Search results for: IoT automation

Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

Procedia PDF Downloads 109

Authors: Björn de Kruijf, Arjen Edzes, Sietske Waslander

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In an ever-quickly changing society, lifelong development is seen as a solution to labor market problems by politicians and policymakers. In this paper, we investigate how policy instruments are used to increase participation in lifelong development and on which behavioral principles policy is based. Digitization, automation, and an aging population change society and the labor market accordingly. Skills that were once most sought after in the workforce can become abundantly present. For people to remain relevant in the working population, they need to continue adapting new skills useful in the current labor market. Many reports have been written that focus on the role of lifelong development in this changing society and how lifelong development can help keep people adapt and stay relevant. Inspired by these reports, governments have implemented a broad range of policies to support participation in lifelong development. The question we ask ourselves is how government policies promote participation in lifelong development. This stems from a complex interplay of policy instruments and learning. Regulation, economic and soft instruments can be combined to promote lifelong development, and different types of education further complex policies on lifelong development. Literature suggests that different stages in people’s lives might warrant different methods of learning. Governments could anticipate this in their policies. In order to influence people’s behavior, the government can tap into a broad range of sociological, psychological, and (behavioral) economic principles. The traditional economic assumption that behavior is rational is known to be only partially true, and the government can use many biases in human behavior to stimulate participation in lifelong development. In this paper, we also try to find which biases the government taps into to promote participation if they tap into any of these biases. The goal of this paper is to analyze government policies intended to promote participation in lifelong development. To do this, we develop a framework to analyze the policies on lifelong development. We specifically incorporate the role of learning and the behavioral principles underlying policy instruments in the framework. We apply this framework to the case of the Netherlands, where we examine a set of policy documents. We single out the policies the government has put in place and how they are vertically and horizontally related. Afterward, we apply the framework and classify the individual policies by policy instrument and by type of learning. We find that the Dutch government focuses on formal and non-formal learning in their policy instruments. However, the literature suggests that learning at a later age is mainly done in an informal manner through experiences.

Keywords: learning, lifelong development, policy analysis, policy instruments

Procedia PDF Downloads 82

Authors: Luís Miguel Cabeça Marques, Alberto Manuel Martinho Vale, José Pedro Miragaia Trancoso Vaz, Ana Sofia Baptista Fernandes, Rui Alexandre de Barros Coito, Tiago Miguel Prates da Costa

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The detection and localization of hidden radioactive sources are of significant importance in countering the illicit traffic of Special Nuclear Materials and other radioactive sources and materials. Radiation portal monitors are commonly used at airports, seaports, and international land borders for inspecting cargo and vehicles. However, these equipment can be expensive and are not available at all checkpoints. Consequently, the localization of SNM and other radioactive sources often relies on handheld equipment, which can be time-consuming. The current study presents the advantages of real-time analysis of gamma-ray count rate data from a mobile radiation detection system based on simulated data and field tests. The incorporation of profit functions and decision criteria to optimize the detection system's path significantly enhances the radiation field information and reduces survey time during cargo inspection. For source position estimation, a maximum likelihood estimation algorithm is employed, and confidence intervals are derived using the Fisher information. The study also explores the impact of uncertainties, baselines, and thresholds on the performance of the profit function. The proposed detection system, utilizing a plastic scintillator with silicon photomultiplier sensors, boasts several benefits, including cost-effectiveness, high geometric efficiency, compactness, and lightweight design. This versatility allows for seamless integration into any mobile platform, be it air, land, maritime, or hybrid, and it can also serve as a handheld device. Furthermore, integration of the detection system into drones, particularly multirotors, and its affordability enable the automation of source search and substantial reduction in survey time, particularly when deploying a fleet of drones. While the primary focus is on inspecting maritime container cargo, the methodologies explored in this research can be applied to the inspection of other infrastructures, such as nuclear facilities or vehicles.

Keywords: plastic scintillators, profit functions, path planning, gamma-ray detection, source localization, mobile radiation detection system, security scenario

Procedia PDF Downloads 115

Authors: Kuhorfah Emmanuel Mawuli

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Generally, for firms to enhance their operational efficiency of logistics, it is imperative to assess the logistics function. The cost of logistics conventionally represents a key consideration in the pricing decisions of firms, which suggests that cost efficiency in logistics can go a long way to improve margins. Warehousing, which is a key part of logistics operations, has the prospect of influencing operational efficiency in logistics management as well as customer value, but this potential has often not been recognized. It has been found that there is a paucity of research that evaluates the efficiency of warehouses. Indeed, limited research has been conducted to examine potential barriers to effective warehousing management. Due to this paucity of research, there is limited knowledge on how to address the obstacles associated with warehousing management. In order for warehousing management to become profitable, there is the need to integrate, balance, and manage the economic inputs and outputs of the entire warehouse operations, something that many firms tend to ignore. Management of warehousing is not solely related to storage functions. Instead, effective warehousing management requires such practices as maximum possible mechanization and automation of operations, optimal use of space and capacity of storage facilities, organization through "continuous flow" of goods, a planned system of storage operations, and safety of goods. For example, there is an important need for space utilization of the warehouse surface as it is a good way to evaluate the storing operation and pick items per hour. In the setting of Mantrac Ghana, not much knowledge regarding the management of the warehouses exists. The researcher has personally observed many gaps in the management of the warehouse facilities in the case organization Mantrac Ghana. It is important, therefore, to assess the warehouse facility management of the case company with the objective of identifying weaknesses for improvement. The study employs an in-depth qualitative research approach using interviews as a mode of data collection. Respondents in the study mainly comprised warehouse facility managers in the studied company. A total of 10 participants were selected for the study using a purposive sampling strategy. Results emanating from the study demonstrate limited warehousing effectiveness in the case company. Findings further reveal that the major barriers to effective warehousing facility management comprise poor layout, poor picking optimization, labour costs, and inaccurate orders; policy implications of the study findings are finally outlined.

