Search results for: context based planning model

Authors: Thanh N. Do

Abstract:

This paper addresses the modeling of two critical behaviors of concrete material in reinforced concrete components: (1) the increase in strength and ductility due to confining stresses from surrounding transverse steel reinforcements, and (2) the progressive deterioration in strength and stiffness due to high strain and/or cyclic loading. To improve the state-of-the-art, the author presents a new 3D constitutive model of concrete material based on plasticity and continuum damage mechanics theory to simulate both the confinement effect and the strength deterioration in reinforced concrete components. The model defines a yield function of the stress invariants and a compressive damage threshold based on the level of confining stresses to automatically capture the increase in strength and ductility when subjected to high compressive stresses. The model introduces two damage variables to describe the strength and stiffness deterioration under tensile and compressive stress states. The damage formulation characterizes well the degrading behavior of concrete material, including the nonsymmetric strength softening in tension and compression, as well as the progressive strength and stiffness degradation under primary and follower load cycles. The proposed damage model is implemented in a general purpose finite element analysis program allowing an extensive set of numerical simulations to assess its ability to capture the confinement effect and the degradation of the load-carrying capacity and stiffness of structural elements. It is validated against a collection of experimental data of the hysteretic behavior of reinforced concrete columns and shear walls under different load histories. These correlation studies demonstrate the ability of the model to describe vastly different hysteretic behaviors with a relatively consistent set of parameters. The model shows excellent consistency in response determination with very good accuracy. Its numerical robustness and computational efficiency are also very good and will be further assessed with large-scale simulations of structural systems.

Keywords: concrete, damage-plasticity, shear wall, confinement

Procedia PDF Downloads 173

Authors: Seung-Un Chae, Heung-Yul Kim, Sa-Kil Kim

Abstract:

This paper presents the findings of preliminary study on human control performance in case of fire. The relationship between human control and human decision is studied in decision processes and stress model of human in a fire. Human behavior aspects involved in the decision process during a fire incident. The decision processes appear that six of individual perceptual processes: recognition, validation, definition, evaluation, commitment, and reassessment. Then, human may be stressed in order to get an optimal decision for their activity. This paper explores problems in human control processes and stresses in a catastrophic situation. Thus, the future approach will be concerned to reduce stresses and ambiguous irrelevant information.

Keywords: human reliability, decision processes, stress model, fire

Procedia PDF Downloads 990

Authors: F. Calderón-Vega, A. D. García-Soto, C. Mösso

Abstract:

Recorded significant wave heights sometimes exhibit large uncommon values (outliers) that can be associated with extreme phenomena such as hurricanes and cold fronts. In this study, some extremely large wave heights recorded in NOAA buoys (National Data Buoy Center, noaa.gov) are used to investigate their effect in the prediction of future wave heights associated with given return periods. Extreme waves are predicted through a time-dependent model based on the so-called generalized extreme value distribution. It is found that the outliers do affect the estimated wave heights. It is concluded that a detailed inspection of outliers is envisaged to determine whether they are real recorded values since this will impact defining design wave heights for coastal protection purposes.

Keywords: GEV model, non-stationary, seasonality, outliers

Procedia PDF Downloads 202

Authors: Rachel S. E. Lim, Winnie L. C. Tan

Abstract:

Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

Procedia PDF Downloads 116

Authors: Elham Koohikerade, Silvio Jose Gumiere

Abstract:

In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

Procedia PDF Downloads 47

Authors: Shahid Nishat, Keith Thomas

Abstract:

E-government initiatives attract substantial public investments around the world. These investments are based on the premise of digital transformation of the public services, improved efficiency and transparency, and citizen participation in the social democratic processes. However, many e-Government projects, especially in developing countries, fail to achieve their intended outcomes, and a strong disparity exists between the investments made and outcomes achieved, often referred to as e-Government paradox. Further, there is lack of research on evaluating the impacts of e-Government in terms of public value it creates, which ultimately drives usage. This study aims to address these gaps by identifying key enablers of e-Government success and by proposing a public value based framework to examine impact of e-Government services. The study will extend Delone and McLean Information System (IS) Success model by integrating Technology Readiness (TR) characteristics to develop an integrated success model. Level of analysis will be mobile government applications, and the framework will be empirically tested using quantitative methods. The research will add to the literature on e-Government success and will be beneficial for governments, especially in developing countries aspiring to improve public services through the use of Information Communication Technologies (ICT).

