Search results for: function strategies

Authors: Francis Kwesi Bondinuba, Seidu Abdullah, Mewomo Cecilia, Opoku Alex

Abstract:

Purpose: The purpose of this research is to develop a framework for understanding how sustainable project management contributes to the construction industry's pursuit of sustainable development goals. Study design/methodology/approach: The study employed a theoretical methodology to review existing theories and models that support Sustainable Project Management (SPM) in the construction industry. Additionally, a comprehensive review of current literature on SPM is conducted to provide a thorough understanding of this study. Findings: Sustainable Project Management (SPM) practices, including stakeholder engagement and collaboration, resource efficiency, waste management, risk management, and resilience, play a crucial role in achieving the Sustainable Development Goals (SDGs) within the construction industry. Conclusion: Adopting Sustainable Project Management (SPM) practices in the Ghanaian construction industry enhances social inclusivity by engaging communities and creating job opportunities. The adoption of these practices faces significant challenges, including a lack of awareness and understanding, insufficient regulatory frameworks, financial constraints, and a shortage of skilled professionals. Recommendation: There should be a comprehensive approach to project planning and execution that includes stakeholders such as local communities, government bodies, and environmental organisations, the use of green building materials and technologies, and the implementation of effective waste management strategies, all of which will ensure the achievement of SDGs in Ghana's construction industry. Originality/value: This paper adds to the current literature by offering the various theories and models in Sustainable Project Management (SPM) and a detailed review of how Sustainable Project Management (SPM) contribute to the achievement of the Sustainable Development Goals (SDGs) in the Ghanaian Construction Industry.

Keywords: sustainable development, sustainable development goals, construction industry, ghana, sustainable project management

Procedia PDF Downloads 12

Authors: Rachel Y. Zhang, Christopher K. Anderson

Abstract:

A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

Procedia PDF Downloads 122

Authors: Roman Kulikov, Svetlana Kolesnikova

Abstract:

Last decade Cloud Computing technologies have been rapidly becoming ubiquitous. Each year more and more organizations, corporations, internet services and social networks trust their business sensitive information to Public Cloud. The data storage in Public Cloud is protected by security mechanisms such as firewalls, cryptography algorithms, backups, etc.. In this way, however, only outsider attacks can be prevented, whereas virtualization tools can be easily compromised by insider. The protection of Public Cloud’s critical elements from internal intruder remains extremely challenging. A hypervisor, also called a virtual machine manager, is a program that allows multiple operating systems (OS) to share a single hardware processor in Cloud Computing. One of the hypervisor's functions is to enforce access control policies. Furthermore, it prevents guest OS from disrupting each other and from accessing each other's memory or disk space. Hypervisor is the one of the most critical and vulnerable elements in Cloud Computing infrastructure. Nevertheless, it has been poorly protected from being compromised by insider. By exploiting certain vulnerabilities, privilege escalation can be easily achieved in insider attacks on hypervisor. In this way, an internal intruder, who has compromised one process, is able to gain control of the entire virtual machine. Thereafter, the consequences of insider attacks in Public Cloud might be more catastrophic and significant to virtual tools and sensitive data than of outsider attacks. So far, almost no preventive security countermeasures have been developed. There has been little attention paid for developing models to assist risks mitigation strategies. In this paper formal model of insider attacks on hypervisor is designed. Our analysis identifies critical hypervisor`s vulnerabilities that can be easily compromised by internal intruder. Consequently, possible conditions for successful attacks implementation are uncovered. Hence, development of preventive security countermeasures can be improved on the basis of the proposed model.

Keywords: insider attack, public cloud, cloud computing, hypervisor

Procedia PDF Downloads 355

Authors: Olga Shapovalova, Vladimir Vinogradov

Abstract:

Among many different sol – gel matrices only alumina can be successfully parenteral injected in the human body. And this is not surprising, because boehmite (aluminium oxyhydroxide) is the metal oxide approved by FDA and EMA for intravenous and intramuscular administrations, and also has been using for a longtime as adjuvant for producing of many modern vaccines. In our earlier study, it has been shown, that denaturation temperature of enzymes entrapped in sol-gel boehmite matrix increases for 30 – 60 °С with preserving of initial activity. It makes such matrices more attractive for long-term storage of non-stable drugs. In current work we present ultrasound-assisted sol-gel synthesis of nano-boehmite. This method provides bio-friendly, very stable, highly homogeneous alumina sol with using only water and aluminium isopropoxide as a precursor. Many parameters of the synthesis were studied in details: time of ultrasound treatment, US frequency, surface area, pore and nanoparticle size, zeta potential and others. Here we investigated the dependence of stability of colloidal sols and textural properties of the final composites as a function of the time of ultrasonic treatment. Chosen ultrasonic treatment time was between 30 and 180 minutes. Surface area, average pore diameter and total pore volume of the final composites were measured by surface and pore size analyzer Nova 1200 Quntachrome. It was shown that the matrices with ultrasonic treatment time equal to 90 minutes have the biggest surface area 431 ± 24 m2/g. On the other had such matrices have a smaller stability in comparison with the samples with ultrasonic treatment time equal to 120 minutes that have the surface area 390 ± 21 m2/g. It was shown that the stable sols could be formed only after 120 minutes of ultrasonic treatment, otherwise the white precipitate of boehmite is formed. We conclude that the optimal ultrasonic treatment time is 120 minutes.