Keywords: assessing, warehousing, facility, management

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Authors: Ahmed Abdulfatah Yusuf, Collins Oduor Ondiek

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The automation of farming activities can have a transformational impact on the agricultural sector, especially from the emerging new technologies such as the Internet of Things (IoT). The system uses water level sensors and soil moisture sensors that measure the content of water in the soil as the values generated from the sensors enable the system to use an appropriate quantity of water, which avoids over or under irrigation. Due to the increase in the world’s population, there is a need to increase food production. With this demand in place, it is difficult to increase crop yield using the traditional manual approaches that lead to the wastage of water, thus affecting crop production. Food insecurity has become a scourge greatly affecting the developing countries and agriculture is an essential part of human life and tends to be the mainstay of the economy in most developing nations. Thus, without the provision of adequate food supplies, the population of those living in poverty is likely to multiply. The project’s main objective is to design and develop an IoT (Internet of Things) microcontroller-based Smart Irrigation System. In addition, the specific research objectives are to find out the challenges with traditional irrigation approaches and to determine the benefits of IoT-based smart irrigation systems. Furthermore, the system includes Arduino, a website and a database that works simultaneously in collecting and storing the data. The system is designed to pave the way in attaining the Sustainable Development Goal (SDG 1), which aims to end extreme poverty in all forms by 2030. The research design aimed at this project is a descriptive research design. Data was gathered through online questionnaires that used both quantitative and qualitative in order to triangulate the data. Out of the 32 questionnaires sent, there were 32 responses leading to a 100% response rate. In terms of sampling, the target group of this project is urban farmers, which account for about 25% of the population of Nairobi. From the findings of the research carried out, it is evident that there is a need to move away from manual irrigation approaches due to the high wastage of water to the use of smart irrigation systems that propose a better way of conserving water while maintaining the quality and moisture of the soil. The research also found out that urban farmers are willing to adopt this system to better their farming practices. However, this system can be improved in the future by incorporating it with other features and deploying it to a larger geographical area.

Keywords: crop production, food security, smart irrigation system, sustainable development goal

Procedia PDF Downloads 151

Authors: Mballa Abanda Luc Aurelien Serge, Henda Gnakate Biba, Kuate Guemo Romaric, Akono Rufine Nicole, Zabotom Yaya Fadel Biba, Petfiang Sidonie, Bella Suzane Jenifer

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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original, and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological, and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation, and the question of modeling in the human sciences: mathematics, computer science, translation automation, and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal, and random music. The experimentation confirming the theorization, I designed a semi-digital, semi-analog application that translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music, and deterministic and random music). To test this application, I use music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). The translation is done (from writing to writing, from writing to speech, and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz, and world music or variety, etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: language, music, sciences, quantum entenglement

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Authors: Ivan Maguire, Ciprian Briciu, Alan Barrett, Dara Kervick, Jens Ducrèe, Fiona Regan

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With the ever-increasing myriad of applications of which microfluidic devices are capable, reliable fluidic actuation development has remained fundamental to the success of these microfluidic platforms. There are a number of approaches which can be taken in order to integrate liquid actuation on microfluidic platforms, which can usually be split into two primary categories; active microvalves and passive microvalves. Active microvalves are microfluidic valves which require a physical parameter change by external, or separate interaction, for actuation to occur. Passive microvalves are microfluidic valves which don’t require external interaction for actuation due to the valve’s natural physical parameters, which can be overcome through sample interaction. The purpose of this paper is to illustrate how further improvements to past microvalve solutions can largely enhance systematic reliability and performance, with both novel active and passive microvalves demonstrated. Covered within this scope will be two alternative and novel microvalve solutions for centrifugal microfluidic platforms; a revamped pneumatic-dissolvable film active microvalve (PAM) strategy and a spray-on Sol-Gel based hydrophobic passive microvalve (HPM) approach. Both the PAM and the HPM mechanisms were demonstrated on a centrifugal microfluidic platform consisting of alternating layers of 1.5 mm poly(methyl methacrylate) (PMMA) (for reagent storage) sheets and ~150 μm pressure sensitive adhesive (PSA) (for microchannel fabrication) sheets. The PAM approach differs from previous SOLUBON™ dissolvable film methods by introducing a more reliable and predictable liquid delivery mechanism to microvalve site, thus significantly reducing premature activation. This approach has also shown excellent synchronicity when performed in a multiplexed form. The HPM method utilises a new spray-on and low curing temperature (70°C) sol-gel material. The resultant double layer coating comprises a PMMA adherent sol-gel as the bottom layer and an ultra hydrophobic silica nano-particles (SNPs) film as the top layer. The optimal coating was integrated to microfluidic channels with varying cross-sectional area for assessing microvalve burst frequencies consistency. It is hoped that these microvalving solutions, which can be easily added to centrifugal microfluidic platforms, will significantly improve automation reliability.

