Search results for: dairy industries inventory optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5956

Search results for: dairy industries inventory optimization

2236 The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models

Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

Abstract:

This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

Procedia PDF Downloads 149
2235 Multi-Criteria Goal Programming Model for Sustainable Development of India

Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

Abstract:

Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

Procedia PDF Downloads 223
2234 Analysis of Structural Modeling on Digital English Learning Strategy Use

Authors: Gyoomi Kim, Jiyoung Bae

Abstract:

The purpose of this study was to propose a framework that verifies the structural relationships among students’ use of digital English learning strategy (DELS), affective domains, and their individual variables. The study developed a hypothetical model based on previous studies on language learning strategy use as well as digital language learning. The participants were 720 Korean high school students and 430 university students. The instrument was a self-response questionnaire that contained 70 question items based on Oxford’s SILL (Strategy Inventory for Language Learning) as well as the previous studies on language learning strategies in digital learning environment in order to measure DELS and affective domains. The collected data were analyzed through structural equation modeling (SEM). This study used quantitative data analysis procedures: Explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). Firstly, the EFA was conducted in order to verify the hypothetical model; the factor analysis was conducted preferentially to identify the underlying relationships between measured variables of DELS and the affective domain in the EFA process. The hypothetical model was established with six indicators of learning strategies (memory, cognitive, compensation, metacognitive, affective, and social strategies) under the latent variable of the use of DELS. In addition, the model included four indicators (self-confidence, interests, self-regulation, and attitude toward digital learning) under the latent variable of learners’ affective domain. Secondly, the CFA was used to determine the suitability of data and research models, so all data from the present study was used to assess model fits. Lastly, the model also included individual learner factors as covariates and five constructs selected were learners’ gender, the level of English proficiency, the duration of English learning, the period of using digital devices, and previous experience of digital English learning. The results verified from SEM analysis proposed a theoretical model that showed the structural relationships between Korean students’ use of DELS and their affective domains. Therefore, the results of this study help ESL/EFL teachers understand how learners use and develop appropriate learning strategies in digital learning contexts. The pedagogical implication and suggestions for the further study will be also presented.

Keywords: Digital English Learning Strategy, DELS, individual variables, learners' affective domains, Structural Equation Modeling, SEM

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2233 Identifying the Knowledge Management and its Capabilities in Universities: A Case Study of Public Universities in Nigeria

Authors: Hilary Joseph Watsilla

Abstract:

Research work is a vital part of the university system; in Nigeria public universities, research is used in measuring the development of individuals and departments within the academic system. Information technology has impacted the way research is carried out by providing easy access to information and improved collaboration between research and other instruments necessary for research activities. However, access to some of these IT facilities is not readily available in most of the public institutions in Nigeria. Research activities are usually tedious and rigorous and any inadequacy in research resources might affect the quality of research outcome. This study aims to identify the IT capability and knowledge management capabilities necessary for academic researchers in public universities in Nigeria, as it will provide more incite to the knowledge creation processes of research. The research will be conducted using an interpretive lens, which will provide a more qualitative understanding of the subject matter. The outcome of the research will provide an empirical understanding of the IT capabilities, which help in the optimization of the knowledge management capabilities of the university.

Keywords: IT capabilities, KM capabilities, universities, academic research

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2232 Periodicity of Solutions to Impulsive Equations

Authors: Jin Liang, James H. Liu, Ti-Jun Xiao

Abstract:

It is known that there exist many physical phenomena where abrupt or impulsive changes occur either in the system dynamics, for example, ad-hoc network, or in the input forces containing impacts, for example, the bombardment of space antenna by micrometeorites. There are many other examples such as ultra high-speed optical signals over communication networks, the collision of particles, inventory control, government decisions, interest changes, changes in stock price, etc. These are impulsive phenomena. Hence, as a combination of the traditional initial value problems and the short-term perturbations whose duration can be negligible in comparison with the duration of the process, the systems with impulsive conditions (i.e., impulsive systems) are more realistic models for describing the impulsive phenomenon. Such a situation is also suitable for the delay systems, which include some of the past states of the system. So far, there have been a lot of research results in the study of impulsive systems with delay both in finite and infinite dimensional spaces. In this paper, we investigate the periodicity of solutions to the nonautonomous impulsive evolution equations with infinite delay in Banach spaces, where the coefficient operators (possibly unbounded) in the linear part depend on the time, which are impulsive systems in infinite dimensional spaces and come from the optimal control theory. It was indicated that the study of periodic solutions for these impulsive evolution equations with infinite delay was challenging because the fixed point theorems requiring some compactness conditions are not applicable to them due to the impulsive condition and the infinite delay. We are happy to report that after detailed analysis, we are able to combine the techniques developed in our previous papers, and some new ideas in this paper, to attack these impulsive evolution equations and derive periodic solutions. More specifically, by virtue of the related transition operator family (evolution family), we present a Poincaré operator given by the nonautonomous impulsive evolution system with infinite delay, and then show that the operator is a condensing operator with respect to Kuratowski's measure of non-compactness in a phase space by using an Amann's lemma. Finally, we derive periodic solutions from bounded solutions in view of the Sadovskii fixed point theorem. We also present a relationship between the boundedness and the periodicity of the solutions of the nonautonomous impulsive evolution system. The new results obtained here extend some earlier results in this area for evolution equations without impulsive conditions or without infinite delay.

Keywords: impulsive, nonautonomous evolution equation, optimal control, periodic solution

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2231 Integrating RAG with Prompt Engineering for Dynamic Log Parsing and Anomaly Detections

Authors: Liu Lin Xin

Abstract:

With the increasing complexity of systems, log parsing and anomaly detection have become crucial for maintaining system stability. However, traditional methods often struggle with adaptability and accuracy, especially when dealing with rapidly evolving log content and unfamiliar domains. To address these challenges, this paper proposes approach that integrates Retrieval Augmented Generation (RAG) technology with Prompt Engineering for Large Language Models, applied specifically in LogPrompt. This approach enables dynamic log parsing and intelligent anomaly detection by combining real-time information retrieval with prompt optimization. The proposed method significantly enhances the adaptability of log analysis and improves the interpretability of results. Experimental results on several public datasets demonstrate the method's superior performance, particularly in scenarios lacking training data, where it significantly outperforms traditional methods. This paper introduces a novel technical pathway for log parsing and anomaly detection, showcasing the substantial theoretical value and practical potential.

Keywords: log parsing, anomaly detection, RAG, prompt engineering, LLMs

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2230 Micro-Hydrokinetic for Remote Rural Electrification

Authors: S. P. Koko, K. Kusakana, H. J. Vermaak

Abstract:

Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).

Keywords: economic analysis, micro-hydrokinetic, rural-electrification, cost of energy (COE), net present cost (NPC)

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2229 Machine Learning Model Applied for SCM Processes to Efficiently Determine Its Impacts on the Environment

Authors: Elena Puica

Abstract:

This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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2228 Spatio-Temporal Analysis of Land Use Land Cover Change Using Remote Sensing and Multispectral Satellite Imagery of Islamabad Pakistan

Authors: Basit Aftab, Feng Zhongke

Abstract:

The land use/land cover change (LULCC) is a significant indicator sensitive to an area's environmental changes. As a rapidly developing capital city near the Himalayas Mountains, the city area of Islamabad, Pakistan, has expanded dramatically over the past 20 years. In order to precisely measure the impact of urbanization on the forest and agricultural lands, the Spatio-temporal analysis of LULCC was utilized, which helped us to know the impacts of urbanization, especially on ecosystem processes, biological cycles, and biodiversity. The Islamabad region's Multispectral Satellite Images (MSI) for 2000, 2010, and 2020 were employed as the remote sensing data source. Local documents of city planning, forest inventory and archives in the agriculture management departments were included to verify the image-derived result. The results showed that from 2000 to 2020, the built-up area increased to 48.3% (505.02 Km2). Meanwhile, the forest, agricultural, and barre land decreased to 28.9% (305.64 Km2), 10.04% (104.87 Km2), and 11.61% (121.30 Km2). The overall percentage change in land area between 2000 – 2020 was recorded maximum for the built-up (227.04%). Results revealed that the increase in the built-up area decreased forestland, barren, and agricultural lands (-0.36, -1.00 & -0.34). The association of built-up with respective years was positively linear (R2 = 0.96), whereas forestland, agricultural, and barren lands association with years were recorded as negatively linear (R2 = -0.29, R2 = -0.02, and R2 = -0.96). Large-scale deforestation leads to multiple negative impacts on the local environment, e.g., water degradation and climate change. It would finally affect the environment of the greater Himalayan region in some way. We further analyzed the driving forces of urbanization. It was determined by economic expansion, climate change, and population growth. We hope our study could be utilized to develop efforts to mitigate the consequences of deforestation and agricultural land damage, reducing greenhouse gas emissions while preserving the area's biodiversity.