Keywords: boehmite matrix, stabilisation, ultrasound-assisted sol-gel synthesis

Procedia PDF Downloads 254

Authors: Rahele Mesbah, Nic Van Der Wee, Manja Koenders, Erik Giltay, Albert Van Hemert, Max De Leeuw

Abstract:

Introduction: Patients with bipolar disorder (BD), characterized by depressive and manic episodes, often suffer from cognitive dysfunction. An up-to-date meta-analysis of functional Magnetic Resonance Imaging (fMRI) studies examining cognitive function in BD is lacking. Objective: The aim of the current fMRI meta-analysis is to investigate brain functioning of bipolar patients compared with healthy subjects within three domains of emotion processing, reward processing, and working memory. Method: Differences in brain regions activation were tested within whole-brain analysis using the activation likelihood estimation (ALE) method. Separate analyses were performed for each cognitive domain. Results: A total of 50 fMRI studies were included: 20 studies used an emotion processing (316 BD and 369 HC) task, 9 studies a reward processing task (215 BD and 213 HC), and 21 studies used a working memory task (503 BD and 445 HC). During emotion processing, BD patients hyperactivated parts of the left amygdala and hippocampus as compared to HC’s, but showed hypoactivation in the inferior frontal gyrus (IFG). Regarding reward processing, BD patients showed hyperactivation in part of the orbitofrontal cortex (OFC). During working memory, BD patients showed increased activity in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Conclusions: This meta-analysis revealed evidence for activity disturbances in several brain areas involved in the cognitive functioning of BD patients. Furthermore, most of the found regions are part of the so-called fronto-limbic network which is hypothesized to be affected as a result of BD candidate genes' expression.

Keywords: cognitive functioning, fMRI analysis, bipolar disorder, fronto-limbic network

Procedia PDF Downloads 448

Authors: Antonia Stergiou

Abstract:

Background: Due to the developmental trajectory of executive function in preschool age, the majority of existing studies investigating the association between acute physical activity and cognitive control have focused on adolescents and adult population. Aim- The aim of this study was to investigate the possible effects of physical activity on the inhibitory control of pre-school children. Methods: This is a prospectively designed study that was conducted in a primary school in Bristol in June 2015. The total number of subjects was n=61 and 20 trials of a modified Eriksen Flanker Task were completed before and after a 30-minutes session of moderate exercise (including both 5 minutes of warm up and cool down). For each test a pre- and post-test assessment took place that included both congruent and incongruent trials. The congruent trials were considered as the control condition and the incongruent trials as those that measure inhibitory control (experimental condition). At the end of the assessment, the participants were instructed to choose the face that described their current feelings between three options (happy, neutral, sad). Results: There was a trend for increased accuracy following moderate exercise, but there was statistical significance (p > .05). However, there was statistically significant improvement in the reaction time following the same type of exercise (p = .005). Face board assessment revealed positive emotions after 30 minutes of moderate exercise. Conclusions: The current study supports findings from previous studies related to the benefits of physical activity on the children’s inhibitory control and provides evidence of those benefits in even younger ages. Further research should take place considering each child individually. Implementation of those findings could result in an improved curriculum in schools with additional time spent on physical education courses.

Keywords: cognitive control, inhibition, physical activity, pre-school children

Procedia PDF Downloads 244

Authors: Ajmal Hussain

Abstract:

In Indian music parlance, Rasa denotes a distinct aesthetic experience that builds up in the mind of the listeners while listening to a piece of Indian classical music. The distinction of the experience is rooted in the concept that it gives rise to an enhanced awareness about the Self or God and creates a mental state detached from mundane issues of everyday life. The theory of Rasa was initially proposed in the context of theatre but became a part of Indian musicological discourse roughly two thousand years ago, however, to this day, it remains shrouded in mystery due to its religious associations and connotations. This paper attempts to demystify the theory of Rasa in the light of available scientific knowledge fund particularly in Brain and Mind sciences. The paper initially describes the religious context of the theory of Rasa and then discusses its classical formulations by Bharata and Abhinavagupta including the steps and stages laid down by the latter to explain the creation of musical experience. The classical formulations are then interpreted with reference to the scientific knowledge fund about the human mind and mechanics of perception. The study uses the model of human mind as proposed by Portuguese-American neuroscientist Antonio Damasio in his theory ‘A Nesting Principle’. On the basis of the findings by Damasio, the paper interprets the experience of Rasa from a scientific perspective and clarifies the sequence of steps and stages involved in the making of musical experience. The study concludes that although the classical formulations of Rasa identify key aspects of musical experience, the association of Rasa with religion is misleading. The association with religion does not depend upon musical stimulus but the intellectual orientation of the listener. It further establishes that the function of Rasa is more profound as, from an evolutionary perspective, it can be seen as a catalyst for higher consciousness.