Keywords: e-Government, IS success model, public value, technology adoption, technology readiness

Procedia PDF Downloads 135

Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia

Abstract:

This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.

Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry

Procedia PDF Downloads 131

Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri

Abstract:

Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.

Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size

Procedia PDF Downloads 228

Authors: Anh T. P. Tran, Harald Von Korflesch

Abstract:

Entrepreneurial intention play a major role in entrepreneurship academia and practice. The spectrum ranges from the first model of the so-called Entrepreneurial Event, then the Theory of Planned Behavior, the Theory of Planned Behavior Entrepreneurial Model, and the Social Cognitive Career Theory to some typical empirical studies with more or less diverse results. However, little is known so far about the intentions of entrepreneurs in the social areas of venture creation. It is surprising that, since social entrepreneurship is an emerging field with growing importance. Currently, all around the world, there is a big challenge with a lot of urgent soaring social and environmental problems such as poor households, people with disabilities, HIV/AIDS infected people, the lonely elderly, or neglected children, some of them even actual in the Western countries. In addition, the already existing literature on entrepreneurial intentions demonstrates a high level of theoretical diversity in general, especially the missing link to the social dimension of entrepreneurship. Seeking to fill the mentioned gaps in the social entrepreneurial intentions literature, this paper proposes a conceptual model of social entrepreneurial intentions based on the Social Cognitive Career Theory with two main factors influencing entrepreneurial intentions namely self-efficacy and outcome expectation. Moreover, motives, goals and plans do not arise from empty nothingness, but are shaped by interacting with the environment. Hence, personalities (i.e., agreeableness, conscientiousness, extraversion, neuroticism, openness) as well as contextual factors (e.g., role models, education, and perceived support) are also considered as the antecedents of social entrepreneurship intentions.

Keywords: entrepreneurial intention, social cognitive career theory, social entrepreneurial intention, social entrepreneurship

Procedia PDF Downloads 483

Authors: Victor Birikorang Danquah

Abstract:

Ghana's primary energy supply is heavily reliant on petroleum, biomass, and hydropower. Currently, Ghana gets its energy from hydropower (Akosombo and Bui), thermal power plants powered by crude oil, natural gas, and diesel, solar power, and imports from La Cote d'Ivoire. Until the early 2000s, large hydroelectric dams dominated Ghana's electricity generation. Due to unreliable weather patterns, Ghana increased its reliance on thermal power. However, thermal power contributes the highest percentage in terms of electricity generation in Ghana and is predominantly supplied by Independent Power Producers (IPPs). Ghana's electricity industry operates the corporate utility model as its business model. This model is typically' vertically integrated,' with a single corporation selling the majority of power generated by its generation assets to its retail business, which then sells the electricity to retail market consumers. The corporate utility model has a straightforward value proposition that is based on increasing the number of energy units sold. The unit volume business model drives the entire energy value chain to increase throughput, locking system users into unsustainable practices. This report uses the qualitative research approach to explore the electricity industry in Ghana. There is a need for increasing renewable energy, such as wind and solar, in electricity generation. The research recommends two critical business models for the penetration of renewable energy in Ghana's power sector. The first model is the peer-to-peer electricity trading model, which relies on a software platform to connect consumers and generators in order for them to trade energy directly with one another. The second model is about encouraging local energy generation, incentivizing optimal time-of-use behaviour, and allowing any financial gains to be shared among the community members.

