factor models are considered. Results show that default risk increased sharply in the South African financial market during COVID-19 and the CIR model with jumps exhibits a better performance.

Keywords: default intensity, unobservable state variables, CIR, α-CIR, extended kalman filtering

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Authors: S. Al Dandachli, F. Perales, Y. Monerie, F. Jamin, M. S. El Youssoufi, C. Pelissou

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The goal of this research is to study the fracture process and mechanical behavior of concrete under I–II mixed-mode stress, which is essential for ensuring the safety of concrete structures. For this purpose, two-dimensional simulations of three-point bending tests under variable load and geometry on notched cement paste samples of composite samples (cement paste/siliceous aggregate) are modeled by employing Cohesive Zone Models (CZMs). As a result of experimental validation of these tests, the CZM model demonstrates its capacity to predict fracture propagation at the local scale.

Keywords: cement paste, interface, cohesive zone model, fracture, three-point flexural test bending

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Authors: Mihika Shivkumar, Krishna Kumar, C. Perisamy

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3D printing is a method of manufacturing wherein materials, such as plastic or metal, are deposited in layers one on top of the other to produce a three dimensional object. 3D printing is most commonly associated with creating engineering prototypes. However, its applications in the field of human health care have been frequently disregarded. Medical applications for 3D printing are expanding rapidly and are envisaged to revolutionize health care. Medical applications for 3D printing, both present and its potential, can be categorized broadly, including: creation of customized prosthetics tissue and organ fabrication; creation of implants, and anatomical models and pharmaceutical research regarding drug dosage forms. This piece breaks down bioprinting in the healthcare sector. It focuses on the better subtle elements of every particular point, including how 3D printing functions in the present, its impediments, and future applications in the health care sector.

Keywords: bio-printing, prototype, drug delivery, organ regeneration

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of predictive models has facilitated the estimation process in recent years. In this research, 176 crude palm oil (CPO) samples acquired from Felda Johor Bulker Sdn Bhd were studied. A FOSS NIRSystem was used to tak e absorbance measurements from the sample. The wavelength range for the spectral measurement is taken at 1600nm to 1900nm. Partial Least Square Regression (PLSR) prediction model with 50 optimal number of principal components was implemented to study the relationship between the measured Free Fatty Acid (FFA) values and the measured spectral absorption. PLSR showed predictive ability of FFA values with correlative coefficient (R) of 0.9808 for the training set and 0.9684 for the testing set.

Keywords: palm oil, fatty acid, NIRS, PLSR

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Authors: Mutaz Shurahabeel Ahmed Ombada

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This paper investigates potential health and financial settlement of health information technology, this paper evaluates health care with the use of IT and other associated industries. It assesses prospective savings and costs of extensive acceptance of Electronic Medical Record Systems (EMRS), models significant to health as well as safety remuneration, and conclude that efficient EMRS execution and networking could ultimately save more than US $55 billion annually through recuperating health care effectiveness and that Health Information Technology -enabled prevention and administration of chronic disease could eventually double those savings while rising health and other social remuneration. On the contrary, this is improbable to be realized without related to significant modifications to the health care system.

Keywords: electronic medical record systems, health care economics, EMRS

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Yamileth P. Herrera, Ronald R. Gutierrez, Carlos, Pacheco-Bustos

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This research aims at the numerical modeling of a rectangular contact tank in order to improve the hydrodynamic behavior and the retention time of the water to be treated with the disinfecting agent. The methodology to be followed includes a hydraulic analysis of the tank to observe the fluid velocities, which will allow evidence of low-speed areas that may generate pathogenic agent incubation or high-velocity areas, which may decrease the optimal contact time between the disinfecting agent and the microorganisms to be eliminated. Based on the results of the numerical model, the efficiency of the tank under the geometric and hydraulic conditions considered will be analyzed. This would allow the performance of the tank to be improved before starting a construction process, thus avoiding unnecessary costs.