Keywords: aesthetic, consciousness, music, Rasa

Procedia PDF Downloads 122

Authors: ȘercăIanu Mihai, Aldea Mihaela, Iacoboaea Cristina, Luca Oana, Nenciu Ioana

Abstract:

The emergence and neutralization of illegal waste dumps represent a global concern for waste management ecosystems with a particularly pronounced impact on disadvantaged communities. All over the world, and in this particular case in Romania, a relevant number of people resided in houses lacking any legal forms such as land ownership documents or building permits. These areas are referred to as “informal settlements”. An increasing number of regions and cities in Romania are struggling to manage their waste dumps, especially in the context of increasing poverty and lack of regulation related to informal settlements. An example of such informal settlement can be found at the terminus of Bistra Street in Câlnic, which falls under the jurisdiction of the Municipality of Reșița in Caras Severin County. The article presents a case study that focuses on employing remote sensing techniques and spatial data to monitor and map illegal waste practices, with subsequent integration into a geographic information system tailored for the Reșița community. In addition, the paper outlines the steps involved in devising strategies aimed at enhancing waste management practices in disadvantaged areas, aligning with the shift toward a circular economy. Results presented in the paper contain a spatial mapping and visualization methodology calibrated with in situ data collection applicable for identifying illegal landfills. The emergence and neutralization of illegal dumps pose a challenge in the field of waste management. These approaches, which prove effective where conventional solutions have failed, need to be replicated and adopted more wisely.

Keywords: waste dumps, waste management, monitoring, GIS, informal settlements

Procedia PDF Downloads 69

Authors: Jacky Liu

Abstract:

This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

Procedia PDF Downloads 87

Authors: Tomi Setiawan, Wahyu Y. Subekti, Siti S. Nur'Adya, Khusnul Ilmiah

Abstract:

Dye-Sensitized Solar Cell (DSSC) is one type of solar cell, where solar cells function to convert light energy become the electrical energy. DSSC has two important parts of dye and counter electrode. Anthocyanin compounds in the coffee beans peel can be potential as natural dye and also counter electrodes as activated carbon in the DSSC system. The purpose of this research is to find out how to isolate Anthocyanin, manufacture of counter electrode, and to know the efficiency of counter electrode produced from the coffee pulp waste in DSSC prototype. In this research we used 2 x 2 cm FTO glass coated carbon paste with a thickness variation of 100 μL, 200 μL and 300 μL as counter electrode and other FTO glass coated with TiO₂ paste as work electrode, then two FTO glasses are connected to form a sandwich-liked structure and add Triiodide electrolyte solution in its gap, thus forming a DSSC prototype. The results showed that coffee pulp waste contains anthocyanin of 12.23 mL/80gr and it can produce activated carbon. The characterization performed shows that the UV-Vis Anthocyanin result is at wavelength of ultra violet area that is 219,50 nm with absorbance value equal to 1,469, and maximum wavelength at visible area is 720,00 nm with absorbance value equal to 0,013. The functional groups contained in the anthocyanin are O-H groups at wave numbers 3385.60 cm⁻¹, C = O groups at wave numbers 1618.63 cm⁻¹, and C-O-C groups at 1065.40 cm⁻¹ wave numbers. Morphological characterization using the SEM shows the activated carbon surface area becomes larger and evenly distributed. Voltage obtained on Counter Electrode 100 μL variation of 395mV, 200 μL of 334mV 100 μL of 254mV.

Keywords: DSSC, anthocyanin, counter electrode, solar cell, coffee pulp

Procedia PDF Downloads 179

Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon

Abstract:

Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.

Keywords: exergy analysis, genetic algorithm, rankine cycle, single and multi-objective function

Procedia PDF Downloads 139

Authors: Andras Dezső, Peter Baumli, George Kaptay

Abstract:

The phosphorous is the important components in the steels, because it makes the changing of the mechanical properties and possibly modifying the structure. The phosphorous can be create the Fe3P compounds, what is segregated in the ferrite grain boundary in the intervals of the nano-, or microscale. This intermetallic compound is decreasing the mechanical properties, for example it makes the blue brittleness which means that the brittle created by the segregated particles at 200 ... 300°C. This work describes the phosphide solubility by the other components effect. We make calculations for the Ni, Mo, Cu, S, V, C, Si, Mn, and the Cr elements by the Thermo-Calc software. We predict the effects by approximate functions. The binary Fe-P system has a solubility line, which has a determinating equation. The result is below: lnwo = -3,439 – 1.903/T where the w0 means the weight percent of the maximum soluted concentration of the phosphorous, and the T is the temperature in Kelvin. The equation show that the P more soluble element when the temperature increasing. The nickel, molybdenum, vanadium, silicon, manganese, and the chromium make dependence to the maximum soluted concentration. These functions are more dependent by the elements concentration, which are lower when we put these elements in our steels. The copper, sulphur and carbon do not make effect to the phosphorous solubility. We predict that all of cases the maximum solubility concentration increases when the temperature more and more high. Between 473K and 673 K, in the phase diagram, these systems contain mostly two or three phase eutectoid, and the singe phase, ferritic intervals. In the eutectoid areas the ferrite, the iron-phosphide, and the metal (III)-phospide are in the equilibrium. In these modelling we predicted that which elements are good for avoid the phosphide segregation or not. These datas are important when we make or choose the steels, where the phosphide segregation stopping our possibilities.

