Search results for: intelligence cycle

Authors: Yohanes Kristianto

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The objective of this paper is to compose a sustainable supply chain that integrates product, process and networks design. An integrated life cycle assessment and techno-economic optimization is proposed that might deliver more economically feasible operations, minimizes environmental impacts and maximizes social contributions. Closed loop economy of the supply chain is achieved by reusing waste to be raw material of final products. Societal benefit is given by the supply chain by absorbing waste as source of raw material and opening new work opportunities. A case study of ethanol supply chain from rice straws is considered. The modeling results show that optimization within the scope of LCA is capable of minimizing both CO₂ emissions and energy and utility consumptions and thus enhancing raw materials utilization. Furthermore, the supply chain is capable of contributing to local economy through jobs creation. While the model is quite comprehensive, the future research recommendation on energy integration and global sustainability is proposed.

Keywords: life cycle assessment, techno-economic optimization, sustainable supply chains, closed loop economy

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Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira

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This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.

Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision

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Authors: Jessica Bain, Greg Thoma, Marty Matlock, Jeyam Subbiah, Ebenezer Kwofie

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The environmental impact and particulate matter emissions (PM) associated with the production and packaging of 1 kg of almonds were evaluated using life cycle assessment (LCA). The assessment began at the point of ready to harvest with a system boundary was a cradle-to-gate assessment of almond packaging in California. The assessment included three scenarios of off-ground harvesting of almonds. The three general off-ground harvesting scenarios with variations include the harvested almonds solar dried on a paper tarp in the orchard, the harvested almonds solar dried on the floor in a separate lot, and the harvested almonds dried mechanically. The life cycle inventory (LCI) data for almond production were based on previously published literature and data provided by Almond Board of California (ABC). The ReCiPe 2016 method was used to calculate the midpoint impacts. Using consequential LCA model, the global warming potential (GWP) for the three harvesting scenarios are 2.90, 2.86, and 3.09 kg CO2 eq/ kg of packaged almond for scenarios 1, 2a, and 3a, respectively. The global warming potential for conventional harvesting method was 2.89 kg CO2 eq/ kg of packaged almond. The particulate matter emissions for each scenario per hectare for each off-ground harvesting scenario is 77.14, 9.56, 66.86, and 8.75 for conventional harvesting and scenarios 1, 2, and 3, respectively. The most significant contributions to the overall emissions were from almond production. The farm gate almond production had a global warming potential of 2.12 kg CO2 eq/ kg of packaged almond, approximately 73% of the overall emissions. Based on comparisons between the GWP and PM emissions, scenario 2a was the best tradeoff between GHG and PM production.

Keywords: life cycle assessment, low moisture foods, sustainability, LCA

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Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov

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One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.

Keywords: logic, fuzzy sets, performance measurement, project analysis

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Authors: Buket Boz, Alvaro Diez

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Waste heat recovery by means of Organic Rankine Cycle is a promising technology for the recovery of engine exhaust heat. However, it is complex to find out the optimum cycle conditions with appropriate working fluids to match exhaust gas waste heat due to its high temperature. Hence, this paper focuses on comparing sub-critical and supercritical ORC conditions with eight working fluids on a combined diesel engine-ORC system. The model employs two ORC designs, Regenerative-ORC and Pre-Heating-Regenerative-ORC respectively. The thermodynamic calculations rely on the first and second law of thermodynamics, thermal efficiency and exergy destruction factors are the fundamental parameters evaluated. Additionally, in this study, environmental and safety, GWP (Global Warming Potential) and ODP (Ozone Depletion Potential), characteristic of the refrigerants are taken into consideration as evaluation criteria to define the optimal ORC configuration and conditions. Consequently, the studys outcomes reveal that supercritical ORCs with alkane and siloxane are more suitable for high temperature exhaust waste heat recovery in contrast to sub-critical conditions.

Keywords: internal combustion engine, organic Rankine cycle, waste heat recovery, working fluids

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Authors: Rafaella Nogaroli

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It is presented hypothetical cases in the context of AI algorithms to support clinical decisions, in order to discuss the importance of doctors to respect AI ethical principles. Regarding the principle of transparency and explanation, there is an impact on the new model of patient consent and on the understanding of qualified information. Besides, the human control of technology (AI as a tool) should guide the physician's activity; otherwise, he breaks the patient's legitimate expectation in a specific result, with the consequent transformation of the medical obligation nature.

