Search results for: MIMO (Multiple Input Multiple Output)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7999

Search results for: MIMO (Multiple Input Multiple Output)

6439 Artificial Neural Network in Predicting the Soil Response in the Discrete Element Method Simulation

Authors: Zhaofeng Li, Jun Kang Chow, Yu-Hsing Wang

Abstract:

This paper attempts to bridge the soil properties and the mechanical response of soil in the discrete element method (DEM) simulation. The artificial neural network (ANN) was therefore adopted, aiming to reproduce the stress-strain-volumetric response when soil properties are given. 31 biaxial shearing tests with varying soil parameters (e.g., initial void ratio and interparticle friction coefficient) were generated using the DEM simulations. Based on these 45 sets of training data, a three-layer neural network was established which can output the entire stress-strain-volumetric curve during the shearing process from the input soil parameters. Beyond the training data, 2 additional sets of data were generated to examine the validity of the network, and the stress-strain-volumetric curves for both cases were well reproduced using this network. Overall, the ANN was found promising in predicting the soil behavior and reducing repetitive simulation work.

Keywords: artificial neural network, discrete element method, soil properties, stress-strain-volumetric response

Procedia PDF Downloads 393
6438 Data and Model-based Metamodels for Prediction of Performance of Extended Hollo-Bolt Connections

Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

Abstract:

Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

Procedia PDF Downloads 153
6437 Effects of Starvation, Glucose Treatment and Metformin on Resistance in Chronic Myeloid Leukemia Cells

Authors: Nehir Nebioglu

Abstract:

Chemotherapy is widely used for the treatment of cancer. Doxorubicin is an anti-cancer chemotherapy drug that is classified as an anthracycline antibiotic. Antitumor antibiotics consist of natural products produced by species of the soil fungus Streptomyces. These drugs act in multiple phases of the cell cycle and are known cell-cycle specific. Although DOX is a precious clinical antineoplastic agent, resistance is also a problem that limits its utility besides cardiotoxicity problem. The drug resistance of cancer cells results from multiple factors including individual variation, genetic heterogeneity within a tumor, and cellular evolution. The mechanism of resistance is thought to involve, in particular, ABCB1 (MDR1, Pgp) and ABCC1 (MRP1) as well as other transporters. Several studies on DOX-resistant cell lines have shown that resistance can be overcome by an inhibition of ABCB1, ABCC1, and ABCC2. This study attempts to understand the effects of different concentration levels of glucose treatment and starvation on the proliferation of Doxorubicin resistant cancer cells lines. To understand the effect of starvation, K562/Dox and K562 cell lines were treated with 0, 5 nM, 50 nM, 500 nM, 5 uM and 50 uM Dox concentrations in both starvation and normal medium conditions. In addition to this, to interpret the effect of glucose treatment, different concentrations (0, 1 mM, 5 mM, 25 mM) of glucose were applied to Dox-treated (with 0, 5 nM, 50 nM, 500 nM, 5 uM and 50 uM) K562/Dox and K652 cell lines. All results show significant decreasing in the cell count of K562/Dox, when cells were starved. However, while proliferation of K562/Dox lines decrease is associated with the increasingly applied Dox concentration, K562/Dox starved ones remain at the same proliferation level. Thus, the results imply that an amount of K562/Dox lines gain starvation resistance and remain resistant. Furthermore, for K562/Dox, there is no clear effect of glucose treatment in terms of cell proliferation. In the presence of a moderate level of glucose (5 mM), proliferation increases compared to other concentration of glucose for each different Dox application. On the other hand, a significant increase in cell proliferation in moderate level of glucose is only observed in 5 uM Dox concentration. The moderate concentration level of Dox can be examined in further studies. For the high amount of glucose (25 mM), cell proliferation levels are lower than moderate glucose application. The reason could be high amount of glucose may not be absorbable by cells. Also, in the presence of low amount of glucose, proliferation is decreasing in an orderly manner of increase in Dox concentration. This situation can be explained by the glucose depletion -Warburg effect- in the literature.