Keywords: contact tank, numerical models, hydrodynamic modeling, residence time

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Authors: Noah Yusuf

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The present paper examined the current level of socio-political and economic development in Africa. Models and experiences from other regions of the world, especially, developing ones with similar historical experience with Africa, were explored. The paper concluded that recommendations emanating from past conferences, seminars and symposia on the continent’s socio-economic and political challenges have been poorly implemented because of lack of strong political will; the donor syndrome; weak resource base; capacity constraints in institutions; and lack of accountability, transparency and poor governance. It is, therefore, recommended that African countries need implement sound policies and reforms on a comprehensive basis, if they are to achieve the desired socio-economic and political transformation; and the African in Diasporas represent critical instruments in attaining the socio-economic and political objectives of the continent.

Keywords: Africa, political transformation, economic transformation, Africans in diasporas

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Authors: Diana Vieira Figueiredo, Rita Ramos Miguel, Maria do Céu Salvador, Luiza Nobre-Lima, Daniel RIjo, Paula Vagos

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Social Anxiety Disorder (SAD) is characterized by a marked and persistent fear of social and/or performance situations in which one may be exposed to the scrutiny of others.  SAD has its usual onset and is highly prevalent during adolescence; if left untreated, it often has a chronic and unremitting course. So, it seems important to understand the psychological processes that might predict the development of SAD. One of these processes may be self-compassion, which has been found to be associated with social anxiety in both adults and adolescents. Self-compassion involves three main components, each with a positive (compassionate behavior) and negative (uncompassionate behavior) pole – self-kindness versus self-judgment, common humanity versus isolation, and mindfulness versus over-identification. The negative indicators of self-compassion (self-judgement, isolation, and over-identification) were found to be more strongly linked to mental health problems than the positive indicators (self-kindness, common humanity, and mindfulness). Additionally, negative associations were found between the positive indicators of self-compassion (self-kindness, common humanity, mindfulness) and psychopathology. The current study aimed to investigate the role of self-kindness, self-judgment, common humanity, isolation, mindfulness, and over-identification in the likelihood of an adolescent presenting SAD by comparing groups of normative and socially anxious adolescents. The sample consisted of 32 adolescents (Mage = 15.88, SD = .833) of which 23 were girls. Adolescents were assessed through a clinical structured interview that led 17 to be assigned to the clinical group (presenting a primary diagnosis of SAD) and 15 to be assigned to the non-clinical group (presenting no clinical diagnosis). Variables under study were measured through the Self-Compassion Scale for adolescents (SCS-A), which assesses the six indicators of self-compassion presented above. Six separate models were tested, each with one of the subscales of the SCS-A as the independent variable and with the group (clinical versus non-clinical) as the dependent variable. The models considering isolation, over-identification, self-judgement, and self-kindness fitted the data and accurately predicted group belonging for between 75% to 84.4% of cases. Results indicated that the log of the odds of an adolescent presenting SAD was positively related to isolation, over-identification, and self-judgement and negatively associated with self-kindness. Findings provide support for the idea that decreased self-compassion may place adolescents at increased risk for experiencing clinical levels of social anxiety: on the one hand, adolescents with higher levels of isolation, over-identification, and self-judgement seem to be more prone to the development of psychopathological levels of social anxiety; on the other hand, self-kindness may play a protective role in the development of SAD in this developmental phase. So, if focusing on social feared consequences and perceiving to be different from others may be distinctive features of SAD, developing self-kindness may be the antidote to promote diminished levels of social anxiety and more.

Keywords: adolescents, social anxiety disorder, self-compassion, diagnosis odds-ration

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Authors: Francois Brambati, Daniele Ruscio, Federica Biassoni, Rebecca Hueting, Alessandra Tedeschi