Keywords: business model innovation, electricity generation, renewable energy, solar energy, sustainability, wind energy

Procedia PDF Downloads 191

Authors: Yating Yang, Xue Zhang, Chengli Zhao

Abstract:

Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

Procedia PDF Downloads 99

Authors: Alireza Behfar, Mohammad Mahdavi

Abstract:

Nowadays, in the light of progress in the world of science, technology and communications, mastery of learning international languages is a sure and needful matter. In learning any language as a second language, progress and achieving a desirable level in speaking is indeed important for approximately all learners. In this research, we find out how preparation can influence L2 learners' oral fluency with respect to individual differences in working memory capacity. The participants consisted of sixty-one advanced L2 learners including MA students of TEFL at Isfahan University as well as instructors teaching English at Sadr Institute in Isfahan. The data collection consisted of two phases: A working memory test (reading span test) and a picture description task, with a one-month interval between the two tasks. Speaking was elicited through speech generation task in which the individuals were asked to discuss four topics emerging in two pairs. The two pairs included one simple and one complex topic and was accompanied by planning time and without any planning time respectively. Each topic was accompanied by several relevant pictures. L2 fluency was assessed based on preparation. The data were then analyzed in terms of the number of syllables, the number of silent pauses, and the mean length of pauses produced per minute. The study offers implications for strategies to improve learners’ both fluency and working memory.

Keywords: two factors, fluency, working memory capacity, preparation, L2 speech production reading span test picture description

Procedia PDF Downloads 235

Authors: A. Kourou, S. Kyriakopoulos, N. Anyfanti

Abstract:

A lot of children under the age of five spend their daytime hours away from their home, in a kindergarten. Caring for children is a serious subject, and their safety in case of earthquake is the first priority. Being aware of earthquakes helps to prioritize the needs and take the appropriate actions to limit the effects. Earthquakes occurring anywhere at any time require emergency planning. Earthquake planning is a cooperative effort and childcare providers have unique roles and responsibilities. Greece has high seismicity and Ionian Islands Region has the highest seismic activity of the country. The last five years Earthquake Planning and Protection Organization (EPPO), which is a national organization, has analyzed the needs and requirements of kindergartens on earthquake protection issues. In this framework it has been noticed that although the State requires child care centers to hold drills, the standards for emergency preparedness in these centers are varied, and a lot of them had not written plans for emergencies. For these reasons, EPPO supports the development of emergency planning guidance and familiarizes the day care centers’ staff being prepared for earthquakes. Furthermore, the Handbook on Day Care Earthquake Planning that has been developed by EPPO helps the providers to understand that emergency planning is essential to risk reduction. Preparedness and training should be ongoing processes, thus EPPO implements every year dozens of specific seminars on children’s disaster related needs. This research presents the results of a survey that detects the level of earthquake preparedness of kindergartens in all over the country and Ionian Islands too. A closed-form questionnaire of 20 main questions was developed for the survey in order to detect the aspects of participants concerning the earthquake preparedness actions at individual, family and day care environment level. 2668 questionnaires were gathered from March 2014 to May 2019, and analyzed by EPPO’s Department of Education. Moreover, this paper presents the EPPO’s educational activities targeted to the Ionian Islands Region that implemented in the framework of “Telemachus” Project. To provide safe environment for children to learn, and staff to work is the foremost goal of any State, community and kindergarten. This project is funded under the Priority Axis "Environmental Protection and Sustainable Development" of Operational Plan "Ionian Islands 2014-2020". It is increasingly accepted that emergency preparedness should be thought of as an ongoing process rather than a one-time activity. Creating an earthquake safe daycare environment that facilitates learning is a challenging task. Training, drills, and update of emergency plan should take place throughout the year at kindergartens to identify any gaps and to ensure the emergency procedures. EPPO will continue to work closely with regional and local authorities to actively address the needs of children and kindergartens before, during and after earthquakes.