Keywords: drug resistance, cancer cells, chemotherapy, doxorubicin

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6436 Application of Neural Network on the Loading of Copper onto Clinoptilolite

Authors: John Kabuba

Abstract:

The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

Procedia PDF Downloads 412
6435 Corporate Governance and Bank Performance: A Study of Selected Deposit Money Banks in Nigeria

Authors: Ayodele Ajayi, John Ajayi

Abstract:

This paper investigates the effect of corporate governance with a view to determining the relationship between board size and bank performance. Data for the study were obtained from the audited financial statements of five sampled banks listed on the Nigerian Stock Exchange. Panel data technique was adopted and analysis was carried out with the use of multiple regression and pooled ordinary least square. Results from the study show that the larger the board size, the greater the profit implying that corporate governance is positively correlated with bank performance.

Keywords: corporate governance, banks performance, board size, pooled data

Procedia PDF Downloads 352
6434 An Output Oriented Super-Efficiency Model for Considering Time Lag Effect

Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

Procedia PDF Downloads 648
6433 Assessment of Climate Change Impacts on the Hydrology of Upper Guder Catchment, Upper Blue Nile

Authors: Fikru Fentaw Abera

Abstract:

Climate changes alter regional hydrologic conditions and results in a variety of impacts on water resource systems. Such hydrologic changes will affect almost every aspect of human well-being. The goal of this paper is to assess the impact of climate change on the hydrology of Upper Guder catchment located in northwest of Ethiopia. The GCM derived scenarios (HadCM3 A2a & B2a SRES emission scenarios) experiments were used for the climate projection. The statistical downscaling model (SDSM) was used to generate future possible local meteorological variables in the study area. The down-scaled data were then used as input to the soil and water assessment tool (SWAT) model to simulate the corresponding future stream flow regime in Upper Guder catchment of the Abay River Basin. A semi distributed hydrological model, SWAT was developed and Generalized Likelihood Uncertainty Estimation (GLUE) was utilized for uncertainty analysis. GLUE is linked with SWAT in the Calibration and Uncertainty Program known as SWAT-CUP. Three benchmark periods simulated for this study were 2020s, 2050s and 2080s. The time series generated by GCM of HadCM3 A2a and B2a and Statistical Downscaling Model (SDSM) indicate a significant increasing trend in maximum and minimum temperature values and a slight increasing trend in precipitation for both A2a and B2a emission scenarios in both Gedo and Tikur Inch stations for all three bench mark periods. The hydrologic impact analysis made with the downscaled temperature and precipitation time series as input to the hydrological model SWAT suggested for both A2a and B2a emission scenarios. The model output shows that there may be an annual increase in flow volume up to 35% for both emission scenarios in three benchmark periods in the future. All seasons show an increase in flow volume for both A2a and B2a emission scenarios for all time horizons. Potential evapotranspiration in the catchment also will increase annually on average 3-15% for the 2020s and 7-25% for the 2050s and 2080s for both A2a and B2a emissions scenarios.

Keywords: climate change, Guder sub-basin, GCM, SDSM, SWAT, SWAT-CUP, GLUE

Procedia PDF Downloads 356
6432 A Classical Method of Optimizing Manufacturing Systems Using a Number of Industrial Engineering Techniques

Authors: John M. Ikome, Martha E. Ikome, Therese Van Wyk

Abstract:

Productivity optimization of a company can significantly increase the company’s output and productivity which can be in the form of corrective actions of ineffective activities, process simplification, and reduction of variations, responsiveness, and reduction of set-up-time which are all under the classification of waste within the manufacturing environment. Deriving a means to eliminate a number of these issues has a key importance for manufacturing organization. This paper focused on a number of industrial engineering techniques which include a cause and effect diagram, to identify and optimize the method or systems being used. Based on our results, it shows that there are a number of variations within the production processes that can significantly disrupt the expected output.

Keywords: optimization, fishbone, diagram, productivity

Procedia PDF Downloads 306
6431 Effect of Company Value, Leadership, and Ownership Succession on Financial Performance of Family Business

Authors: Theresia Dwi Hastuti, Kristiana Haryanti, Agustine Eva Maria Soekesi

Abstract:

Today's family business continues to grow in big cities and in rural areas throughout Indonesia in line with the development of the business world and global competition. This study aims to analyze the effect of company value, leadership, and ownership succession on the financial performance of the family business. The research method was carried out quantitatively with multiple regression. The respondent amounted to 63 entrepreneurs. This study found that company value, leadership succession, relationships, and communication affect the financial performance of the family business.