Keywords: medical law, artificial intelligence, ethical principles, patient´s informed consent, medical obligations

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Authors: Elmongi Elbellili, Ben Lauwens, Daan Huybrechs

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The increasing complexity of modern engineering systems presents a challenge to the digital simulation of these systems which usually can be represented by differential equations. The Linearly Implicit Quantized State System (LIQSS) offers an alternative approach to traditional numerical integration techniques for solving Ordinary Differential Equations (ODEs). This method proved effective for handling discontinuous and large stiff systems. However, the inherent discrete nature of LIQSS may introduce oscillations that result in unnecessary computational steps. The current oscillation detection mechanism relies on a condition that checks the significance of the derivatives, but it could be further improved. This paper describes a different cycle detection mechanism and presents the outcomes using LIQSS order one in simulating the Advection Diffusion problem. The efficiency of this new cycle detection mechanism is verified by comparing the performance of the current solver against the new version as well as a reference solution using a Runge-Kutta method of order14.

Keywords: numerical integration, quantized state systems, ordinary differential equations, stiffness, cycle detection, simulation

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Authors: Sani Mohammed Adam

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This work seeks to review the security challenges facing Nigeria and explore the relevance of laws and policies in tackling the menace. The work looks at the adequacy of available legislations and the functionality of relevant institutions such as the Armed Forces, the Nigeria Police Force, the State Security Service, the Defence Intelligence Agency and the Nigerian Intelligence Agency etc. Comparisons would be made with other jurisdictions, such as inter alia, the Homeland Security in the USA and Counter Terrorism Laws of the United Kingdom. Recommendations would be made on how to strengthen both institutions and laws to curtail the growth of Terrorism in Nigeria.

Keywords: legislations, Nigeria, security, terrorism

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Authors: Phalaunnnaphat Siriwongs

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The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: multiple intelligences, role play, performance assessment, formative assessment

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Authors: Yuhanis Yusof, Zuriani Mustaffa, Siti Sakira Kamaruddin

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Data mining is a fundamental technique in identifying patterns from large data sets. The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical. Prior to that, data are consolidated so that the resulting mining process may be more efficient. This study investigates the effect of different data normalization techniques, which are Min-max, Z-score, and decimal scaling, on Swarm-based forecasting models. Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC). Forecasting models are later developed to predict the daily spot price of crude oil and gasoline. Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max. Nevertheless, the GWO is more superior that ABC as its model generates the highest accuracy for both crude oil and gasoline price. Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.

Keywords: artificial bee colony, data normalization, forecasting, Grey Wolf optimizer

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Authors: Rene A. Salmingo

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In pursuing higher educational institution’s transition to sustainable future, this research initiative was conducted. The study aimed to determine the level of sustainability, environmental impact and life cycle phase assessment of the industrial technology research projects at the Institute of Information Technology, Carlos Hilado Memorial State College (CHMSC), Alijis Campus, Bacolod City, Negros Occidental, Philippines. The research method was descriptive utilizing a researcher made questionnaire to assess the ten (10) industrial technology completed research projects. Mean was used to treat the data and instrument for Good and Scates’ validity through revisions and consultations from the environmental experts, technology specialists; and Cronbach Alpha was used to measure reliability. Results indicated that the level of sustainability and life cycle phase assessment was very high while the environmental impact of the industrial research projects was rated low. Moreover, the current research projects and environmental education courses in the college were relevant to support sustainable industrial technology research projects in the future. Hence, this research initiative will contribute to the transformation of CHMSC as a greening higher educational institution and as a center for sustainable development in the region.

Keywords: environmental impact, industrial technology research projects, life cycle phase assessment, sustainability

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Authors: Loke Mun Sei

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Software testing has become a mandatory process in assuring the software product quality. Hence, test management is needed in order to manage the test activities conducted in the software test life cycle. This paper discusses on the challenges faced in the software test life cycle, and how the test processes and test activities, mainly on test cases creation, test execution, and test reporting is being managed and automated using several test automation tools, i.e. Jira, Robot Framework, and Jenkins.

