Search results for: loss models

Authors: Lauren B. Birney

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The envisioned long-term outcome of this three-year research, and implementation plan is for 1) teachers and students to design and build their own computational models of real-world environmental-human health phenomena occurring within the context of the “Human Harbor” and 2) project researchers to evaluate the degree to which these integrated Computer Science (CS) education experiences in New York City (NYC) public school classrooms (PreK-12) impact students’ computational-technical skill development, job readiness, career motivations, and measurable abilities to understand, articulate, and solve the underlying phenomena at the center of their models. This effort builds on the partnership’s successes over the past eight years in developing a benchmark Model of restoration-based Science, Technology, Engineering, and Math (STEM) education for urban public schools and achieving relatively broad-based implementation in the nation’s largest public school system. The Billion Oyster Project Curriculum and Community Enterprise for Restoration Science (BOP-CCERS STEM + Computing) curriculum, teacher professional developments, and community engagement programs have reached more than 200 educators and 11,000 students at 124 schools, with 84 waterfront locations and Out of School of Time (OST) programs. The BOP-CCERS Partnership is poised to develop a more refined focus on integrating computer science across the STEM domains; teaching industry-aligned computational methods and tools; and explicitly preparing students from the city’s most under-resourced and underrepresented communities for upwardly mobile careers in NYC’s ever-expanding “digital economy,” in which jobs require computational thinking and an increasing percentage require discreet computer science technical skills. Project Objectives include the following: 1. Computational Thinking (CT) Integration: Integrate computational thinking core practices across existing middle/high school BOP-CCERS STEM curriculum as a means of scaffolding toward long term computer science and computational modeling outcomes. 2. Data Science and Data Analytics: Enabling Researchers to perform interviews with Teachers, students, community members, partners, stakeholders, and Science, Technology, Engineering, and Mathematics (STEM) industry Professionals. Collaborative analysis and data collection were also performed. As a centerpiece, the BOP-CCERS partnership will expand to include a dedicated computer science education partner. New York City Department of Education (NYCDOE), Computer Science for All (CS4ALL) NYC will serve as the dedicated Computer Science (CS) lead, advising the consortium on integration and curriculum development, working in tandem. The BOP-CCERS Model™ also validates that with appropriate application of technical infrastructure, intensive teacher professional developments, and curricular scaffolding, socially connected science learning can be mainstreamed in the nation’s largest urban public school system. This is evidenced and substantiated in the initial phases of BOP-CCERS™. The BOP-CCERS™ student curriculum and teacher professional development have been implemented in approximately 24% of NYC public middle schools, reaching more than 250 educators and 11,000 students directly. BOP-CCERS™ is a fully scalable and transferable educational model, adaptable to all American school districts. In all settings of the proposed Phase IV initiative, the primary beneficiary group will be underrepresented NYC public school students who live in high-poverty neighborhoods and are traditionally underrepresented in the STEM fields, including African Americans, Latinos, English language learners, and children from economically disadvantaged households. In particular, BOP-CCERS Phase IV will explicitly prepare underrepresented students for skilled positions within New York City’s expanding digital economy, computer science, computational information systems, and innovative technology sectors.

Keywords: computer science, data science, equity, diversity and inclusion, STEM education

Procedia PDF Downloads 33

Authors: Van-Thanh Ho, Hyoungsoon Lee, Jaiyoung Ryu

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Efficient pressure distribution within soft robotic systems, specifically to the pneumatic artificial muscle (PAM) regions, is essential to minimize energy consumption. This optimization involves adjusting reservoir pressure, pipe diameter, and branching network layout to reduce flow speed and pressure drop while enhancing flow efficiency. The outcome of this optimization is a lightweight power source and reduced mechanical impedance, enabling extended wear and movement. To achieve this, a branching network system was created by combining pipe components and intricate cross-sectional area variations, employing the principle of minimal work based on a complete virtual human exosuit. The results indicate that modifying the cross-sectional area of the branching network, gradually decreasing it, reduces velocity and enhances momentum compensation, preventing flow disturbances at separation regions. These optimized designs achieve uniform velocity distribution (uniformity index > 94%) prior to entering the connection pipe, with a pressure drop of less than 5%. The design must also consider the length-to-diameter ratio for fluid dynamic performance and production cost. This approach can be utilized to create a comprehensive PAM system, integrating well-designed tube networks and complex pneumatic models.

Keywords: pneumatic artificial muscles, pipe networks, pressure drop, compressible turbulent flow, uniformity flow, murray's law

Procedia PDF Downloads 44

Authors: Ching-I Chen

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The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system. To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.

