Search results for: supply chain delivery models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11603

Search results for: supply chain delivery models

8153 Concurrent Engineering Challenges and Resolution Mechanisms from Quality Perspectives

Authors: Grmanesh Gidey Kahsay

Abstract:

In modern technical engineering applications, quality is defined in two ways. The first one is that quality is the parameter that measures a product or service’s characteristics to meet and satisfy the pre-stated or fundamental needs (reliability, durability, serviceability). The second one is the quality of a product or service free of any defect or deficiencies. The American Society for Quality (ASQ) describes quality as a pursuit of optimal solutions to confirm successes and fulfillment to be accountable for the product or service's requirements and expectations. This article focuses on quality engineering tools in modern industrial applications. Quality engineering is a field of engineering that deals with the principles, techniques, models, and applications of the product or service to guarantee quality. Including the entire activities to analyze the product’s design and development, quality engineering emphasizes how to make sure that products and services are designed and developed to meet consumers’ requirements. This episode acquaints with quality tools such as quality systems, auditing, product design, and process control. The finding presents thoughts that aim to improve quality engineering proficiency and effectiveness by introducing essential quality techniques and tools in some selected industries.

Keywords: essential quality tools, quality systems and models, quality management systems, and quality assurance

Procedia PDF Downloads 148
8152 Empirical Modeling of Air Dried Rubberwood Drying System

Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit

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Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (= 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.

Keywords: empirical models, rubberwood, moisture ratio, hot air drying

Procedia PDF Downloads 262
8151 Computer-Assisted Management of Building Climate and Microgrid with Model Predictive Control

Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

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With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: price-optimal building climate control, Microgrid power flow optimisation, hierarchical model predictive control, energy efficient buildings, energy market participation

Procedia PDF Downloads 460
8150 Cognitive eTransformation Framework for Education Sector

Authors: A. Hol

Abstract:

21st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.

Keywords: education sector, business transformation, eTransformation model, cognitive model, cognitive systems, eTransformation

Procedia PDF Downloads 133
8149 A Dynamic Neural Network Model for Accurate Detection of Masked Faces

Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

Procedia PDF Downloads 60
8148 Spatial Analysis of Survival Pattern and Treatment Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) Patients in Lagos, Nigeria

Authors: Akinsola Oluwatosin, Udofia Samuel, Odofin Mayowa

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The study is aimed at assessing the Geographic Information System (GIS)-based spatial analysis of Survival Pattern and Treatment Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) cases for Lagos, Nigeria, with an objective to inform priority areas for public health planning and resource allocation. Multi-drug resistant tuberculosis (MDR-TB) develops due to problems such as irregular drug supply, poor drug quality, inappropriate prescription, and poor adherence to treatment. The shapefile(s) for this study were already georeferenced to Minna datum. The patient’s information was acquired on MS Excel and later converted to . CSV file for easy processing to ArcMap from various hospitals. To superimpose the patient’s information the spatial data, the addresses was geocoded to generate the longitude and latitude of the patients. The database was used for the SQL query to the various pattern of the treatment. To show the pattern of disease spread, spatial autocorrelation analysis was used. The result was displayed in a graphical format showing the areas of dispersing, random and clustered of patients in the study area. Hot and cold spot analysis was analyzed to show high-density areas. The distance between these patients and the closest health facility was examined using the buffer analysis. The result shows that 22% of the points were successfully matched, while 15% were tied. However, the result table shows that a greater percentage of it was unmatched; this is evident in the fact that most of the streets within the State are unnamed, and then again, most of the patients are likely to supply the wrong addresses. MDR-TB patients of all age groups are concentrated within Lagos-Mainland, Shomolu, Mushin, Surulere, Oshodi-Isolo, and Ifelodun LGAs. MDR-TB patients between the age group of 30-47 years had the highest number and were identified to be about 184 in number. The outcome of patients on ART treatment revealed that a high number of patients (300) were not ART treatment while a paltry 45 patients were on ART treatment. The result shows the Z-score of the distribution is greater than 1 (>2.58), which means that the distribution is highly clustered at a significance level of 0.01.