Keywords: company value, family business, financial performance, leadership succession, ownership succession

Procedia PDF Downloads 124
6430 Affordability and Expenditure Patterns towards Sustainable Consumption in Malaysia

Authors: Affordability, Expenditure Patterns towards Sustainable Consumption in Malaysia

Abstract:

Safe drinking water is needed for survival. Households have to pay the water bill monthly. However, lower income households are sometimes unable to afford the cost. This study examines water access and affordability among households in Malaysia and the determinants of water affordability using cross-sectional data and multiple regression. The paper expects that the bill for basic water consumption is inversely related to average income. This means that policy makers need to redesign the water tariff to improve the quality of life of lower income households.

Keywords: affordability, sustainable consumption, income, water tariff

Procedia PDF Downloads 238
6429 A Rare Case Report of Non-Langerhans Cell Cutaneous Histiocytosis in a 6-Month Old Infant

Authors: Apoorva D. R.

Abstract:

INTRODUCTION: Hemophagocytic lymphohistiocytosis (HLH) is a severe, potentially fatal syndrome in which there is excessive immune activation. The disease is seen in children and people of all ages, but infants from birth to 18 months are most frequently affected. HLH is a sporadic or familial condition that can be triggered by various events that disturb immunological homeostasis. In cases with a genetic predisposition and sporadic occurrences, infection is a frequent trigger. Because of the rarity of this disease, the diverse clinical presentation, and the lack of specificity in the clinical and laboratory results, prompt treatment is essential, but the biggest obstacle to a favorable outcome is frequently a delay in identification. CASE REPORT: Here we report a case of a 6-month-old male infant who presented to the dermatology outpatient with disseminated skin lesions present over the face, abdomen, scalp, and bilateral upper and lower limbs for the past month. The lesions were insidious in onset, initially started over the abdomen, and gradually progressed to involve other body parts. The patient also had a history of fever which was moderate in grade, on and off in nature for 1 month. There were no significant complaints in the past, family, or drug history. There was no history of feeding difficulties in the baby. Parents gave a history of developmental milestones appropriate for age. Examination findings include multiple well-defined monomorphic erythematous papules with a central crater present over bilateral cheeks. Few lichenoid shiny papules present over bilateral arms, legs, and abdomen. Ultrasound of the abdomen and pelvis showed mild degree hepatosplenomegaly, intraabdominal lymphadenopathy, and bilateral inguinal lymphadenopathy. Routine blood investigations showed anemia and lymphopenia. Multiple X-rays of the skull, chest, and bilateral upper and lower limbs were done and were normal. Histopathology features were suggestive of non-Langerhans cell cutaneous histiocytosis. CONCLUSION: HLH is a fatal and rare disease. A high level of suspicion and an interdisciplinary approach among experienced clinicians, pathologists, and microbiologists to define the diagnosis and causative disease are key to diagnosing this case. Early detection and treatment can reduce patient morbidity and mortality.

Keywords: histiocytosis, non langerhans cell, case report, fatal, rare

Procedia PDF Downloads 84
6428 Uniform and Controlled Cooling of a Steel Block by Multiple Jet Impingement and Airflow

Authors: E. K. K. Agyeman, P. Mousseau, A. Sarda, D. Edelin

Abstract:

During the cooling of hot metals by the circulation of water in canals formed by boring holes in the metal, the rapid phase change of the water due to the high initial temperature of the metal leads to a non homogenous distribution of the phases within the canals. The liquid phase dominates towards the entrance of the canal while the gaseous phase dominates towards the exit. As a result of the different thermal properties of both phases, the metal is not uniformly cooled. This poses a problem during the cooling of moulds, where a uniform temperature distribution is needed in order to ensure the integrity of the part being formed. In this study, the simultaneous use of multiple water jets and an airflow for the uniform and controlled cooling of a steel block is investigated. A circular hole is bored at the centre of the steel block along its length and a perforated steel pipe is inserted along the central axis of the hole. Water jets that impact the internal surface of the steel block are generated from the perforations in the steel pipe when the water within it is put under pressure. These jets are oriented in the opposite direction to that of gravity. An intermittent airflow is imposed in the annular space between the steel pipe and the surface of hole bored in the steel block. The evolution of the temperature with respect to time of the external surface of the block is measured with the help of thermocouples and an infrared camera. Due to the high initial temperature of the steel block (350 °C), the water changes phase when it impacts the internal surface of the block. This leads to high heat fluxes. The strategy used to control the cooling speed of the block is the intermittent impingement of its internal surface by the jets. The intervals of impingement and of non impingement are varied in order to achieve the desired result. An airflow is used during the non impingement periods as an additional regulator of the cooling speed and to improve the temperature homogeneity of the impinged surface. After testing different jet positions, jet speeds and impingement intervals, it’s observed that the external surface of the steel block has a uniform temperature distribution along its length. However, the temperature distribution along its width isn’t uniform with the maximum temperature difference being between the centre of the block and its edge. Changing the positions of the jets has no significant effect on the temperature distribution on the external surface of the steel block. It’s also observed that reducing the jet impingement interval and increasing the non impingement interval slows down the cooling of the block and improves upon the temperature homogeneity of its external surface while increasing the duration of jet impingement speeds up the cooling process.