Keywords: centrifugal microfluidics, hydrophobic microvalves, lab-on-a-disc, pneumatic microvalves

Procedia PDF Downloads 188

Authors: Ray Bryant

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3Strands Global Foundation (3SGF), a non-profit with a mission to mobilize communities to combat human trafficking through prevention education and reintegration programs, launched a groundbreaking study that calls out the usage and benefits of artificial intelligence in the war against human trafficking. Having gathered more than 30,000 stories from counselors and school staff who have gone through its PROTECT Prevention Education program, 3SGF sought to develop a methodology to measure the effectiveness of the training, which helps educators and school staff identify physical signs and behaviors indicating a student is being victimized. The program further illustrates how to recognize and respond to trauma and teaches the steps to take to report human trafficking, as well as how to connect victims with the proper professionals. 3SGF partnered with Levity, a leader in no-code Artificial Intelligence (AI) automation, to create the research study utilizing natural language processing, a branch of artificial intelligence, to measure the effectiveness of their prevention education program. By applying the logic created for the study, the platform analyzed and categorized each story. If the story, directly from the educator, demonstrated one or more of the desired outcomes; Increased Awareness, Increased Knowledge, or Intended Behavior Change, a label was applied. The system then added a confidence level for each identified label. The study results were generated with a 99% confidence level. Preliminary results show that of the 30,000 stories gathered, it became overwhelmingly clear that a significant majority of the participants now have increased awareness of the issue, demonstrated better knowledge of how to help prevent the crime, and expressed an intention to change how they approach what they do daily. In addition, it was observed that approximately 30% of the stories involved comments by educators expressing they wish they’d had this knowledge sooner as they can think of many students they would have been able to help. Objectives Of Research: To solve the problem of needing to analyze and accurately categorize more than 30,000 data points of participant feedback in order to evaluate the success of a human trafficking prevention program by using AI and Natural Language Processing. Methodologies Used: In conjunction with our strategic partner, Levity, we have created our own NLP analysis engine specific to our problem. Contributions To Research: The intersection of AI and human rights and how to utilize technology to combat human trafficking.

Keywords: AI, technology, human trafficking, prevention

Procedia PDF Downloads 59

Authors: Muhammad Khairi bin Sulaiman

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The utilization of Building Information Modelling (BIM) in the construction industry has provided an opportunity for designers in the Architecture, Engineering and Construction (AEC) industry to proceed from the conventional method of using manual drafting to a way that creates alternative designs quickly, produces more accurate, reliable and consistent outputs. By using BIM Software, designers can create digital content that manipulates the use of data using the parametric model of BIM. With BIM software, more alternative designs can be created quickly and design problems can be explored further to produce a better design faster than conventional design methods. Generally, BIM is used as a documentation mechanism and has not been fully explored and utilised its capabilities as a design tool. Relative to the current issue, Modular Coordination (MC) design as a sustainable design practice is encouraged since MC design will reduce material wastage through standard dimensioning, pre-fabrication, repetitive, modular construction and components. However, MC design involves a complex process of rules and dimensions. Therefore, a tool is needed to make this process easier. Since the parameters in BIM can easily be manipulated to follow MC rules and dimensioning, thus, the integration of BIM software with MC design is proposed for architects during the design stage. With this tool, there will be an improvement in acceptance and practice in the application of MC design effectively. Consequently, this study will analyse and explore the function and customization of BIM objects and the capability of BIM software to expedite the application of MC design during the design stage for architects. With this application, architects will be able to create building models and locate objects within reference modular grids that adhere to MC rules and dimensions. The parametric modeling capabilities of BIM will also act as a visual tool that will further enhance the automation of the 3-Dimensional space planning modeling process. (Method) The study will first analyze and explore the parametric modeling capabilities of rule-based BIM objects, which eventually customize a reference grid within the rules and dimensioning of MC. Eventually, the approach will further enhance the architect's overall design process and enable architects to automate complex modeling, which was nearly impossible before. A prototype using a residential quarter will be modeled. A set of reference grids guided by specific MC rules and dimensions will be used to develop a variety of space planning and configuration. With the use of the design, the tool will expedite the design process and encourage the use of MC Design in the construction industry.