Keywords: test automation tools, test case, test execution, test reporting

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Authors: Bambang Heliyanto, Rully Dyah Purwati, Hasnam, Fadjry Djufry

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Jatropha curcas L., a drought tolerant and monoecious perennial shrub, has received attention worldwide during the past decade. Realizing the facts, the Indonesian government has decided to option for Jatropha and palm oil for in country biofuel production. To support the program development of high yielding jatropha varieties is necessary. This paper reviews Jatropha improvement program in Indonesia using mass selection and hybrid development. To start with, at the end of 2005, in-country germplasm collection was mobilized to Lampung and Nusa Tenggara Barat (NTB) provinces and successfully collected 15 provenances/sub-provenances which serves as a base population for selection. A significant improvement has been achieved through a simple recurrent breeding selection during 2006 to 2007. Seed yield productivity increased more than double, from 0.36 to 0.97 ton dry seed per hectare during the first selection cycle (IP-1), and then increased to 2.2 ton per hectare during the second cycles (IP-2) in Lampung provenance. Similar result was also observed in NTB provenance. Seed yield productivity increased from 0.43 ton to 1 ton dry seed per hectare in the first cycle (IP-1), and then 1.9 ton in the second cycle (IP-2). In 2008, the population IP-3 resulted from the third cycle of selection have been identified which were capable of producing 2.2 to 2.4 ton seed yield per hectare. To improve the seed yield per hectare, jatropha hybrid varieties was developed involving superior provenances. As a result a Jatropha Energy Terbarukan (JET) variety-2 was released in 2017 with seed yield potential of 2.6 ton per hectare. The use of this high yielding genotypes for biofuel is discussed.

Keywords: Jatropha curcas, provenance, biofuel, improve population, hybrid

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Authors: David Chao, John Lai, Alvin Wu, Carl Wang

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For lithium-ion batteries with multiple cell configurations, some use scenarios can cause uneven aging effects to each cell within the battery because of uneven current distribution. Hence the focus of the study is to explore the aging effect(s) on batteries with different construction designs. In order to systematically study the influence of various factors in some key battery configurations, a detailed analysis of three key battery construction factors is conducted. And those key factors are (1) terminal position; (2) cell alignment matrix; and (3) interconnect resistance between cells. In this study, the 2S2P circuitry has been set as a model multi-cell battery to set up different battery samples, and the aging behavior is studied by a cycling test to analyze the current distribution and recoverable capacity. According to the outcome of aging tests, some key findings are: (I) different cells alignment matrices can have an impact on the cycle life of the battery; (II) symmetrical structure has been identified as a critical factor that can influence the battery cycle life, and unbalanced resistance can lead to inconsistent cell aging status; (III) the terminal position has been found to contribute to the uneven current distribution, that can cause an accelerated battery aging effect; and (IV) the internal connection resistance increase can actually result in cycle life increase; however, it is noteworthy that such increase in cycle life is accompanied by a decline in battery performance. In summary, the key findings from the study can help to identify the key aging factor of multi-cell batteries, and it can be useful to effectively improve the accuracy of battery capacity predictions.

Keywords: multiple cells battery, current distribution, battery aging, cell connection

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: O. A. Olagunju, S. L. Kiambi

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Municipal Plastic Wastes (MPW) can have several negative effects on the environment, and this is causing a growing concern which requires urgent intervention. Addressing these environmental challenges by proffering alternative end-of-life (EOL) techniques for MPW treatment is thus critical for designing and implementing effective long-term remedies. In this study, the environmental implications of several MPW treatment technologies were assessed using life cycle assessment (LCA). Our focus was on four potential waste treatment scenarios for MPW: waste disposal via landfill, waste incineration, waste regeneration, and reusability of recycled waste. The findings show that recycling has a greater benefit over landfilling and incineration methods. The most important environmental benefit comes from the recycling of plastics, which may serve as reliable source materials for environmentally friendly products. Following a holistic evaluation, five major factors that influence the overall impact on the environment were outlined: the mass fraction in waste, the recycling rate, the conversion efficiency, the waste-to-energy conversion rate, and the type of energy which can be utilized from incineration generated energy

