Search results for: dairy industries inventory optimization

Authors: Vakamalla Teja Reddy, Narasimha Mangadoddy

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Hydrocyclones are used to separate particles into different size fractions in the mineral processing, chemical and metallurgical industries. High speed video imaging, Laser Doppler Anemometry (LDA), X-ray and Gamma ray tomography are previously used to measure the two-phase flow characteristics in the cyclone. However, investigation of solids flow characteristics inside the cyclone is often impeded by the nature of the process due to slurry opaqueness and solid metal wall vessels. In this work, a dual-plane high speed Electrical resistance tomography (ERT) is used to measure hydrocyclone internal flow dynamics in situ. Experiments are carried out in 3 inch hydrocyclone for feed solid concentrations varying in the range of 0-50%. ERT data analysis through the optimized FEM mesh size and reconstruction algorithms on air-core and solid concentration tomograms is assessed. Results are presented in terms of the air-core diameter and solids volume fraction contours using Maxwell’s equation for various hydrocyclone operational parameters. It is confirmed by ERT that the air core occupied area and wall solids conductivity levels decreases with increasing the feed solids concentration. Algebraic slip mixture based multi-phase computational fluid dynamics (CFD) model is used to predict the air-core size and the solid concentrations in the hydrocyclone. Validation of air-core size and mean solid volume fractions by ERT measurements with the CFD simulations is attempted.

Keywords: air-core, electrical resistance tomography, hydrocyclone, multi-phase CFD

Procedia PDF Downloads 379

Authors: Swati Rajput

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Environmental psychology explains that the person is a social agent that seeks to extract meaning from their built and natural environment to behave in a particular manner. It also shows the attachment or detachment of people to their environment. Assessing environmental psychology of people is imperative for planners and policy makers for urban planning. The paper investigates the environmental psychology of people living in nine districts of Delhi by calculating and assessing their Environmental Emotional Quotient (EEQ). Emotional Quotient deals with the ability to sense, understand, attach and respond according to the power of emotions. An Environmental Emotional Quotient has been formulated based upon the inventory administered to them. The respondents were asked questions related to their view and emotions about the green spaces, water resource conservation, air and environmental quality. An effort has been made to assess the feeling of belongingness among the residents. Their views were assessed on green spaces, reuse, and recycling of resources and their participation level. They were also been assessed upon health awareness level by considering both preventive and curative segments of health care. It was found that only 12 percent of the people is emotionally attached to their surroundings in the city. The emotional attachment reduces as we move away from the house to housing complex to neighbouring areas and rest of the city. In fact, the emotional quotient goes lower to lowest from house to other ends of the city. It falls abruptly after the radius of 1 km from the residence. The result also shows that nearly 54% respondents accept that there is environment pollution in their area. Around 47.8% respondents in the survey consider that diseases occur because of green cover depiction in their area. Major diseases are to airborne diseases like asthma and bronchitis. Seasonal disease prevalent, which specially occurred from last 3-4 years are malaria, dengue and chikengunya. Survey also shows that only 31 % of respondents visit government hospitals while 69% respondents visit private hospitals or small clinics for healthcare services. The paper suggests the need for environmental sensitive policies and need for green insurance in mega cities like Delhi.

Keywords: environmental psychology, environmental emotional quotient, preventive health care and curative health care, sustainable living

Procedia PDF Downloads 280

Authors: Safayat Ali Shaikh

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Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

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Authors: Maria E. Laconi, Kyla D. Scherr, Mary A. Jamieson