Keywords: building information modeling, modular coordination, space planning, customization, BIM application, MC space planning

Procedia PDF Downloads 84

Authors: M. A. Okezue, K. L. Clase, S. R. Byrn

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The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO₄) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO₄ tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO₄ tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.

Keywords: data integrity, spreadsheets, titrimetry, validation, zinc sulphate tablets

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

Procedia PDF Downloads 178

Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu

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Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.

Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior

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Authors: Sungho Kim, Jaechoul Shin, Yujin Baek

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In recent years, due to the environmental impacts and time factor, etc., various type of pavement deterioration is increasing rapidly such as crack, pothole, rutting and roughness degradation. The Ministry of Land, Infrastructure and Transport maintains regular pavement condition of the highway and the national highway using the pavement condition survey equipment and structural survey equipment in Korea. Local governments that maintain local roads, farm roads, etc. are difficult to maintain the pavement condition using the pavement condition survey equipment depending on economic conditions, skills shortages and local conditions such as narrow roads. This study presents a quantitative evaluation method of the pavement condition through the visual inspection to overcome these problems of roads managed by local governments. It is difficult to evaluate rutting and roughness with the naked eye. However, the condition of cracks can be evaluated with the naked eye. Linear cracks (m), area cracks (m²) and potholes (number, m²) were investigated with the naked eye every 100 meters for survey the cracks. In this paper, crack ratio was calculated using the results of the condition of cracks and pavement condition was evaluated by calculated crack ratio. The pavement condition survey equipment also investigated the pavement condition in the same section in order to evaluate the reliability of pavement condition evaluation by the calculated crack ratio. The pavement condition was evaluated through the SPI (Seoul Pavement Index) and calculated crack ratio using results of field survey. The results of a comparison between 'the SPI considering only crack ratio' and 'the SPI considering rutting and roughness either' using the equipment survey data showed a margin of error below 5% when the SPI is less than 5. The SPI 5 is considered the base point to determine whether to maintain the pavement condition. It showed that the pavement condition can be evaluated using only the crack ratio. According to the analysis results of the crack ratio between the visual inspection and the equipment survey, it has an average error of 1.86%(minimum 0.03%, maximum 9.58%). Economically, the visual inspection costs only 10% of the equipment survey and will also help the economy by creating new jobs. This paper advises that local governments maintain the pavement condition through the visual investigations. However, more research is needed to improve reliability. Acknowledgment: The author would like to thank the MOLIT (Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: asphalt pavement maintenance, crack ratio, evaluation of asphalt pavement condition, SPI (Seoul Pavement Index), visual investigation

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Authors: Gurkirandeep Kaur, Rana Pratap Yadav

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This experimental study is aimed to examine the radiation characteristics of different plasma structures of a surface wave-driven plasma antenna by an automated measuring system. In this study, a 30 cm long plasma column of argon gas with a diameter of 3 cm is excited by surface wave discharge mechanism operating at 13.56 MHz with RF power level up to 100 Watts and gas pressure between 0.01 to 0.05 mb. The study reveals that a single structured plasma monopole can be modified into an array of plasma antenna elements by forming multiple striations or plasma blobs inside the discharge tube by altering the values of plasma properties such as working pressure, operating frequency, input RF power, discharge tube dimensions, i.e., length, radius, and thickness. It is also reported that plasma length, electron density, and conductivity are functions of operating plasma parameters and controlled by changing working pressure and input power. To investigate the antenna radiation efficiency for the far-field region, an automation-based radiation measuring system has been fabricated and presented in detail. This developed automated system involves a combined setup of controller, dc servo motors, vector network analyzer, and computing device to evaluate the radiation intensity, directivity, gain and efficiency of plasma antenna. In this system, the controller is connected to multiple motors for moving aluminum shafts in both elevation and azimuthal plane whereas radiation from plasma monopole antenna is measured by a Vector Network Analyser (VNA) which is further wired up with the computing device to display radiations in polar plot forms. Here, the radiation characteristics of both continuous and array plasma monopole antenna have been studied for various working plasma parameters. The experimental results clearly indicate that the plasma antenna is as efficient as a metallic antenna. The radiation from plasma monopole antenna is significantly influenced by plasma properties which provides a wider range in radiation pattern where desired radiation parameters like beam-width, the direction of radiation, radiation intensity, antenna efficiency, etc. can be achieved in a single monopole. Due to its wide range of selectivity in radiation pattern; this can meet the demands of wider bandwidth to get high data speed in communication systems. Moreover, this developed system provides an efficient and cost-effective solution for measuring the radiation pattern in far-field zone for any kind of antenna system.