Keywords: multiple-category purchase behavior, inter-purchase time, market basket analysis, e-commerce

Procedia PDF Downloads 345

Authors: Saima Shaikh, Andre Brown, Wallace Enegbuma

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Earthquakes strike both developed and developing countries, causing tremendous damage and the loss of lives of millions of people, mainly due to the collapsing of buildings, particularly in poorer countries. Despite the socio-economic and technological restrictions, the poorer countries have adopted proven and established housing-strengthening techniques from affluent countries. Rural communities are aware of the earthquake-strengthening mechanisms for improving housing resilience, but owing to socio-economic and technological constraints, the seismic guidelines are rarely implemented, resulting in informal construction practice. Unregistered skilled laborers make substantial contributions to the informal construction sector, particularly in rural areas where knowledge is scarce. Laborers employ their local expertise in house construction; however, owing to a lack of seismic expertise in safe building procedures, the authorities' regulated seismic norms are not applied. From the perspective of seismic knowledge transformation in safe buildings practices, the study focuses on the feasibility of seismic guidelines implementation. The study firstly employs a literature review of massive-scale reconstruction after the 2005 earthquake in rural Pakistan. The 2005-earthquake damaged over 400,000 homes, killed 70,000 people and displaced 2.8 million people. The research subsequently corroborated the pragmatic approach using questionnaire field survey among the rural people in 2005-earthquake affected areas. Using the literature and the questionnaire survey, the research analyzing people's perspectives on technical acceptability, financial restrictions, and socioeconomic viability and examines the effectiveness of seismic knowledge transfer in safe buildings practices. The findings support the creation of a knowledge transfer framework in disaster mitigation and recovery planning, assisting rural communities and builders in minimising losses and improving response and recovery, as well as improving housing resilience and lowering vulnerabilities. Finally, certain conclusions are obtained in order to continue the resilience research. The research can be further applied in rural areas of developing countries having similar construction practices.

Keywords: earthquakes, knowledge transfer, resilience, informal construction practices

Procedia PDF Downloads 140

Authors: Basyir Yaman, Fades Br. Gultom

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The picture and pattern of Islamic education in the Prophet's period in Mecca and Medina is the history of the past that we need to bring back. The Basic Education Institute called Kuttab. Kuttab or Maktab comes from the word kataba which means to write. The popular Kuttab in the Prophet’s period aims to resolve the illiteracy in the Arab community. In Indonesia, this Institution has 25 branches; one of them is located in Semarang (i.e. Kuttab Al-Fatih). Kuttab Al-Fatih as a non-formal institution of Islamic education is reserved for children aged 5-12 years. The independently designed curriculum is a distinctive feature that distinguishes between Kuttab Al-Fatih curriculum and the formal institutional curriculum in Indonesia. The curriculum includes the faith and the Qur’an. Kuttab Al-Fatih has been licensed as a Community Activity Learning Center under the direct supervision and guidance of the National Education Department. Here, we focus to describe the implementation of curriculum Kuttab Al-Fatih Semarang (i.e. faith and al-Qur’an). After that, we determine the relevance between the implementation of the Kuttab Al-Fatih education system with the formal education system in Indonesia. This research uses literature review and field research qualitative methods. We obtained the data from the head of Kuttab Al-Fatih Semarang, vice curriculum, faith coordinator, al-Qur’an coordinator, as well as the guardians of learners and the learners. The result of this research is the relevance of education system in Kuttab Al-Fatih Semarang about education system in Indonesia. Kuttab Al-Fatih Semarang emphasizes character building through a curriculum designed in such a way and combines thematic learning models in modules.

Keywords: Islamic education system, implementation of curriculum, Kuttab Al-Fatih Semarang, formal education system, Indonesia

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Authors: Lovro Štefan

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The main purpose of the present study was to investigate the associations between the overweight/obesity status and lifestyle factors. In this cross-sectional study, participants were 1950 urban secondary-school students (54.7% of female students) aged 17-18 years old. Dependent variable was body-mass index status derived from self-reported height and weight. The outcome was binarised, where participants with value <25 kg/m2 were collapsed into „normal“, while those ≥25 kg/m2 into „overweight/obesity“ category. Independent variables were gender, type of school, physical activity, sedentary behaviour, self-rated health, self-perceived socioeconomic status and psychological distress. The associations between the dependent and independent variables were analyzed by using multiple logistic regression analysis. In the univariate model, being overweight/obese was significantly associated with being a male student (OR 0.31; 95% CI 0.23 to 0.42), attending a vocational school (OR 1.87; 95% CI 1.42 to 2.48), not meeting the recommendations for moderate-to-vigorous physical activity (OR 0.44; 95% CI 0.22 to 0.88), more time spending in sedentary behaviour (OR 1.53; 95% CI 1.07 to 2.19), poor self-rated health (OR 0.35, 95% CI 0.20 to 0.56) and lower socioeconomic status (OR 0.63; 95% CI 0.48 to 0.84). In the multivariate model, the same associations occured between the dependent and independent variable. In both models, psychological distress was not associated with being overweight/obese. In conclusion, our findings suggest, that lifestyle factors are independently associated with body-mass index

Keywords: body mass index, secondary-school students, Croatia, physical activity, sedentary behaviour, logistic regression

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Authors: Marwa Abida, Florian Gehring, Jamel Mars, Alexandre Vivet, Fakhreddine Dammak, Mohamed Haddar