Keywords: end-of-life, incineration, landfill, life cycle assessment, municipal plastic waste, recycling, waste-to-energy

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Authors: Sami Ayad, Mengshan Lee

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The Sustainable Development Goals (SDGs) were designed to be the best possible blueprint to achieve peace, prosperity, and overall, a better and more sustainable future for the Earth and all its people, and such a blueprint is needed more than ever. The SDGs face many hurdles that will prevent them from becoming a reality, one of such hurdles, arguably, is the chemical pollution and unintended chemical impacts generated through the production of various goods and resources that we consume. Chemical Alternatives Assessment has proven to be a viable solution for chemical pollution management in terms of filtering out hazardous chemicals for a greener alternative. However, the current substitution practice lacks crucial quantitative datasets (exposures and life cycle impacts) to ensure no unintended trade-offs occur in the substitution process. A Chemical Life Cycle Alternative Assessment (CLiCAA) framework is proposed as a reliable and replicable alternative to Life Cycle Based Alternative Assessment (LCAA) as it integrates chemical molecular structure analysis and Chemical Life Cycle Collaborative (CLiCC) web-based tool to fill in data gaps that the former frameworks suffer from. The CLiCAA framework consists of a four filtering layers, the first two being mandatory, with the final two being optional assessment and data extrapolation steps. Each layer includes relevant impact categories of each chemical, ranging from human to environmental impacts, that will be assessed and aggregated into unique scores for overall comparable results, with little to no data. A feasibility study will demonstrate the efficiency and accuracy of CLiCAA whilst bridging both cancer potency and exposure limit data, hoping to provide the necessary categorical impact information for every firm possible, especially those disadvantaged in terms of research and resource management.

Keywords: chemical alternative assessment, LCA, LCAA, CLiCC, CLiCAA, chemical substitution framework, cancer potency data, chemical molecular structure analysis

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Authors: Xiaoyu Sun

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In recent years, the rapid development of Artificial Intelligence (AI) has extensively promoted medicine, pharmaceutical, and other related fields. The medical research and development of artificial intelligence by scientific and commercial organizations are on the fast track. The ethics review is one of the critical procedures of registration to get the products approved and launched. However, the SOPs for ethics review is not enough to guide the healthy and rapid development of artificial intelligence in healthcare in China. Ethical Review Measures for Biomedical Research Involving Human Beings was enacted by the National Health Commission of the People's Republic of China (NHC) on December 1st, 2016. However, from a legislative design perspective, it was neither updated timely nor in line with the trends of AI international development. Therefore, it was great that NHC published a consultation paper on the updated version on March 16th, 2021. Based on the most updated laws and regulations in the States and EU, and in-depth-interviewed 11 subject matter experts in China, including lawmakers, regulators, and key members of ethics review committees, heads of Regulatory Affairs in SaMD industry, and data scientists, several suggestions were proposed on top of the updated version. Although the new version indicated that the Ethics Review Committees need to be created by National, Provincial and individual institute levels, the review authorities of different levels were not clarified. The suggestion is that the precise scope of review authorities for each level should be identified based on Risk Analysis and Management Model, such as the complicated leading technology, gene editing, should be reviewed by National Ethics Review Committees, it will be the job of individual institute Ethics Review Committees to review and approve the clinical study with less risk such as an innovative cream to treat acne. Furthermore, to standardize the research and development of artificial intelligence in healthcare in the age of AI, more clear guidance should be given to data security in the layers of data, algorithm, and application in the process of ethics review. In addition, transparency and responsibility, as two of six principles in the Rome Call for AI Ethics, could be further strengthened in the updated version. It is the shared goal among all countries to manage well and develop AI to benefit human beings. Learned from the other countries who have more learning and experience, China could be one of the most advanced countries in artificial intelligence in healthcare.