Keywords: tuberculosis, patients, treatment, GIS, MDR-TB

Procedia PDF Downloads 146
8147 Use Cloud-Based Watson Deep Learning Platform to Train Models Faster and More Accurate

Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

Procedia PDF Downloads 204
8146 Numerical Investigation of Cavitation on Different Venturi Shapes by Computational Fluid Dynamics

Authors: Sedat Yayla, Mehmet Oruc, Shakhwan Yaseen

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Cavitation phenomena might rigorously impair machine parts such as pumps, propellers and impellers or devices as the pressure in the fluid declines under the liquid's saturation pressure. To evaluate the influence of cavitation, in this research two-dimensional computational fluid dynamics (CFD) venturi models with variety of inlet pressure values, throat lengths and vapor fluid contents were applied. In this research three different vapor contents (0%, 5% 10%), four inlet pressures (2, 4, 6, 8 and 10 atm) and two venturi models were employed at different throat lengths ( 5, 10, 15 and 20 mm) for discovering the impact of each parameter on the cavitation number. It is uncovered that there is a positive correlation between pressure inlet and vapor fluid content and cavitation number. Furthermore, it is unveiled that velocity remains almost constant at the inlet pressures of 6, 8,10atm, nevertheless increasing the length of throat results in the substantial escalation in the velocity of the throat at inlet pressures of 2 and 4 atm. Furthermore, velocity and cavitation number were negatively correlated. The results of the cavitation number varied between 0.092 and 0.495 depending upon the velocity values of the throat.

Keywords: cavitation number, computational fluid dynamics, mixture of fluid, two-phase flow, velocity of throat

Procedia PDF Downloads 394
8145 Simulation of the Visco-Elasto-Plastic Deformation Behaviour of Short Glass Fibre Reinforced Polyphthalamides

Authors: V. Keim, J. Spachtholz, J. Hammer

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The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

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8144 Effect of Span 60, Labrasol, and Cholesterol on Labisia pumila Loaded Niosomes Quality

Authors: H. Binti Ya’akob, C. Siew Chin, A. Abd Aziz, I. Ware, M. Fauzi Abd Jalil, N. Rashidah Ahmed, R. Sabtu

Abstract:

Labisia pumila (LP) plant extract has the potential to be applied in cosmeceutical products due to its anti-photoaging properties. The main purpose of this study was to improve transdermal delivery of LP by encapsulating LP in niosomes. Niosomes loaded LPs were prepared by coacervation phase separation method using non-ionic surfactant (Span 60), labrasol, and cholesterol. The optimum formula obtained were Span 60, labrasol and cholesterol at the mole ratio of 6:1:4. At the optimum formulation, the niosome obtained significantly improved the quality of transdermal penetration of LP compared to free LP.

Keywords: Labisia pumila, niosomes, transdermal, quality

Procedia PDF Downloads 309
8143 Energizing Value Added Farming in Agriculture Economic Aspects towards Sustaining Crop Yield, Quality and Food Safety of Small-Scale Cocoa Farmer in Indonesia