Keywords: cooling speed, homogenous cooling, jet impingement, phase change

Procedia PDF Downloads 120
6427 Analysis of Ferroresonant Overvoltages in Cable-fed Transformers

Authors: George Eduful, Ebenezer A. Jackson, Kingsford A. Atanga

Abstract:

This paper investigates the impacts of cable length and capacity of transformer on ferroresonant overvoltage in cable-fed transformers. The study was conducted by simulation using the EMTP RV. Results show that ferroresonance can cause dangerous overvoltages ranging from 2 to 5 per unit. These overvoltages impose stress on insulations of transformers and cables and subsequently result in system failures. Undertaking Basic Multiple Regression Analysis (BMR) on the results obtained, a statistical model was obtained in terms of cable length and transformer capacity. The model is useful for ferroresonant prediction and control in cable-fed transformers.

Keywords: ferroresonance, cable-fed transformers, EMTP RV, regression analysis

Procedia PDF Downloads 527
6426 A Finite Memory Residual Generation Filter for Fault Detection

Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

Abstract:

In the current paper, a residual generation filter with finite memory structure is proposed for fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults.

Keywords: residual generation filter, finite memory structure, kalman filter, fast detection

Procedia PDF Downloads 693
6425 Integrating a Six Thinking Hats Approach Into the Prewriting Stage of Argumentative Writing In English as a Foreign Language: A Chinese Case Study of Generating Ideas in Action

Authors: Mei Lin, Chang Liu

Abstract:

Argumentative writing is the most prevalent genre in diverse writing tests. How to construct academic arguments is often regarded as a difficult task by most English as a foreign language (EFL) learners. A failure to generate enough ideas and organise them coherently and logically as well as a lack of competence in supporting their arguments with relevant evidence are frequent problems faced by EFL learners when approaching an English argumentative writing task. Overall, these problems are closely related to planning, and planning an argumentative writing at pre-writing stage plays a vital role in a good academic essay. However, how teachers can effectively guide students to generate ideas is rarely discussed in planning English argumentative writing, apart from brainstorming. Brainstorming has been a common practice used by teachers to help students generate ideas. However, some limitations of brainstorming suggest that it can help students generate many ideas, but ideas might not necessarily be coherent and logic, and could sometimes impede production. It calls for a need to explore effective instructional strategies at pre-writing stage of English argumentative writing. This paper will first examine how a Six Thinking Hats approach can be used to provide a dialogic space for EFL learners to experience and collaboratively generate ideas from multiple perspectives at pre-writing stage. Part of the findings of the impact of a twelve-week intervention (from March to July 2021) on students learning to generate ideas through engaging in group discussions of using Six Thinking Hats will then be reported. The research design is based on the sociocultural theory. The findings present evidence from a mixed-methods approach and fifty-nine participants from two first-year undergraduate natural classes in a Chinese university. Analysis of pre- and post- questionnaires suggests that participants had a positive attitude toward the Six Thinking Hats approach. It fosters their understanding of prewriting and argumentative writing, helps them to generate more ideas not only from multiple perspectives but also in a systematic way. A comparison of participants writing plans confirms an improvement in generating counterarguments and rebuttals to support their arguments. Above all, visual and transcripts data of group discussion collected from different weeks throughout the intervention enable teachers and researchers to ‘see’ the hidden process of learning to generate ideas in action.