Keywords: antenna radiation characteristics, dynamically reconfigurable, plasma antenna, plasma column, plasma striations, surface wave

Procedia PDF Downloads 119

Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

Procedia PDF Downloads 133

Authors: Mahadehe Hassan

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In most countries manufacturing, trading and distribution of gasoline and diesel fuels belongs to the most important sectors of national economy. For Bangladesh, a robust, well-functioning, secure and smartly managed national fuel distribution chain is an essential precondition for achieving Government top priorities in development and modernization of transportation infrastructure, protection of national environment and population health as well as, very importantly, securing due tax revenue for the State Budget. Bangladesh is a developing country with complex fuel supply network, high fuel taxes incidence and – till now - limited possibilities in application of modern, automated technologies for Government national fuel market control. Such environment allows dishonest physical and legal persons and organized criminals to build and profit from illegal fuel distribution schemes and fuel illicit trade. As a result, the market transparency and the country attractiveness for foreign investments, law-abiding economic operators, national consumers, State Budget and the Government ability to finance development projects, and the country at large suffer significantly. Research shows that over 50% of retail petrol stations in major agglomerations of Bangladesh sell adulterated fuels and/or cheat customers on the real volume of the fuel pumped into their vehicles. Other forms of detected fuel illicit trade practices include misdeclaration of fuel quantitative and qualitative parameters during internal transit and selling of non-declared and smuggled fuels. The aim of the study is to recommend the implementation of a National Fuel Distribution Integrity Program (FDIP) in Bangladesh to address and resolve fuel adulteration and illicit trade problems. The program should be customized according to the specific needs of the country and implemented in partnership with providers of advanced technologies. FDIP should enable and further enhance capacity of respective Bangladesh Government authorities in identification and elimination of all forms of fuel illicit trade swiftly and resolutely. FDIP high-technology, IT and automation systems and secure infrastructures should be aimed at the following areas (1) fuel adulteration, misdeclaration and non-declaration; (2) fuel quality and; (3) fuel volume manipulation at retail level. Furthermore, overall concept of FDIP delivery and its interaction with the reporting and management systems used by the Government shall be aligned with and support objectives of the Vision 2041 and Smart Bangladesh Government programs.

Keywords: fuel adulteration, octane, kerosene, diesel, petrol, pollution, carbon emissions

Procedia PDF Downloads 73

Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 189

Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

Procedia PDF Downloads 121

Authors: Heikki Valmu, Eero Kupila, Raisa Vartia

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A major curricular reform was implemented in Metropolia UAS in 2014. The teaching was to be based on larger course entities and collaborative pedagogy. The most thorough reform was conducted in the department of electrical engineering and automation technology. It has been already shown that the reform has been extremely successful with respect to student progression and drop-out rate. The improvement of the results has been much more significant in this department compared to the other engineering departments making only minor pedagogical changes. In the beginning of the spring term of 2017, a thorough student feedback project was conducted in the department. The study consisted of thirty questions about the implementation of the curriculum, the student workload and other matters related to student satisfaction. The reply rate was more than 40%. The students were divided to four different categories: first year students [cat.1] and students of all the three different majors [categories 2-4]. These categories were found valid since all the students have the same course structure in the first two semesters after which they may freely select the major. All staff members are divided into four teams respectively. The curriculum consists of consecutive 15 credit (ECTS) courses each taught by a group of teachers (3-5). There are to be no end exams and continuous assessment is to be employed. In 2014 the different teacher groups were encouraged to employ innovatively different assessment methods within the given specs. One of these methods has been since used in categories 1 and 2. These students have to complete a number of compulsory tasks each week to pass the course and the actual grade is defined by a smaller number of tests throughout the course. The tasks vary from homework assignments, reports and laboratory exercises to larger projects and the actual smaller tests are usually organized during the regular lecture hours. The teachers of the other two majors have been pedagogically more conservative. The student progression has been better in categories 1 and 2 compared to categories 3 and 4. One of the main goals of this survey was to analyze the reasons for the difference and the assessment methods in detail besides the general student satisfaction. The results show that in the categories following more strictly the specified assessment model much more versatile assessment methods are used and the basic spirit of the new pedagogy is followed. Also, the student satisfaction is significantly better in categories 1 and 2. It may be clearly stated that continuous assessment and teacher cooperation improve the learning outcomes, student progression as well as student satisfaction. Too much academic freedom seems to lead to worse results [cat 3 and 4]. A standardized assessment model is launched for all students in autumn 2017. This model is different from the one used so far in categories 1 and 2 allowing more flexibility to teacher groups, but it will force all the teacher groups to follow the general rules in order to improve the results and the student satisfaction further.

Keywords: continuous assessment, course integration, curricular reform, student feedback