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Human populations in urban environments have rapidly grown in recent decades. Consequently, the intensity of land-use and development has also increased in many urban and peri-urban environments. Some cities, such as Detroit, Michigan, USA, have embraced urban agriculture and local food production. Little is known, however, about how the local and landscape scale environmental factors influence crop productivity on urban farms. Our study aims to evaluate factors influencing the productivity of strawberries on community farms and gardens in the Detroit metropolitan area. Strawberries are one of few fruits that can provide an abundant harvest just after the first season of being planted, which is ideal for urban gardeners in developed areas. In the spring of 2016, we planted six different strawberry cultivars (three everbearing and three June bearing varieties) at five farm sites in Wayne and Oakland County (six replicate plants per cultivar per site). We surveyed flower and fruit phenology and production for everbearing varieties weekly (flowers for June bearing varieties were removed to enhance productivity in the coming growing season). Additionally, we conducted one initial 36hr pollinator survey in mid-September during peak fruit production and characterized local and landscape scale land-cover data. Preliminary results and observations from this first year of our study revealed that strawberry production varied significantly by site. Specifically, productivity at our most northern site appeared to suffer from delayed phenology and early frost damage to ripening strawberries. Bee abundance and diversity also differed among farms, though further surveys are needed to adequately inventory the pollinator community. Finally, strawberry cultivars demonstrated significant differences in the number and size of fruits produced. We plan to continue this study in the coming years, increasing the number of sites surveyed and number of pollinator sampling events. Our study aims to inform strategies for enhancing crop productivity on urban and peri-urban farms.

Keywords: insect pollination, strawberry productivity, sustainable agriculture, urban gardening

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Ese Urhie, Olabisi Popoola, Obindah Gershon, Olabanji Ewetan

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Modern agriculture involves the use of improved tools and equipment (instead of crude and ineffective tools) like tractors, hand operated planters, hand operated fertilizer drills and combined harvesters - which increase agricultural productivity. Farmers in Nigeria still have huge potentials to enhance their productivity. The study argues that the increase in agricultural output due to increased productivity, orchestrated by modern agriculture will promote forward linkages and opportunities in the processing sub-sector; both the manufacturing of machines and the processing of raw materials. Depending on existing incentives, foreign investment could be attracted to augment local investment in the sector. The availability of raw materials in large quantity – which prices are competitive – will attract investment in other industries. In addition, potentials for backward linkages will also be created. In a nutshell, adopting the unbalanced growth theory in favour of the agricultural sector could engender industrialization in a country with untapped potentials. The paper highlights the numerous potentials of modern agriculture that are yet to be tapped in Nigeria and also provides a theoretical analysis of how the realization of such potentials could promote industrialization in the country. The study adopts the Lewis’ theory of structural–change model and Hirschman’s theory of unbalanced growth in the design of the analytical framework. The framework will be useful in empirical studies that will guide policy formulation.

Keywords: modern agriculture, industrialization, structural change model, unbalanced growth

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Authors: Jonathan Doku

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The study's goal was to evaluate construction site safety management in Ghana. The construction sector has long been seen as a high-risk business. It entails a variety of hazardous and challenging labor duties, such as lifting and working at a height, among others. The accident rate is a standard indicator for comparing the safety performance of construction projects. Because of its high-risk and fast-changing work environment, the construction business is regarded as one of the industries with the highest accident rates in the world. Many mishaps and work-related diseases have occurred there, and construction workers are particularly vulnerable to catastrophic calamities such as falls, collapses, and burial. The study's main goals were to discover characteristics that have a substantial impact on construction site safety, to evaluate the safety management methods utilized on construction sites, and to assess the obstacles associated with construction site safety management. The study was conducted using a quantitative research method and a purposive sampling strategy. Google forms were used to distribute self-administered surveys to 85 responders. 72 of the 85 questionnaires were completed and submitted for analysis, accounting for 84.7 percent of the total. The variables were analyzed using descriptive statistics, mean score ranking, and Cronbach's Alpha Coefficient to ensure the scale's reliability. The formal safety organization structure and the Safety checklist were identified as the key practices of safety management on site as part of the study goals. In addition, it was discovered that the most serious problem with safety management is ineffective supervision. To guarantee efficient monitoring and proper implementation of health and safety rules on building sites, management must be on the ball.