Authors: Burmansyah Muhammad, Supriyoto Supriyoto

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Crop yield, quality and food safety are three important components that all estate and food crops must put into consideration to lifting the economic value. These measurements should be evaluated because marketplace demand is simultaneously changing and farmers must adapt quickly to remain competitive. The increase in economic value could be done by producing high quality product that aligns with harvest collector preferences. The purpose of this study is to examine the causal effects of value added farming in agriculture economic aspects towards crop yield, quality and food security. This research is using descriptive survey research by employing data from small-scale cocoa farmers listed to off-taker company, located on Sulawesi area of Indonesia. The questionnaire was obtained from 650 cocoa farmers, selected randomly. Major findings of the study indicate that 78% of respondents agree that agriculture inputs have positive effect on crop yield, quality and food safety. The study recommended that cocoa stakeholders should ensure access to agriculture inputs in first priority and then followed by ensuring access to cocoa supply chain trader and micro-financing. Value Added Farming refers to lifting the economic value of a commodity through particular intervention. Regarding access to agriculture inputs, one of significant intervention is fertilization and plant nutrition management, both organic and inorganic fertilizer. Small-scale cocoa farmers can get access to fertilizer intervention through establishment of demo farm. Ordinary demo farm needs large area, selective requirements, lots of field resources and centralization impact. On the contrary, satellite demo farm is developing to wide-spread the impact of agriculture economic aspects and also the involvement in number of farmers. In Sulawesi Project, we develop leveling strata of small-scale demo farm with group of farmers and local cooperative. With this methodology, all of listed small-scale farmers can get access to agriculture input, micro-financing and how to deliver quality output. PT Pupuk Kaltim is member firm of holding company PT Pupuk Indonesia, private company belongs to the government of Indonesia. The company listed as Indonesia's largest producer of urea fertilizers, besides ammonia, Compound Fertilizer (NPK) and biological fertilizers. To achieve strategic objectives, the company has distinguished award such as SNI Platinum, SGS Award IFA Protect and Sustain Stewardship and Gold Rank of Environment Friendly Company. This achievement has become the strategic foundation for our company to energize value added farming in sustaining food security program. Moreover, to ensure cocoa sustainability farming the company has developed partnership with international companies and Non-Government Organization (NGO).

Keywords: fertilizer and plant nutrition management, good agriculture practices, agriculture economic aspects, value-added farming

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8142 Exact and Approximate Controllability of Nuclear Dynamics Using Bilinear Controls

Authors: Ramdas Sonawane, Mahaveer Gadiya

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The control problem associated with nuclear dynamics is represented by nonlinear integro-differential equation with additive controls. To control chain reaction, certain amount of neutrons is added into (or withdrawn out of) chamber as and when required. It is not realistic. So, we can think of controlling the reactor dynamics by bilinear control, which enters the system as coefficient of state. In this paper, we study the approximate and exact controllability of parabolic integro-differential equation controlled by bilinear control with non-homogeneous boundary conditions in bounded domain. We prove the existence of control and propose an explicit control strategy.

Keywords: approximate control, exact control, bilinear control, nuclear dynamics, integro-differential equations

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8141 Access to Financial Services to Rural Poor in Nepal: Challenges and Way Forward

Authors: Krishna Prasad Sharma

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Nepal’s financial sector has become deeper and wider, and the number and types of financial intermediaries have grown rapidly over the past two decades. However, access to financial services remains limited for many people in many parts of rural Nepal. While financial institutions have been expanding rapidly in an urban area in recent years, the access to the rural poor is excessively inadequate due to financial illiteracy and limited numbers of financial institutions that confined only to the district headquarters. Based on the focus group discussion, semi-structured interview of key people and literature review, this paper aims to examine the supply of and demand for financial services in Nepal and the constraints to increasing access to them, and offers way forward for making the financial sector work for all of Nepal’s people, especially the rural poor. While Nepal’s government has tried to increase access to formal financial services for small businesses and low-income households through directed lending programs for small businesses and low-income households, created specialized wholesale and retail institutions, and lowered market entry requirements, formal financial services are declining, and financial intermediation is stagnating. Supply and demand indicators show that, despite government efforts, formal financial institutions do not serve the needs of most of the Nepalese population. While access to and use of formal financial services are limited, in general, the problem is acute for small businesses and low-income households. Indeed, both access and use are closely correlated with business loan size and household income. This study concludes that banks and microfinance institutions with the use of mobile phones can connect hundreds of millions of unbanked and low-income people, especially rural poor to financial services at low costs. While there are many challenges ahead in expanding the service to rural areas, the mobile financial services will be beneficial that makes payments faster and cheaper, more convenient and accessible to a greater number of senders and recipients in rural areas. In rural areas, clients will benefit from money transfer and other mobile and online services.

