Search results for: equation model
14427 Parameter Estimation of Additive Genetic and Unique Environment (AE) Model on Diabetes Mellitus Type 2 Using Bayesian Method
Authors: Andi Darmawan, Dewi Retno Sari Saputro, Purnami Widyaningsih
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Diabetes mellitus (DM) is a chronic disease in human that occurred if pancreas cannot produce enough of insulin hormone or the body uses ineffectively insulin hormone which causes increasing level of glucose in the blood, or it was called hyperglycemia. In Indonesia, DM is a serious disease on health because it can cause blindness, kidney disease, diabetic feet (gangrene), and stroke. The type of DM criteria can also be divided based on the main causes; they are DM type 1, type 2, and gestational. Diabetes type 1 or previously known as insulin-independent diabetes is due to a lack of production of insulin hormone. Diabetes type 2 or previously known as non-insulin dependent diabetes is due to ineffective use of insulin while gestational diabetes is a hyperglycemia that found during pregnancy. The most one type commonly found in patient is DM type 2. The main factors of this disease are genetic (A) and life style (E). Those disease with 2 factors can be constructed with additive genetic and unique environment (AE) model. In this article was discussed parameter estimation of AE model using Bayesian method and the inheritance character simulation on parent-offspring. On the AE model, there are response variable, predictor variables, and parameters were capable of representing the number of population on research. The population can be measured through a taken random sample. The response and predictor variables can be determined by sample while the parameters are unknown, so it was required to estimate the parameters based on the sample. Estimation of AE model parameters was obtained based on a joint posterior distribution. The simulation was conducted to get the value of genetic variance and life style variance. The results of simulation are 0.3600 for genetic variance and 0.0899 for life style variance. Therefore, the variance of genetic factor in DM type 2 is greater than life style.Keywords: AE model, Bayesian method, diabetes mellitus type 2, genetic, life style
Procedia PDF Downloads 28414426 The Effect of Material Properties and Volumetric Changes in Phase Transformation to the Final Residual Stress of Welding Process
Authors: Djarot B. Darmadi
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The wider growing Finite Element Method (FEM) application is caused by its benefits of cost saving and environment friendly. Also, by using FEM a deep understanding of certain phenomenon can be achieved. This paper observed the role of material properties and volumetric change when Solid State Phase Transformation (SSPT) takes place in residual stress formation due to a welding process of ferritic steels through coupled Thermo-Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by experiment. From parametric study of the FEM model, it can be concluded that the material properties change tend to over-predicts residual stress in the weld center whilst volumetric change tend to underestimates it. The best final result is the compromise of both by incorporates them in the model which has a better result compared to a model without SSPT.Keywords: residual stress, ferritic steels, SSPT, coupled-TMM
Procedia PDF Downloads 27014425 The Origin, Diffusion and a Comparison of Ordinary Differential Equations Numerical Solutions Used by SIR Model in Order to Predict SARS-CoV-2 in Nordic Countries
Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco
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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.Keywords: forecasting, ordinary differential equations, SARS-COV-2 epidemic, SIR model
Procedia PDF Downloads 15214424 GPS Devices to Increase Efficiency of Indian Auto-Rickshaw Segment
Authors: Sanchay Vaidya, Sourabh Gupta, Gouresh Singhal
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There are various modes of transport in metro cities in India, auto-rickshaws being one of them. Auto-rickshaws provide connectivity to all the places in the city offering last mile connectivity. Among all the modes of transport, the auto-rickshaw industry is the most unorganized and inefficient. Although unions exist in different cities they aren’t good enough to cope up with the upcoming advancements in the field of technology. An introduction of simple technology in this field may do wonder and help increase the revenues. This paper aims to organize this segment under a single umbrella using GPS devices and mobile phones. The paper includes surveys of about 300 auto-rickshaw drivers and 1000 plus commuters across 6 metro cities in India. Carrying out research and analysis provides a base for the development of this model and implementation of this innovative technique, which is discussed in this paper in detail with ample emphasis given on the implementation of this model.Keywords: auto-rickshaws, business model, GPS device, mobile application
Procedia PDF Downloads 22714423 A Novel Approach of Power Transformer Diagnostic Using 3D FEM Parametrical Model
Authors: M. Brandt, A. Peniak, J. Makarovič, P. Rafajdus