Keywords: child care centers, education on earthquake, emergency planning, kindergartens, Ionian Islands Region of Greece

Procedia PDF Downloads 121

Authors: R. L. Ujjwal, Abhishek Jain

Abstract:

In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

Procedia PDF Downloads 373

Authors: Nattabhorn Leamcharaskul

Abstract:

This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

Procedia PDF Downloads 119

Authors: Aniruddha Joshi

Abstract:

This paper discusses a simulation study of automated sand casting production system. Therefore, the first aims of this study is development of automated sand casting process model and analyze this model with a simulation software Witness. Production methodology aims to improve overall productivity through elimination of wastes and that leads to improve quality. Integration of automation with Simulation is beneficial to identify the obstacles in implementation and to take appropriate options to implement successfully. For this integration, there are different Simulation Software’s. To study this integration, with the help of “WITNESS” Simulation Software the model is created. This model is based on literature review. The input parameters are Setup Time, Number of machines, cycle time and output parameter is number of castings, avg, and time and percentage usage of machines. Obtained results are used for Statistical Analysis. This analysis concludes the optimal solution to get maximum output.

Keywords: automated sand casting production system, simulation, WITNESS software, performance evaluation

Procedia PDF Downloads 792

Authors: V. Nagammai

Abstract:

Very-large-scale integration (VLSI) is the process of creating an integrated circuit (IC) by combining thousands of transistors into a single chip. Development of technology increases the complexity in IC manufacturing which may vary the power consumption, increase the size and latency period. Topology defines a number of connections between network. In this project, NoC topology is generated using atlas tool which will increase performance in turn determination of constraints are effective. The routing is performed by XY routing algorithm and wormhole flow control. In NoC topology generation, the value of power, area and latency are predetermined. In previous work, placement, routing and shortest path evaluation is performed using an algorithm called floor planning with cluster reconstruction and path allocation algorithm (FCRPA) with the account of 4 3x3 switch, 6 4x4 switch, and 2 5x5 switches. The usage of the 4x4 and 5x5 switch will increase the power consumption and area of the block. In order to avoid the problem, this paper has used one 8x8 switch and 4 3x3 switches. This paper uses IPRCA which of 3 steps they are placement, clustering, and shortest path evaluation. The placement is performed using min – cut placement and clustering are performed using an algorithm called cluster generation. The shortest path is evaluated using an algorithm called Dijkstra's algorithm. The power consumption of each block is determined. The experimental result shows that the area, power, and wire length improved simultaneously.

Keywords: application specific noc, b* tree representation, floor planning, t tree representation

Procedia PDF Downloads 395

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 111

Authors: Pradapet Krutchangthong, Jirawat Sudsawart

Abstract:

This research aims to study the health tourism administration and factors related to health tourism promotion at Ban Nam Chieo Community, Laem Ngop, Trat Province. The sample in this research is 361 tourists who use the service and Ban Nam Chieo Community residents who provide the service. Sampling was done from a population size of 3,780 using Taro Yamane’s formula. The tools used in the study were questionnaires and interviews. The statistics used in this research are percentage, mean and standard deviation. The result of Model Development of Health Tourism at Ban Nam Chieo Community, Laem Ngop , Trat Province shows that most of them are female with bachelor degree. They are government officers with an average income between 16,001-20,000 Baht. Suggested health system activities for health tourism development are: 1) health massage, 2) herbal compress, 3) exercise in the water by walking on shell. Meanwhile, factors related to health tourism promotion at Ban Nam Chieo Community, Laem Ngop, Trat Province are: 1) understanding the context of the community and service providers, 2) cooperation from related government and private sectors.

Keywords: health tourism, health system activities, promotion, administration

Procedia PDF Downloads 392

Authors: R. Pääkkönen, L. Korpinen

Abstract:

This study aimed to evaluate parameters influencing well-being and how to maintain well-being as long as possible after retirement. There is contradictory information on the health changes after retirement in Finland. This work is based on interviews, statistics, and literature evaluation of Finland. Most often, balance, multitasking reaction time, and adaptation of vision in dim and darks areas are worsened. Slowing is one characteristic that is difficult to measure properly. The most important is try to determine ways to manage daily activities and symptoms of disease after retirement. Medicine is advancing, problems are often also on the economic side. Information of technical aids is important. It is worth planning a retirement age.

