Search results for: ambient computing

Authors: Leila Goosen

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The research problem reported on in this paper relates to improving success in Computer Science and Information Technology subjects where students are learning applications, especially when teaching occurs in a distance education context. An investigation was launched in order to address students’ struggles with applications, and improve their assessment in such subjects. Some of the main arguments presented centre on formulating and situating significant concepts within an appropriate conceptual framework. The paper explores the experiences and perceptions of computing instructors, teaching assistants, students and higher education institutions on how they are empowered by using technologies such as myITLab. They also share how they are working with the available features to successfully teach applications to their students. The data collection methodology used is then described. The paper includes discussions on how myITLab empowers instructors, teaching assistants, students and higher education institutions. Conclusions are presented on the way in which this paper could make an original and significant contribution to the promotion and development of knowledge in fields related to successfully teaching applications for student learning, including in a distance education context. The paper thus provides a forum for practitioners to highlight and discuss insights and successes, as well as identify new technical and organisational challenges, lessons and concerns regarding practical activities related to myITLab as an implementation instance of distance education technologies.

Keywords: distance, education, myITLab, technologies

Procedia PDF Downloads 356

Authors: Meltem Kürtüncü, Işın Alkan

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Objective: This study was carried out with an experimental design in order to determine whether the lullaby, which was listened from mother’s voice and a stranger’s voice to the babies born at term and hospitalized in neonatal intensive care unit, had an effect on stress and relaxation symptoms of the infants. Method: Data from the study were obtained from 90 newborn babies who were hospitalized in Neonatal Intensive Care Unit of Zonguldak Maternity And Children Hospital between September 2015-January 2016 and who met the eligibility criteria. Lullaby concert was performed by choosing one of the suitable care hours. Stress and relaxation symptoms were recorded by the researcher on “Newborn response follow-up form” at pre-care and post-care. Results: After lullaby concert when stress symptoms compared to infants in the experimental and control groups before the care was not detected statistically significant difference between crying, contraction, facial grimacing, flushing, cyanosis and the rates of increase in temperature. After care, crying, contractions, facial grimacing, flushing, and restlessness revealed a statistically significant difference between the groups, but as the cyanosis and temperature increased stress responses did not result in a significant difference between the groups. In the control group babies the crying, contraction, facial grimacing, flushing, and restlessness behaviors rates were found to be significantly higher than experimental group babies. After lullaby concert when relaxation symptoms compared to infants in the experimental and control groups before the care, eye contact rates who listen to lullaby from mother’s voice was found to be significantly higher than infants who listen to lullaby from stranger’s voice and infants in the control group. After care as eye contact, smiling, sucking/searching, yawning, non-crying and sleep behaviors relaxation symptoms revealed statistically significant results. In the control group, these behaviors were found statistically lower degree than the experimental groups. Conclusion: Lullaby concerts as masking the ambient noise, reducing the stress symptoms and increasing the relaxation symptoms, and also for soothing and stimulant affects, due to ease the transition to the sleep state should be preferred in the neonatal intensive care units.

Keywords: lullaby, mother voice, relaxation, stress

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Authors: Hussein Moselhy, Islam Salam

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There have been some challenges and problems which hinder the implementation of the e-marketing systems such as the high cost of information systems infrastructure and maintenance as well as their unavailability within the institution. Also, there is no system which supports all programming languages and different platforms. Another problem is the lack of integration between these systems on one hand and the operating systems and different web browsers on the other hand. No system for customer relationship management is established which recognizes their desires and puts them in consideration while performing e-marketing functions is available. Therefore, the service-oriented architecture emerged as one of the most important techniques and methodologies to build systems that integrate with various operating systems and different platforms and other technologies. This technology allows realizing the data exchange among different applications. The service-oriented architecture represents distributed computing concepts to demonstrate its success in achieving the requirements of systems through web services. It also reflects the appropriate design for the services to use different web services in supporting the requirements of business processes and software users. In a service-oriented environment, web services are deployed on the web in the form of independent services to be accessed without knowledge of the nature of the programs and systems with in. This Paper presents a proposal for a new model which contributes to the application of methods and means of e-marketing with the integration of marketing mix elements to improve marketing efficiency (E-MSOA). And apply it in the educational city of one of the Egyptian sector.