Keywords: urbanization, Himalaya mountains, landuse landcover change (LULCC), remote sensing., multi-spectral satellite imagery

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2227 Optimization Model for Support Decision for Maximizing Production of Mixed Fresh Fruit Farms

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

Abstract:

Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

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2226 Sustainability and Energy-Efficiency in Buildings: A review

Authors: Medya Fathi

Abstract:

Moving toward sustainable development is among today’s critical issues worldwide that make all industries, particularly construction, pay increasing attention to a healthy environment and a society with a prosperous economy. One of the solutions is to improve buildings’ energy performance by cutting energy consumption and related carbon emissions, eventually improving the quality of life. Unfortunately, the energy demand for buildings is rising. For instance, in Europe, the building sector accounts for 19% of the global energy-related greenhouse gas (GHGs) emissions, the main contributor to global warming in the last 50 years, and 36% of the total CO2 emissions, according to European Commission 2019. The crisis of energy use demands expanding knowledge and understanding of the potential benefits of energy-efficient buildings. In this regard, the present paper aims to critically review the existing body of knowledge on improving energy efficiency in buildings and detail the significant research contributions. Peer-reviewed journal articles published in the last decade in reputed journals were reviewed using the database Scopus and keywords of Sustainability, Sustainable Development, Energy Performance, Energy Consumption, Energy Efficiency, and Buildings. All contributions will be classified by journal type, publication time, country/region, building occupancy type, applied strategies, and findings. This study will provide an essential basis for researchers working on missing areas and filling the existing gaps in the body of knowledge.

Keywords: sustainability, energy performance, energy efficiency, buildings, review

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2225 Optimal Dynamic Economic Load Dispatch Using Artificial Immune System

Authors: I. A. Farhat

Abstract:

The dynamic economic dispatch (DED) problem is one of the complex, constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: artificial immune system, dynamic economic dispatch, optimal economic operation, large-scale problem

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2224 Raman and FTIR Studies of Azobenzene: Experimental and Theoretical Approach

Authors: Gomti Devi

Abstract:

Photoisomerization has been attracting to researchers due to its wide range of applications in optical switches, polymeric chains, liquid-crystalline systems and bilayer membranes etc. Azobenzene is a photochromic molecule which exhibits a reversible isomerisation process between its trans and cis isomers of different stability. An investigation has been conducted of the effects of temperature on intensity and position of Raman band of N=N, C-N stretching modes of Azobenzene (AZBN). It was found that the N=N stretching mode of Raman band shape shifts to lower frequency region with the increase in temperature. The Raman intensity was also decreased with the increase of temperature. The change in bandwidth with the increase in temperature has been studied. The FTIR spectrum of the molecule is recorded so as to complement the Raman spectra. In order to investigate the possibility of undergoing dimerization and trimerization as well as the stability of this molecule, ab initio calculation for geometry optimization and vibrational wavenumber calculation have been performed. Theoretically calculated values are found in good agreement with the experimental results.

Keywords: azobenzene, temperature, ab-initio, frequency

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2223 Analysis of a Single Motor Finger Mechanism for a Prosthetic Hand

Authors: Shaukat Ali, Kanber Sedef, Mustafa Yilmaz

Abstract:

This work analyzes a finger mechanism for a prosthetic hand that will help in improving the living standards of people who have lost their hands for a variety of reasons. The finger mechanism is single degree of freedom and hence has advantages such as compact size, reduced mass and less energy consumption. The proposed finger mechanism is a six bar linkage actuated by a single motor. The kinematic, static and dynamic analyses have been done by using the conventional methods of mechanism analysis. The kinematic results present the motion of the proposed finger mechanism and location of the fingertip. The static and dynamic analyses provide the useful information about the gripping force at the fingertip for various configurations and the selection of motor that will move the finger over its range of configuration. This single motor finger mechanism is simple and resembles the human finger’s motion suitable for grasping operation. This study can be used in the optimization of geometrical parameters of the proposed mechanism to obtain the desired configurations with minimum torque and enhanced griping.