Keywords: financial inclusion, financial enabling environment, microfinance, branchless banking, rural poor

Procedia PDF Downloads 285
8140 Exploring Problem-Based Learning and University-Industry Collaborations for Fostering Students’ Entrepreneurial Skills: A Qualitative Study in a German Urban Setting

Authors: Eylem Tas

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This empirical study aims to explore the development of students' entrepreneurial skills through problem-based learning within the context of university-industry collaborations (UICs) in curriculum co-design and co-delivery (CDD). The research question guiding this study is: "How do problem-based learning and university-industry collaborations influence the development of students' entrepreneurial skills in the context of curriculum co-design and co-delivery?” To address this question, the study was conducted in a big city in Germany and involved interviews with stakeholders from various industries, including the private sector, government agencies (govt), and non-governmental organizations (NGOs). These stakeholders had established collaborative partnerships with the targeted university for projects encompassing entrepreneurial development aspects in CDD. The study sought to gain insights into the intricacies and subtleties of UIC dynamics and their impact on fostering entrepreneurial skills. Qualitative content analysis, based on Mayring's guidelines, was employed to analyze the interview transcriptions. Through an iterative process of manual coding, 442 codes were generated, resulting in two main sections: "the role of problem-based learning and UIC in fostering entrepreneurship" and "challenges and requirements of problem-based learning within UIC for systematical entrepreneurship development.” The chosen experimental approach of semi-structured interviews was justified by its capacity to provide in-depth perspectives and rich data from stakeholders with firsthand experience in UICs in CDD. By enlisting participants with diverse backgrounds, industries, and company sizes, the study ensured a comprehensive and heterogeneous sample, enhancing the credibility of the findings. The first section of the analysis delved into problem-based learning and entrepreneurial self-confidence to gain a deeper understanding of UIC dynamics from an industry standpoint. It explored factors influencing problem-based learning, alignment of students' learning styles and preferences with the experiential learning approach, specific activities and strategies, and the role of mentorship from industry professionals in fostering entrepreneurial self-confidence. The second section focused on various interactions within UICs, including communication, knowledge exchange, and collaboration. It identified key elements, patterns, and dynamics of interaction, highlighting challenges and limitations. Additionally, the section emphasized success stories and notable outcomes related to UICs' positive impact on students' entrepreneurial journeys. Overall, this research contributes valuable insights into the dynamics of UICs and their role in fostering students' entrepreneurial skills. UICs face challenges in communication and establishing a common language. Transparency, adaptability, and regular communication are vital for successful collaboration. Realistic expectation management and clearly defined frameworks are crucial. Responsible data handling requires data assurance and confidentiality agreements, emphasizing the importance of trust-based relationships when dealing with data sharing and handling issues. The identified key factors and challenges provide a foundation for universities and industrial partners to develop more effective UIC strategies for enhancing students' entrepreneurial capabilities and preparing them for success in today's digital age labor market. The study underscores the significance of collaborative learning and transparent communication in UICs for entrepreneurial development in CDD.

Keywords: collaborative learning, curriculum co-design and co-delivery, entrepreneurial skills, problem-based learning, university-industry collaborations

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8139 Financial Liberalization, Exchange Rates and Demand for Money in Developing Economies: The Case of Nigeria, Ghana and Gambia