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The demand for bio-based materials in semi-structural and structural applications is constantly growing to conform to new environmental policies. Among them, Plant Fiber Reinforced Composites (PFRC) are attractive for the scientific community as well as the industrial world. Due to their relatively low densities and low environmental impact, vegetal fibers appear to be suitable as reinforcing materials for polymers. However, the major issue of plant fibers and PFRC in general is their hydrophilic behavior (high affinity to water molecules). Indeed, when absorbed, water causes fiber swelling and a loss of mechanical properties. Thus, the environmental loadings (moisture, temperature, UV) can strongly affect their mechanical properties and therefore play a critical role in the service life of PFRC. In order to analyze the influence of conditioning at relative humidity on the behavior of flax fiber reinforced composites, a preliminary study on flax fabrics has been conducted. The conditioning of the fabrics in different humid atmospheres made it possible to study the influence of the water content on the hygro-mechanical behavior of flax reinforcement through mechanical tensile tests. This work shows that increasing the relative humidity of the atmosphere induces an increase of the water content in the samples. It also brings up the significant influence of water content on the stiffness and elongation at break of the fabric, while no significant change of the breaking load is detected. Non-linear decrease of flax fabric rigidity and increase of its elongation at maximal force with the increase of water content are observed. It is concluded that water molecules act as a softening agent on flax fabrics. Two kinds of typical tensile curves are identified. Most of the tensile curves of samples show one unique linear region where the behavior appears to be linear prior to the first yarn failure. For some samples in which water content is between 2.7 % and 3.7 % (regardless the conditioning atmosphere), the emergence of a two-linear region behavior is pointed out. This phenomenon could be explained by local heterogeneities of water content which could induce premature local plasticity in some regions of the flax fabric sample behavior.

Keywords: hygro-mechanical behavior, hygroscopy, flax fabric, relative humidity, mechanical properties

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Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: M. S. Sarkar, J. A. Johnson, S. Sen, G. K. Saha, K. Ramesh

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There is growing recognition of several important roles played by tigers for maintaining sustainable biodiversity at diverse ecosystems in South and South-East Asia. Only <3200 individuals are left in the wild because of poaching and habitat loss. Thus, restoring wild population is an emerging as well as important conservation initiative, but such efforts still remain challenging due to their elusive and solitary behavior. After careful translocation of few individuals, how reintroduced individuals colonize into suitable habitat and achieve stable stage population through reproduction is vital information for forest managers and policy makers of its 13 distribution range countries. Four wild and two captive radio collared tigers were reintroduced at Panna Tiger Reserve, Madhya-pradesh, India during 2009-2014. We critically examined their settlement behavior and population growth over the period. Results from long term telemetry data showed that male explored larger areas rapidly in short time span, while females explored small area in long time period and with significant high rate of movement in both sexes during exploratory period. Significant difference in home range sizes of tigers were observed in exploratory and settlement period. Though all reintroduced tigers preferred densely vegetated undisturbed forest patches within the core area of tiger reserve, a niche based k select analysis showed that individual variation in habitat selection was prominent among reintroduced tigers. Total 18 litter of >42 known cubs were born with low mortality rate, high maternity rate, high observed growth rate and short generation time in both the sexes. The population achieved its carrying capacity in a very short time span, marking success of this current tiger conservation programme. Our study information could provide significant insights on the tiger biology of translocated tigers with implication for future conservation strategies that consider translocation based recovery in their range countries.

Keywords: reintroduction, tiger, home range, demography

Procedia PDF Downloads 197

Authors: Lourdes Gutierrez, Eric Williams

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Post-occupancy research shows that only 11% of commercial buildings met the ASHRAE thermal comfort standard. Many buildings are too warm in winter and/or too cool in summer, wasting energy and not providing comfort. In this paper, potential energy savings in U.S. offices and restaurants if thermostat settings are calculated according the updated ASHRAE 55-2013 comfort model that accounts for outdoor temperature and clothing choice for different climate zones. eQUEST building models are calibrated to reproduce aggregate energy consumption as reported in the U.S. Commercial Building Energy Consumption Survey. Changes in energy consumption due to the new settings are analyzed for 14 cities in different climate zones and then the results are extrapolated to estimate potential national savings. It is found that, depending on the climate zone, each degree increase in the summer saves 0.6 to 1.0% of total building electricity consumption. Each degree the winter setting is lowered saves 1.2% to 8.7% of total building natural gas consumption. With new thermostat settings, national savings are 2.5% of the total consumed in all office buildings and restaurants, summing up to national savings of 69.6 million GJ annually, comparable to all 2015 total solar PV generation in US. The goals of improved comfort and energy/economic savings are thus co-aligned, raising the importance of thermostat management as an energy efficiency strategy.