Procedia PDF Downloads 203

Authors: Diom Loreen Ndum, Omarine Njimanted

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With increasing automation in clinical laboratories, the requirements for quality control materials have greatly increased in order to monitor daily performance. The constant use of commercial control material is not economically feasible for many developing countries because of non-availability or the high-cost of the materials. Therefore, preparation and use of in-house quality control serum will be a very cost-effective measure with respect to laboratory needs.The objective of this study was to determine the efficacy of in-house prepared pooled sera with respect to commercially acquired control sample for routine internal quality control at the Nkwen District Hospital Laboratory. This was an analytical study, serum was taken from leftover serum samples of 5 healthy adult blood donors at the blood bank of Nkwen District Hospital, which had been screened negative for human immunodeficiency virus (HIV), hepatitis C virus (HCV) and Hepatitis B antigens (HBsAg), and were pooled together in a sterile container. From the pooled sera, sixty aliquots of 150µL each were prepared. Forty aliquots of 150µL each of commercially acquired samples were prepared after reconstitution and stored in a deep freezer at − 20°C until it was required for analysis. This study started from the 9th June to 12th August 2022. Every day, alongside with commercial control sample, one aliquot of pooled sera was removed from the deep freezer and allowed to thaw before analyzed for the following parameters: blood urea, serum creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), potassium and sodium. After getting the first 20 values for each parameter of pooled sera, the mean, standard deviation and coefficient of variation were calculated, and a Levey-Jennings (L-J) chart established. The mean and standard deviation for commercially acquired control sample was provided by the manufacturer. The following results were observed; pooled sera had lesser standard deviation for creatinine, urea and AST than commercially acquired control samples. There was statistically significant difference (p<0.05) between the mean values of creatinine, urea and AST for in-house quality control when compared with commercial control. The coefficient of variation for the parameters for both commercial control and in-house control samples were less than 30%, which is an acceptable difference. The L-J charts revealed shifts and trends (warning signs), so troubleshooting and corrective measures were taken. In conclusion, in-house quality control sample prepared from pooled serum can be a good control sample for routine internal quality control.

Keywords: internal quality control, levey-jennings chart, pooled sera, shifts, trends, westgard rules

Procedia PDF Downloads 77

Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

Procedia PDF Downloads 56

Authors: L. M. H. Mustonen, S. A. Heikkilä

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The focus of the paper is to describe team teaching as a HAMK’s pedagogical method, and its impacts to the teachers work. Background: Traditionally it is thought that teaching is a job where one mostly works alone. More and more teachers feel that their work is getting more stressful. Solutions to these problems have been sought in Häme University of Applied sciences’ (From now on referred to as HAMK). HAMK has made a strategic change to move to the group oriented working of teachers. Instead of isolated study courses, there are now larger 15 credits study modules. Implementation: As examples of the method, two cases are presented: technical project module and summer studies module, which was integrated into the EU development project called Energy Efficiency with Precise Control. In autumn 2017, technical project will be implemented third time. There are at least three teachers involved in it and it is the first module of the new students. Main focus is to learn the basic skills of project working. From communicational viewpoint, they learn the basics of written and oral reporting and the basics of video reporting skills. According to our quality control system, the need for the development is evaluated in the end of the module. There are always some differences in each implementation but the basics are the same. The other case summer studies 2017 is new and part of a larger EU project. For the first time, we took a larger group of first to third year students from different study programmes to the summer studies. The students learned professional skills and also skills from different fields of study, international cooperation, and communication skills. Benefits and challenges: After three years, it is possible to consider what the changes mean in the everyday work of the teachers - and of course – what it means to students and the learning process. The perspective is HAMK’s electrical and automation study programme: At first, the change always means more work. The routines born after many years and the course material used for years may not be valid anymore. Teachers are teaching in modules simultaneously and often with some subjects overlapping. Finding the time to plan the modules together is often difficult. The essential benefit is that the learning outcomes have improved. This can be seen in the feedback given by both the teachers and the students. Conclusions: A new type of working environment is being born. A team of teachers designs a module that matches the objectives and ponders the answers to such questions as what are the knowledge-based targets of the module? Which pedagogical solutions will achieve the desired results? At what point do multiple teachers instruct the class together? How is the module evaluated? How can the module be developed further for the next execution? The team discusses openly and finds the solutions. Collegiate responsibility and support are always present. These are strengthening factors of the new communal university teaching culture. They are also strong sources of pleasure of work.

Keywords: pedagogical development, summer studies, team teaching, well-being at work

Procedia PDF Downloads 109

Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

Procedia PDF Downloads 69

Authors: Catariny C. Aleman, Flavio B. Campos, Matheus A. Caliman, Everardo C. Mantovani

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The seedling production stage is a critical point in the vegetable production system. Obtaining high-quality seedlings is a prerequisite for subsequent cropping to occur well and productivity optimization is required. The water management is an important step in agriculture production. The adequate water requirement in horticulture seedlings can provide higher quality and increase field production. The practice of irrigation is indispensable and requires a duly adjusted quality irrigation system, together with a specific water management plan to meet the water demand of the crop. Irrigation management in seedling management requires a great deal of specific information, especially when it involves the use of inputs such as hydrorentering polymers and automation technologies of the data acquisition and irrigation system. The experiment was conducted in a greenhouse at the Federal University of Viçosa, Viçosa - MG. Tomato seedlings (Lycopersicon esculentum Mill) were produced in plastic trays of 128 cells, suspended at 1.25 m from the ground. The seedlings were irrigated by 4 micro sprinklers of fixed jet 360º per tray, duly isolated by sideboards, following the methodology developed for this work. During Phase 1, in January / February 2017 (duration of 24 days), the cultivation coefficient (Kc) of seedlings cultured in the presence and absence of hydrogel was evaluated by weighing lysimeter. In Phase 2, September 2017 (duration of 25 days), the seedlings were submitted to 4 irrigation managements (Kc, timer, 0.50 ETo, and 1.00 ETo), in the presence and absence of hydrogel and then evaluated in relation to quality parameters. The microclimate inside the greenhouse was monitored with the use of air temperature, relative humidity and global radiation sensors connected to a microcontroller that performed hourly calculations of reference evapotranspiration by Penman-Monteith standard method FAO56 modified for the balance of long waves according to Walker, Aldrich, Short (1983), and conducted water balance and irrigation decision making for each experimental treatment. Kc of seedlings cultured on a substrate with hydrogel (1.55) was higher than Kc on a pure substrate (1.39). The use of the hydrogel was a differential for the production of earlier tomato seedlings, with higher final height, the larger diameter of the colon, greater accumulation of a dry mass of shoot, a larger area of crown projection and greater the rate of relative growth. The handling 1.00 ETo promoted higher relative growth rate.