Keywords: construction, safety, risk, management

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Authors: Balwinder Singh

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Castings are produced by using aluminum alloy ADC 10 through the process of Ceramic Shell Investment Casting. Experiments are conducted as per the Taguchi L9 orthogonal array. In order to evaluate the effect of process parameters such as mould preheat temperature, preheat time, firing temperature and pouring temperature on surface roughness of ceramic shell investment castings, the Taguchi parameter design and optimization approach is used. Plots of means of significant factors and S/N ratios have been used to determine the best relationship between the responses and model parameters. It is found that the pouring temperature is the most significant factor. The best tensile strength of aluminum alloy ADC 10 is given by 150 ºC shell preheat temperature, 45 minutes preheat time, 900 ºC firing temperature, 650 ºC pouring temperature.

Keywords: investment casting, shell preheat temperature, firing temperature, Taguchi method

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Authors: Kanayo Kenneth Asogwa

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The influence of the flow of nanoparticles in nanofluids across a vertical surface is significant, and its application in medical sciences, engineering, pharmaceutical, and food industries is enormous & widely published. However, the comparative examination of alumina nanoparticles with cupric nanoparticles past a rapid progressive Riga plate remains unknown. Thus, this report investigates water-based alumina and cupric nanoparticles passing through an exponentially accelerated Riga plate. Nanofluids containing copper (II) oxide (CuO) and aluminum oxide (Al2O3) nanoparticles are considered. The Laplace transform technique is used to solve the partial differential equations guiding the flow. The effect of various factors on skin friction coefficient, Nusselt number, velocity and temperature profiles is investigated and reported in tabular and graphical form. The upsurge of Modified Hartmann number and radiative impact improves copper (II) oxide nanofluid compared to aluminum oxide nanofluid due to Lorentz force and since CuO is a better heat conductor. At the same time, heat absorption and reactive species favor a slight decline in Alumina nanofluid than Cupric nanofluid in the thermal and velocity fields. The higher density of Cupric nanofluid is enhanced by increasing nanoparticle volume fraction over Alumina nanofluid with a decline in velocity distribution.

Keywords: alumina, cupric, nanoparticles, water-based

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Authors: Farzaneh Rajabighamchi, Stan van Hoesel, Christof Defryn

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The generalized traveling salesman problem (GTSP) is an extension of the traveling salesman problem (TSP) where the set of nodes is partitioned into clusters, and the salesman must visit exactly one node per cluster. In this research, we apply the definition of the GTSP to an order picker routing problem with multiple locations per product. As such, each product represents a cluster and its corresponding nodes are the locations at which the product can be retrieved. To pick a certain product item from the warehouse, the picker needs to visit one of these locations during its pick tour. As all products are scattered throughout the warehouse, the product clusters not separated geographically. We propose an exact LP model as well as heuristic and meta-heuristic solution algorithms for the order picking problem with multiple product locations.

Keywords: warehouse optimization, order picking problem, generalised travelling salesman problem, heuristic algorithm

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Authors: Luigina Mortari, Alessia Bevilacqua, Roberta Silva

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The experience presented in this paper aims to understand how educational research can support the introduction and optimization of teaching innovations in legal education. In this increasingly complex context, a strong need to introduce paths aimed at acquiring not only professional knowledge and skills but also transversal such as reflective, critical, and problem-solving skills emerges. Through a peer observation intertwined with an analysis of discursive practices, researchers and the teacher worked together through a process of participatory and transformative accompaniment whose objective was to promote the active participation and engagement of students in learning processes, an element indispensable to work in the more specific direction of strengthening key competences. This reflective faculty development path led the teacher to activate metacognitive processes, becoming thus aware of the strengths and areas of improvement of his teaching innovation.