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This paper deals with a novel approach of power transformers diagnostics. This approach identifies the exact location and the range of a fault in the transformer and helps to reduce operation costs related to handling of the faulty transformer, its disassembly and repair. The advantage of the approach is a possibility to simulate healthy transformer and also all faults, which can occur in transformer during its operation without its disassembling, which is very expensive in practice. The approach is based on creating frequency dependent impedance of the transformer by sweep frequency response analysis measurements and by 3D FE parametrical modeling of the fault in the transformer. The parameters of the 3D FE model are the position and the range of the axial short circuit. Then, by comparing the frequency dependent impedances of the parametrical models with the measured ones, the location and the range of the fault is identified. The approach was tested on a real transformer and showed high coincidence between the real fault and the simulated one.Keywords: transformer, parametrical model of transformer, fault, sweep frequency response analysis, finite element method
Procedia PDF Downloads 48314422 Excitation Modeling for Hidden Markov Model-Based Speech Synthesis Based on Wavelet Analysis
Authors: M. Kiran Reddy, K. Sreenivasa Rao
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The conventional Hidden Markov Model (HMM)-based speech synthesis system (HTS) uses only a pulse excitation model, which significantly differs from natural excitation signal. Hence, buzziness can be perceived in the speech generated using HTS. This paper proposes an efficient excitation modeling method that can significantly reduce the buzziness, and improve the quality of HMM-based speech synthesis. The proposed approach models the pitch-synchronous residual frames extracted from the residual excitation signal. Each pitch synchronous residual frame is parameterized using 30 wavelet coefficients. These 30 wavelet coefficients are found to accurately capture the perceptually important information present in the residual waveform. In synthesis phase, the residual frames are reconstructed from the generated wavelet coefficients and are pitch-synchronously overlap-added to generate the excitation signal. The proposed excitation modeling method is integrated into HMM-based speech synthesis system. Evaluation results indicate that the speech synthesized by the proposed excitation model is significantly better than the speech generated using state-of-the-art excitation modeling methods.Keywords: excitation modeling, hidden Markov models, pitch-synchronous frames, speech synthesis, wavelet coefficients
Procedia PDF Downloads 24914421 Effect of Slope Height and Horizontal Forces on the Bearing Capacity of Strip Footings near Slopes in Cohesionless Soil
Authors: Sven Krabbenhoft, Kristian Krabbenhoft, Lars Damkilde
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The problem of determining the bearing capacity of a strip foundation located near a slope of infinite height has been dealt with by several authors. Very often in practical problems the slope is of limited height, and furthermore the resulting load may be inclined at an angle to the horizontal, and in such cases the bearing capacity of the footing cannot be found using the existing methods. The present work comprises finite element based upper- and lower-bound calculations, using the geotechnical software OptumG2 to investigate the effect of the slope height and horizontal forces on the total bearing capacity, both without and with using superposition as presupposed in the traditional bearing capacity equation. The results for friction angles 30, 35 and 40 degrees, slope inclinations 1:2, 1:3 and 1:4, for selfweight and surcharge are given as charts showing the slope inclination factors suitable for design.Keywords: footings, bearing capacity, slopes, cohesionnless soil
Procedia PDF Downloads 46614420 Adopting the Transition Management Model as a Tool for Sustainable Groundwater Management in Nigeria
Authors: Ali Bakari Mohammed
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Transitioning is a continuous process of radical change in a society which involves co-evolution of institutional, technological, socio-cultural, and ecological developments at different scales and levels. Transition management model is a methodology that influences structural change of complex systems over a period (0-30 years) by experimenting and implementing new techniques. A transition management in the context of groundwater is a radical change from the current operate and control system to a next generation integrated and sustainable system that takes into account quality protection and sustained supply into the future. This study evaluates the transition management model in adopting it as a viable tool for the attainment of sustainable groundwater management. The outcome of the evaluation shows that there are three levels (strategic, tactical and operational) of operating the transition management model. At the strategic level, long-term goals for sustainable groundwater management are formulated, at the tactical level activities such as inter institutional networking, negotiation, planning and financing are carried out, and at the operational level, transition experiments and strategic niche management are carried out at the societal level. Overall, different actors and set of activities are required to partake at each management level. The outcome of this paper will provide basis for the implementation of the Sustainable Development Goal (SDG) 6 in Nigeria.Keywords: transition management, groundwater, sustainable management, tool, Nigeria