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This research, in the frame of social acceptance of renewable energies and community-based production and consumption models, aims at (1) supporting a data-driven approachable to dealing with climate change and (2) identifying & quantifying the psycho-sociological dimensions and factors that could support the transition from a technology-driven approach to a consumer-driven approach throughout the emerging “prosumer business models.” In addition to the existing Social Acceptance dimensions, this research tries to identify a purely individual psychological fourth dimension to understand processes and factors underling individual acceptance and adoption of renewable energy business models, realizing a Prosumer Acceptance Index. Questionnaire data collection has been performed throughout an online survey platform, combining standardized and ad-hoc questions adapted for the research purposes. To identify the main factors (individual/social) influencing the relation with renewable energy technology (RET) adoption, a Factorial Analysis has been conducted to identify the latent variables that are related to each other, revealing 5 latent psychological factors: Factor 1. Concern about environmental issues: global environmental issues awareness, strong beliefs and pro-environmental attitudes rising concern on environmental issues. Factor 2. Interest in energy sharing: attentiveness to solutions for local community’s collective consumption, to reduce individual environmental impact, sustainably improve the local community, and sell extra energy to the general electricity grid. Factor 3. Concern on climate change: environmental issues consequences on climate change awareness, especially on a global scale level, developing pro-environmental attitudes on global climate change course and sensitivity about behaviours aimed at mitigating such human impact. Factor 4. Social influence: social support seeking from peers. With RET, advice from significant others is looked for internalizing common perceived social norms of the national/geographical region. Factor 5. Impact on bill cost: inclination to adopt a RET when economic incentives from the behaviour perception affect the decision-making process could result in less expensive or unvaried bills. Linear regression has been conducted to identify and quantify the factors that could better predict behavioural intention to become a prosumer. An overall scale measuring “acceptance of a renewable energy solution” was used as the dependent variable, allowing us to quantify the five factors that contribute to measuring: awareness of environmental issues and climate change; environmental attitudes; social influence; and environmental risk perception. Three variables can significantly measure and predict the scores of the “Acceptance in becoming a prosumer” ad hoc scale. Variable 1. Attitude: the agreement to specific environmental issues and global climate change issues of concerns and evaluations towards a behavioural intention. Variable 2. Economic incentive: the perceived behavioural control and its related environmental risk perception, in terms of perceived short-term benefits and long-term costs, both part of the decision-making process as expected outcomes of the behaviour itself. Variable 3. Age: despite fewer economic possibilities, younger adults seem to be more sensitive to environmental dimensions and issues as opposed to older adults. This research can facilitate policymakers and relevant stakeholders to better understand which relevant psycho-sociological factors are intervening in these processes and what and how specifically target when proposing change towards sustainable energy production and consumption.

Keywords: behavioural intention, environmental risk perception, prosumer, renewable energy technology, social acceptance

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Authors: Awol Mekonnen, Temesgen Sidamo, Epherm Engdawork, Kaleab Asresb

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Ethnopharmacological Relevance: The leaves of Kalanchoe petitiana A. Rich (Crassulaceae) are used in Ethiopian folk medicine for treatment of evil eye, fractured surface for bone setting and several skin disorders including for the treatment of sores, boils, and malignant wounds. Aim of the Study: In order to scientifically prove the claimed utilization of the plant, the effects of the extracts and the fractions were investigated using in vivo excision, incision and dead space wound models. Materials and Method: Mice were used for wound healing study, while rats and rabbit were used for skin irritation test. For studying healing activity, 80% methanolic extract and the fractions were formulated in strength of 5% and 10%, either as ointment (hydroalcoholic extract, aqueous and methanol fractions) or gel (chloroform fraction). Oral administration of the crude extract was used for dead space model. Negative controls were treated either with simple ointment or sodium carboxyl methyl cellulose xerogel, while positive controls were treated with nitrofurazone (0.2 w/v) skin ointment. Negative controls for dead space model were treated with 1% carboxy methyl cellulose. Parameters, including rate of wound contraction, period of complete epithelializtion, hydroxyproline contents and skin breaking strength were evaluated. Results: Significant wound healing activity was observed with ointment formulated from the crude extract at both 5% and 10% concentration (p<0.01) compared to controls in both excision and incision models. In dead space model, 600 mg/kg (p<0.01), but not 300 mg/kg, significantly increased hydroxyproline content. Fractions showed variable effect, with the chloroform fraction lacking any significant effect. Both 5% and 10% formulations of the aqueous and methanolic fractions significantly increased wound contraction, decreased epithelializtion time and increased hydroxyproline content in excision wound model (p<0.05) as compared to controls. These fractions were also endowed with higher skin breaking strength in incision wound model (p<0.01). Conclusions: The present study provided evidence that the leaves of Kalanchoe petitiana A. Rich possess remarkable wound healing activities supporting the folkloric assertion of the plant. Fractionation revealed that polar or semi-polar compound may play vital role, as both aqueous and methanolic fractions were endowed with wound healing activity.