Keywords: legal education, teaching innovation, peer observation, discursive analysis, faculty development

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Authors: Naga Velamakuri, Jyothi K. Reddy

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Quality must be designed into a product and not inspected has become the main motto of all the companies globally. Due to the rapidly increasing technology in the past few decades, the nature of demands from the consumers has become more sophisticated. To sustain this global revolution of innovation in production systems, companies have to take steps to accommodate this technology growth. In this process of understanding the customers' expectations, all the firms globally take steps to deliver a perfect output. Most of these techniques also concentrate on the consistent development and optimization of the product to exceed the expectations. Quality Function Deployment(QFD) and Modular Function Deployment(MFD) are such techniques which rely on the voice of the customer and help deliver the needs. In this paper, Quality Function Deployment and Modular Function Deployment techniques which help in converting the quantitative descriptions to qualitative outcomes are discussed. The area of interest would be to understand the scope of each of the techniques and the application range in product development when these are applied together to any problem. The research question would be mainly aimed at comprehending the limitations using modularity in product development.

Keywords: quality function deployment, modular function deployment, house of quality, methodology

Procedia PDF Downloads 328

Authors: M. Bassas, J. Grané-Morcillo, J. Segura, J. M. Soldevila

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Mental health prevention is key in a society where, according to the World Health Organization, the fourth leading cause of death worldwide is suicide. Compassion is closely linked to personal growth. It shows once again that therapies based on prevention remain an urgent and social need. In this sense, a growing body of research demonstrates how cultivating a compassionate mind can help alleviate and prevent a variety of psychological problems. In the early 21st century, there has been a boom in third-generation compassion-based therapies, although there is a lack of empirical evidence of their efficacy. This study proposes a psychotherapy method (‘Being Method’), whose central axis revolves around emotional management through the cultivation of compassion. Therefore, the objective of this research was to analyze the effectiveness of this method with regard to the emotional changes experienced when we focus on what we are concerned about through the filter of compassion. The Being Method was born from the influence of Buddhist philosophy and contemporary psychology based mainly on Western rationalist currents. A quantitative cross-sectional study has been carried out in a sample of women between 18 and 53 years old (n=47; Mage=36.02; SDage= 11.86) interested in personal growth in which the following 6 measuring instruments were administered: Peace of mind Scale (PoM), Rosenberg Self-Esteem Scale (RSES), Subjective Happiness Scale (SHS), 2 Sacles of the Compassionate Action and Engagement Scales (CAES), Coping Response Inventory for Adults (CRI-A) and Cognitive-Behavioral Strategies Evaluation Scale (MOLDES). Following an experimental method approach, participants were divided into an experimental and control group. Longitudinal analysis was also carried out through a pre-post program comparison. Pre-post comparison outcomes indicated significant differences (p<.05) between before and after the therapy in the variables Peace of Mind, Self-esteem, Happiness, Self-compassion (A-B), Compassion (A-B), in several mental molds, as well as in several coping strategies. Also, between-groups tests proved significantly higher means obtained in the experimental group. Thus, these outcomes highlighted the effectiveness of the therapy, improving all the analyzed dimensions. The social, clinical and research implications are discussed.

Keywords: being method, compassion, effectiveness, emotional management, intervention program, personal growth therapy

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Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

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Authors: Seyed Mehran Kazemi, Bahare Fatemi

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Sudoku is a logic-based combinatorial puzzle game which is popular among people of different ages. Due to this popularity, computer softwares are being developed to generate and solve Sudoku puzzles with different levels of difficulty. Several methods and algorithms have been proposed and used in different softwares to efficiently solve Sudoku puzzles. Various search methods such as stochastic local search have been applied to this problem. Genetic Algorithm (GA) is one of the algorithms which have been applied to this problem in different forms and in several works in the literature. In these works, chromosomes with little or no information were considered and obtained results were not promising. In this paper, we propose a new way of applying GA to this problem which uses more-informed chromosomes than other works in the literature. We optimize the parameters of our GA using puzzles with different levels of difficulty. Then we use the optimized values of the parameters to solve various puzzles and compare our results to another GA-based method for solving Sudoku puzzles.