Procedia PDF Downloads 27114419 Cryptocurrencies: Business Students’ Awareness and Universities’ Adoption Readiness and Compatibility of Use Considering the Mediation of Attitudes
Authors: Eric S. Parilla, Marc Edward Abadilla
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The study aims to determine the effect of awareness of business students towards cryptocurrencies and the readiness of universities and colleges to accept cryptocurrencies as a medium of exchange, considering the mediation of business students’ attitudes. The research used partial least squares structural equation modeling (PLS-SEM) and deployed a questionnaire attuned to the awareness and attitudes of business students towards cryptocurrencies and readiness and compatibility of use in universities and colleges in Ilocos Norte. The output of the investigation revealed that awareness of business students is not correlated to the readiness of universities and colleges, which means that even though students understand cryptocurrencies, it is not an assurance that universities and colleges are ready to accept them as the medium of exchange. The study proposes that training and seminars for business students and professionals should be conducted to expand understanding and acceptance of cryptocurrencies.Keywords: cryptocurrencies, awareness, readiness, attitudes
Procedia PDF Downloads 22514418 Uplift Segmentation Approach for Targeting Customers in a Churn Prediction Model
Authors: Shivahari Revathi Venkateswaran
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Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering
Procedia PDF Downloads 7114417 Gimbal Structure for the Design of 3D Flywheel System
Authors: Cheng-En Tsai, Chung-Chun Hsiao, Fu-Yuan Chang, Liang-Lun Lan, Jia-Ying Tu
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New design of three dimensional (3D) flywheel system based on gimbal and gyro mechanics is proposed. The 3D flywheel device utilizes the rotational motion of three spherical shells and the conservation of angular momentum to achieve planar locomotion. Actuators mounted to the ring-shape frames are installed within the system to drive the spherical shells to rotate, for the purpose of steering and stabilization. Similar to the design of 2D flywheel system, it is expected that the spherical shells may function like a “flyball” to store and supply mechanical energy; additionally, in comparison with typical single-wheel and spherical robots, the 3D flywheel can be used for developing omnidirectional robotic systems with better mobility. The Lagrangian method is applied to derive the equation of motion of the 3D flywheel system, and simulation studies are presented to verify the proposed design.Keywords: Gimbal, spherical robot, gyroscope, Lagrangian formulation, flyball
Procedia PDF Downloads 62914416 Finding the Reaction Constant between Humic Acid and Aluminum Ion by Fluorescence Quenching Effect
Authors: Wen Po Cheng, Chen Zhao Feng, Ruey Fang Yu, Lin Jia Jun, Lin Ji Ye, Chen Yuan Wei
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Humic acid was used as the removal target for evaluating the coagulation efficiency in this study. When the coagulant ions mix with a humic acid solution, a Fluorescence quenching effect may be observed conditionally. This effect can be described by Stern-Volmer linear equation which can be used for quantifying the quenching value (Kq) of the Fluorescence quenching effect. In addition, a Complex-Formation Titration (CFT) theory was conducted and the result was used to explain the electron-neutralization capability of the coagulant (AlCl₃) at different pH. The results indicated that when pH of the ACl₃ solution was between 6 and 8, fluorescence quenching effect obviously occurred. The maximum Kq value was found to be 102,524 at pH 6. It means that the higher the Kq value is, the better complex reaction between a humic acid and aluminum salts will be. Through the Kq value study, the optimum pH can be quantified when the humic acid solution is coagulated with aluminum ions.Keywords: humic acid, fluorescence quenching effect, complex reaction, titration
Procedia PDF Downloads 57814415 Marketing in the Age of Artificial Intelligence: Implications for Consumption Patterns of Halal Food
Authors: Djermani Farouk, Sri Rahayu Hijrah Hati, Fenitra Maminirin, Permata Wulandari
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This study investigates the implications of Artificial Intelligence Marketing (AIM) marketing mix (PRD) Product, (PRC) Price, (PRM), Promotion and (PLC) Place on consumption patterns of halal food (CPHF). A quantitative approach was adopted in this study and responses were obtained from 350 Indonesian consumers. Using Partial Least Squares-Structural Equation Modeling (PLS-SEM), the results show that there is a direct support of marketing mix (PRD, PRC, PLC) to AIM and CPHF, while PRM does not play a significant role in CPHF. In addition, the findings reveal that AIM mediates significantly the relationship between PLC, PRC and PRM and CPHF, while AIM indicates no mediation between PRD and CPHF. Indonesian consumer’s exhibit serious concerns with consumption patterns of halal food. it is recommended that managers focus their attention on marketing strategies to predict consumer behavior in terms of consumption patterns of halal food through the integration of AIM.Keywords: marketing mix, consumption patterns, artificial intelligence marketing, Halal food