Keywords: service-oriented architecture, electronic commerce, virtual retailing, unified modeling language

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Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

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Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

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The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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Knowledge management is essential ingredient of successful coordination in globally distributed software engineering. Various frameworks, KMSs, and tools have been proposed to foster coordination and communication between virtual teams but practical implementation of these solutions has not been found. Organizations have to face challenges to implement knowledge management system. For this purpose at first, a literature review is arranged to investigate about challenges that restrict organizations to implement KMS and then by taking in account these challenges a problem of need of integrated solution in the form of standardized KMS that can easily store tacit and explicit knowledge, has traced down to facilitate coordination and collaboration among virtual teams. Literature review has been already shown that knowledge is a complex perception with profound meanings, and one of the most important resources that contributes to the competitive advantage of an organization. In order to meet the different challenges caused by not properly managing knowledge related to projects among virtual teams in GSE, we suggest making use of the cloud computing model. In this research a distributed architecture to support KM storage is proposed called conceptual framework of KM as a service in cloud. Framework presented is enhanced and conceptual framework of KM is embedded into that framework to store projects related knowledge for future use.

Keywords: management, Globsl software development, global software engineering

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Authors: Ruchi Makani, B. V. R. Reddy

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Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

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Authors: Bernd Sauer, Michel Werner, Stefan Emrich, Michael Kopnarski, Oliver Koch

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Friction reduction is an important aspect in the context of sustainability and energy transition. Rolling bearings are therefore used in many applications in which components move relative to each other. Conventionally lubricated rolling bearings are used in a wide range of applications, but are not suitable under certain conditions. Conventional lubricants such as grease or oil cannot be used at very high or very low temperatures. In addition, these lubricants evaporate at very low ambient pressure, e.g. in a high vacuum environment, making the use of solid lubricated bearings unavoidable. With the use of solid-lubricated bearings, predicting the service life becomes more complex. While the end of the service life of bearings with conventional lubrication is mainly caused by the failure of the bearing components due to material fatigue, solid-lubricated bearings fail at the moment when the lubrication layer is worn and the rolling elements come into direct contact with the raceway during operation. In order to extend the service life of these bearings beyond the service life of the initial coating, the use of transfer lubrication is recommended, in which pockets or sacrificial cages are used in which the balls run and can thus absorb the lubricant, which is then available for lubrication in tribological contact. This contribution presents the results of wear and service life tests on solid-lubricated rolling bearings with sacrificial cage pockets. The cage of the bearing consists of a polyimide (PI) matrix with 15% molybdenum disulfide (MoS2) and serves as a lubrication depot alongside the silver-coated balls. The bearings are tested under high vacuum (pE < 10-2 Pa) at a temperature of 300 °C on a four-bearing test rig. First, investigations of the bearing system within the bearing service life are presented and the torque curve, the wear mass and surface analyses are discussed. With regard to wear, it can be seen that the bearing rings tend to increase in mass over the service life of the bearing, while the balls and the cage tend to lose mass. With regard to the elementary surface properties, the surfaces of the bearing rings and balls are examined in terms of the mass of the elements on them. Furthermore, service life investigations with different material pairings are presented, whereby the focus here is on the service life achieved in addition to the torque curve, wear development and surface analysis. It was shown that MoS2 in the cage leads to a longer service life, while a silver (Ag) coating on the balls has no positive influence on the service life and even appears to reduce it in combination with MoS2.

Keywords: ball bearings, molybdenum disulfide, solid lubricated bearings, solid lubrication mechanisms

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Authors: Kimberly J. Cribbs, Ryan M. Lefers, TorOve Leiknes, Noreddine Ghaffour