Keywords: argumentative writing, innovative pedagogy, six thinking hats, dialogic space, prewriting, higher education

Procedia PDF Downloads 83
6424 The Changing Role of Technology-Enhanced University Library Reform in Improving College Student Learning Experience and Career Readiness – A Qualitative Comparative Analysis (QCA)

Authors: Xiaohong Li, Wenfan Yan

Abstract:

Background: While it is widely considered that the university library plays a critical role in fulfilling the institution's mission and providing students’ learning experience beyond the classrooms, how the technology-enhanced library reform changed college students’ learning experience hasn’t been thoroughly investigated. The purpose of this study is to explore how technology-enhanced library reform affects students’ learning experience and career readiness and further identify the factors and effective conditions that enable the quality learning outcome of Chinese college students. Methodologies: This study selected the qualitative comparative analysis (QCA) method to explore the effects of technology-enhanced university library reform on college students’ learning experience and career readiness. QCA is unique in explaining the complex relationship between multiple factors from a holistic perspective. Compared with the traditional quantitative and qualitative analysis, QCA not only adds some quantitative logic but also inherits the characteristics of qualitative research focusing on the heterogeneity and complexity of samples. Shenyang Normal University (SNU) selected a sample of the typical comprehensive university in China that focuses on students’ learning and application of professional knowledge and trains professionals to different levels of expertise. A total of 22 current university students and 30 graduates who joined the Library Readers Association of SNU from 2011 to 2019 were selected for semi-structured interviews. Based on the data collected from these participating students, qualitative comparative analysis (QCA), including univariate necessity analysis and the multi-configuration analysis, was conducted. Findings and Discussion: QCA analysis results indicated that the influence of technology-enhanced university library restructures and reorganization on student learning experience and career readiness is the result of multiple factors. Technology-enhanced library equipment and other hardware restructured to meet the college students learning needs and have played an important role in improving the student learning experience and learning persistence. More importantly, the soft characteristics of technology-enhanced library reform, such as library service innovation space and culture space, have a positive impact on student’s career readiness and development. Technology-enhanced university library reform is not only the change in the building's appearance and facilities but also in library service quality and capability. The study also provides suggestions for policy, practice, and future research.

Keywords: career readiness, college student learning experience, qualitative comparative analysis (QCA), technology-enhanced library reform

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6423 Synthetic Dermal Template Use in the Reconstruction of a Chronic Scalp Wound

Authors: Stephanie Cornish

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The use of synthetic dermal templates, also known as dermal matrices, such as PolyNovo® Biodegradable Temporising Matrix (BTM), has been well established in the reconstruction of acute wounds with a full thickness defect of the skin. Its use has become common place in the treatment of full thickness burns and is not unfamiliar in the realm of necrotising fasciitis, free flap donor site reconstruction, and the management of acute traumatic wounds. However, the use of dermal templates for more chronic wounds is rare. The authors present the successful use of BTM in the reconstruction of a chronic scalp wound following the excision of a malignancy and multiple previous failed attempts at repair, thus demonstrating the potential for an increased scope of use.

Keywords: dermal template, BTM, chronic, scalp wound, reconstruction

Procedia PDF Downloads 87
6422 Networks, Regulations and Public Action: The Emerging Experiences of Sao Paulo

Authors: Lya Porto, Giulia Giacchè, Mario Aquino Alves

Abstract:

The paper aims to describe the linkage between government and civil society proposing a study on agro-ecological agriculture policy and urban action in São Paulo city underling the main achievements obtained. The negotiation processes between social movements and the government (inputs) and its results on political regulation and public action for Urban Agriculture (UA) in São Paulo city (outputs) have been investigated. The method adopted is qualitative, with techniques of semi-structured interviews, participant observation, and documental analysis. The authors conducted 30 semi-structured interviews with organic farmers, activists, governmental and non-governmental managers. Participant observation was conducted in public gardens, urban farms, public audiences, democratic councils, and social movements meetings. Finally, public plans and laws were also analyzed. São Paulo city with around 12 million inhabitants spread out in a 1522 km2 is the economic capital of Brazil, marked by spatial and socioeconomic segregation, currently aggravated by environmental crisis, characterized by water scarcity, pollution, and climate changes. In recent years, Urban Agriculture (UA) social movements gained strength and struggle for a different city with more green areas, organic food production, and public occupation. As the dynamics of UA occurs by the action of multiple actresses and institutions that struggle to build multiple senses on UA, the analysis will be based on literature about solidarity economy, governance, public action and networks. Those theories will mark out the analysis that will emphasize the approach of inter-subjectivity built between subjects, as well as the hybrid dynamics of multiple actors and spaces in the construction of policies for UA. Concerning UA we identified four main typologies based on land ownership, main function (economic or activist), form of organization of the space, and type of production (organic or not). The City Hall registers 500 productive unities of agriculture, with around 1500 producers, but researcher estimated a larger number of unities. Concerning the social movements we identified three categories that differ in goals and types of organization, but all of them work by networks of activists and/or organizations. The first category does not consider themselves as a movement, but a network. They occupy public spaces to grow organic food and to propose another type of social relations in the city. This action is similar to what became known as the green guerrillas. The second is configured as a movement that is structured to raise awareness about agro-ecological activities. The third one is a network of social movements, farmers, organizations and politicians that work focused on pressure and negotiation with executive and legislative government to approve regulations and policies on organic and agro-ecological Urban Agriculture. We conclude by highlighting how the interaction among institutions and civil society produced important achievements for recognition and implementation of UA within the city. Some results of this process are awareness for local production, legal and institutional recognition of the rural zone around the city into the planning tool, the investment on organic school public procurements, the establishment of participatory management of public squares, the inclusion of UA on Municipal Strategic Plan and Master Plan.