Procedia PDF Downloads 3414414 Agriculture and Global Economy vis-à-vis the Climate Change
Authors: Assaad Ghazouani, Ati Abdessatar
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In the world, agriculture maintains a social and economic importance in the national economy. Its importance is distinguished by its ripple effects not only downstream but also upstream vis-à-vis the non-agricultural sector. However, the situation is relatively fragile because of weather conditions. In this work, we propose a model to highlight the impacts of climate change (CC) on economic growth in the world where agriculture is considered as a strategic sector. The CC is supposed to directly and indirectly affect economic growth by reducing the performance of the agricultural sector. The model is tested for Tunisia. The results validate the hypothesis that the potential economic damage of the CC is important. Indeed, an increase in CO2 concentration (temperatures and disruption of rainfall patterns) will have an impact on global economic growth particularly by reducing the performance of the agricultural sector. Analysis from a vector error correction model also highlights the magnitude of climate impact on the performance of the agricultural sector and its repercussions on economic growthKeywords: Climate Change, Agriculture, Economic Growth, World, VECM, Cointegration.
Procedia PDF Downloads 61914413 A Selection Approach: Discriminative Model for Nominal Attributes-Based Distance Measures
Authors: Fang Gong
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Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor
Procedia PDF Downloads 11414412 Sea-Spray Calculations Using the MESO-NH Model
Authors: Alix Limoges, William Bruch, Christophe Yohia, Jacques Piazzola
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A number of questions arise concerning the long-term impact of the contribution of marine aerosol fluxes generated at the air-sea interface on the occurrence of intense events (storms, floods, etc.) in the coastal environment. To this end, knowledge is needed on sea-spray emission rates and the atmospheric dynamics of the corresponding particles. Our aim is to implement the mesoscale model MESO-NH on the study area using an accurate sea-spray source function to estimate heat fluxes and impact on the precipitations. Based on an original and complete sea-spray source function, which covers a large size spectrum since taking into consideration the sea-spray produced by both bubble bursting and surface tearing process, we propose a comparison between model simulations and experimental data obtained during an oceanic scientific cruise on board the navy ship Atalante. The results show the relevance of the sea-spray flux calculations as well as their impact on the heat fluxes and AOD.Keywords: atmospheric models, sea-spray source, sea-spray dynamics, aerosols
Procedia PDF Downloads 14914411 Tuning Cubic Equations of State for Supercritical Water Applications
Authors: Shyh Ming Chern
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Cubic equations of state (EoS), popular due to their simple mathematical form, ease of use, semi-theoretical nature and, reasonable accuracy are normally fitted to vapor-liquid equilibrium P-v-T data. As a result, They often show poor accuracy in the region near and above the critical point. In this study, the performance of the renowned Peng-Robinson (PR) and Patel-Teja (PT) EoS’s around the critical area has been examined against the P-v-T data of water. Both of them display large deviations at critical point. For instance, PR-EoS exhibits discrepancies as high as 47% for the specific volume, 28% for the enthalpy departure and 43% for the entropy departure at critical point. It is shown that incorporating P-v-T data of the supercritical region into the retuning of a cubic EoS can improve its performance above the critical point dramatically. Adopting a retuned acentric factor of 0.5491 instead of its genuine value of 0.344 for water in PR-EoS and a new F of 0.8854 instead of its original value of 0.6898 for water in PT-EoS reduces the discrepancies to about one third or less.Keywords: equation of state, EoS, supercritical water, SCW
Procedia PDF Downloads 53514410 The Intention to Use Telecare in People of Fall Experience: Application of Fuzzy Neural Network
Authors: Jui-Chen Huang, Shou-Hsiung Cheng
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This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.Keywords: fall, fuzzy neural network, health belief model, telecare, willingness
Procedia PDF Downloads 20114409 The Case for Strategic Participation: How Facilitated Engagement Can Be Shown to Reduce Resistance and Improve Outcomes Through the Use of Strategic Models
Authors: Tony Mann