Keywords: retirement, working, aging, wellness

Procedia PDF Downloads 241

Authors: Fuchun Li, Hong Xiao

Abstract:

We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

Procedia PDF Downloads 442

Authors: Xilu Liu, Ameen Farooq

Abstract:

Beijing has several compact residential housing settings in many of its urban districts. The study in this paper reveals that urban compactness, as predictor of density, may carry an altogether different meaning in the developing world when compared to the U.S for achieving objectives of urban sustainability. Recent urban design studies in the U.S are debating for compact and mixed-use higher density housing to achieve sustainable and energy efficient living environments. While the concept of urban compactness is widely accepted as an approach in modern architectural and urban design fields, this belief may not directly carry well into all areas within cities of developing countries. Beijing’s technology-driven economy, with its historic and rich cultural heritage and a highly speculated real-estate market, extends its urban boundaries into multiple compact urban settings of varying scales and densities. The accelerated pace of migration from the countryside for better opportunities has led to unsustainable and uncontrolled buildups in order to meet the growing population demand within and outside of the urban center. This unwarranted compactness in certain urban zones has produced an unhealthy physical density with serious environmental and ecological challenging basic living conditions. In addition, crowding, traffic congestion, pollution and limited housing surrounding this compactness is a threat to public health. Several residential blocks in close proximity to each other were found quite compacted, or ill-planned, with residential sites due to lack of proper planning in Beijing. Most of them at first sight appear to be compact and dense but further analytical studies revealed that what appear to be dense actually are not as dense as to make a good case that could serve as the corner stone of sustainability and energy efficiency. This study considered several factors including floor area ratio (FAR), ground coverage (GSI), open space ratio (OSR) as indicators in analyzing urban compactness as a predictor of density. The findings suggest that these measures, influencing the density of residential sites under study, were much smaller in density than expected given their compact adjacencies. Further analysis revealed that several residential housing appear to support the notion of density in its compact layout but are actually compacted due to unregulated planning marred by lack of proper urban design standards, policies and guidelines specific to their urban context and condition.

Keywords: Beijing, density, sustainability, urban compactness

Procedia PDF Downloads 428

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

Procedia PDF Downloads 271

Authors: Ruchika Malhotra, Megha Khanna

Abstract:

The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

Procedia PDF Downloads 421

Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

Abstract:

Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

Procedia PDF Downloads 518

Authors: Mohd Asrul Affendi Bi Abdullah, Nyi Nyi Naing

Abstract:

The purpose of this study was to identify comparable manner between negative binomial death rate (NBDR) and zero inflated negative binomial death rate (ZINBDR) with died patients with (HIV + T B+) and (HIV + T B−). HIV and TB is a serious world wide problem in the developing country. Data were analyzed with applying NBDR and ZINBDR to make comparison which a favorable model is better to used. The ZINBDR model is able to account for the disproportionately large number of zero within the data and is shown to be a consistently better fit than the NBDR model. Hence, as a results ZINBDR model is a superior fit to the data than the NBDR model and provides additional information regarding the died mechanisms HIV+TB. The ZINBDR model is shown to be a use tool for analysis death rate according age categorical.

Keywords: zero inflated negative binomial death rate, HIV and TB, AIC and BIC, death rate

Procedia PDF Downloads 437

Authors: Megan E. Davies

Abstract:

The effects of climate change impact the environment and our physical health but also demonstrate a growing risk factor for Canadians’ individual and collective mental health. Past research and expert predictions are discussed while exploring the connection between mental health concerns and climate change consequences, resulting in a call to action for psychological sciences to be integrated into solution planning. With the direct and indirect effects of climate change steadily increasing, political and legal aspects of sustainability, as well as the repercussions for mental health being seen in Canada regarding climate change, are investigated. An interdisciplinary perspective for reviewing the challenges of climate change is applied in order to propose a realistic plan for how policymakers and mental health professionals can work together moving forward in applying interventions that mediate against the effects of climate change on Canadians’ mental health.