Keywords: dynamics, finger mechanism, grasping, kinematics

Procedia PDF Downloads 358
2222 Bank Competition: On the Relationship with Revenue Diversification and Funding Strategy from Selected ASEAN Countries

Authors: Oktofa Y. Sudrajad, Didier V. Caillie

Abstract:

Association of Southeast Asian Countries Nations (ASEAN) is moving forward to the next level of regional integration by the initiation of ASEAN Economic Community (AEC) which is already started in 2015, 8 years after its declaration for the creation of AEC in 2007. This commitment imposes financial integration in the region is one of the main agenda which will be achieved until 2025. Therefore, the commitment to financial integration including banking integration will bring new landscape in the competition and business model in this region. This study investigates the effect of competition on bank business model using a sample of 324 banks from seven members of Association of Southeast Asian Nations (ASEAN) countries (Cambodia, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam). We use market power approach and Boone indicator as competition measures, while income diversification and bank funding strategies are employed as bank business model representation. Moreover, we also evaluate bank business model based by grouping the banks based on the main banking characteristics. We use unbalanced bank-specific annual panel data over the period of 2003 – 2015. Our empirical analysis shows that the banking industries in ASEAN countries adapt their business model by increasing non-interest income proportion due to the level of competition increase in the sector.

Keywords: bank business model, banking competition, Boone indicator, market power

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2221 Effect of Internet Addiction on Dietary Behavior and Lifestyle Characteristics among University Students

Authors: Hafsa Kamran, Asma Afreen, Zaheer Ahmed

Abstract:

Internet addiction, an emerging mental health disorder from last two decades, is manifested by the inability in the controlled use of internet leading to academics, social, physiological and/or psychological difficulties. The present study aimed to assess the levels of internet addiction among university students in Lahore and to explore the effects of internet addiction on their dietary behavior and lifestyle. It was an analytical cross-sectional study. Data was collected from October to December 2016 from students of four universities selected through two-stage sampling method. The numbers of participants were 500 and 13 questionnaires were rejected due to incomplete information. Levels of Internet Addiction (IA) were calculated using Young Internet Addiction Test (YIAT). Data was also collected on students’ demographics, lifestyle factors and dietary behavior using self-reported questionnaire. Data was analyzed using SPSS (version 21). Chi-square test was applied to evaluate the relationship between variables. Results of the study revealed that 10% of the population had severe internet addiction while moderate Internet Addiction was present in 42%. High prevalence was found among males (11% vs. 8%), private sector university students (p = 0.008) and engineering students (p = 0.000). The lifestyle habits of internet addicts were significantly of poorer quality than normal users (p = 0.05). Internet addiction was found associated with lesser physically activity (p = 0.025), had shorter duration of physical activity (p = 0.016), had more disorganized sleep pattern (p = 0.023), had less duration of sleep (p = 0.019), reported being more tired and sleepy in class (p = 0.033) and spending more time on internet as compared to normal users. Severe and moderate internet addicts also found to be more overweight and obese than normal users (p = 0.000). The dietary behavior of internet addicts was significantly poorer than normal users. Internet addicts were found to skip breakfast more than a normal user (p = 0.039). Common reasons for meal skipping were lack of time and snacking between meals (p = 0.000). They also had increased meal size (p = 0.05) and habit of snacking while using the internet (p = 0.027). Fast food (p = 0.016) and fried items (p = 0.05) were most consumed snacks, while carbonated beverages (p = 0.019) were most consumed beverages among internet addicts. Internet Addicts were found to consume less than recommended daily servings of dairy (p = 0.008) and fruits (p = 0.000) and more servings of meat group (p = 0.025) than their no internet addict counterparts. In conclusion, in this study, it was demonstrated that internet addicts have unhealthy dietary behavior and inappropriate lifestyle habits. University students should be educated regarding the importance of balanced diet and healthy lifestyle, which are critical for effectual primary prevention of numerous chronic degenerative diseases. Furthermore, it is necessary to raise awareness concerning adverse effects of internet addiction among youth and their parents.