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This paper sets out the case for involving and engaging employees/workers/stakeholders/staff in any significant change that is being considered by the senior executives of the organization. It establishes the rationale, the approach, the methodology of engagement and the benefits of a participative approach. It challenges the new norm of imposing change for fear of resistance and instead suggests that involving people has better outcomes and a longer-lasting impact. Various strategic models are introduced and illustrated to explain how the process can be most effective. The paper highlights one model in particular (the Process Iceberg® Organizational Change model) that has proven to be instrumental in developing effective change. Its use is demonstrated in its various forms and explains why so much change fails to address the key elements and how we can be more productive in managing change. ‘Participation’ in change is too often seen as negative, expensive and unwieldy. The paper aims to show that another model: UIA=O+E, can offset the difficulties and, in fact, produce much more positive and effective change.Keywords: facilitation, stakeholders, buy-in, digital workshops
Procedia PDF Downloads 11014408 Investigation of a Technology Enabled Model of Home Care: the eShift Model of Palliative Care
Authors: L. Donelle, S. Regan, R. Booth, M. Kerr, J. McMurray, D. Fitzsimmons
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Palliative home health care provision within the Canadian context is challenged by: (i) a shortage of registered nurses (RN) and RNs with palliative care expertise, (ii) an aging population, (iii) reliance on unpaid family caregivers to sustain home care services with limited support to conduct this ‘care work’, (iv) a model of healthcare that assumes client self-care, and (v) competing economic priorities. In response, an interprofessional team of service provider organizations, a software/technology provider, and health care providers developed and implemented a technology-enabled model of home care, the eShift model of palliative home care (eShift). The eShift model combines communication and documentation technology with non-traditional utilization of health human resources to meet patient needs for palliative care in the home. The purpose of this study was to investigate the structure, processes, and outcomes of the eShift model of care. Methodology: Guided by Donebedian’s evaluation framework for health care, this qualitative-descriptive study investigated the structure, processes, and outcomes care of the eShift model of palliative home care. Interviews and focus groups were conducted with health care providers (n= 45), decision-makers (n=13), technology providers (n=3) and family care givers (n=8). Interviews were recorded, transcribed, and a deductive analysis of transcripts was conducted. Study Findings (1) Structure: The eShift model consists of a remotely-situated RN using technology to direct care provision virtually to patients in their home. The remote RN is connected virtually to a health technician (an unregulated care provider) in the patient’s home using real-time communication. The health technician uses a smartphone modified with the eShift application and communicates with the RN who uses a computer with the eShift application/dashboard. Documentation and communication about patient observations and care activities occur in the eShift portal. The RN is typically accountable for four to six health technicians and patients over an 8-hour shift. The technology provider was identified as an important member of the healthcare team. Other members of the team include family members, care coordinators, nurse practitioners, physicians, and allied health. (2) Processes: Conventionally, patient needs are the focus of care; however within eShift, the patient and the family caregiver were the focus of care. Enhanced medication administration was seen as one of the most important processes, and family caregivers reported high satisfaction with the care provided. There was perceived enhanced teamwork among health care providers. (3) Outcomes: Patients were able to die at home. The eShift model enabled consistency and continuity of care, and effective management of patient symptoms and caregiver respite. Conclusion: More than a technology solution, the eShift model of care was viewed as transforming home care practice and an innovative way to resolve the shortage of palliative care nurses within home care.Keywords: palliative home care, health information technology, patient-centred care, interprofessional health care team
Procedia PDF Downloads 41814407 Multi-Objective Simulated Annealing Algorithms for Scheduling Just-In-Time Assembly Lines
Authors: Ghorbanali Mohammadi
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New approaches to sequencing mixed-model manufacturing systems are present. These approaches have attracted considerable attention due to their potential to deal with difficult optimization problems. This paper presents Multi-Objective Simulated Annealing Algorithms (MOSAA) approaches to the Just-In-Time (JIT) sequencing problem where workload-smoothing (WL) and the number of set-ups (St) are to be optimized simultaneously. Mixed-model assembly lines are types of production lines where varieties of product models similar in product characteristics are assembled. Moreover, this type of problem is NP-hard. Two annealing methods are proposed to solve the multi-objective problem and find an efficient frontier of all design configurations. The performances of the two methods are tested on several problems from the literature. Experimentation demonstrates the relative desirable performance of the presented methodology.Keywords: scheduling, just-in-time, mixed-model assembly line, sequencing, simulated annealing