Keywords: energy savings quantifications, commercial building stocks, dynamic clothing insulation model, operation-focused interventions, energy management, thermal comfort, thermostat settings

Procedia PDF Downloads 279

Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

Procedia PDF Downloads 61

Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 114

Authors: Pranee Suecharoen, Ratchadaporn Soontornpas, Jaturat Kanpittaya

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Background: Contrast media has an important role for disease diagnosis through detection of pathologies. Contrast media can, however, cause adverse reactions after administration of its agents. Although non-ionic contrast media are commonly used, the incidence of adverse events is relatively low. The most common reactions found (10.5%) were mild and manageable and/or preventable. Pharmacists can play an important role in evaluating adverse reactions, including awareness of the specific preparation and the type of adverse reaction. As most common types of adverse reactions are idiosyncratic or pseudo-allergic reactions, common standards need to be established to prevent and control adverse reactions promptly and effectively. Objective: To measure the effect of using tools for symptom evaluation in order to reduce the severity, or prevent the occurrence, of adverse reactions from contrast media. Methods: Retrospective review descriptive research with data collected on adverse reactions assessment and Naranjo’s algorithm between June 2015 and May 2016. Results: 158 patients (10.53%) had adverse reactions. Of the 1,500 participants with an adverse event evaluation, 137 (9.13%) had a mild adverse reaction, including hives, nausea, vomiting, dizziness, and headache. These types of symptoms can be treated (i.e., with antihistamines, anti-emetics) and the patient recovers completely within one day. The group with moderate adverse reactions, numbering 18 cases (1.2%), had hypertension or hypotension, and shortness of breath. Severe adverse reactions numbered 3 cases (0.2%) and included swelling of the larynx, cardiac arrest, and loss of consciousness, requiring immediate treatment. No other complications under close medical supervision were recorded (i.e., corticosteroids use, epinephrine, dopamine, atropine, or life-saving devices). Using the guideline, therapies are divided into general and specific and are performed according to the severity, risk factors and ingestion of contrast media agents. Patients who have high-risk factors were screened and treated (i.e., prophylactic premedication) for prevention of severe adverse reactions, especially those with renal failure. Thus, awareness for the need for prescreening of different risk factors is necessary for early recognition and prompt treatment. Conclusion: Studying adverse reactions can be used to develop a model for reducing the level of severity and setting a guideline for a standardized, multidisciplinary approach to adverse reactions.

Keywords: role of pharmacist, management of adverse reactions, guideline for contrast media, non-ionic contrast media

Procedia PDF Downloads 278

Authors: Rose-Michelle Smith, Musandji Fuamba, Salomon Salumu

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Water is vital for life. Access to drinking water and sanitation for humans is one of the Sustainable Development Goals (specifically the sixth) approved by United Nations Member States in September 2015. There are various problems identified relating to water: insufficient fresh water, inequitable distribution of water resources, poor water management in certain places on the planet, detection of water-borne diseases due to poor water quality, and the negative impacts of climate change on water. One of the major challenges in the world is finding ways to ensure that people and the environment have enough water resources to sustain and support their existence. Thus, this research project aims to develop a tool to assess the availability, quality and needs of water in current and future situations with regard to climate change. This tool was tested using threshold values for three regions in three countries: the Metropolitan Community of Montreal (Canada), Normandie Region (France) and North Department (Haiti). The WEAP software was used to evaluate the available quantity of water resources. For water quality, two models were performed: the Canadian Council of Ministers of the Environment (CCME) and the Malaysian Water Quality Index (WQI). Preliminary results showed that the ratio of the needs could be estimated at 155, 308 and 644 m3/capita in 2023 for Normandie, Cap-Haitian and CMM, respectively. Then, the Water Quality Index (WQI) varied from one country to another. Other simulations regarding the water availability and quality are still in progress. This tool will be very useful in decision-making on projects relating to water use in the future; it will make it possible to estimate whether the available resources will be able to satisfy the needs.

Keywords: climate change, water needs, balance sheet, water quality

Procedia PDF Downloads 39

Authors: Anaissia Franca, Julian Fernandez, Curran Crawford, Ned Djilali

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A methodology to estimate the state-of-charge (SOC) of battery electric buses, including degradation effects, for a given driving cycle is presented to support long-term techno-economic analysis integrating electric buses and charging infrastructure. The degradation mechanisms, characterized by both capacity and power fade with time, have been modeled using an electrochemical model for Li-ion batteries. Iterative changes in the negative electrode film resistance and decrease in available lithium as a function of utilization is simulated for every cycle. The cycles are formulated to follow typical transit bus driving patterns. The power and capacity decay resulting from the degradation model are introduced as inputs to a longitudinal chassis dynamic analysis that calculates the power consumption of the bus for a given driving cycle to find the state-of-charge of the battery as a function of time. The method is applied to an in-depot charging scenario, for which the bus is charged exclusively at the depot, overnight and to its full capacity. This scenario is run both with and without including degradation effects over time to illustrate the significant impact of degradation mechanisms on bus performance when doing feasibility studies for a fleet of electric buses. The impact of battery degradation on battery lifetime is also assessed. The modeling tool can be further used to optimize component sizing and charging locations for electric bus deployment projects.