Authors: John Adebayo Oloyhede

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This paper examines effect of financial liberalization on the stability of the demand for money function and its implication for exchange rate behaviour of three African countries. As the demand for money function is regarded as one of the two main building blocks of most exchange rate determination models, the other being purchasing power parity, its stability is required for the monetary models of exchange rate determination to hold. To what extent has the liberalisation policy of these countries, for instance liberalised interest rate, affected the demand for money function and what has been the consequence on the validity and relevance of floating exchange rate models? The study adopts the Autoregressive Instrumental Package (AIV) of multiple regression technique and followed the Almon Polynomial procedure with zero-end constraint. Data for the period 1986 to 2011 were drawn from three developing countries of Africa, namely: Gambia, Ghana and Nigeria, which did not only start the liberalization and floating system almost at the same period but share similar and diverse economic and financial structures. Its findings show that the demand for money was a stable function of income and interest rate at home and abroad. Other factors such as exchange rate and foreign interest rate exerted some significant effect on domestic money demand. The short-run and long-run elasticity with respect to income, interest rates, expected inflation rate and exchange rate expectation are not greater than zero. This evidence conforms to some extent to the expected behaviour of the domestic money function and underscores its ability to serve as good building block or assumption of the monetary model of exchange rate determination. This will, therefore, assist appropriate monetary authorities in the design and implementation of further financial liberalization policy packages in developing countries.

Keywords: financial liberalisation, exchange rates, demand for money, developing economies

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8138 Multi-Faceted Growth in Creative Industries

Authors: Sanja Pfeifer, Nataša Šarlija, Marina Jeger, Ana Bilandžić

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The purpose of this study is to explore the different facets of growth among micro, small and medium-sized firms in Croatia and to analyze the differences between models designed for all micro, small and medium-sized firms and those in creative industries. Three growth prediction models were designed and tested using the growth of sales, employment and assets of the company as dependent variables. The key drivers of sales growth are: prudent use of cash, industry affiliation and higher share of intangible assets. Growth of assets depends on retained profits, internal and external sources of financing, as well as industry affiliation. Growth in employment is closely related to sources of financing, in particular, debt and it occurs less frequently than growth in sales and assets. The findings confirm the assumption that growth strategies of small and medium-sized enterprises (SMEs) in creative industries have specific differences in comparison to SMEs in general. Interestingly, only 2.2% of growing enterprises achieve growth in employment, assets and sales simultaneously.

Keywords: creative industries, growth prediction model, growth determinants, growth measures

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8137 Development of Anterior Lumbar Interbody Fusion (ALIF) Peek Cage Based on the Korean Lumbar Anatomical Information

Authors: Chang Soo Chon, Cheol Woong Ko, Han Sung Kim

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The aim of this study is to develop an anterior lumbar interbody fusion (ALIF) PEEK cage suitable for Korean people. In this study, CT images were obtained from Korean male (173cm, 71kg) and 3D Korean lumbar models were reconstructed based on the CT images to investigate anatomical characteristics. Major design parameters of anterior lumbar interbody fusion (ALIF) PEEK Cage were selected using the morphological measurement information of the Korean Lumbar models. Through finite element analysis and mechanical tests, the developed ALIF PEEK Cage prototype was compared with the Fidji Cage (Zimmer.Inc, USA) and it was found that the ALIF prototype showed similar and/or superior mechanical performance compared to the FidJi Cage. Also, clinical validation for the ALIF PEEK Cage prototype was carried out to check predictable troubles in surgical operations. Finally, it is considered that the convenience and stability of the prototype was clinically verified.

Keywords: inter-body anterior fusion, ALIF cage, PEEK, Korean lumbar, CT image, animal test

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8136 Price Gouging in Time of Covid-19 Pandemic: When National Competition Agencies are Weak Institutions that Exacerbate the Effects of Exploitative Economic Behaviour