Procedia PDF Downloads 12814406 Creative Self-efficacy and Innovation Speed of New Ventures: The Mediating Role of Entrepreneurial Bricolage
Authors: Yi-Wen Chen, Hsueh-Liang Fan
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Evidence shows that start-ups success is positively correlated with innovation speed. However, new ventures are seldom able to acquire abundant resources for new product development (NPD), which means that entrepreneurs may depend on personal creativity instead of physical investments to achieve and accelerate speed of first product launch. This study accentuates the role of entrepreneurial bricolage, which defined as making do by applying combinations of the resources at hand to new problems and opportunities, in the relations of creative self-efficacy and innovation speed. This study uses structural equation modeling to test the hypotheses in a sample of 203 start-ups operating various creative markets. Results reveal that creative self-efficacy is positively and directly associated with innovation speed, whereas entrepreneurial bricolage plays a full mediator. These findings offer important theoretical and practical implications.Keywords: creative self-efficacy, innovation speed, entrepreneurial bricolage, new ventures
Procedia PDF Downloads 53014405 A Sharp Interface Model for Simulating Seawater Intrusion in the Coastal Aquifer of Wadi Nador (Algeria)
Authors: Abdelkader Hachemi, Boualem Remini
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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.Keywords: seawater intrusion, sharp interface, coastal aquifer, algeria
Procedia PDF Downloads 12014404 Molecular Communication Noise Effect Analysis of Diffusion-Based Channel for Considering Minimum-Shift Keying and Molecular Shift Keying Modulations
Authors: A. Azari, S. S. K. Seyyedi
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One of the unaddressed and open challenges in the nano-networking is the characteristics of noise. The previous analysis, however, has concentrated on end-to-end communication model with no separate modelings for propagation channel and noise. By considering a separate signal propagation and noise model, the design and implementation of an optimum receiver will be much easier. In this paper, we justify consideration of a separate additive Gaussian noise model of a nano-communication system based on the molecular communication channel for which are applicable for MSK and MOSK modulation schemes. The presented noise analysis is based on the Brownian motion process, and advection molecular statistics, where the received random signal has a probability density function whose mean is equal to the mean number of the received molecules. Finally, the justification of received signal magnitude being uncorrelated with additive non-stationary white noise is provided.Keywords: molecular, noise, diffusion, channel
Procedia PDF Downloads 27914403 Decoding Socio-Cultural Trends in Indian Urban Youth Using Ogilvy 3E Model
Authors: Falguni Vasavada, Pradyumna Malladi
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The research focuses on studying the ecosystem of the youth using Ogilvy's 3E model, Ethnography and Thematic Analysis. It has been found that urban Indian youth today is an honest generation, hungry for success, living life by the moment, fiercely independent, are open about sex, sexuality and embrace individual differences. Technology and social media dominate their life. However, they are also phobic about commitments, often drifting along life and engage in unsubstantiated brave-talk.Keywords: ethnography, youth, culture, track, buyer behavior
Procedia PDF Downloads 36014402 Estimation of Optimum Parameters of Non-Linear Muskingum Model of Routing Using Imperialist Competition Algorithm (ICA)
Authors: Davood Rajabi, Mojgan Yazdani
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Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood
Procedia PDF Downloads 50514401 Time Series Analysis the Case of China and USA Trade Examining during Covid-19 Trade Enormity of Abnormal Pricing with the Exchange rate
Authors: Md. Mahadi Hasan Sany, Mumenunnessa Keya, Sharun Khushbu, Sheikh Abujar
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Since the beginning of China's economic reform, trade between the U.S. and China has grown rapidly, and has increased since China's accession to the World Trade Organization in 2001. The US imports more than it exports from China, reducing the trade war between China and the U.S. for the 2019 trade deficit, but in 2020, the opposite happens. In international and U.S. trade, Washington launched a full-scale trade war against China in March 2016, which occurred a catastrophic epidemic. The main goal of our study is to measure and predict trade relations between China and the U.S., before and after the arrival of the COVID epidemic. The ML model uses different data as input but has no time dimension that is present in the time series models and is only able to predict the future from previously observed data. The LSTM (a well-known Recurrent Neural