Keywords: genetic algorithm, optimization, solving Sudoku puzzles, stochastic local search

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram

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With the increase of prevailing non-traditional rivalry, mobile banking experiences an ever changing commercial backdrop. Substantial customer demands have established to be more intricate as customers request more expediency and superintend over their banking services. To enterprise advance and modernization in mobile banking applications, it is gradually obligatory to deeply leapfrog the scuffle using business model transformation. The dramaturgical vicissitudes taking place in mobile banking entail advanced traditions to exploit security. By reforming and transforming older back office into integrated mobile banking applications, banks can engender a supple and nimble banking environment that can rapidly respond to new business requirements over cloud computing. Cloud computing is transfiguring ecosystems in numerous industries, and mobile banking is no exemption providing services innovation, greater flexibility to respond to improved security and enhanced business intelligence with less cost. Cloud technology offer secure deployment possibilities that can provision banks in developing new customer experiences, empower operative relationship and advance speed to efficient banking transaction. Cloud adoption is escalating quickly since it can be made secured for commercial mobile banking transaction through backend as a service in scrutinizing the security strategies of the cloud service provider along with the antiquity of transaction details and their security related practices.

Keywords: cloud adoption, backend as a service, business intelligence, secured mobile banking

Procedia PDF Downloads 254

Authors: Otman Jai, Otman Elhajjaji, Jaouad Tajmouati

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Several neutronic calculation codes must be used to solve the equation for different levels of discretization which all necessitate a specific modelisation. This chain of such models, known as a calculation scheme, leads to the knowledge of the neutron flux in a reactor from its own geometry, its isotopic compositions and a cross-section library. Being small in size, the 'Slowpoke-2' reactor is difficult to model due to the importance of the leaking neutrons. In the paper, the simulation model is presented (geometry, cross section library, assumption, etc.), and the results obtained by DRAGON4/DONJON4 codes were compared to the calculations performed with Monte Carlo code MCNP using detailed geometrical model of the reactor and the experimental data. Criticality calculations have been performed to verify and validate the model. Since created model properly describes the reactor core, it can be used for calculations of reactor core parameters and for optimization of research reactor application.

Keywords: transport equation, Dragon4, Donjon4, neutron flux, effective multiplication factor

Procedia PDF Downloads 470

Authors: Helen S. Ghali, Haidy S. Ghali, Salma Ibrahim, Ossama Hosny, Hatem S. Elbehairy

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Infrastructure systems are essential assets in any community; accordingly, authorities aim to maximize its life span while minimizing the life cycle cost. This requires studying the asset conditions throughout its operation and forming a cost-efficient maintenance strategy plan. The objective of this study is to develop a highway management system that provides medium-term maintenance plans with the minimum life cycle cost subject to budget constraints. The model is applied to data collected for the highway network in India with the aim to output a 5-year maintenance plan strategy from 2019 till 2023. The main element considered is the surface coarse, either rigid or flexible pavement. The model outputs a 5-year maintenance plan for each segment given the budget constraint while maximizing the new pavement condition rating and minimizing its life cycle cost.

Keywords: infrastructure, asset management, optimization, maintenance plan

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Authors: Yoftahe Nigussie Worku

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This research focuses on advancing fire tube boiler technology by systematically optimizing design parameters to achieve efficient saturated steam production. The main objective is to design a high-performance boiler with a production capacity of 2000kg/h at a 12-bar design pressure while minimizing costs. The methodology employs iterative analysis, utilizing relevant formulas, and considers material selection and production methods. The study successfully results in a boiler operating at 85.25% efficiency, with a fuel consumption rate of 140.37kg/hr and a heat output of 1610kW. Theoretical importance lies in balancing efficiency, safety considerations, and cost minimization. The research addresses key questions on parameter optimization, material choices, and safety-efficiency balance, contributing valuable insights to fire tube boiler design.