Keywords: dietary behavior, internet addiction, lifestyle, university students

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2220 A Review on Microbial Enhanced Oil Recovery and Controlling Its Produced Hydrogen Sulfide Effects on Reservoir and Transporting Pipelines

Authors: Ali Haratian, Soroosh Emami Meybodi

Abstract:

Using viable microbial cultures within hydrocarbon reservoirs so as to the enhancement of oil recovery through metabolic activities is exactly what we recognize as microbial enhanced oil recovery (MEOR). In similar to many other processes in industries, there are some cons and pros following with MEOR. The creation of sulfides such as hydrogen sulfide as a result of injecting the sulfate-containing seawater into hydrocarbon reservoirs in order to maintain the required reservoir pressure leads to production and growth of sulfate reducing bacteria (SRB) approximately near the injection wells, turning the reservoir into sour; however, SRB is not considered as the only microbial process stimulating the formation of sulfides. Along with SRB, thermochemical sulfate reduction or thermal redox reaction (TSR) is also known to be highly effective at resulting in having extremely concentrated zones of ?2S in the reservoir fluids eligible to cause corrosion. Owing to extent of the topic, more information on the formation of ?₂S is going to be put finger on. Besides, confronting the undesirable production of sulfide species in the reservoirs can lead to serious operational, environmental, and financial problems, in particular the transporting pipelines. Consequently, conjuring up reservoir souring control strategies on the way production of oil and gas is the only way to prevent possible damages in terms of environment, finance, and manpower which requires determining the compound’s reactivity, origin, and partitioning behavior. This article is going to provide a comprehensive review of progress made in this field and the possible advent of new strategies in this technologically advanced world of the petroleum industry.

Keywords: corrosion, hydrogen sulfide, NRB, reservoir souring, SRB

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2219 Countercurrent Flow Simulation of Gas-Solid System in a Purge Column Using Computational Fluid Dynamics Techniques

Authors: T. J. Jamaleddine

Abstract:

Purge columns or degasser vessels are widely used in the polyolefin process for removing trapped hydrocarbons and in-excess catalyst residues from the polymer particles. A uniform distribution of purged gases coupled with a plug-flow characteristic inside the column system is desirable to obtain optimum desorption characteristics of trapped hydrocarbon and catalyst residues. Computational Fluid Dynamics (CFD) approach is a promising tool for design optimization of these vessels. The success of this approach is profoundly dependent on the solution strategy and the choice of geometrical layout at the vessel outlet. Filling the column with solids and initially solving for the solids flow minimized numerical diffusion substantially. Adopting a cylindrical configuration at the vessel outlet resulted in less numerical instability and resembled the hydrodynamics flow of solids in the hopper segment reasonably well.

Keywords: CFD, degasser vessel, gas-solids flow, gas purging, purge column, species transport

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2218 Intelligent Path Tracking Hybrid Fuzzy Controller for a Unicycle-Type Differential Drive Robot

Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Muhammad Moaz

Abstract:

In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.

Keywords: differential drive robot, hybrid fuzzy controller, optimization, path tracking, unicycle robot

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2217 Investigating Knowledge Management in Financial Organisation: Proposing a New Model for Implementing Knowledge Management

Authors: Ziba R. Tehrani, Sanaz Moayer

Abstract:

In the age of the knowledge-based economy, knowledge management has become a key factor in sustainable competitive advantage. Knowledge management is discovering, acquiring, developing, sharing, maintaining, evaluating, and using right knowledge in right time by right person in organization; which is accomplished by creating a right link between human resources, information technology, and appropriate structure, to achieve organisational goals. Studying knowledge management financial institutes shows the knowledge management in banking system is not different from other industries but because of complexity of bank’s environment, the implementation is more difficult. The bank managers found out that implementation of knowledge management will bring many advantages to financial institutes, one of the most important of which is reduction of threat to lose subsequent information of personnel job quit. Also Special attention to internal conditions and environment of the financial institutes and avoidance from copy-making in designing the knowledge management is a critical issue. In this paper, it is tried first to define knowledge management concept and introduce existing models of knowledge management; then some of the most important models which have more similarities with other models will be reviewed. In second step according to bank requirements with focus on knowledge management approach, most major objectives of knowledge management are identified. For gathering data in this stage face to face interview is used. Thirdly these specified objectives are analysed with the response of distribution of questionnaire which is gained through managers and expert staffs of ‘Karafarin Bank’. Finally based on analysed data, some features of exiting models are selected and a new conceptual model will be proposed.