Authors: Cesar Leines

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The social effects of the pandemic are significant and diverse, most of those effects have widened the gap of economic inequality. Without a doubt, each country faces difficulties associated with the strengths and weaknesses of its own institutions that can address these causes and consequences. Around the world, pricing practices that have no connection to production costs have been used extensively in numerous markets beyond those relating to the supply of essential goods and services, and although it is not unlawful to adjust pricing considering the increased demand of certain products, shortages and disruption of supply chains, illegitimate pricing practices may arise and these tend to transfer wealth from consumers to producers that affect the purchasing power of the former, making people worse off. High prices with no objective justification indicate a poor state of the competitive process in any market and the impact of those underlying competition issues leading to inefficiency is increased when national competition agencies are weak and ineffective in enforcing competition in law and policy. It has been observed that in those countries where competition authorities are perceived as weak or ineffective, price increases of a wide range of products and services were more significant during the pandemic than those price increases observed in countries where the perception of the effectiveness of the competition agency is high. When a perception is created of a highly effective competition authority, one which enforces competition law and its non-enforcement activities result in the fulfillment of its substantive functions of protecting competition as the means to create efficient markets, the price rise observed in markets under its jurisdiction is low. A case study focused on the effectiveness of the national competition agency in Mexico (COFECE) points to institutional weakness as one of the causes leading to excessive pricing. There are many factors that contribute to its low effectiveness and which, in turn, have led to a very significant price hike, potentiated by the pandemic. This paper contributes to the discussion of these factors and proposes different steps that overall help COFECE or any other competition agency to increase the perception of effectiveness for the benefit of the consumers.

Keywords: agency effectiveness, competition, institutional weakness, price gouging

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8135 Proposal Evaluation of Critical Success Factors (CSF) in Lean Manufacturing Projects

Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Critical success factors (CSF) are used to design the practice of project management that can lead directly or indirectly to the success of the project. This management includes many elements that have to be synchronized in order to ensure the project on-time delivery, quality and the lowest possible cost. The objective of this work is to develop a proposal for evaluation of the FCS in lean manufacturing projects, and apply the evaluation in a pilot project. The results show that the use of continuous improvement programs in organizations brings benefits as the process cost reduction and improve productivity.

Keywords: continuous improvement, critical success factors (csf), lean thinking, project management

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8134 The Best Prediction Data Mining Model for Breast Cancer Probability in Women Residents in Kabul

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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8133 Conduction Transfer Functions for the Calculation of Heat Demands in Heavyweight Facade Systems

Authors: Mergim Gasia, Bojan Milovanovica, Sanjin Gumbarevic

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Better energy performance of the building envelope is one of the most important aspects of energy savings if the goals set by the European Union are to be achieved in the future. Dynamic heat transfer simulations are being used for the calculation of building energy consumption because they give more realistic energy demands compared to the stationary calculations that do not take the building’s thermal mass into account. Software used for these dynamic simulation use methods that are based on the analytical models since numerical models are insufficient for longer periods. The analytical models used in this research fall in the category of the conduction transfer functions (CTFs). Two methods for calculating the CTFs covered by this research are the Laplace method and the State-Space method. The literature review showed that the main disadvantage of these methods is that they are inadequate for heavyweight façade elements and shorter time periods used for the calculation. The algorithms for both the Laplace and State-Space methods are implemented in Mathematica, and the results are compared to the results from EnergyPlus and TRNSYS since these software use similar algorithms for the calculation of the building’s energy demand. This research aims to check the efficiency of the Laplace and the State-Space method for calculating the building’s energy demand for heavyweight building elements and shorter sampling time, and it also gives the means for the improvement of the algorithms used by these methods. As the reference point for the boundary heat flux density, the finite difference method (FDM) is used. Even though the dynamic heat transfer simulations are superior to the calculation based on the stationary boundary conditions, they have their limitations and will give unsatisfactory results if not properly used.

Keywords: Laplace method, state-space method, conduction transfer functions, finite difference method

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8132 The Patterns Designation by the Inspiration from Flower at Suan Sunandha Palace

Authors: Nawaporn Srisarankullawong

Abstract:

This research is about the creating the design by the inspiration of the flowers, which were once planted in Suan Sunandha Palace. The researcher have conducted the research regarding the history of Suan Sunandha Palace and the flowers which have been planted in the palace’s garden, in order to use this research to create the new designs in the future. The objective are as follows; 1. To study the shape and the pattern of the flowers in Suan Sunandha Palace, in order to select a few of them as the model to create the new design. 2. In order to create the flower design from the flowers in Suan Sunandha Palace by using the current photograph of the flowers which were once used to be planted inside the palace and using adobe Illustrator and Adobe Photoshop programs to create the patterns and the model. The result of the research: From the research, the researcher had selected three types of flowers to crate the pattern model; they are Allamanda, Orchids and Flamingo Plant. The details of the flowers had been reduced in order to show the simplicity and create the pattern model to use them for models, so three flowers had created three pattern models and they had been developed into six patterns, using universal artist techniques, so the pattern created are modern and they can be used for further decoration.