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In Gulf Cooperation Council (GCC) countries, domestic agriculture is hindered by a lack of freshwater, poor soil quality, and ambient temperatures unsuitable for cultivation resulting in a heavy reliance on imported food. Attempts to minimize the risk of food insecurity by growing crops domestically creates a significant demand on limited freshwater resources in this region. Cultivating food in a greenhouse allows some of these challenges, such as poor soil quality and temperatures unsuitable for cultivation, to be overcome. One of the most common methods for greenhouse cooling is evaporative cooling. This method cools the air by the evaporation of water and requires a large amount of water relative to that needed for plant growth and air with a low relative humidity. Considering that much of the population in GCC countries live within 100 km of a coast and that sea water can be utilized for evaporative cooling, coastal agriculture could reduce the risk of food insecurity and water demand. Unfortunately, coastal regions tend to experience both high temperatures and high relative humidity causing evaporative cooling by itself to be inadequate. Therefore, dehumidification is needed prior to utilizing evaporative cooling. Utilizing a liquid desiccant for air dehumidification is promising, but the desiccant regeneration to retain its dehumidification potential remains a significant obstacle for the adoption of this technology. This project studied the regeneration of a magnesium chloride (MgCl₂) desiccant solution from 20wt% to 30wt% by direct contact membrane distillation (DCMD) and explored the possibility of using the recovered water for irrigation. Two 0.2 µm hydrophobic PTFE membranes were tested at feed temperatures of 80, 70, and 60°C and with a permeate temperature of 20°C. It was observed that the permeate flux increases as the difference between the feed and coolant temperature increases and also as the feed concentration decreases. At 21wt% the permeate flux was 34,17, and 14 L m⁻² h⁻¹ for feed temperatures of 80, 70, and 60°C, respectively. Salt rejection decreased overtime; however, it remained greater than 99.9% over an experimental time span of 10 hours. The results show that DCMD can successfully regenerate the magnesium chloride desiccant solution.

Keywords: agriculture, direct contact membrane distillation, GCC countries, liquid desiccant, water recovery

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Authors: Ajay Mandal, Jitendar Kumar Tiwari, N. Sathish, A. K. Srivastava

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A fundamental investigation is performed on the development of graphene (Gr) reinforced stainless steel 316L (SS 316L) metal matrix composite via selective laser melting (SLM) in order to improve specific strength and wear resistance property of SS 316L. Firstly, SS 316L powder and graphene were mixed in a fixed ratio using low energy planetary ball milling. The milled powder is then subjected to the SLM process to fabricate composite samples at a laser power of 320 W and exposure time of 100 µs. The prepared composite was mechanically tested (hardness and tensile test) at ambient temperature, and obtained results indicate that the properties of the composite increased significantly with the addition of 0.2 wt. % Gr. Increment of about 25% (from 194 to 242 HV) and 70% (from 502 to 850 MPa) is obtained in hardness and yield strength of composite, respectively. Raman mapping and XRD were performed to see the distribution of Gr in the matrix and its effect on the formation of carbide, respectively. Results of Raman mapping show the uniform distribution of graphene inside the matrix. Electron back scatter diffraction (EBSD) map of the prepared composite was analyzed under FESEM in order to understand the microstructure and grain orientation. Due to thermal gradient, elongated grains were observed along the building direction, and grains get finer with the addition of Gr. Most of the mechanical components are subjected to several types of wear conditions. Therefore, it is very necessary to improve the wear property of the component, and hence apart from strength and hardness, a tribological property of composite was also measured under dry sliding condition. Solid lubrication property of Gr plays an important role during the sliding process due to which the wear rate of composite reduces up to 58%. Also, the surface roughness of worn surface reduces up to 70% as measured by 3D surface profilometry. Finally, it can be concluded that SLM is an efficient method of fabricating cutting edge metal matrix nano-composite having Gr like reinforcement, which was very difficult to fabricate through conventional manufacturing techniques. Prepared composite has superior mechanical and tribological properties and can be used for a wide variety of engineering applications. However, due to the unavailability of a considerable amount of literature in a similar domain, more experimental works need to perform, such as thermal property analysis, and is a part of ongoing study.