Keywords: safety consideration, efficiency, production methods, material selection

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Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: Justyna Minkiewicz

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Artificial Intelligence (AI) applied in the arts may influence the development of AI knowledge in other sectors and then also impact mutual collaboration with the artistic environment. Hence this collaboration may also impact the development of art projects. The paper will reflect the qualitative research outcomes based on in-depth (IDI) interviews within the marketing sector in Poland and desk research. Art is a reflection of the spirit of our times. Moreover, now we are experiencing a significant acceleration in the development of technologies and their use in various sectors. The leading technologies that contribute to the development of the economy, including the creative sector, embrace technologies such as artificial intelligence, blockchain, extended reality, voice processing, and virtual beings. Artificial intelligence is one of the leading technologies developed for several decades, which is currently reaching a high level of interest and use in various sectors. However, the conducted research has shown that there is still low awareness of artificial intelligence and its wide application in various sectors. The study will show how artists use artificial intelligence in their art projects and how it can be translated into practice within the business. At the same time, the paper will raise awareness of the need for businesses to be inspired by the artistic environment. The research proved that there is still a need to popularize knowledge about this technology which is crucial for many sectors. Art projects are tools to develop knowledge and awareness of society and also various sectors. At the same time, artists may benefit from such collaboration. The paper will include selected aspects of mutual relations, areas of possible inspiration, and possible transfers of technological solutions. Those are AI applications in creative industries such as advertising and film, image recognition in art, and projects from different sectors.

Keywords: artificial intelligence, business, art, creative industry, technology

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Authors: Kamalendu Pal

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Supply chains are the spinal cord of trade and commerce. Their logistics use different transport corridors on regular basis for operational purpose. The international supply chain transport corridors include different infrastructure elements (e.g. weighbridge, package handling equipment, border clearance authorities, and so on) in supply chains. This paper presents the use of multi-agent systems (MAS) to model and simulate some aspects of transportation corridors, and in particular the area of weighbridge resource optimization for operational profit generation purpose. An underlying multi-agent model provides a means of modeling the relationships among stakeholders in order to enable coordination in a transport corridor environment. Simulations of the costs of container unloading, reloading, and waiting time for queuing up tracks have been carried out using data sets. Results of the simulation provide the potential guidance in making decisions about optimal service resource allocation in a trade corridor.

Keywords: multi-agent systems, simulation, supply chain, transport corridor, weighbridge

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Authors: Agnieszka Rolinska, Marta Makara-Studzinska

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Introduction: In recent years, there has been an intensive development of research into the physiological relationships between the experienced stress and obesity. Moreover, strong chronic stress leads to the disorganization of a person’s activeness on various levels of functioning, including the behavioral and cognitive sphere (also in one’s diet). Aim: The present work addresses the following research questions: Is there a relationship between an increase in stress related to the disease and the need for the cyclicality of diabetologic education in gestational diabetes? Are there any differences in terms of the experienced stress during the last three months of pregnancy in women with gestational diabetes and in normal pregnancy between the patients with normal weight gains and those with abnormal weight gains? Are there any differences in terms of stress coping styles in women with gestational diabetes and in normal pregnancy between the patients with normal weight gains and those with abnormal weight gains? Method: The study involved pregnant women with gestational diabetes (treated with diet, without insulin therapy) and in normal pregnancy – 206 women in total. The following psychometric tools were employed: Perceived Stress Scale (PSS; Cohen, Kamarck, Mermelstein), Coping Inventory for Stressful Situations (CISS; Endler, Parker) and authors’ own questionnaire. Gestational diabetes mellitus was diagnosed on the basis of the results of fasting oral glucose tolerance test (75 g OGTT). Body weight measurements were confirmed in a diagnostic interview, taking into account medical data. Regularities in weight gains in pregnancy were determined according to the recommendations of the Polish Gynecological Society and American norms determined by the Institute of Medicine (IOM). Conclusions: An increase in stress related to the disease varies in patients with differing requirements for the cyclical nature of diabetologic education (i.e. education which is systematically repeated). There are no differences in terms of recently experienced stress and stress coping styles between women with gestational diabetes and those in normal pregnancy. There is a relationship between weight gains in pregnancy and the stress experienced in life as well as stress coping styles – both in pregnancy complicated by diabetes and in physiological pregnancy. In the discussion of the obtained results, the authors refer to scientific reports from English-language magazines of international range.