Keywords: battery electric bus, E-bus, in-depot charging, lithium-ion battery, battery degradation, capacity fade, power fade, electric vehicle, SEI, electrochemical models

Procedia PDF Downloads 293

Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: Kirill D. Semavin, Norbert S. Chilingarov, Eugene.V. Skokan

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The ionic liquids (ILs) based on imidazolium cation are well known nowadays. The changing anions and substituents in imidazolium ring may lead to different physical and chemical properties of ILs. It is important that such ILs with halogen as anion are characterized by a low thermal stability. The data about thermal stability of 1-ethyl-3-methylimidazolium chloride are ambiguous. In the works of last years, thermal stability of this IL was investigated by thermogravimetric analysis and obtained results are contradictory. Moreover, in the last study, it was shown that the observed temperature of the beginning of decomposition significantly depends on the experimental conditions, for example, the heating rate of the sample. The vapor pressure of this IL is not presented at the literature. In this study, the vapor pressure of 1-ethyl-3-methylimidazolium chloride was obtained by Knudsen effusion mass-spectrometry (KEMS). The samples of [ЕMIm]Cl (purity > 98%) were supplied by Sigma–Aldrich and were additionally dried at dynamic vacuum (T = 60 0C). Preliminary procedures with Il were derived into glove box. The evaporation studies of [ЕMIm]Cl were carried out by KEMS with using original research equipment based on commercial MI1201 magnetic mass spectrometer. The stainless steel effusion cell had an effective evaporation/effusion area ratio of more than 6000. The cell temperature, measured by a Pt/Pt−Rh (10%) thermocouple, was controlled by a Termodat 128K5 device with an accuracy of ±1 K. In first step of this study, the optimal temperature of experiment and heating rate of samples were customized: 449 K and 5 K/min, respectively. In these conditions the sample is decomposed, but the experimental measurements of the vapor pressures are possible. The thermodynamic activity of [ЕMIm]Cl is close to 1 and products of decomposition don’t affect it at firstly 50 hours of experiment. Therefore, it lets to determine the saturated vapor pressure of IL. The electronic ionization mass-spectra shows that the decomposition of [ЕMIm]Cl proceeds with two ways. Nonetheless, the MALDI mass spectra of the starting sample and residue in the cell were similar. It means that the main decomposition products are gaseous under experimental conditions. This result allows us to obtain information about the kinetics of [ЕMIm]Cl decomposition. Thus, the original KEMS-based procedure made it possible to determine the IL vapor pressure under decomposition conditions. Also, the loss of sample mass due to the evaporation was obtained.

Keywords: ionic liquids, Knudsen effusion mass spectrometry, thermal stability, vapor pressure

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Authors: Girgis Younan, Ikram Eltayeb

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Geigeria alata belongs to the family Asteraceae, is an effective plant traditionally used in Sudan as a therapy for hepatic disease and as an antiepileptic, antispasmodic and to treat cough and intestinal complaints.The liver is responsible for many critical functions within the body and any liver disease or injury will result in the loss of those functions leading to significant damage in the body. Liver diseases cause increase in liver enzymes (AST, ALP ALT) and total bilirubin and a decrease in total blood protein level. The objective of this study is to investigate the hepato-protective activity of Geigeria alata leaves ethanolic extract. The plant leaves were extracted using 96% ethanol using Soxhlet apparatus. The hepatoprotective effect was determined using 25 wistar rats, the rats was divided to 5 groups, each group contain 5 rats: [Normal control group] receiving purified water, liver damage was induced in wistar rats by administering a 1:1 (v/v) mixture of CCl4 (1.25 ml/kg) and olive oil once at day four of the experiment [negative control group]. Two doses of extract [400mg/kg and 200mg/kg] was applied daily for 7 days, and standard drug Silymarin (200 mg/kg) were administered daily for 7 days to CCl4-treated rats. The degree of hepato-protective activity was evaluated by determining the hepatic marker enzymes AST, ALP, ALT, total Bilirubin and total proteins (TP). Results have shown that, the extract of G.alata leaves reduced the level of liver enzymes ALT, AST, ALP, total bilirubin and increased the level of total proteins. Since the levels of liver enzymes; bilirubin and total protein are considered as markers of liver function, the extract has proven to reduce the detrimental effects of liver toxicity induced using CCl4. The hepato-protective effect of extract on liver was found to be dose dependent, where the 400mg/kg dose of the extract exhibited higher activity than 200mg/kg dose. In addition, the effect of the higher dose (400mg/kg) of the extract was found to be higher than Silymarin standard drug. The result concludes that, G.alata leaves extract was found to exhibit profound hepato-protective activity, which justifies the traditional use of the plant for the treatment of hepatic diseases.

Keywords: alata, extract, geigeria, hepatoprotective

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Authors: Ikra Khan, Reenu Singh

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Composition is essential when designing the interiors of residential spaces. The ability to adopt a unique style of using design principles and design elements is another. This research report explores how the visual aesthetic within a space is achieved through the use of design principles and design elements while maintaining a signature style. It also observes the relationship between design styles and compositions that are achieved as a result of the implementation of the principles. Information collected from books and the internet helped to understand how a composition can be achieved in residential interiors by resorting to design principles and design elements as tools for achieving an aesthetic composition. It also helped determine the results of authentic representation of design ideas and how they make one’s work exceptional. A questionnaire survey was also conducted to understand the impact of a visually aesthetic residential interior of a signature style on the lifestyle of individuals residing in them. The findings denote a pattern in the application of design principles and design elements. Individual principles and elements or a combination of the same are used to achieve an aesthetically pleasing composition. This was supported by creating CAD illustrations of two different residential projects with varying approaches and design styles. These illustrations include mood boards, 3D models, and sectional elevations as rendered views to understand the concept design and its translation via these mediums. A direct relation is observed between the application of design principles and design elements to achieve visually aesthetic residential interiors that suit an individual’s taste. These practices can be applied when designing bespoke commercial as well as industrial interiors that are suited to specific aesthetic and functional needs.