Keywords: selective laser melting, graphene, composite, mechanical property, tribological property

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Suraj D. Khadka, Priyantha W. Jayawickrama

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In search of a sustainable construction material, geopolymer has been investigated for past decades to evaluate its advantage over conventional products. Synthesis of geopolymer requires a source of aluminosilicate mixed with sodium hydroxide and sodium silicate at different proportions to maintain a Si/Al molar ratio of 1-3 and Na/Al molar ratio of unity. A comprehensive geopolymer study was performed with Metakaolin and Class C Fly ash as primary aluminosilicate sources. Synthesized geopolymer was analyzed for time-dependent viscosity, setting period and strength at varying initial moisture content, curing temperature and humidity. Different concentration of Ca(OH)₂ and CaSO₄.2H₂O were added to vary the amount of calcium contained in synthesized geopolymer. Influence of calcium content in unconfined compressive strength behavior of geopolymer were analyzed. Finally, Scanning Electron Microscopy-Energy Dispersive Spectroscopy (SEM-EDS) was performed to investigate the hardened product. It was observed that fly ash based geopolymer had shortened setting time and faster increase in viscosity as compared to geopolymer synthesized from metakaolin. This was primarily attributed to higher calcium content resulting in formation of calcium silicate hydrates (CSH). SEM-EDS was performed to verify the presence of CSH phases. Spectral analysis of geopolymer prepared by addition of Ca(OH)₂ and CaSO₄.2H₂O indicated higher CSH phases at higher concentration. It was observed that lower concentration of added calcium favored strength gain in geopolymer. However, at higher calcium concentration, decrease in strength was observed. Strength variation was also observed with humidity at initial curing condition. At 100% humidity, geopolymer with added calcium presented higher strength compared to samples cured at ambient humidity condition (40%). Reduction in strength in these samples at lower humidity was primarily attributed to reduction in moisture content in specimen due to the formation of CSH phases and loss of moisture through evaporation. For low calcium content geopolymers, with increase in temperature, gain in strength was observed with maximum strength observed at 200 ˚C. However, samples with higher calcium content demonstrated severe cracking resulting in low strength at elevated temperatures.

Keywords: calcium silicate hydrates, geopolymer, humidity, Scanning Electron Microscopy-Energy Dispersive Spectroscopy, unconfined compressive strength

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

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Authors: Abdul Hakim Chikho

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Most international codes allow the use of an equivalent lateral load method for designing practical buildings to withstand earthquake actions. This method requires calculating an approximation to the fundamental mode period of vibrations of these buildings. Several empirical equations have been suggested to calculate approximations to the fundamental periods of different types of structures. Most of these equations are knowing to provide an only crude approximation to the required fundamental periods and repeating the calculation utilizing a more accurate formula is usually required. In this paper, a new formula to calculate a satisfactory approximation of the fundamental period of a practical building is proposed. This formula takes into account the mass and the stiffness of the building therefore, it is more logical than the conventional empirical equations. In order to verify the accuracy of the proposed formula, several examples have been solved. In these examples, calculating the fundamental mode periods of several farmed buildings utilizing the proposed formula and the conventional empirical equations has been accomplished. Comparing the obtained results with those obtained from a dynamic computer has shown that the proposed formula provides a more accurate estimation of the fundamental periods of practical buildings. Since the proposed method is still simple to use and requires only a minimum computing effort, it is believed to be ideally suited for design purposes.

Keywords: earthquake, fundamental mode period, design, building

Procedia PDF Downloads 278

Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

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Authors: Armando Cartenì

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Within the design of sustainable transportation engineering, the problem of reducing particulate matter (PM) concentrations in railways metro system was not much discussed. It is well known that PM levels in railways metro system are mainly produced by mechanical friction at the rail-wheel-brake interactions and by the PM re-suspension caused by the turbulence generated by the train passage, which causes dangerous problems for passenger health. Starting from these considerations, the aim of this research was twofold: i) to investigate the particulate matter concentrations in a ‘traditional’ railways metro system; ii) to investigate the particulate matter concentrations of a ‘high quality’ metro system equipped with design devices useful for reducing PM concentrations: platform screen doors, rubber-tyred and an advanced ventilation system. Two measurement surveys were performed: one in the ‘traditional’ metro system of Naples (Italy) and onother in the ‘high quality’ rubber-tyred metro system of Turin (Italy). Experimental results regarding the ‘traditional’ metro system of Naples, show that the average PM10 concentrations measured in the underground station platforms are very high and range between 172 and 262 µg/m3 whilst the average PM2,5 concentrations range between 45 and 60 µg/m3, with dangerous problems for passenger health. By contrast the measurements results regarding the ‘high quality’ metro system of Turin show that: i) the average PM10 (PM2.5) concentrations measured in the underground station platform is 22.7 µg/m3 (16.0 µg/m3) with a standard deviation of 9.6 µg/m3 (7.6 µg/m3); ii) the indoor concentrations (both for PM10 and for PM2.5) are statistically lower from those measured in outdoors (with a ratio equal to 0.9-0.8), meaning that the indoor air quality is greater than those in urban ambient; iii) that PM concentrations in underground stations are correlated to the trains passage; iv) the inside trains concentrations (both for PM10 and for PM2.5) are statistically lower from those measured at station platform (with a ratio equal to 0.7-0.8), meaning that inside trains the use of air conditioning system could promote a greater circulation that clean the air. The comparison among the two case studies allow to conclude that the metro system designed with PM reduction devices allow to reduce PM concentration up to 11 times against a ‘traditional’ one. From these results, it is possible to conclude that PM concentrations measured in a ‘high quality’ metro system are significantly lower than the ones measured in a ‘traditional’ railway metro systems. This result allows possessing the bases for the design of useful devices for retrofitting metro systems all around the world.