Keywords: automatic system; efficiency of water use; precision irrigation, micro sprinkler.

Procedia PDF Downloads 116

Authors: Mona Shojaei

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The Sub-Atmospheric Vapor Pipeline (SAVP) introduces a distinct approach to seawater desalination with promising applications in both land and industrial sectors. SAVP systems exploit the temperature difference between a hot source and a cold environment to facilitate efficient vapor transfer, offering substantial benefits in diverse industrial and field applications. This approach incorporates dynamic boundary conditions, where the temperatures of hot and cold sources vary over time, particularly in natural and industrial environments. Such variations critically influence convection and diffusion processes, introducing challenges that require the refinement of the convection-diffusion equation and the derivation of temperature profiles along the pipeline through advanced engineering mathematics. This study formulates vapor temperature as a function of time and length using two mathematical approaches: Eigen functions and Green’s equation. Combining detailed theoretical modeling, mathematical simulations, and extensive field and industrial tests, this research underscores the SAVP system’s scalability for real-world applications. Results reveal a high degree of accuracy, highlighting SAVP’s significant potential for energy conservation and environmental sustainability. Furthermore, the integration of SAVP technology within smart and green building systems creates new opportunities for sustainable urban water management. By capturing and repurposing vapor for non-potable uses such as irrigation, greywater recycling, and ecosystem support in green spaces, SAVP aligns with the principles of smart and green buildings. Smart buildings emphasize efficient resource management, enhanced system control, and automation for optimal energy and water use, while green buildings prioritize environmental impact reduction and resource conservation. SAVP technology bridges both paradigms, enhancing water self-sufficiency and reducing reliance on external water supplies. The sustainable and energy-efficient properties of SAVP make it a vital component in resilient infrastructure development, addressing urban water scarcity while promoting eco-friendly living. This dual alignment with smart and green building goals positions SAVP as a transformative solution in the pursuit of sustainable urban resource management.

Keywords: sub-atmospheric vapor pipeline, seawater desalination, energy efficiency, vapor transfer dynamics, mathematical modeling, sustainable water solutions, smart buildings

Procedia PDF Downloads 12

Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

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Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

Procedia PDF Downloads 152

Authors: Marcel Heimar Ribeiro Utiyama, Fernanda Caveiro Correia, Dario Henrique Alliprandini

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The importance of the correct allocation of improvement programs is of growing interest in recent years. Due to their limited resources, companies must ensure that their financial resources are directed to the correct workstations in order to be the most effective and survive facing the strong competition. However, to our best knowledge, the literature about allocation of improvement programs does not analyze in depth this problem when the flow shop process has two capacity constrained resources. This is a research gap which is deeply studied in this work. The purpose of this work is to identify the best strategy to allocate improvement programs in a flow shop with two capacity constrained resources. Data were collected from a flow shop process with seven workstations in an industrial control and automation company, which process 13.690 units on average per month. The data were used to conduct a simulation with the System Dynamics-Factory Physics model. The main variables considered, due to their importance on lead time reduction, were the mean time between failures and the mean time to repair. The lead time reduction was the output measure of the simulations. Ten different strategies were created: (i) focused time to repair improvement, (ii) focused time between failures improvement, (iii) distributed time to repair improvement, (iv) distributed time between failures improvement, (v) focused time to repair and time between failures improvement, (vi) distributed time to repair and between failures improvement, (vii) hybrid time to repair improvement, (viii) hybrid time between failures improvements, (ix) time to repair improvement strategy towards the two capacity constrained resources, (x) time between failures improvement strategy towards the two capacity constrained resources. The ten strategies tested are variations of the three main strategies for improvement programs named focused, distributed and hybrid. Several comparisons among the effect of the ten strategies in lead time reduction were performed. The results indicated that for the flow shop analyzed, the focused strategies delivered the best results. When it is not possible to perform a large investment on the capacity constrained resources, companies should use hybrid approaches. An important contribution to the academy is the hybrid approach, which proposes a new way to direct the efforts of improvements. In addition, the study in a flow shop with two strong capacity constrained resources (more than 95% of utilization) is an important contribution to the literature. Another important contribution is the problem of allocation with two CCRs and the possibility of having floating capacity constrained resources. The results provided the best improvement strategies considering the different strategies of allocation of improvement programs and different positions of the capacity constrained resources. Finally, it is possible to state that both strategies, hybrid time to repair improvement and hybrid time between failures improvement, delivered best results compared to the respective distributed strategies. The main limitations of this study are mainly regarding the flow shop analyzed. Future work can further investigate different flow shop configurations like a varying number of workstations, different number of products or even different positions of the two capacity constrained resources.