Keywords: patterns design, Suan Sunandha Palace, pattern of the flowers, visual arts and design

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8131 Contribution of the Corn Milling Industry to a Global and Circular Economy

Authors: A. B. Moldes, X. Vecino, L. Rodriguez-López, J. M. Dominguez, J. M. Cruz

Abstract:

The concept of the circular economy is focus on the importance of providing goods and services sustainably. Thus, in a future it will be necessary to respond to the environmental contamination and to the use of renewables substrates by moving to a more restorative economic system that drives towards the utilization and revalorization of residues to obtain valuable products. During its evolution our industrial economy has hardly moved through one major characteristic, established in the early days of industrialization, based on a linear model of resource consumption. However, this industrial consumption system will not be maintained during long time. On the other hand, there are many industries, like the corn milling industry, that although does not consume high amount of non renewable substrates, they produce valuable streams that treated accurately, they could provide additional, economical and environmental, benefits by the extraction of interesting commercial renewable products, that can replace some of the substances obtained by chemical synthesis, using non renewable substrates. From this point of view, the use of streams from corn milling industry to obtain surface-active compounds will decrease the utilization of non-renewables sources for obtaining this kind of compounds, contributing to a circular and global economy. However, the success of the circular economy depends on the interest of the industrial sectors in the revalorization of their streams by developing relevant and new business models. Thus, it is necessary to invest in the research of new alternatives that reduce the consumption of non-renewable substrates. In this study is proposed the utilization of a corn milling industry stream to obtain an extract with surfactant capacity. Once the biosurfactant is extracted, the corn milling stream can be commercialized as nutritional media in biotechnological process or as animal feed supplement. Usually this stream is combined with other ingredients obtaining a product namely corn gluten feed or may be sold separately as a liquid protein source for beef and dairy feeding, or as a nutritional pellet binder. Following the productive scheme proposed in this work, the corn milling industry will obtain a biosurfactant extract that could be incorporated in its productive process replacing those chemical detergents, used in some point of its productive chain, or it could be commercialized as a new product of the corn manufacture. The biosurfactants obtained from corn milling industry could replace the chemical surfactants in many formulations, and uses, and it supposes an example of the potential that many industrial streams could offer for obtaining valuable products when they are manage properly.

Keywords: biosurfactantes, circular economy, corn, sustainability

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8130 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

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8129 Developing a Framework for Online Auction Effectiveness

Authors: Chechen Liao, Pui-Lai To, Chiao-Ying Chen

Abstract:

An introduction of internet auction has significantly widened the pool of consumers who participate in auctions and increased the number of companies attempting to sell their products in an auction format. Previous research on auctions has focused almost exclusively on the behavior of professional bidders. In this study, we focus on the characteristic of seller, auction parameter and the effect of supply and demand, and examine these impacts on auction effectiveness. In particular, a framework for online auction effectiveness was developed. The framework will help researchers and practitioner to find ways to improve online auction effectiveness.

Keywords: Auction Effectiveness, Framework Developing, Online Auction, Selling Strategy

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8128 Explaining the Impact of Poverty Risk on Frailty Trajectories in Old Age Using Growth Curve Models

Authors: Erwin Stolz, Hannes Mayerl, Anja Waxenegger, Wolfgang Freidl

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Research has often found poverty associated with adverse health outcomes, but it is unclear which (interplay of) mechanisms actually translate low economic resources into poor physical health. The goal of this study was to assess the impact of educational, material, psychosocial and behavioural factors in explaining the poverty-health association in old age. We analysed 28,360 observations from 11,390 community-dwelling respondents (65+) from the Survey of Health, Ageing and Retirement in Europe (SHARE, 2004-2013, 10 countries). We used multilevel growth curve models to assess the impact of combined income- and asset poverty risk on old age frailty index levels and trajectories. In total, 61.8% of the variation of poverty risk on frailty levels could be explained by direct and indirect effects, thereby highlighting the role of material and particularly psychosocial factors, such as perceived control and social isolation. We suggest strengthening social policy and public health efforts in order to fight poverty and its deleterious effects from early age on and to broaden the scope of interventions with regard to psychosocial factors.