Keywords: air quality, pollutant emission, quality in public transport, underground railway, external cost reduction, transportation planning

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Authors: Joni Asitashvili, Eka Chabashvili, Maya Virsaladze, Alexander Chokhonelidze

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Studying the soundscape is a major challenge in many countries of the civilized world today. The sound environment and music itself are part of the Earth's ecosystem. Therefore, researching its positive or negative impact is important for a clean and healthy environment. The acoustics of nature gave people many musical ideas, and people enriched musical features and performance skills with the ability to imitate the surrounding sound. For example, a population surrounded by mountains invented the technique of antiphonal singing, which mimics the effect of an echo. Canadian composer Raymond Murray Schafer viewed the world as a kind of musical instrument with ever-renewing tuning. He coined the term "Soundscape" as a name of a natural environmental sound, including the sound field of the Earth. It can be said that from which the “music of nature” is constructed. In the 21st century, a new field–Ecomusicology–has emerged in the field of musical art to study the sound ecosystem and various issues related to it. Ecomusicology considers the interconnections between music, culture, and nature–According to the Aaron Allen. Eco-music is a field of ecomusicology concerning with the depiction and realization of practical processes using modern composition techniques. Finding an artificial sound source (instrumental or electronic) for the piece that will blend into the soundscape of Sound Oases. Creating a composition, which sounds in harmony with the vibrations of human, nature, environment, and micro- macrocosm as a whole; Currently, we are exploring the ambient sound of the Georgian urban and suburban environment to discover “Sound Oases" and compose Eco-music works. We called “Sound Oases" an environment with a specific sound of the ecosystem to use in the musical piece as an instrument. The most interesting examples of Eco-music are the round dances, which were already created in the BC era. In round dances people would feel the united energy. This urge to get united revealed itself in our age too, manifesting itself in a variety of social media. The virtual world, however, is not enough for a healthy interaction; we created plan of “contemporary round dance” in sound oasis, found during expedition in Georgian caves, where people interacted with cave's soundscape and eco-music, they feel each other sharing energy and listen to earth sound. This project could be considered a contemporary round dance, a long improvisation, particular type of art therapy, where everyone can participate in an artistic process. We would like to present research result of our eco-music experimental performance.

Keywords: eco-music, environment, sound, oasis

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Authors: Lukasz Grzegorz Broda, Taiwo Oseni, Andrew Stranieri, Rodrigo Marino, Ronelle Welton, Mark Yates

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The oral health of residents in aged care centres in Australia is poor, contributing to infections, hospital admissions, and increased suffering. Although the use of electric toothbrushes has been deployed in many centres, smartbrushes that record and transmit information about brushing patterns and duration are not routinely deployed. Yet, the use of smartbrushes for aged care residents promises better oral care. Thus, a study aimed at investigating the appropriateness and suitability of a smartbrush for aged care residents is currently underway. Due to the peculiarity of the aged care setting, the incorporation of smartbrushes into residents’ care does require careful planning and design considerations. This paper describes an initial design process undertaken through the use of an actor to understand the important elements to be incorporated whilst installing a smartbrush for use in aged care settings. The design covers the configuration settings of the brush and app, including ergonomic factors related to brush and smartphone placement. A design science approach led to an installation re-design and a revised protocol for the planned study, the ultimate aim being to design installations to enhance perceived usefulness, ease of use, and attitudes towards the incorporation of smartbrushes for improving oral health care for aged care residents.