Keywords: phosphorous, steel, segregation, thermo-calc software

Procedia PDF Downloads 620

Authors: Kechnit Djamel, Ammarri Abdelhadi, Raphael Tshimang, Mark Trrig

Abstract:

One of the most important aspects of monitoring rivers is navigation. The variation of discharge in the river generally produces a change in available draft for a vessel, particularly in the low flow season, which can impact the navigable water path, especially when the water depth is less than the normal one, which allows safe navigation for boats. The water depth is related to the bathymetry of the channel as well as the discharge. For a seasonal update of the navigation maps, a daily discharge value is required. Many novel approaches based on earth observation and remote sensing have been investigated for large rivers. However, it should be noted that most of these approaches are not currently able to directly estimate river discharge. This paper discusses the application of remote sensing tools using the analysis of the reflectance value of MODIS imagery and is combined with field measurements for the estimation of discharge. This approach is applied in the lower reach of the Congo River (Pool Malebo) for the period between 2019 and 2021. The correlation obtained between the observed discharge observed in the gauging station and the reflectance ratio time series is 0.81. In this context, a Discharge Reflectance Model (DRM) was developed to express discharge as a function of reflectance. This model introduces a non-contact method that allows discharge monitoring using earth observation. DRM was validated by field measurements using ADCP, in different sections on the Pool Malebo, over two different periods (dry and wet seasons), as well as by the observed discharge in the gauging station. The observed error between the estimated and measured discharge values ranges from 1 to 8% for the ADCP and from (1% to 11%) for the gauging station. The study of the uncertainties will give us the possibility to judge the robustness of the DRM.

Keywords: discharge monitoring, navigation, MODIS, empiric, ADCP, Congo River

Procedia PDF Downloads 81

Authors: Alessandro Poma, Kal Karim, Sergey Piletsky, Giuseppe Battaglia

Abstract:

The recent increasing emergency threat to public health of infectious influenza diseases has prompted interest in the detection of avian influenza virus (AIV) H5N1 in humans as well as animals. A variety of technologies for diagnosing AIV infection have been developed. However, various disadvantages (costs, lengthy analyses, and need for high-containment facilities) make these methods less than ideal in their practical application. Molecularly Imprinted Polymeric Nanoparticles (MIP NPs) are suitable to overcome these limitations by having high affinity, selectivity, versatility, scalability and cost-effectiveness with the versatility of post-modification (labeling – fluorescent, magnetic, optical) opening the way to the potential introduction of improved diagnostic tests capable of providing rapid differential diagnosis. Here we present our first results in the production and testing of MIP NPs for the detection of AIV H5N1. Recent developments in the solid-phase synthesis of MIP NPs mean that for the first time a reliable supply of ‘soluble’ synthetic antibodies can be made available for testing as potential biological or diagnostic active molecules. The MIP NPs have the potential to detect viruses that are widely circulating in farm animals and indeed humans. Early and accurate identification of the infectious agent will expedite appropriate control measures. Thus, diagnosis at an early stage of infection of a herd or flock or individual maximizes the efficiency with which containment, prevention and possibly treatment strategies can be implemented. More importantly, substantiating the practicability’s of these novel reagents should lead to an initial reduction and eventually to a potential total replacement of animals, both large and small, to raise such specific serological materials.

Keywords: influenza virus, molecular imprinting, nanoparticles, polymers

Procedia PDF Downloads 339

Authors: Thomas Schalow

Abstract:

It is commonly recognized that our present curriculum is not preparing students to function in the 21st century. This is particularly true in regard to communication needs across cultures - both human and non-human. In this paper, a comprehensive theory of communication-based on communication with non-human cultures and intelligences is presented to meet the following three imminent contingencies: communicating with sentient biological intelligences, communicating with extraterrestrial intelligences, and communicating with artificial super-intelligences. The paper begins with the argument that we need to become much more serious about communicating with the non-human, intelligent life forms that already exists around us here on Earth. We need to broaden our definition of communication and reach out to other sentient life forms in order to provide humanity with a better perspective of its place within our ecosystem. The paper next examines the science and philosophy behind CETI (communication with extraterrestrial intelligences) and how it could prove useful even in the absence of contact with alien life. However, CETI’s assumptions and methodology need to be revised in accordance with the communication theory being proposed in this paper if we are truly serious about finding and communicating with life beyond Earth. The final theme explored in this paper is communication with non-biological super-intelligences. Humanity has never been truly compelled to converse with other species, and our failure to seriously consider such intercourse has left us largely unprepared to deal with communication in a future that will be mediated and controlled by computer algorithms. Fortunately, our experience dealing with other cultures can provide us with a framework for this communication. The basic concepts behind intercultural communication can be applied to the three types of communication envisioned in this paper if we are willing to recognize that we are in fact dealing with other cultures when we interact with other species, alien life, and artificial super-intelligence. The ideas considered in this paper will require a new mindset for humanity, but a new disposition will yield substantial gains. A curriculum that is truly ready for the 21st century needs to be aligned with this new theory of communication.