Keywords: composition, design principles, elements, interiors, residential spaces

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Authors: Syed Amer Mahmood, Rao Mansor Ali Khan

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This study deals with the remote sensing analysis of tectonic deformation and its implications to understand the regional uplift conditions in the lower Jhelum and eastern Potwar. Identification and mapping of active structures is an important issue in order to assess seismic hazards and to understand the Quaternary deformation of the region. Digital elevation models (DEMs) provide an opportunity to quantify land surface geometry in terms of elevation and its derivatives. Tectonic movement along the faults is often reflected by characteristic geomorphological features such as elevation, stream offsets, slope breaks and the contributing drainage area. The river profile analysis in this region using SRTM digital elevation model gives information about the tectonic influence on the local drainage network. The steepness and concavity indices have been calculated by power law of scaling relations under steady state conditions. An uplift rate map is prepared after carefully analysing the local drainage network showing uplift rates in mm/year. The active faults in the region control local drainages and the deflection of stream channels is a further evidence of the recent fault activity. The results show variable relative uplift conditions along MBT and Riasi and represent a wonderful example of the recency of uplift, as well as the influence of active tectonics on the evolution of young orogens.

Keywords: quaternary deformation, SRTM DEM, geomorphometric indices, active tectonics and MBT

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Authors: Mohd Tahseen Islam Talukder, Sheikh Adnan Enam, Latifa Akter Lithi, Soebur Rahman

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Composite structures have made significant advances in construction applications during the last few decades. Composite structures are composed of structural steel shapes and reinforced concrete combined with shear connectors, which benefit each material's unique properties. Significant research has been conducted on different types of connectors’ behavior and shear capacity. Moreover, the AISC 360-16 “Specification for Steel Structural Buildings” consists of a formula for channel shear connectors' shear capacity. This research compares the behavior of C type and L type shear connectors using Finite Element Analysis. Experimental results from published literature are used to validate the finite element models. The 3-D Finite Element Model (FEM) was built using ABAQUS 2017 to investigate non-linear capabilities and the ultimate load-carrying potential of the connectors using push-out tests. The changes in connector dimensions were analyzed using this non-linear model in parametric investigations. The parametric study shows that by increasing the length of the shear connector by 10 mm, its shear strength increases by 21%. Shear capacity increased by 13% as the height was increased by 10 mm. The thickness of the specimen was raised by 1 mm, resulting in a 2% increase in shear capacity. However, the shear capacity of channel connectors was reduced by 21% due to an increase of thickness by 2 mm.

Keywords: finite element method, channel shear connector, angle shear connector, ABAQUS, composite structure, shear connector, parametric study, ultimate shear capacity, push-out test

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Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Anupam Bhatia

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Upon reviewing the literature and the pragmatic work done in the field of E- textiles, it is observed that the applications of wearable technologies have found a steady growth in the field of military, medical, industrial, sports; whereas fashion is at a loss to know how to treat this technology and bring it to market. The purpose of this paper is to understand the practical issues of integration of electronics in garments; cutting patterns for mass production, maintaining the basic properties of textiles and daily maintenance of garments that hinder the wide adoption of interactive fabric technology within Fashion and leisure wear. To understand the practical hindrances an experimental and laboratory approach is taken. “Techno Meets Fashion” has been an interactive fashion project where sensor technologies have been embedded with textiles that result in set of ensembles that are light emitting garments, sound sensing garments, proximity garments, shape memory garments etc. Smart textiles, especially in the form of textile interfaces, are drastically underused in fashion and other lifestyle product design. Clothing and some other textile products must be washable, which subjects to the interactive elements to water and chemical immersion, physical stress, and extreme temperature. The current state of the art tends to be too fragile for this treatment. The process for mass producing traditional textiles becomes difficult in interactive textiles. As cutting patterns from larger rolls of cloth and sewing them together to make garments breaks and reforms electronic connections in an uncontrolled manner. Because of this, interactive fabric elements are integrated by hand into textiles produced by standard methods. The Arduino has surely made embedding electronics into textiles much easier than before; even then electronics are not integral to the daily wear garments. Soft and flexible interfaces of MEMS (micro sensors and Micro actuators) can be an option to make this possible by blending electronics within E-textiles in a way that’s seamless and still retains functions of the circuits as well as the garment. Smart clothes, which offer simultaneously a challenging design and utility value, can be only mass produced if the demands of the body are taken care of i.e. protection, anthropometry, ergonomics of human movement, thermo- physiological regulation.