Keywords: smartbrush, applied computing, life and medical sciences, health informatics

Procedia PDF Downloads 162

Authors: Ritula Thakur, Babankumar S. Bansod, Puneet Mehta, S. Chatterji

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Moisture plays an important role in storage, harvesting and processing of food grains and related agricultural products. It is an important characteristic of most agricultural products for maintenance of quality. Accurate knowledge of the moisture content can be of significant value in maintaining quality and preventing contamination of cereal grains. The present work reports the design and development of microcontroller based low cost non-destructive moisture meter, which uses complex impedance measurement method for moisture measurement of wheat using parallel plate capacitor arrangement. Moisture can conveniently be sensed by measuring the complex impedance using a small parallel-plate capacitor sensor filled with the kernels in-between the two plates of sensor, exciting the sensor at 30 KHz and 100 KHz frequencies. The effects of density and temperature variations were compensated by providing suitable compensations in the developed algorithm. The results were compared with standard dry oven technique and the developed method was found to be highly accurate with less than 1% error. The developed moisture meter is low cost, highly accurate, non-destructible method for determining the moisture of grains utilizing the fast computing capabilities of microcontroller.

Keywords: complex impedance, moisture content, electrical properties, safety of food

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

Procedia PDF Downloads 123

Authors: Nelson Ponce Jr., Jonas R. Gazoli, Alessandro Sete, Roberto M. G. Velásquez, Valério L. Borges, Moacir A. S. de Andrade

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The search for increased efficiency in generation systems has been of great importance in recent years to reduce the impact of greenhouse gas emissions and global warming. For clean energy sources, such as the generation systems that use concentrated solar power technology, this efficiency improvement impacts a lower investment per kW, improving the project’s viability. For the specific case of parabolic trough solar concentrators, their performance is strongly linked to their geometric precision of assembly and the individual efficiencies of their main components, such as parabolic mirrors and receiver tubes. Thus, for accurate efficiency analysis, it should be conducted empirically, looking for mounting and operating conditions like those observed in the field. The Brazilian power generation and distribution company Eletrobras Furnas, through the R&D program of the National Agency of Electrical Energy, has developed a plant for testing parabolic trough concentrators located in Aparecida de Goiânia, in the state of Goiás, Brazil. The main objective of this test plant is the characterization of the prototype concentrator that is being developed by the company itself in partnership with Eudora Energia, seeking to optimize it to obtain the same or better efficiency than the concentrators of this type already known commercially. This test plant is a closed pipe system where a pump circulates a heat transfer fluid, also calledHTF, in the concentrator that is being characterized. A flow meter and two temperature transmitters, installed at the inlet and outlet of the concentrator, record the parameters necessary to know the power absorbed by the system and then calculate its efficiency based on the direct solar irradiation available during the test period. After the HTF gains heat in the concentrator, it flows through heat exchangers that allow the acquired energy to be dissipated into the ambient. The goal is to keep the concentrator inlet temperature constant throughout the desired test period. The developed plant performs the tests in an autonomous way, where the operator must enter the HTF flow rate in the control system, the desired concentrator inlet temperature, and the test time. This paper presents the methodology employed for design and operation, as well as the instrumentation needed for the development of a parabolic trough test plant, being a guideline for standardization facilities.