Network) model is applied as the best time series model for trading forecasting. We have been able to create a sustainable forecasting system in trade between China and the US by closely monitoring a dataset published by the State Website NZ Tatauranga Aotearoa from January 1, 2015, to April 30, 2021. Throughout the survey, we provided a 180-day forecast that outlined what would happen to trade between China and the US during COVID-19. In addition, we have illustrated that the LSTM model provides outstanding outcome in time series data analysis rather than RFR and SVR (e.g., both ML models). The study looks at how the current Covid outbreak affects China-US trade. As a comparative study, RMSE transmission rate is calculated for LSTM, RFR and SVR. From our time series analysis, it can be said that the LSTM model has given very favorable thoughts in terms of China-US trade on the future export situation.Keywords: RFR, China-U.S. trade war, SVR, LSTM, deep learning, Covid-19, export value, forecasting, time series analysis
Procedia PDF Downloads 19814400 Competency Based Talent Acquisition: Concept, Practice, and Model, with Reference to Indian Industries
Authors: Manasi V. Shah
Abstract:
Organizations, in the competitive era, are participating in the competency act. They have discerned that, strategically researched and defined competencies when put up on the shelf, can help in achieving business goals. The research focuses on critical elements of competency-based talent acquisition process from practical vantage, with significant experience in a variety of business settings. The research is exploratory and descriptive in nature. The research conduct and outcome is the hinge on with reference to Indian Industries. It elaborates about the concept, practice and a brief model that human resource practitioner can use for effective talent acquisition process, which in turn would be in alignment with business performance. The research helps to present a prudent understanding of recruiting and selecting apt human capital, that can fit in a given job role and has action oriented competency based assessment approach for measuring the probable success of a job incumbent in a given job role.Keywords: competency based talent acquisition, competency model, talent acquisition concept, talent acquisition practice
Procedia PDF Downloads 31214399 Using Social Network Analysis for Cyber Threat Intelligence
Authors: Vasileios Anastopoulos
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Cyber threat intelligence assists organizations in understanding the threats they face and helps them make educated decisions on preparing their defenses. Sharing of threat intelligence and threat information is increasingly leveraged by organizations and enterprises, and various software solutions are already available, with the open-source malware information sharing platform (MISP) being a popular one. In this work, a methodology for the production of cyber threat intelligence using the threat information stored in MISP is proposed. The methodology leverages the discipline of social network analysis and the diamond model, a model used for intrusion analysis, to produce cyber threat intelligence. The workings are demonstrated with a case study on a production MISP instance of a real organization. The paper concluded with a discussion on the proposed methodology and possible directions for further research.Keywords: cyber threat intelligence, diamond model, malware information sharing platform, social network analysis
Procedia PDF Downloads 17814398 Combined Analysis of m⁶A and m⁵C Modulators on the Prognosis of Hepatocellular Carcinoma
Authors: Hongmeng Su, Luyu Zhao, Yanyan Qian, Hong Fan
Abstract:
Aim: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that endanger human health seriously. RNA methylation, especially N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), a crucial epigenetic transcriptional regulatory mechanism, plays an important role in tumorigenesis, progression and prognosis. This research aims to systematically evaluate the prognostic value of m⁶A and m⁵C modulators in HCC patients. Methods: Twenty-four modulators of m⁶A and m⁵C were candidates to analyze their expression level and their contribution to predict the prognosis of HCC. Consensus clustering analysis was applied to classify HCC patients. Cox and LASSO regression were used to construct the risk model. According to the risk score, HCC patients were divided into high-risk and low/medium-risk groups. The clinical pathology factors of HCC patients were analyzed by univariate and multivariate Cox regression analysis. Results: The HCC patients were classified into 2 clusters with significant differences in overall survival and clinical characteristics. Nine-gene risk model was constructed including METTL3, VIRMA, YTHDF1, YTHDF2, NOP2, NSUN4, NSUN5, DNMT3A and ALYREF. It was indicated that the risk score could serve as an independent prognostic factor for patients with HCC. Conclusion: This study constructed a Nine-gene risk model by modulators of m⁶A and m⁵C and investigated its effect on the clinical prognosis of HCC. This model may provide important consideration for the therapeutic strategy and prognosis evaluation analysis of patients with HCC.Keywords: hepatocellular carcinoma, m⁶A, m⁵C, prognosis, RNA methylation
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