Keywords: allocation of improvement programs, capacity constrained resource, hybrid strategy, lead time, mean time to repair, mean time between failures

Procedia PDF Downloads 122

Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

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Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

Procedia PDF Downloads 204

Authors: Eyosiyas Aga

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The development of information communication technology has transformed the paper-based mapping and land registration processes to a computerized and networked system. The computerization and networking of real property information system play a vital role in good governance and sustainable development of emerging countries through cost effective, easy and accessible service delivery for the customer. The efficient, transparent and sustainable real property system is becoming the basic infrastructure for the urban development thus improve the data management system and service delivery in the organizations. In Ethiopia, the real property administration is paper based as a result, it confronted problems of data management, illegal transactions, corruptions, and poor service delivery. In order to solve this problem and to facilitate real property market, the implementation of web-based real property updating system is crucial. A web-based real property updating is one of the automation (computerizations) methods to facilitate data sharing, reduce time and cost of the service delivery in real property administration system. In additions, it is useful for the integration of data onto different information systems and organizations. This system is designed by combining open source software which supported by open Geo-spatial consortium. The web-based system is mainly designed by using open source software with the help of open Geo-spatial Consortium. The Open Geo-spatial Consortium standards such as the Web Feature Service and Web Map Services are the most widely used standards to support and improves web-based real property updating. These features allow the integration of data from different sources, and it can be used to maintain consistency of data throughout transactions. The PostgreSQL and Geoserver are used to manage and connect a real property data to the flex viewer and user interface. The system is designed for both internal updating system (municipality); which is mainly updating of spatial and textual information, and the external system (customer) which focus on providing and interacting with the customer. This research assessed the potential of open source web applications and adopted this technology for real property updating system in Ethiopia through simple, cost effective and secured way. The system is designed by combining and customizing open source software to enhance the efficiency of the system in cost effective way. The existing workflow for real property updating is analyzed to identify the bottlenecks, and the new workflow is designed for the system. The requirement is identified through questionnaire and literature review, and the system is prototype for the study area. The research mainly aimed to integrate human resource with technology in designing of the system to reduce data inconsistency and security problems. In additions, the research reflects on the current situation of real property administration and contributions of effective data management system for efficient, transparent and sustainable urban development in Ethiopia.

Keywords: cadaster, real property, sustainable, transparency, web feature service, web map service

Procedia PDF Downloads 266

Authors: Rene Hellmuth

Abstract:

The requirements for the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Restrictions regarding new areas, shorter life cycles of product and production technology as well as a VUCA (volatility, uncertainty, complexity and ambiguity) world cause more frequently occurring rebuilding measures within a factory. Restructuring of factories is the most common planning case today. Restructuring is more common than new construction, revitalization and dismantling of factories. The increasing importance of restructuring processes shows that the ability to change was and is a promising concept for the reaction of companies to permanently changing conditions. The factory building is the basis for most changes within a factory. If an adaptation of a construction project (factory) is necessary, the inventory documents must be checked and often time-consuming planning of the adaptation must take place to define the relevant components to be adapted, in order to be able to finally evaluate them. The different requirements of the planning participants from the disciplines of factory planning (production planner, logistics planner, automation planner) and industrial construction planning (architect, civil engineer) come together during reconstruction and must be structured. This raises the research question: Which requirements do the disciplines involved in the reconstruction planning place on a digital factory model? A subordinate research question is: How can model-based decision support be provided for a more efficient design of the conversion within a factory? Because of the high adaptation rate of factories and its building described above, a methodology for rescheduling factories based on the requirements engineering method from software development is conceived and designed for practical application in factory restructuring projects. The explorative research procedure according to Kubicek is applied. Explorative research is suitable if the practical usability of the research results has priority. Furthermore, it will be shown how to best use a digital factory model in practice. The focus will be on mobile applications to meet the needs of factory planners on site. An augmented reality (AR) application will be designed and created to provide decision support for planning variants. The aim is to contribute to a shortening of the planning process and model-based decision support for more efficient change management. This requires the application of a methodology that reduces the deficits of the existing approaches. The time and cost expenditure are represented in the AR tablet solution based on a building information model (BIM). Overall, the requirements of those involved in the planning process for a digital factory model in the case of restructuring within a factory are thus first determined in a structured manner. The results are then applied and transferred to a construction site solution based on augmented reality.

Keywords: augmented reality, digital factory model, factory planning, restructuring

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