Keywords: knowledge management, financial institute, knowledge management model, organisational knowledge

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2216 Optimation of Ethanol Extract of Gotu Kola and Majapahit Composition as Natural Antioxidant Source

Authors: Mustofa Ahda, Fiqri Rozi, Gina Noor Habibah, Mas Ulfah Lestari, Tomy Hardianto, Yuni Andriani

Abstract:

The development of natural antioxidants in the Centella asiatica and Majapahit is a great potential. This research has been optimizing the composition of ethanol extract of Centella asiatica and leaves Majapahit as an antioxidants source using measure the free radical scavenging activity of DPPH. The results of the research showed that both the ethanol extract of Centella asiatica and leaves Majapahit has a total content of phenol. It is shown with the ability to reduce reagent Folin Ciocalteu become blue colour. The composition optimization of extract Centella asiatica leaves Majapahit = 30:70 has free radical scavenging activity of DPPH most well compared ethanol extract of Centella asiatica and leaves Majapahit. IC50 values for the composition of ethanol extract of Centella asiatica : leaves Majapahit = 30:70 is 0,103 mg/mL.

Keywords: antioxidant activity, Centella asiatica, Cresentia cujete, composition extract

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2215 A Preliminary Study of Local Customers' Perception towards the Image of the Spa and Their Intention to Visit

Authors: Felsy J. Sandi

Abstract:

There is a potential of growth in the spa industry due to the influx of domestic and international tourist coming to Sabah, Malaysia. It is a good opportunity to venture into this industry for the country’s economic future growth, and therefore, it is essential for this area to be researched. Being one of the fastest growing industries in the world, has led to enormous challenges, which need to be addressed. Malaysia is also riding with this phenomenon. The President of the Malaysian Association of Wellness and Spa stated that the misconception about the Spa industry’s image, especially amongst the elderly is the biggest challenge faced by the industry, as they perceived the spa industry is equivalent to a prostitution center. Therefore, the objective of this study is to explore the issue by analyzing whether image can be added in the theory of planned behavior to better understand the consumer’s intention to visit, in the spa context. The Theory of Planned Behavior by Ajzen, a theory or model in predicting intention, has three constructs; such as Attitude as the first construct, the second construct is Subjective Norm and the third construct is Perceived Behavioral Control. Qualitative research is used as this is an exploratory research. The site of study will be at Jari Jari Spa, located in Kota Kinabalu, the only spa in Sabah that was awarded as the Center of Excellence (CoE) by the Ministry of Tourism and Culture in Malaysia. The findings propose to provide useful information to the relevant stakeholders on ways to approach local customers to convince them to visit the spa and for spa marketers to help them develop and design effective marketing strategies. Future investigation should consider more on the perception and loyalty of the local customers.

Keywords: consumer's perception, image, local customer, spa, visit intention

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2214 Awareness and Perception of Food Safety, Nutrition and Food Security among Omani Women

Authors: Abeer Al Kalbani

Abstract:

Oman is a sub-tropical country with limited water resources, harsh weather and limited soil fertility, constraining food production. Therefore, it largely depends on international markets to assure supply of food. In the light of these circumstances, food security in Oman is defined as the ability of the country to grant the staple food needs of people (e.g. rice, wheat, lentil, sugar, dates, dairy products, fish and plant or vegetable oils). It also involves exporting local goods with high production rates to exchange them with required food products. This concept of food security includes the availability of food through production and/or importing, stability of the market prices during all circumstances, and the ability of people to meet their needs within their income capabilities. As a result, most of the food security work is focused on availability and access dimensions of the issue. Not much research is focused on the utilization aspect of food security in Oman. Although women play a vital role in food security, there is limited research on women’s role in food security neither in Oman nor in neighboring Gulf countries. Women play an important role not only by carrying the responsibility of feeding their families but also by setting the consumption model for the household. Therefore, the research aims to contribute to the work done on food security in Oman and similar regions of the world by studying the role women play at the utilization level. Methods used in this research include Qualitative unstructured interviews, focus groups, survey questionnaire and an experimental study. Based on the FAO definition of food security, it consists of availability, access, utilization and sustainability. Results from a pilot study conducted for this research on two groups of women in Oman; urban and rural women, showed that women in Oman are responsible for achieving these four pillars at the household level. Moreover, awareness of women increased as their educational level increased. Urban women showed more awareness and openness to adopt healthier and proper food related choices than rural women. Urban women seem also more open than rural women to new ideas and concepts and ways to healthier food. However, both urban and rural women claim that no training and educational programs are available for them and awareness of food security in general remains relatively low in both groups. In the light of these findings, this research attempts to further investigate the social beliefs, practices and attitudes women adopt in relation to food purchase, storage, preparation and consumption as considered as important parts of the food system. It also seeks to examine the effect of educational training programs and media on the level of women awareness on the issue.