Keywords: biomedical research involving human beings, data security, ethics committees, ethical review, medical artificial intelligence

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Authors: John R Evans, Sook-Ying Ho, Rey Chin

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This paper describes the research investigations orientated to the starting and propelling of a solid fuel rocket engine which operates as combined cycle propulsion system using three thrust pulses. The vehicle has been designed to minimise the cost of launching small number of Nano/Cube satellites into low earth orbits (LEO). A technology described in this paper is a ground-based launch propulsion system which starts the rocket vertical motion immediately causing air flow to enter the ramjet’s intake. Current technology has a ramjet operation predicted to be able to start high subsonic speed of 280 m/s using a liquid fuel ramjet (LFRJ). The combined cycle engine configuration is in many ways fundamentally different from the LFRJ. A much lower subsonic start speed is highly desirable since the use of a mortar to obtain the latter speed for rocket means a shorter launcher length can be utilized. This paper examines the means and has some performance calculations, including Computational Fluid Dynamics analysis of air-intake at suitable operational conditions, 3-DOF point mass trajectory analysis of multi-pulse propulsion system (where pulse ignition time and thrust magnitude can be controlled), etc. of getting a combined cycle rocket engine use in a single stage vehicle.

Keywords: combine cycle propulsion system, low earth orbit launch vehicle, computational fluid dynamics analysis, 3dof trajectory analysis

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Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

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Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

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Authors: Danying Gu, Xiaoyan Li, Yuanlei He

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As a knowledge-intensive industry, nuclear industry highly values the importance of safety and quality. The life cycle of a NPP (Nuclear Power Plant) can last 100 years from the initial research and design to its decommissioning. How to implement the high-quality knowledge management and how to contribute to a more safe, advanced and economic NPP (Nuclear Power Plant) is the most important issue and responsibility for knowledge management. As the lead of nuclear industry, nuclear research and design institute has competitive advantages of its advanced technology, knowledge and information, DKM (Design Knowledge Management) of nuclear research and design institute is the core of the knowledge management in the whole nuclear industry. In this paper, the study and practice on DKM and knowledge transfer across the life cycle of a new-built NPP in China is introduced. For this digital intelligent NPP, the whole design process is based on a digital design platform which includes NPP engineering and design dynamic analyzer, visualization engineering verification platform, digital operation maintenance support platform and digital equipment design, manufacture integrated collaborative platform. In order to make all the design data and information transfer across design, construction, commissioning and operation, the overall architecture of new-built digital NPP should become a modern knowledge management system. So a digital information transfer model across the NPP life cycle is proposed in this paper. The challenges related to design knowledge transfer is also discussed, such as digital information handover, data center and data sorting, unified data coding system. On the other hand, effective delivery of design information during the construction and operation phase will contribute to the comprehensive understanding of design ideas and components and systems for the construction contractor and operation unit, largely increasing the safety, quality and economic benefits during the life cycle. The operation and maintenance records generated from the NPP operation process have great significance for maintaining the operating state of NPP, especially the comprehensiveness, validity and traceability of the records. So the requirements of an online monitoring and smart diagnosis system of NPP is also proposed, to help utility-owners to improve the safety and efficiency.

Keywords: design knowledge management, digital nuclear power plant, knowledge transfer, life cycle

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: Mohamed M. Ali, Adel Nofal, Amr Kandil, Mahmoud Agour

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High phosphorus gray iron (HPGI) is used to connect the steel stub of an anode rod to a prebaked anode carbon block in the aluminium reduction cells. In this paper, a complete characterization for HPGI was done, includes studying the chemical composition of the HPGI collar, anodic voltage drop, collar temperature over 30 days anode life cycle, microstructure and mechanical properties. During anode life cycle, the carbon content in HPGI was lowed from 3.73 to 3.38%, and different changes in the anodic voltage drop at the stub- collar-anode connection were recorded. The collar temperature increases over the anode life cycle and reaches to 850°C in four weeks after anode changing. Significant changes in the HPGI microstructure were observed after 3 and 30 days from the anode changing. To simulate the actual operating conditions in the steel stub/collar/carbon anode connection, a bench-scale experimental set-up was designed and used for electrical resistance and resistivity respectively. The results showed the current HPGI properties needed to modify or producing new alloys with excellent electrical and mechanical properties. The steel stub and HPGI thermal expansion were measured and studied. Considerable permanent expansion was observed for the HPGI collar after the completion of the heating-cooling cycle.