Keywords: ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology

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Authors: James Killian, Sarah Cox

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The use of stability criteria within geotechnical engineering is the way the results of analyses are conveyed, and sensitivities and risk assessments are performed. Historically, the primary stability criteria for slope design has been the Factor of Safety (FOS) coming from a limit calculation. Increasingly, the value derived from Strength Reduction Factor (SRF) analysis is being used as the criteria for stability analysis. The purpose of this work was to study in detail the relationship between SRF values produced from a numerical modeling technique and the traditional FOS values produced from Limit Equilibrium (LEM) analyses. This study utilized a model of a 3000-foot-high slope with a 45-degree slope angle, assuming a perfectly plastic mohr-coulomb constitutive model with high cohesion and friction angle values typical of a large hard rock mine slope. A number of variables affecting the values of the SRF in a numerical analysis were tested, including zone size, in-situ stress, tensile strength, and dilation angle. This paper demonstrates that in most cases, SRF values are lower than the corresponding LEM FOS values. Modeled zone size has the greatest effect on the estimated SRF value, which can vary as much as 15% to the downside compared to FOS. For consistency when using SRF as a stability criteria, the authors suggest that numerical model zone sizes should not be constructed to be smaller than about 1% of the overall problem slope height and shouldn’t be greater than 2%. Future work could include investigations of the effect of anisotropic strength assumptions or advanced constitutive models.

Keywords: FOS, SRF, LEM, comparison

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Authors: Zhifei Hu, Feng Xia

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In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Potaliya Pushpa, Kataria Sushma, D. S. Chowdhary, Dadhich Abhilasha

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Introduction: Stress is a nonspecific response of the body to a stressor or triggering stimulus. Chronic stress exposure contributes to various remarkable alterations o growth and development. Collective effects of stressors lead to several changes which are physical, physiological and behavioral in nature. Objective: To understand on an animal model how various chronic stress affect the somatic body growth as it can be useful for effective stress treatment and prevention of stress related illnesses. Material and Method: By selective fostering only male pup colonies were made and 102 male albino rats were studied. They were divided two groups as Control and Stressed. The experimental groups were exposed to four major types of stress as maternal deprivation, Restraint stress, electric foot shock and noise stress for affecting emotional, physical and physiological activities. Exposure was from birth to 17 week of life. Roentgenographs were taken in two planes as Dorso-ventral and Lateral and then measured for each rat. Various parameters were observed at specific intervals. Parameters recorded were Body weight and for linear growth it was summation of Cranial length, Head rump length and tail length. Behavior changes were also observed. Result: Multiple chronic stresses resulted in loss of approx. 25% of mean body weight. Maximal difference was found on 119th day (i.e. 87.81 gm) between the control and stressed group. Linear growth showed retardation which was found to be significant in stressed group on statistical analysis. Cranial Length and Head-rump Length showed maximum difference after maternal deprivation stress. After maternal deprivation (Day 21) and electric foot shock (Day 101) maximum difference i.e. 0.39 cm and 0.47 cm were found in cranial length of two groups. Electric foot shock had considerable impact on tail length. Noise Stress affected moreover behavior as compact to physical growth. Conclusion: Collective study showed that chronic stress not only resulted in reduced body weight in albino rats but also total linear size of rat thus affecting whole growth and development.

Keywords: stress, microscopic anatomy, macroscopic anatomy, chronic multiple stress, birth

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Authors: Emin Z. Mahmud

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Shaking table tests are planned in order to deepen the understanding of the behavior of confined masonry structures with or without openings. The tests are realized in the laboratory of the Institute of Earthquake Engineering and Engineering Seismology (IZIIS) – Skopje. The specimens were examined separately on the shaking table, with uniaxial, in-plane excitation. After testing, samples were strengthened with GFRP (Glass Fiber Reinforced Plastic) and re-tested. This paper presents the observations from a series of shaking-table tests done on a 1:1 scaled confined masonry wall model, with opening for a window – specimens CMWuS (before strengthening) and CMWS (after strengthening). Frequency and stiffness changes before and after GFRP wall strengthening are analyzed. Definition of dynamic properties of the models was the first step of the experimental testing, which enabled acquiring important information about the achieved stiffness (natural frequencies) of the model. The natural frequency was defined in the Y direction of the model by applying resonant frequency search tests. It is important to mention that both specimens CMWuS and CMWS are subjected to the same effects. The initial frequency of the undamaged model CMWuS is 18.79 Hz, while at the end of the testing, the frequency decreased to 12.96 Hz. This emphasizes the reduction of the initial stiffness of the model due to damage, especially in the masonry and tie-beam to tie-column connection. After strengthening the damaged wall, the natural frequency increases to 14.67 Hz. This highlights the beneficial effect of strengthening. After completion of dynamic testing at CMWS, the natural frequency is reduced to 10.75 Hz.