Keywords: public action, policies, agroecology, urban and peri-urban agriculture, Sao Paulo

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6421 Identification and Selection of a Supply Chain Target Process for Re-Design

Authors: Jaime A. Palma-Mendoza

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A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

Procedia PDF Downloads 485
6420 Modeling of Daily Global Solar Radiation Using Ann Techniques: A Case of Study

Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

Procedia PDF Downloads 339
6419 The New World Kirkpatrick Model as an Evaluation Tool for a Publication Writing Programme

Authors: Eleanor Nel

Abstract:

Research output is an indicator of institutional performance (and quality), resulting in increased pressure on academic institutions to perform in the research arena. Research output is further utilised to obtain research funding. Resultantly, academic institutions face significant pressure from governing bodies to provide evidence on the return for research investments. Research output has thus become a substantial discourse within institutions, mainly due to the processes linked to evaluating research output and the associated allocation of research funding. This focus on research outputs often surpasses the development of robust, widely accepted tools to additionally measure research impact at institutions. A publication writing programme, for enhancing research output, was launched at a South African university in 2011. Significant amounts of time, money, and energy have since been invested in the programme. Although participants provided feedback after each session, no formal review was conducted to evaluate the research output directly associated with the programme. Concerns in higher education about training costs, learning results, and the effect on society have increased the focus on value for money and the need to improve training, research performance, and productivity. Furthermore, universities rely on efficient and reliable monitoring and evaluation systems, in addition to the need to demonstrate accountability. While publishing does not occur immediately, achieving a return on investment from the intervention is critical. A multi-method study, guided by the New World Kirkpatrick Model (NWKM), was conducted to determine the impact of the publication writing programme for the period of 2011 to 2018. Quantitative results indicated a total of 314 academics participating in 72 workshops over the study period. To better understand the quantitative results, an open-ended questionnaire and semi-structured interviews were conducted with nine participants from a particular faculty as a convenience sample. The purpose of the research was to collect information to develop a comprehensive framework for impact evaluation that could be used to enhance the current design and delivery of the programme. The qualitative findings highlighted the critical role of a multi-stakeholder strategy in strengthening support before, during, and after a publication writing programme to improve the impact and research outputs. Furthermore, monitoring on-the-job learning is critical to ingrain the new skills academics have learned during the writing workshops and to encourage them to be accountable and empowered. The NWKM additionally provided essential pointers on how to link the results more effectively from publication writing programmes to institutional strategic objectives to improve research performance and quality, as well as what should be included in a comprehensive evaluation framework.

Keywords: evaluation, framework, impact, research output

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6418 Municipal Solid Waste Management and Analysis of Waste Generation: A Case Study of Bangkok, Thailand

Authors: Pitchayanin Sukholthaman

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Gradually accumulated, the enormous amount of waste has caused tremendous adverse impacts to the world. Bangkok, Thailand, is chosen as an urban city of a developing country having coped with serious MSW problems due to the vast amount of waste generated, ineffective and improper waste management problems. Waste generation is the most important factor for successful planning of MSW management system. Thus, the prediction of MSW is a very important role to understand MSW distribution and characteristic; to be used for strategic planning issues. This study aims to find influencing variables that affect the amount of Bangkok MSW generation quantity.