Keywords: climate change, mental health, policy change, solution planning, sustainability

Procedia PDF Downloads 151

Authors: Khalil Ahmad Kakar

Abstract:

In developing countries increasing the automobile and low capacity public transport (para-transit) which are creating congestion, pollution, noise, and traffic accident are the most critical quandary. These issues are under the analysis of assessors to break down the puzzle and propose sustainable urban public transport system. Kabul city is one of those urban areas that the inhabitants are suffering from lack of tolerable and friendly public transport system. The city is the most-populous and overcrowded with around 4.5 million population. The para-transit is the only dominant public transit system with a very poor level of services and low capacity vehicles (6-20 passengers). Therefore, this study after detailed investigations suggests bus rapid transit (BRT) system in Kabul City. It is aimed to mitigate the role of informal transport and decreases congestion. The research covers three parts. In the first part, aggregated travel demand modelling (four-step) is applied to determine the number of users for para-transit and assesses BRT network based on higher passenger demand for public transport mode. In the second part, state preference (SP) survey and binary logit model are exerted to figure out the utility of existing para-transit mode and planned BRT system. Finally, the impact of predicted BRT system on para-transit is evaluated. The extracted outcome based on high travel demand suggests 10 km network for the proposed BRT system, which is originated from the district tenth and it is ended at Kabul International Airport. As well as, the result from the disaggregate travel mode-choice model, based on SP and logit model indicates that the predicted mass rapid transit system has higher utility with the significant impact regarding the reduction of para-transit.

Keywords: BRT, para-transit, travel demand modelling, Kabul City, logit model

Procedia PDF Downloads 191

Authors: M. Kolotylo, H. Zheng, R. Parente, R. Dahiya

Abstract:

Large number of organizations, frequently motivated by budget and cost cuts, outsource their Information Technology (IT) positions every year. Although the objective of reduction in financial obligations is often not accomplished, many buyer companies still manage to benefit from outsourcing projects. Knowledge Transfer (KT), being one of the major processes that take place during IT outsourcing partnership, may exert a strong impact on the performance of the parties involved, particularly that of the buyer. Research, however, lacks strong conceptual basis for the possible benefits that KT from supplier may bring to the buyer; and for the mechanisms that may be adopted by the buyer to maximize such benefit. This paper aims to fill this gap by proposing a conceptual framework of organizational learning and development of dynamic capabilities enabled by KT from the supplier to the buyer. The study examines buyer-supplier relationships in the context of IT outsourcing transactions, and theorizes how KT from the supplier to the buyer helps the performance of the buyer. It warrants that more research is carried out in order to explicate and provide evidence regarding the role that KT plays in strategic improvements for the buyer. The paper proposes to take up a two-fold approach to the research: conceptual development that utilizes logical argumentation and interpretive historical research, as well as a qualitative case study which aims to capture and understand the complex processes involved. Thus, the study provides a comprehensive visualization of the dynamics of the conditions under which participation in IT outsourcing partnership might be of benefit to the buyer company. The framework demonstrates the mechanisms involved in buyer’s achievement of strategic alignment through organizational learning enabled by KT from the supplier. It highlights that organizational learning involves a balance between exploitation of assets and exploration of new possibilities, and further notes that the dynamic capabilities mediate the effect of organizational learning on firm performance. The paper explicates in what ways managers can leverage outsourcing projects to execute strategy, which would enable their organization achieve better performance. The study concludes that organizational learning enables the firm to develop IT capabilities of strategic planning, IT integration, and IT relationships in the outsourcing context, and that IT capabilities developed through the organizational learning would help the firm in achieving strategic alignment.

Keywords: dynamic capabilities, it outsourcing, knowledge transfer, organizational learning, strategic alignment

Procedia PDF Downloads 445

Authors: Martin Kittel, Alexander Roth

Abstract:

The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

Procedia PDF Downloads 82