Keywords: artificial intelligence, CETI, communication, language

Procedia PDF Downloads 351

Authors: Kevin Montanez, Patricia Garcia

Abstract:

The confinement and restrictions adopted to avoid an exponential spread of the COVID-19 have negatively impacted the Peruvian economy. In this context, Industries offering essential products could continue operating, but they have to follow safety protocols and implement strategies to ensure employee health. In view of the increasing internet access and mobile phone ownership, “Alerta Temprana”, a mobile app, was developed to self-report COVID-19 symptoms in the work context. In this study, the usability of the mobile app “Alerta Temprana” was evaluated from the perspective of health monitors and workers. In addition to reporting the metrics related to the usability of the application, the utility of the system is also evaluated from the monitors' perspective. In this descriptive study, the participants used the mobile app for two months. Afterwards, System Usability Scale (SUS) questionnaire was answered by the workers and monitors. A Usefulness questionnaire with open questions was also used for the monitors. The data related to the use of the application was collected during one month. Furthermore, descriptive statistics and bivariate analysis were used. The workers rated the application as good (70.39). In the case of the monitors, usability was excellent (83.0). The most important feature for the monitors were the emails generated by the application. The average interaction per user was 30 seconds and a total of 6172 self-reports were sent. Finally, a statistically significant association was found between the acceptability scale and the work area. The results of this study suggest that Alerta Temprana has the potential to be used for surveillance and health monitoring in any context of face-to-face modality. Participants reported a high degree of ease of use. However, from the perspective of workers, SUS cannot diagnose usability issues and we suggest we use another standard usability questionnaire to improve "Alerta Temprana" for future use.

Keywords: public health in informatics, mobile app, usability, self-report

Procedia PDF Downloads 104

Authors: Didier Auroux, Vladimir Groza

Abstract:

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

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

Procedia PDF Downloads 308

Authors: Sarit Rashkovits, Anat Drach- Zahavy

Abstract:

The research considers the unresolved question regarding the link between nursing team accountability and team learning and the resulted team performance in nursing teams. Empirical findings reveal disappointing evidence regarding improvement in healthcare safety and quality. Therefore, there is a need in advancing managerial knowledge regarding the factors that enhance constant healthcare teams' proactive improvement efforts, meaning team learning. We first aim to identify the organizational resources that are needed for team learning in nursing teams; second, to test the moderating role of nursing teams' learning resources in the team accountability-team learning link; and third, to test the moderated mediation model suggesting that nursing teams' accountability affects team performance by enhancing team learning when relevant resources are available to the team. We point on the intervening role of three team learning resources, namely time availability, team autonomy and performance data on the relation between team accountability and team learning and test the proposed moderated mediation model on 44 nursing teams (462 nurses and 44 nursing managers). The results showed that, as was expected, there was a positive significant link between team accountability and team learning and the subsequent team performance when time availability and team autonomy were high rather than low. Nevertheless, the positive team accountability- team learning link was significant when team performance feedback was low rather than high. Accordingly, there was a positive mediated effect of team accountability on team performance via team learning when either time availability or team autonomy were high and the availability of team performance data was low. Nevertheless, this mediated effect was negative when time availability and team autonomy were low and the availability of team performance data was high. We conclude that nurturing team accountability is not enough for achieving nursing teams' learning and the subsequent improved team performance. Rather there is need to provide nursing teams with adequate time, autonomy, and be cautious with performance feedback, as the latter may motivate nursing teams to repeat routine work strategies rather than explore improved ones.

Keywords: nursing teams' accountability, nursing teams' learning, performance feedback, teams' autonomy

Procedia PDF Downloads 256

Authors: Michał Lidner, Zbigniew SzcześNiak

Abstract:

The ability to estimate blast load overpressure properly plays an important role in safety design of buildings. The issue of studying of blast loading on structural elements has been explored for many years. However, in many literature reports shock wave overpressure is estimated with simplified triangular or exponential distribution in time. This indicates some errors when comparing real and numerical reaction of elements. Nonetheless, it is possible to further improve setting similar to the real blast load overpressure function versus time. The paper presents a method of numerical analysis of the phenomenon of the air shock wave propagation. It uses Finite Volume Method and takes into account energy losses due to a heat transfer with respect to an adiabatic process rule. A system of three equations (conservation of mass, momentum and energy) describes the flow of a volume of gaseous medium in the area remote from building compartments, which can inhibit the movement of gas. For validation three cases of a shock wave flow were analyzed: a free field explosion, an explosion inside a steel insusceptible tube (the 1D case) and an explosion inside insusceptible cube (the 3D case). The results of numerical analysis were compared with the literature reports. Values of impulse, pressure, and its duration were studied. Finally, an overall good convergence of numerical results with experiments was achieved. Also the most important parameters were well reflected. Additionally analyses of dynamic response of one of considered structural element were made.