Keywords: MSW generation, MSW quantity prediction, MSW management, multiple regression, Bangkok

Procedia PDF Downloads 418
6417 A Survey of Semantic Integration Approaches in Bioinformatics

Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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6416 Analysis of Production Forecasting in Unconventional Gas Resources Development Using Machine Learning and Data-Driven Approach

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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6415 A Systematic Review of Process Research in Software Engineering

Authors: Tulasi Rayasa, Phani Kumar Pullela

Abstract:

A systematic review is a research method that involves collecting and evaluating the information on a specific topic in order to provide a comprehensive and unbiased review. This type of review aims to improve the software development process by ensuring that the research is thorough and accurate. To ensure objectivity, it is important to follow systematic guidelines and consider multiple sources, such as literature reviews, interviews, and surveys. The evaluation process should also be streamlined by incorporating research from journals and other sources, such as grey literature. The main goal of a systematic review is to identify the consistency of current models in the field of computer application and software engineering.

Keywords: computer application, software engineering, process research, data science

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6414 Optimal ECG Sampling Frequency for Multiscale Entropy-Based HRV

Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

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6413 Predicting Personality and Psychological Distress Using Natural Language Processing

Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

Abstract:

Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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6412 The Artificial Intelligence Technologies Used in PhotoMath Application

Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

Abstract:

This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

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6411 Benefit Of Waste Collection Route Optimisation

Authors: Bojana Tot, Goran BošKović, Goran Vujić

Abstract:

Route optimisation is a process of planning one or multiple routes, with the purpose of minimizing overall costs, while achieving the highest possible performance under a set of given constraints. It combines routing or route planning, which is the process of creating the most cost-effective route by minimizing the distance or travelled time necessary to reach a set of planned stops, and route scheduling, which is the process of assigning an arrival and service time for each stop, with drivers being given shifts that adhere to their working hours. The objective of this paper is to provide benefits on the implementation of waste collection route optimisation and thus achieve economic efficiency for public utility companies, better service for citizens and positive environment and health.

Keywords: waste management, environment, collection route optimisation, GIS

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6410 Development of a Stable RNAi-Based Biological Control for Sheep Blowfly Using Bentonite Polymer Technology

Authors: Yunjia Yang, Peng Li, Gordon Xu, Timothy Mahony, Bing Zhang, Neena Mitter, Karishma Mody

Abstract:

Sheep flystrike is one of the most economically important diseases affecting the Australian sheep and wool industry (>356M/annually). Currently, control of Lucillia cuprina relies almost exclusively on chemicals controls and the parasite has developed resistance to nearly all control chemicals used in the past. It is therefore critical to develop an alternative solution for the sustainable control and management of flystrike. RNA interference (RNAi) technologies have been successfully explored in multiple animal industries for developing parasites controls. This research project aims to develop a RNAi based biological control for sheep blowfly. Double-stranded RNA (dsRNA) has already proven successful against viruses, fungi and insects. However, the environmental instability of dsRNA is a major bottleneck for successful RNAi. Bentonite polymer (BenPol) technology can overcome this problem, as it can be tuned for the controlled release of dsRNA in the gut challenging pH environment of the blowfly larvae, prolonging its exposure time to and uptake by target cells. To investigate the potential of BenPol technology for dsRNA delivery, four different BenPol carriers were tested for their dsRNA loading capabilities, and three of them were found to be capable of affording dsRNA stability under multiple temperatures (4°C, 22°C, 40°C, 55°C) in sheep serum. Based on stability results, dsRNA from potential targeted genes was loaded onto BenPol carriers and tested in larvae feeding assays, three genes resulting in knockdowns. Meanwhile, a primary blowfly embryo cell line (BFEC) derived from L. cuprina embryos was successfully established, aim for an effective insect cell model for testing RNAi efficacy for preliminary assessments and screening. The results of this study establish that the dsRNA is stable when loaded on BenPol particles, unlike naked dsRNA rapidly degraded in sheep serum. The stable nanoparticle delivery system offered by BenPol technology can protect and increase the inherent stability of dsRNA molecules at higher temperatures in a complex biological fluid like serum, providing promise for its future use in enhancing animal protection.

Keywords: flystrike, RNA interference, bentonite polymer technology, Lucillia cuprina

Procedia PDF Downloads 84