Keywords: food security, household food security, utilization, role of women

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2213 Quantification of Enzymatic Activities of Proteins, Peroxidase and Phenylalanine Ammonia Lyase, in Growing Phaseolus vulgaris L, with Application Bacterial Consortium to Control Fusarium and Rhizoctonia

Authors: Arredondo Valdés Roberto, Hernández Castillo Francisco Daniel, Laredo Alcalá Elan Iñaky, Gonzalez Gallegos Esmeralda, Castro Del Angel Epifanio

Abstract:

The common bean or Phaseolus vulgaris L. is the most important food legume for direct consumption in the world. Fusarium dry rot in the major fungus disease affects Phaseolus vulgaris L, after planting. In another hand, Rhizoctonia can be found on all underground parts of the plant and various times during the growing season. In recent years, the world has conducted studies about the use of natural products as substitutes for herbicides and pesticides, because of possible ecological and economic benefits. Plants respond to fungal invasion by activating defense responses associated with accumulation of several enzymes and inhibitors, which prevent pathogen infection. This study focused on the role of proteins, peroxidase (POD), phenylalanine ammonia lyase (PAL), in imparting resistance to soft rot pathogens by applied different bacterial consortium, formulated and provided by Biofertilizantes de Méxicanos industries, analyzing the enzyme activity at different times of application (6 h, 12 h and 24 h). The resistance of these treatments was correlated with high POD and PAL enzyme activity as well as increased concentrations of proteins. These findings show that PAL, POD and synthesis of proteins play a role in imparting resistance to Phaseolus vulgaris L. soft rot infection by Fusarium and Rhizoctonia.

Keywords: fusarium, peroxidase, phenylalanine ammonia lyase, rhizoctonia

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2212 Comparative Scanning Electron Microscopic Observations of Anthelminthic Effect of Trigonella foenum-graecum on Paramphistomum cervi in Buffalo

Authors: Kiran Roat, Bhanupriya Sanger, Gayatri Swarnakar

Abstract:

Amphistomiasis disease is the main health problem throughout of the world and responsible for great economic losses to cattle industries, mostly to poor cattle farmers in developing countries. Among the rumen parasites, the Paramphistomum cervi were collected from the rumen of freshly slaughtered buffalo for the further treatment process. Trigonella foenum-graecum is commonly known as methi and fenugreek and their seeds are known for their therapeutic value. The present study was considered to evaluate in vitro efficacy of aqueous extract of Trigonella foenum-graecum on P. cervi. 130 mg/ml concentration of aqueous extract shows total mortality of P. cervi at 5 hours. The ultrastructural surface topography of untreated animal was compared with a treated animal by scanning electron microscope (SEM). The body of untreated P. cervi in conical shape, tegumental surface is highly ridged with transverse folds and present abundance number of papillaes. Observations demonstrated that the body of treated P. cervi become shrunken & elongated. Treated parasite shows the deep breakage in tegument and the disappearance of tegumental folds & papillae. Severe blebs formations have been found. Above findings, it can be concluded that the seeds of Trigonella foenum-graecum can be used as an anthelminthic agent to eliminate P. cervi from the body of buffalo.

Keywords: Paramphistomum cervi, Trigonella foenum-graecum, scanning electron microscope, buffalo

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2211 The Mechanism Underlying Empathy-Related Helping Behavior: An Investigation of Empathy-Attitude- Action Model

Authors: Wan-Ting Liao, Angela K. Tzeng

Abstract:

Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: empathy, cognitive, emotional, psychopathy

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2210 Spectrofluorometric Studies on the Interactions of Bovine Serum Albumin with Dimeric Cationic Surfactants

Authors: Srishti Sinha, Deepti Tikariha, Kallol K. Ghosh

Abstract:

Over the past few decades protein-surfactant interactions have been a subject of extensive studies as they are of great importance in wide variety of industries, biological, pharmaceutical and cosmetic systems. Protein-surfactant interactions have been explored the effect of surfactants on structure of protein in the form of solubilization and denaturing or renaturing of protein. Globular proteins are frequently used as functional ingredients in healthcare and pharmaceutical products, due to their ability to catalyze biochemical reactions, to be adsorbed on the surface of some substance and to bind other moieties and form molecular aggregates. One of the most widely used globular protein is bovine serum albumin (BSA), since it has a well-known primary structure and been associated with the binding of many different categories of molecules, such as dyes, drugs and toxic chemicals. Protein−surfactant interactions are usually dependent on the surfactant features. Most of the research has been focused on single-chain surfactants. More recently, the binding between proteins and dimeric surfactants has been discussed. In present study interactions of one dimeric surfactant Butanediyl-1,4-bis (dimethylhexadecylammonium bromide) (16-4-16, 2Br-) and the corresponding single-chain surfactant cetyl trimethylammonium bromide (CTAB) with bovine serum albumin (BSA) have been investigated by surface tension and spectrofluoremetric methods. It has been found that the bindings of all gemini surfactant to BSA were cooperatively driven by electrostatic and hydrophobic interactions. The gemini surfactant carrying more charges and hydrophobic tails, showed stronger interactions with BSA than the single-chain surfactant.

Keywords: bovine serum albumin, gemini surfactants, hydrophobic interactions, protein surfactant interaction

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2209 Atmospheric CO2 Capture via Temperature/Vacuum Swing Adsorption in SIFSIX-3-Ni

Authors: Eleni Tsalaporta, Sebastien Vaesen, James M. D. MacElroy, Wolfgang Schmitt

Abstract:

Carbon dioxide capture has attracted the attention of many governments, industries and scientists over the last few decades, due to the rapid increase in atmospheric CO2 composition, with several studies being conducted in this area over the last few years. In many of these studies, CO2 capture in complex Pressure Swing Adsorption (PSA) cycles has been associated with high energy consumption despite the promising capture performance of such processes. The purpose of this study is the economic capture of atmospheric carbon dioxide for its transformation into a clean type of energy. A single column Temperature /Vacuum Swing Adsorption (TSA/VSA) process is proposed as an alternative option to multi column Pressure Swing Adsorption (PSA) processes. The proposed adsorbent is SIFSIX-3-Ni, a newly developed MOF (Metal Organic Framework), with extended CO2 selectivity and capacity. There are three stages involved in this paper: (i) SIFSIX-3-Ni is synthesized and pelletized and its physical and chemical properties are examined before and after the pelletization process, (ii) experiments are designed and undertaken for the estimation of the diffusion and adsorption parameters and limitations for CO2 undergoing capture from the air; and (iii) the CO2 adsorption capacity and dynamical characteristics of SIFSIX-3-Ni are investigated both experimentally and mathematically by employing a single column TSA/VSA, for the capture of atmospheric CO2. This work is further supported by a technical-economical study for the estimation of the investment cost and the energy consumption of the single column TSA/VSA process. The simulations are performed using gProms.

Keywords: carbon dioxide capture, temperature/vacuum swing adsorption, metal organic frameworks, SIFSIX-3-Ni

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2208 Coarse-Grained Computational Fluid Dynamics-Discrete Element Method Modelling of the Multiphase Flow in Hydrocyclones

Authors: Li Ji, Kaiwei Chu, Shibo Kuang, Aibing Yu

Abstract:

Hydrocyclones are widely used to classify particles by size in industries such as mineral processing and chemical processing. The particles to be handled usually have a broad range of size distributions and sometimes density distributions, which has to be properly considered, causing challenges in the modelling of hydrocyclone. The combined approach of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) offers convenience to model particle size/density distribution. However, its direct application to hydrocyclones is computationally prohibitive because there are billions of particles involved. In this work, a CFD-DEM model with the concept of the coarse-grained (CG) model is developed to model the solid-fluid flow in a hydrocyclone. The DEM is used to model the motion of discrete particles by applying Newton’s laws of motion. Here, a particle assembly containing a certain number of particles with same properties is treated as one CG particle. The CFD is used to model the liquid flow by numerically solving the local-averaged Navier-Stokes equations facilitated with the Volume of Fluid (VOF) model to capture air-core. The results are analyzed in terms of fluid and solid flow structures, and particle-fluid, particle-particle and particle-wall interaction forces. Furthermore, the calculated separation performance is compared with the measurements. The results obtained from the present study indicate that this approach can offer an alternative way to examine the flow and performance of hydrocyclones

Keywords: computational fluid dynamics, discrete element method, hydrocyclone, multiphase flow

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2207 Stock Prediction and Portfolio Optimization Thesis

Authors: Deniz Peksen

Abstract:

This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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