Keywords: wound healing, Kalanchoae petitiana, excision wound, incision wound, dead space model

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Authors: Jihoon Park, Sungkon Yu, Byungjo Jung

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Although various optical tissue phantoms (OTPs) simulating human skin have been actively studied, their completeness is unclear because skin tissue has the intricate optical property and complicated structure disturbing the optical simulation. In this study, we designed multilayer OTP mimicking skin structure, and fabricated OTP models simulating skin-blood vessel and skin pigmentation in the skin, which are useful in Biomedical optics filed. The OTPs were characterized with the optical property and the cross-sectional structure, and analyzed by using various optical tools such as a laser speckle imaging system, OCT and a digital microscope to show the practicality. The measured optical property was within 5% error, and the thickness of each layer was uniform within 10% error in micrometer scale.

Keywords: blood vessel, optical tissue phantom, optical property, skin tissue, pigmentation

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Authors: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

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This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two ABC models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: activity-based costing, activity-based management, construction, architectural aluminum

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Authors: Christakis Damianou, Christos Christofi, Nicos Mylonas

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The aim of this paper was to conduct a feasibility study using a flat rectangular (3x10 mm2) MRI compatible transducer operating at 5 MHz for destroying atherosclerotic plaque using the thermal effects of ultrasound in in vitro models. A parametric study was performed where the time needed to ablate the plaque was studied as a function of Spatial Average Temporal Average (SATA) intensity, and pulse duration. The time needed to ablate plaque is directly related to intensity, and pulse duration. The temperature measured close to the artery is above safe limits and therefore thermal ultrasound does not have a place in removing plaques in arteries.

Keywords: ultrasound, atherosclerotic, plaque, pulse

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. In this paper we propose a method of fault diagnosis based on neuro-fuzzy technique and the choice of a threshold. The validation of this method on a test bench "Actuator Electro DAMADICS Benchmark". In the first phase of the method, we construct a model represents the normal state of the system to fault detection. With residuals analysis generated and the choice of thresholds for signatures table. These signatures provide us with groups of non-detectable faults. In the second phase, we build faulty models to see the flaws in the system that are not located in the first phase.

Keywords: residuals analysis, threshold, neuro-fuzzy system, residual evaluation

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Authors: Islem Kedidi, Rihab Bedoui Bensalem, Faysal Manssouri

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In traditional models of insurance data, the number and size of claims are assumed to be independent. Relaxing the independence assumption, this article explores the Vine copula to model dependence structure between multivariate frequency and average severity of insurance claim. To illustrate this approach, we use the Wisconsin local government property insurance fund which offers several insurance protections for motor vehicles, property and contractor’s equipment claims. Results show that the C-vine copula can better characterize the multivariate dependence structure between frequency and severity. Furthermore, we find significant dependencies especially between frequency and average severity among different coverage types.

Keywords: dependency modeling, government insurance, insurance claims, vine copula

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Authors: Hatam H. Ali, Mohd Shahrizal Sunar, Hoshang Kolivand, Mohd Azhar Bin M. Arsad

Abstract:

Rendering light shafts is one of the important topics in computer gaming and interactive applications. The methods and models that are used to generate light shafts play crucial role to make a scene more realistic in computer graphics. This article discusses the image-based shadows and geometric-based shadows that contribute in generating volumetric shadows and light shafts, depending on ray tracing, radiosity, and ray marching technique. The main aim of this study is to provide researchers with background on a progress of light scattering methods so as to make it available for them to determine the technique best suited to their goals. It is also hoped that our classification helps researchers find solutions to the shortcomings of each method.

Keywords: shaft of lights, realistic images, image-based, and geometric-based

Procedia PDF Downloads 264

Authors: Amrane Meriem, Oukid Salyha

Abstract:

The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

Procedia PDF Downloads 67