Keywords: adiabatic process, air shock wave, explosive, finite volume method

Procedia PDF Downloads 178

Authors: Antonella Poce, Deborah Seid Howes, Maria Rosaria Re, Mara Valente

Abstract:

The Creative Industries education contexts, Museum Education in particular, generally presents a low emphasis on the use of new digital technologies, digital abilities and transversal skills development. The spread of the Covid-19 pandemic has underlined the importance of these abilities and skills in cultural heritage education contexts: gaining digital skills, museum professionals will improve their career opportunities with access to new distribution markets through internet access and e-commerce, new entrepreneurial tools, or adding new forms of digital expression to their work. However, the use of web, mobile, social, and analytical tools is becoming more and more essential in the Heritage field, and museums, in particular, to face the challenges posed by the current worldwide health emergency. Recent studies highlight the need for stronger partnerships between the cultural and creative sectors, social partners and education and training providers in order to provide these sectors with the combination of skills needed for creative entrepreneurship in a rapidly changing environment. Considering the above conditions, the paper presents different examples of digital learning experiences carried out in Italian and USA contexts with the aim of promoting digital skills in museum professionals. In particular, a quali-quantitative research study has been conducted on two international Postgraduate courses, “Advanced Studies in Museum Education” (2 years) and “Museum Education” (1 year), in order to identify the educational effectiveness of the online learning strategies used (e.g., OBL, Digital Storytelling, peer evaluation) for the development of digital skills and the acquisition of specific content. More than 50 museum professionals participating in the mentioned educational pathways took part in the learning activity, providing evaluation data useful for research purposes.

Keywords: digital skills, museum professionals, technology, education

Procedia PDF Downloads 168

Authors: Hamed K. Esfahani, Bithin Datta

Abstract:

Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

Procedia PDF Downloads 265

Authors: Parvin Goli, Amirhosein Kefayat, Rezvan Goli

Abstract:

Background: It is well established that parents can influence their offspring's neurodevelopment. It is shown that paternal environment and lifestyle is beneficial for the progeny's fitness and might affect their metabolic mechanisms; however, the effects of paternal exercise on the brain in the offspring have not been explored in detail. Objective: This study aims to review the impact of paternal physical exercise on memory and learning, neuroplasticity, as well as DNA methylation levels in the off-spring's hippocampus. Study design: In this systematic review and meta-analysis, an electronic literature search was conducted in databases including PubMed, Scopus, and Web of Science. Eligible studies were those with an experimental design, including an exercise intervention arm, with the assessment of any type of memory function, learning ability, or any type of brain plasticity as the outcome measures. Standardized mean difference (SMD) and 95% confidence intervals (CI) were computed as effect size. Results: The systematic review revealed the important role of environmental enrichment in the behavioral development of the next generation. Also, offspring of exercised fathers displayed higher levels of memory ability and lower level of brain-derived neurotrophic factor. A significant effect of paternal exercise on the hippocampal volume was also reported in the few available studies. Conclusion: These results suggest an intergenerational effect of paternal physical activity on cognitive benefit, which may be associated with hippocampal epigenetic programming in offspring. However, the biological mechanisms of this modulation remain to be determined.

Keywords: hippocampal plasticity, learning ability, memory, parental exercise

Procedia PDF Downloads 202

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

Abstract:

In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

Procedia PDF Downloads 133

Authors: Arya Farjand

Abstract:

This study delves into the Early Pleistocene fauna of the Yuanmou Basin, highlighting two significant findings. The first is the discovery of exceptionally well-preserved canid coprolites, which provide a rare glimpse into the diet and ecological niche of these ancient carnivores. The analysis of these coprolites has revealed a diet rich in diverse prey species, suggesting a complex food web and a dynamic ecological environment. This discovery not only sheds light on the dietary habits of these canids but also offers broader insights into the region's ecological dynamics during the Early Pleistocene. Additionally, the preservation of these coprolites allows for detailed study of the carnivore's role in the ecosystem, including their interactions with other species and the overall health of the environment. The second major finding is the identification of a mustelid species, Eirictis yuanmouensis, from the same fossil horizon as the coprolites. This discovery is crucial for understanding the diversity and evolution of Mustelidae in the region. The detailed analysis of cranial and dental morphology of Eirictis yuanmouensis indicates unique adaptations that suggest a specialized ecological niche. This finding, in conjunction with the coprolite analysis, provides a comprehensive view of the ecological niches occupied by both mustelids and hyenas, enhancing our understanding of their adaptations and interactions within this paleoenvironment. The study's significance is further amplified by the analysis of pollen data from the same horizon, which indicates a paleoenvironment characterized by rapid climatic changes and a dominant semiarid climate. This combination of faunal and floral data paints a detailed picture of the Early Pleistocene environment in the Yuanmou Basin, offering valuable insights into the interactions between different carnivore species and their adaptation strategies in response to changing environmental conditions.