Keywords: behaviour of masonry structures, Eurocode, frequency, masonry, shaking table test, strengthening

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Authors: Carlos G. Santos, Frederico A. Genezini, A. P. Dos Santos, H. Yorivaz, P. T. D. Siqueira

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The Prompt-Gamma Activation Analysis (PGAA) is a valuable technique for investigating the elemental composition of various samples. However, the installation of a PGAA system entails specific conditions such as filtering the neutron beam according to the target and providing adequate shielding for both users and detectors. These requirements incur substantial costs, exceeding $100,000, including manpower. Nevertheless, a cost-effective approach involves leveraging an existing neutron beam facility to create a hybrid system integrating PGAA and Neutron Tomography (NT). The IEA-R1 nuclear reactor at IPEN/USP possesses an NT facility with suitable conditions for adapting and implementing a PGAA device. The NT facility offers a thermal flux slightly colder and provides shielding for user protection. The key additional requirement involves designing detector shielding to mitigate high gamma ray background and safeguard the HPGe detector from neutron-induced damage. This study employs Monte Carlo simulations with the MCNP6 code to optimize the collimator plug for PGAA within the IEA-R1 NT facility. Three collimator models are proposed and simulated to assess their effectiveness in shielding gamma and neutron radiation from nucleon fission. The aim is to achieve a focused prompt-gamma signal while shielding ambient gamma radiation. The simulation results indicate that one of the proposed designs is particularly suitable for the PGAA-NT hybrid system.

Keywords: MCNP6.1, neutron, prompt-gamma ray, prompt-gamma activation analysis

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Authors: Alireza Nikravanshallmani, Jamshid Dehmeshki, Mojtaba Ahmadi

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Modeling of business processes, based on BPMN (Business Process Modeling Notation), helps analysts and managers to understand business processes, and, identify their shortages. These models provide a context to make rational decision of organizing business processes activities in an understandable manner. The purpose of this paper is to provide a framework for better understanding of business processes and their problems by reducing the cognitive load of displayed information for their audience at different managerial levels while keeping the essential information which are needed by them. For this reason, we integrate business process diagrams across the different managerial levels to develop a framework to improve the performance of business process management (BPM) projects. The proposed framework is entitled ‘Business process improvement framework based on managerial levels (BPIML)’. This framework, determine a certain type of business process diagrams (BPD) based on BPMN with respect to the objectives and tasks of the various managerial levels of organizations and their roles in BPM projects. This framework will make us able to provide the necessary support for making decisions about business processes. The framework is evaluated with a case study in a real business process improvement project, to demonstrate its superiority over the conventional method. A questionnaire consisted of 10 questions using Likert scale was designed and given to the participants (managers of Bank Refah Kargaran three managerial levels). By examining the results of the questionnaire, it can be said that the proposed framework provide support for correct and timely decisions by increasing the clarity and transparency of the business processes which led to success in BPM projects.

Keywords: business process management (BPM), business process modeling, business process reengineering (BPR), business process optimizing, BPMN

Procedia PDF Downloads 426

Authors: You-Kai Jhang, Yang-Cheng Lu

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Major contributions of this study are threefold: designing a new model of planar-membrane humidifier for Proton Exchange Membrane Fuel Cell (PEMFC), an index to measure the Effectiveness (εT) of that humidifier, and an air compressor system to replicate related planar-membrane humidifier experiments. PEMFC as a kind of renewable energy has become more and more important in recent years due to its reliability and durability. To maintain the efficiency of the fuel cell, the membrane of PEMFC need to be controlled in a good hydration condition. How to maintain proper membrane humidity is one of the key issues to optimize PEMFC. We developed new humidifier to recycle water vapor from cathode air outlet so as to keep the moisture content of cathode air inlet in a PEMFC. By measuring parameters such as dry side air outlet dew point temperature, dry side air inlet temperature and humidity, wet side air inlet temperature and humidity, and differential pressure between dry side and wet side, we calculated indices obtained by dew point approach temperature (DPAT), water flux (J), water recovery ratio (WRR), effectiveness (εT), and differential pressure (ΔP). We discussed six topics including sealing effect, flow rate effect, flow direction effect, channel effect, temperature effect, and humidity effect by using these indices. Gas cylinders are used as sources of air supply in many studies of humidifiers. Gas cylinder depletes quickly during experiment at 1kW air flow rate, and it causes replication difficult. In order to ensure high stable air quality and better replication of experimental data, this study designs an air supply system to overcome this difficulty. The experimental result shows that the best rate of pressure loss of humidifier is 0.133×10³ Pa(g)/min at the torque of 25 (N.m). The best humidifier performance ranges from 30-40 (LPM) of air flow rates. The counter flow configured humidifies moisturizes the dry side inlet air more effectively than the parallel flow humidifier. From the performance measurements of the channel plates various rib widths studied in this study, it is found that the narrower the rib width is, the more the performance of humidifier improves. Raising channel width in same hydraulic diameter (Dh ) will obtain higher εT and lower ΔP. Moreover, increasing the dry side air inlet temperature or humidity will lead to lower εT. In addition, when the dry side air inlet temperature exceeds 50°C, the effect becomes even more obvious.

Keywords: PEM fuel cell, water management, membrane humidifier, heat and mass transfer, humidifier performance

Procedia PDF Downloads 142