Keywords: high phosphorus gray iron (HPGI), aluminium reduction cells, anodic voltage drop, microstructure, mechanical and electrical properties

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Authors: Asad Naeem, Mohamed Nour Eldin, Jinkoo Kim

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In this study, the seismic performance and life cycle cost (LCC) are evaluated of the structure retrofitted with the damped cable system (DCS). The DCS is a seismic retrofit system composed of a high-strength steel cable and pressurized viscous dampers. The analysis model of the system is first derived using various link elements in SAP2000, and fragility curves of the structure retrofitted with the DCS and viscous dampers are obtained using incremental dynamic analyses. The analysis results show that the residual displacements of the structure equipped with the DCS are smaller than those of the structure with retrofitted with only conventional viscous dampers, due to the enhanced stiffness/strength and self-centering capability of the damped cable system. The fragility analysis shows that the structure retrofitted with the DCS has the least probability of reaching the specific limit states compared to the bare structure and the structure with viscous damper. It is also observed that the initial cost of the DCS method required for the seismic retrofit is smaller than that of the structure with viscous dampers and that the LCC of the structure equipped with the DCS is smaller than that of the structure with viscous dampers.

Keywords: damped cable system, fragility curve, life cycle cost, seismic retrofit, self-centering

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Authors: Elisabete Alberdi, Irantzu Álvarez, Laura Girón

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The objective of this work is to propose a cycle path or network of paths to the UPV/EHU Campus in Leioa. The proposal will be presented from the point of view of sustainability. In order to achieve this, the roads that are already built will be used, and the road or network will be proposed to be built with the least amount of money possible. To select the most suitable route for the bike lane, various sources of information have been used. Through this data, we analyse the transport infrastructure and the mobility around the UPV/EHU Campus in Leioa. This work aims to satisfy the mobility needs of users on the University Campus to contribute to the sustainability of the campus.

Keywords: cycle lane, sustainability, accessibility, transport, agenda 2030

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Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence and business intelligence. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster Evolution. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational Creation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. The significant impact of CEK-DI on PSI highlights the critical role of customer experiences in driving an organization. Companies that actively integrate customer insights into their opportunity creation processes are more likely to create offerings that match customer expectations, which drives higher levels of product and service sophistication. Additionally, the positive and significant impact of MI on CEK-DI underscores the critical role of market insights in shaping evolutionary strategies. While the relationship between MI and PSI is positive, the slightly weaker significance level indicates a subtle association, suggesting that while MI contributes to the development of ideas, In conclusion, the study emphasizes the fundamental role of intelligence capabilities, especially artificial intelligence, emphasizing the need for organizations to leverage market and customer intelligence to achieve effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of development, influencing customer experiential knowledge and shaping organizational strategies and practices. Future research could adopt longitudinal designs and gather data from various sectors to offer broader insights. Additionally, the study focuses on the effects of marketing intelligence, business intelligence, customer experiential knowledge, and innovation, but other unexamined variables may also influence innovation processes. Future studies could investigate additional factors, mediators, or moderators, including the role of emerging technologies like AI and machine learning in driving innovation.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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Authors: Cecilia Amponsem-Boateng, Timothy Bonney Oppongx, Weidong Zhang, Jonathan Boakye Yiadom, Lianke Wang, Kwabena Acheampong, Godfrey Opolot

Abstract:

In Ghana, the management of hypertension in primary health care is a cost-effective way of addressing premature deaths from vascular disorders that include hypertension. There is little or no evidence of large-scale studies on the prevalence, risk, and knowledge/awareness of hypertension in students aged 12–22 years in Ghana. In a cross-sectional study, blood pressure, anthropometric indices, and knowledge/awareness assessment of students at second-cycle schools were recorded from 2018 to 2020 in three regions of Ghana. Multistage cluster sampling was used in selecting regions and the schools. Prevalence of prehypertension and hypertension was categorized by the Joint National Committee 7, where appropriate, chi-square, scatter plots, and correlations were used in showing associations. A total of 3165 students comprising 1776 (56.1%) females and 1389 (43.9%) males participated in this study within three regions of Ghana. The minimum age was 12 years and the maximum age was 22 years. The mean age was 17.21 with standard deviation (SD: 1.59) years. A 95% confidence interval was set for estimations and a P value < 0.05 was set as significant. The prevalence rate of overall hypertension was 19.91% and elevated (prehypertension) was 26.07%. Risk indicators such as weight, BMI, waist circumference, physical activity, and form of the diet were positively correlated with hypertension. Among Ghanaian students currently in second-cycle educational institutions, 19.91% were hypertensive and 26.07% were prehypertensive. This may indicate a probable high prevalence of hypertension in the future adult population if measures are not taken to curb the associated risks.

Keywords: hypertension, second-cycle schools, Ghana, youth

Procedia PDF Downloads 83

Authors: B. J. Sonani, J. K. Ratnadhariya, Srinivas Palanki

Abstract:

Cryogenic engineering is the fast growing branch of the modern technology. There are various applications of the cryogenic engineering such as liquefaction in gas industries, metal industries, medical science, space technology, and transportation. The low-temperature technology developed superconducting materials which lead to reduce the friction and wear in various components of the systems. The liquid oxygen, hydrogen and helium play vital role in space application. The liquefaction process is produced very low temperature liquid for various application in research and modern application. The air liquefaction system for oxygen plants in gas industries is based on the Claude cycle. The effect of process parameters on the overall system is difficult to be analysed by manual calculations, and this provides the motivation to use process simulators for understanding the steady state and dynamic behaviour of such systems. The parametric study of this system via MATLAB simulations provide useful guidelines for preliminary design of air liquefaction system based on the Claude cycle. Every organization is always trying for reduce the cost and using the optimum performance of the plant for the staying in the competitive market.

Keywords: cryogenic, liquefaction, low -temperature, oxygen, claude cycle, optimization, MATLAB

Procedia PDF Downloads 322

Authors: Amira Racha Ben Yakoub, Ali Ferchichi

Abstract:

In order to investigate the impact of sowing time on growth parameters, the length of the development cycle and yield of tossa jute (Corchorus olitorius L.), a field experiment was conducted from March to May 2011 at the Laboratoire d’Aridoculture et Cultures Oasiennes, ‘Institut des Régions Arides de Médénine’, Tunisia. Results of the experiment revealed that the early sowing (the middle of March, the beginning of April) induced a cycle of more than 100 days to reach the stage maturity and generates a marked drop in production. This period of plantation affects plant development and leads to a sharp drop in performance marked primarily by a reduction in growth, number and size of leaves, number of flowers and pods and weight of different parts of plant. Sowing from the end of April seems appropriate for shortening the development cycle and better profitability than the first two dates. Seeding of C. olitorius during May enhance the development of plants more dense, which explains the superiority of production marked by the increase of seed yield and leaf fresh and dry weight of this leafy vegetables.

Keywords: tossa jute (Corchorus olitorius L), sowing date, growth, yield

Procedia PDF Downloads 349

Authors: H. Aksas, S. Boughrara, K. Louhab

Abstract:

The goal of this study was the use of life cycle assessment (LCA) methodology to assess the environmental impact of pharmaceutical product (four kinds of syrup form and tree kinds of pomade form), which are produced in one leader manufactory in Algeria town that is SAIDAL Company. The impacts generated have evaluated using SimpaPro7.1 with CML92 Method for syrup form and EPD 2007 for pomade form. All impacts evaluated have compared between them, with determination of the compound contributing to each impacts in each case. Data needed to conduct Life Cycle Inventory (LCI) came from this factory, by the collection of theoretical data near the responsible technicians and engineers of the company, the practical data are resulting from the assay of pharmaceutical liquid, obtained at the laboratories of the university. This data represent different raw material imported from European and Asian country necessarily to formulate the drug. Energy used is coming from Algerian resource for the input. Outputs are the result of effluent analysis of this factory with different form (liquid, solid and gas form). All this data (input and output) represent the ecobalance.

Keywords: pharmaceutical product, drug residues, LCA methodology, environmental impacts

Procedia PDF Downloads 246