Keywords: Yuanmou Basin, coprolite, Hyaena, eirictis yuanmouensis, early pleistocene

Procedia PDF Downloads 12

Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

Abstract:

Music is ubiquitous in human lives. Ever since the fetus hears the sound inside the mother’s womb and later upon birth, the baby experiences alluring sounds, the curiosity of learning emanates and evokes exploration. Music is an education than mere entertainment. The intricate balance between music, education, and entertainment has well been recognized by the scientific community and is being explored as a viable tool to understand and improve human cognition. There are seven basic swaras (notes) Sa, Ri, Ga, Ma, Pa, Da, and Ni in the Carnatic music system that are analogous to C, D, E, F, G, A, and B of the western system. The Carnatic music builds on the conscious use of microtones, gamakams (oscillation), and rendering styles that evolved over centuries and established its stance. The complex but erudite raga system has been designed with elaborate experiments on srutis (musical sounds) and human perception abilities. In parallel, ‘rasa’- the emotions evoked by certain srutis and hence the ragas been solidified along with the power of language in combination with the musical sounds. The Carnatic music branches out as Kalpita sangeetam (pre-composed music) and Manodharma sangeetam (improvised music). This article explores the Manodharma sangeetam and its subdivisions such as raga alapana, swara kalpana, neraval, and ragam-tanam-pallavi (RTP). The intrinsic mathematical strategies in it’s practice methods toward improvising the music have been explored in detail with concert examples. The techniques on swara weaving for swara kalpana rendering and methods on the alapana development are also discussed at length with an emphasis on the impact on the human cognitive abilities. The articulation of the outlined conscious practice methods not only helps to leave a long-lasting melodic impression on the listeners but also onsets cognitive developments.

Keywords: Carnatic, Manodharmam, music cognition, Alapana

Procedia PDF Downloads 194

Authors: Sohrab Jafarpour, Hamed Farokhi, Mohammad Rahmati, Alireza Gholipour

Abstract:

In the current study, a nonlinear fluid-structure interaction (FSI) biomechanical model of atherosclerosis in the left anterior descending (LAD) coronary artery is developed to perform a detailed sensitivity analysis of the geometrical features of an atheroma plaque. In the development of the numerical model, first, a 3D geometry of the diseased artery is developed based on patient-specific dimensions obtained from the experimental studies. The geometry includes four influential geometric characteristics: stenosis ratio, plaque shoulder-length, fibrous cap thickness, and eccentricity intensity. Then, a suitable strain energy density function (SEDF) is proposed based on the detailed material stability analysis to accurately model the hyperelasticity of the arterial walls. The time-varying inlet velocity and outlet pressure profiles are adopted from experimental measurements to incorporate the pulsatile nature of the blood flow. In addition, a computationally efficient type of structural boundary condition is imposed on the arterial walls. Finally, a non-Newtonian viscosity model is implemented to model the shear-thinning behaviour of the blood flow. According to the results, the structural responses in terms of the maximum principal stress (MPS) are affected more compared to the fluid responses in terms of wall shear stress (WSS) as the geometrical characteristics are varying. The extent of these changes is critical in the vulnerability assessment of an atheroma plaque.

Keywords: atherosclerosis, fluid-Structure interaction modeling, material stability analysis, and nonlinear biomechanics

Procedia PDF Downloads 82

Authors: Yujie Wei

Abstract:

Twitter uses a variety of narrative methods (e.g., messages, featured videos, music, and actual events) to strengthen its cultivation effect. Consumers are receiving mass-produced brand stores or images made by brand managers according to strict market specifications. Drawing on the cultivation theory, this quantitative research investigates how following a brand on Twitter for 12 weeks can cultivate their attitude toward the brand and influence their purchase intentions. We conducted three field experiments on Twitter to test the cultivation effects of following a brand for 12 weeks on consumer attitude toward the followed brand. The cultivation effects were measured by comparing the changes in consumer attitudes before and after they have followed a brand over time. The findings of our experiments suggest that when consumers are exposed to a brand’s stable, pervasive, and recurrent tweets on Twitter for 12 weeks, their attitude toward a brand can be significantly changed, which confirms the cultivating effects on consumer attitude. Also, the results indicate that branding activities on Twitter, when properly implemented, can be very effective in changing consumer attitudes toward a brand, increasing the purchase intentions, and increasing their willingness to spread the word-of-mouth for the brand on social media. The cultivation effects are moderated by brand type and consumer age. The research provides three major marketing implications. First, Twitter marketers should create unique content to engage their brand followers to change their brand attitude through steady, cumulative exposure to the branding activities on Twitter. Second, there is a significant moderating effect of brand type on the cultivation effects, so Twitter marketers should align their branding content with the brand type to better meet the needs and wants of consumers for different types of brands. Finally, Twitter marketers should adapt their tweeting strategies according to the media consumption preferences of different age groups of their target markets. This empirical research proves that content is king.