Keywords: frailty, health inequality, old age, poverty

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8127 Poly (N-Isopropyl Acrylamide-Co-Acrylic Acid)-Graft-Polyaspartate Coated Magnetic Nanoparticles for Molecular Imaging and Therapy

Authors: Van Tran Thi Thuy, Dukjoon Kim

Abstract:

A series of pH- and thermosensitive poly(N-isopropyl acrylamide-co-acrylic acid) were synthesized by radical polymerization and grafted on poly succinimide backbones. The poly succinimide derivatives synthesized were coated on iron oxide magnetic nanoparticles for potential applications in drug delivery systems with theranostic and molecular imaging. The structure of polymer shell was confirmed by FT-IR, H-NMR spectroscopies. Its thermal behavior was tested by UV-Vis spectroscopy. The particle size and its distribution are measured by dynamic light scattering (DLS) and transmission electron microscope (TEM). The mean diameter of the core-shell structure is from 20 to 80 nm.

Keywords: magnetic, nano, PNIPAM, polysuccinimide

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8126 Simulation of Flow through Dam Foundation by FEM and ANN Methods Case Study: Shahid Abbaspour Dam

Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

Abstract:

In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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8125 A Telecoupling Lens to Study Global Sustainability Entanglements along Supply Chains: The Case of Dutch-Kenyan Rose Trade

Authors: Klara Strecker

Abstract:

During times of globalization, socioeconomic systems have become connected across the world through global supply chains. As a result, consumption and production locations have increasingly become spatially decoupled. This decoupling leads to complex entanglements of systems and sustainability challenges across distances -entanglements which can be conceptualized as telecouplings. Through telecouplings, people and environments across the world have become closely connected, bringing challenges as well as opportunities. Some argue that telecoupling dynamics started taking shape during times of colonization when resources were first traded across the world. An example of such a telecoupling is that of the rose. Every third rose sold in Europe is grown in Kenya and enters the European market through the Dutch flower auction system. Many Kenyan farms are Dutch-owned, closely entangling Kenya and the Netherlands through the trade of roses. Furthermore, the globalization of the flower industry and the resulting shift of production away from the Netherlands and towards Kenya has led to significant changes in the Dutch horticulture sector. However, the sustainability effects of this rose telecoupling is limited neither to the horticulture sector nor to the Netherlands and Kenya. Alongside the flow of roses between these countries come complex financial, knowledge-based, and regulatory flows. The rose telecoupling also creates spillover effects to other countries, such as Ethiopia, and other industries, such as Kenyan tourism. Therefore, telecoupling dynamics create complex entanglements that cut across sectors, environments, communities, and countries, which makes effectively governing and managing telecouplings and their sustainability implications challenging. Indeed, sustainability can no longer be studied in spatial and temporal isolation. This paper aims to map the rose telecoupling’s complex environmental and social interactions to identify points of tension guiding sustainability-targeted interventions. Mapping these interactions will provide a more holistic understanding of the sustainability challenges involved in the Dutch-Kenyan rose trade. This interdisciplinary telecoupling approach reframes and integrates interdisciplinary knowledge about the rose trade between the Netherlands, Kenya, and beyond.

Keywords: Dutch-Kenyan rose trade, globalization, socio-ecological system, sustainability, telecoupling

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8124 Deep-Learning to Generation of Weights for Image Captioning Using Part-of-Speech Approach

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

Procedia PDF Downloads 95