Keywords: diabetologic education, gestational diabetes, stress, weight gain in pregnancy

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Authors: Prafulla Kumar Choubey, Krishna Kishor Jha, S. B. Vaisakh Punnekkattu Chirayil

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In Graphics-display subsystem, frame buffers are shared between producer i.e. content rendering and consumer i.e. display. If a common buffer is operated by both producer and consumer simultaneously, their processing rates mismatch can cause tearing effect in displayed content. Therefore, Android OS employs triple buffered system, taking in to account an additional composition stage. Three stages-rendering, composition and display refresh, operate synchronously on three different buffers, which is achieved by using vsync pulses. This synchronization, however, brings in to the pipeline an additional latency of up to 26ms. The present study details about the existing synchronization mechanism of android graphics-display pipeline and discusses a new adaptive architecture which reduces the wait time to 5ms-16ms in all the use-cases. The proposed method uses two adaptive software vsyncs (PLL) for achieving the same result.

Keywords: Android graphics system, vertical synchronization, atrace, adaptive system

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Authors: Regita P. Permata, Ulfa S. Nuraini

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Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

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Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

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This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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Authors: Wai Keng Teng, Gek Cheng Ngoh, Rozita Yusoff, Mohamed Kheireddine Aroua

Abstract:

As a by-product of the biodiesel industries, glycerol has been vastly generated which surpasses the market demand. It is imperative to develop an efficient glycerol valorization processes in minimizing the net energy requirement and intensifying the biodiesel production. In this study, base-catalyzed transesterification of glycerol with dimethyl carbonate using microwave irradiation as heating method to produce glycerol carbonate was conducted by varing grades of glycerol i.e. 70%, 86% and 99% purity that obtained from biodiesel plant. Metal oxide catalysts were used with varying operating parameters including reaction time, DMC/glycerol molar ratio, catalyst weight %, temperature and stirring speed. From the study on the effect of different operating parameters; it was found that the type of catalyst used has the most significant effect on the transesterification reaction. Admist the metal oxide catalysts examined, CaO gave the best performance. This study indicates the feasibility of producing glycerol carbonate using different grade of glycerol in both conventional thermal activation and microwave irradiation with CaO as catalyst. Microwave assisted transesterification (MAT) of glycerol into glycerol carbonate has demostrated itself as an energy efficient route by achieving 94.3% yield of GC at 65°C, 5 minutes reaction time, 1 wt% CaO and DMC/glycerol molar ratio of 2. The advantages of MAT transesterification route has made the direct utilization of bioglycerol from biodiesel production without the need of purification. This has marked a more economical and less-energy intensive glycerol carbonate synthesis route.

Keywords: base-catalyzed transesterification, glycerol, glycerol carbonate, microwave irradiation

Procedia PDF Downloads 287

Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

Abstract:

The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

Procedia PDF Downloads 275

Authors: Reza Karami, Ali Akbar Ebrahimi

Abstract:

This paper discusses concurrent engineering of robot manipulators, based on the Holistic Concurrent Design (HCD) methodology and by using a hardware-in-the-loop simulation platform. The methodology allows for considering numerous design variables with different natures concurrently. It redefines the ultimate goal of design based on the notion of satisfaction, resulting in the simplification of the multi-objective constrained optimization process. It also formalizes the effect of designer’s subjective attitude in the process. To enhance modeling efficiency for both computation and accuracy, a hardware-in-the-loop simulation platform is used, which involves physical joint modules and the control unit in addition to the software modules. This platform is implemented in the HCD design architecture to reliably evaluate the design attributes and performance super criterion during the design process. The resulting overall architecture is applied to redesigning kinematic, dynamic and control parameters of an industrial robot manipulator.

Keywords: concurrent engineering, hardware-in-the-loop simulation, robot manipulator, multidisciplinary systems, mechatronics

Procedia PDF Downloads 454