Keywords: tweeting, cultivation theory, consumer brand attitude, purchase intentions, word-of-mouth

Procedia PDF Downloads 100

Authors: Nir Schreiber, Reuven Cohen, Simi Haber

Abstract:

The Potts model has been widely explored in the literature for the last few decades. While many analytical and numerical results concern with the traditional two site interaction model in various geometries and dimensions, little is yet known about models where more than two spins simultaneously interact. We consider a ferromagnetic four site interaction Potts model on the square lattice (FFPS), where the four spins reside in the corners of an elementary square. Each spin can take an integer value 1,2,...,q. We write the partition function as a sum over clusters consisting of monochromatic faces. When the number of faces becomes large, tracing out spin configurations is equivalent to enumerating large lattice animals. It is known that the asymptotic number of animals with k faces is governed by λᵏ, with λ ≈ 4.0626. Based on this observation, systems with q < 4 and q > 4 exhibit a second and first order phase transitions, respectively. The transition nature of the q = 4 case is borderline. For any q, a critical giant component (GC) is formed. In the finite order case, GC is simple, while it is fractal when the transition is continuous. Using simple equilibrium arguments, we obtain a (zero order) bound on the transition point. It is claimed that this bound should apply for other lattices as well. Next, taking into account higher order sites contributions, the critical bound becomes tighter. Moreover, for q > 4, if corrections due to contributions from small clusters are negligible in the thermodynamic limit, the improved bound should be exact. The improved bound is used to relate the critical point to the finite correlation length. Our analytical predictions are confirmed by an extensive numerical study of FFPS, using the Wang-Landau method. In particular, the q=4 marginal case is supported by a very ambiguous pseudo-critical finite size behavior.

Keywords: entropic sampling, lattice animals, phase transitions, Potts model

Procedia PDF Downloads 152

Authors: P. Valsalal, S. Thangalakshmi

Abstract:

There is a widespread changeover in the electrical power industry universally from old-style monopolistic outline towards a horizontally distributed competitive structure to come across the demand of rising consumption. When the transmission lines of derestricted system are incapable to oblige the entire service needs, the lines are overloaded or congested. The governor between customer and power producer is nominated as Independent System Operator (ISO) to lessen the congestion without obstructing transmission line restrictions. Among the existing approaches for congestion management, the frequently used approaches are reorganizing the generation and load curbing. There is a boundary for reorganizing the generators, and further loads may not be supplemented with the prevailing resources unless more private power producers are added in the system by considerably raising the cost. Hence, congestion is relaxed by appropriate Flexible AC Transmission Systems (FACTS) devices which boost the existing transfer capacity of transmission lines. The FACTs device, namely, Unified Power Flow Controller (UPFC) is preferred, and the correct placement of UPFC is more vital and should be positioned in the highly congested line. Hence, the weak line is identified by using power flow performance index with the new objective function with proposed hybrid Fish – Bee algorithm. Further, the location of UPFC at appropriate line reduces the branch loading and minimizes the voltage deviation. The power transfer capacity of lines is determined with and without UPFC in the identified congested line of IEEE 30 bus structure and the simulated results are compared with prevailing algorithms. It is observed that the transfer capacity of existing line is increased with the presented algorithm and thus alleviating the congestion.

Keywords: available line transfer capability, congestion management, FACTS device, Hybrid Fish-Bee Algorithm, ISO, UPFC

Procedia PDF Downloads 375

Authors: Charles Amoo, Joshua New, Bill Eckman

Abstract:

Buildings in the United States account for a significant proportion of energy consumption and greenhouse gas (GHG) emissions, and this trend is expected to continue as well as rise in the near future. Low-income households, in particular, bear a disproportionate burden of high building energy consumption and spending due to high energy costs. Energy efficiency improvements need to reach an average of 4% per year in this decade in order to meet global net zero emissions target by 2050, but less than 1 % of U.S. buildings are improved each year. The government has recognized the importance of technology in addressing this issue, and energy efficiency programs have been developed to tackle the problem. The Weatherization Assistance Program (WAP), the largest residential whole-house energy efficiency program in the U.S., is specifically designed to reduce energy costs for low-income households. Under the WAP, energy auditors must follow specific audit procedures and use Department of Energy (DOE) approved energy audit tools or software. This article proposes an expanded framework of factors that should be considered in energy audit software that is approved for use in energy efficiency programs, particularly for low-income households. The framework includes more than 50 factors organized under 14 assessment criteria and can be used to qualitatively and quantitatively score different energy audit software to determine their suitability for specific energy efficiency programs. While the tool can be useful for developers to build new tools and improve existing software, as well as for energy efficiency program administrators to approve or certify tools for use, there are limitations to the model, such as the lack of flexibility that allows continuous scoring to accommodate variability and subjectivity. These limitations can be addressed by using aggregate scores of each criterion as weights that could be combined with value function and direct rating scores in a multicriteria decision analysis for a more flexible scoring.

Keywords: buildings, energy efficiency, energy audit, software

Procedia PDF Downloads 70