Keywords: parabolic trough, concentrated solar power, CSP, solar power, test plant, energy efficiency, performance characterization, renewable energy

Procedia PDF Downloads 112

Authors: Dong Zhao

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Abstract—Extensive research on obtaining applicable room temperature superconductors meets the major barrier, and the record Tc of 135 K achieved via cuprate has been idling for decades. Even though, the accomplishment of higher Tc than the cuprate was made through pressurizing certain compounds composed of light elements, such as for the LaH10 and for the metallic hydrogen. Room temperature superconductivity under ambient pressure is still the preferred approach and is believed to be the ultimate solution for many applications. While racing to find the breakthrough method to achieve this room temperature Tc milestone in superconducting research, a report stated a discovery of a possible high-temperature superconductor, i.e., the thorium sulfide ThS. Apparently, ThS’s Tc can be at room temperature or even higher. This is because ThS revealed an unusual property of the ‘coexistence of high electrical conductivity and diamagnetism’. Noticed that this property of coexistence of high electrical conductivity and diamagnetism is in line with superconductors, meaning ThS is also at its superconducting state. Surprisingly, ThS owns the property of superconductivity at least at room temperature and under atmosphere pressure. Further study of the ThS’s electrical and magnetic properties in comparison with thorium di-iodide ThI2 concluded its molecular configuration as [Th4+(e-)2]S. This means the ThS’s cation is composed of a [Th4+(e-)2]2+ cation core. It is noticed that this cation core is built by an oxidation state +4 of thorium atom plus an electron pair on this thorium atom that resulted in an oxidation state +2 of this [Th4+(e-)2]2+ cation core. This special construction of [Th4+(e-)2]2+ cation core may lead to the ThS’s room temperature superconductivity because of this characteristic electron lone pair residing on the thorium atom. Since the study of thorium chemistry was carried out in the period of before 1970s. the exploration about ThS’s possible room temperature superconductivity would require resynthesizing ThS. This re-preparation of ThS will provide the sample and enable professionals to verify the ThS’s room temperature superconductivity. Regrettably, the current regulation prevents almost everyone from getting access to thorium metal or thorium compounds due to the radioactive nature of thorium-232 (Th-232), even though the radioactive level of Th-232 is extremely low with its half-life of 14.05 billion years. Consequently, further confirmation of ThS’s high-temperature superconductivity through experiments will be impossible unless the use of corresponding thorium metal and related thorium compounds can be deregulated. This deregulation would allow researchers to obtain the necessary starting materials for the study of ThS. Hopefully, the confirmation of ThS’s room temperature superconductivity can not only establish a method to obtain applicable superconductors but also to pave the way for fully understanding the mechanism of superconductivity.

Keywords: co-existence of high electrical conductivity and diamagnetism, electron pairing and electron lone pair, room temperature superconductivity, the special molecular configuration of thorium sulfide ThS

Procedia PDF Downloads 42

Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

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This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

Procedia PDF Downloads 143

Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

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It has been over 200 years since margarine was discovered and manufactured using liquid oil, liquified hardstock oils and other oil phase & aqueous phase ingredients. Henry W. Bradley first used vegetable oils in liquid state and around 1871, since then; spreads have been traditionally manufactured using liquified oils. The main objective of this study was to develop a process method to produce spreads using spray dried hardstock fat powders as a structing fats in place of current liquid structuring fats. A high shear mixing system was used to condition the fat phase and the aqueous phase was prepared separately. Using a single scraped surface heat exchanger and pin stirrer, margarine was produced. The process method was developed for to produce spreads with 40%, 50% and 60% fat . The developed method was divided into three steps. In the first step, fat powders were conditioned by melting and dissolving them into liquid oils. The liquified portion of the oils were at 65 °C, whilst the spray dried fat powder was at 25 °C. The two were mixed using a mixing vessel at 900 rpm for 4 minutes. The rest of the ingredients i.e., lecithin, colorant, vitamins & flavours were added at ambient conditions to complete the fat/ oil phase. The water phase was prepared separately by mixing salt, water, preservative, acidifier in the mixing tank. Milk was also separately prepared by pasteurizing it at 79°C prior to feeding it into the aqueous phase. All the water phase contents were chilled to 8 °C. The oil phase and water phase were mixed in a tank, then fed into a single scraped surface heat exchanger. After the scraped surface heat exchanger, the emulsion was fed in a pin stirrer to work the formed crystals and produce margarine. The margarine produced using the developed process had fat levels of 40%, 50% and 60%. The margarine passed all the qualitative, stability, and taste assessments. The scores were 6/10, 7/10 & 7.5/10 for the 40%, 50% & 60% fat spreads, respectively. The success of the trials brought about differentiated knowledge on how to manufacture spreads using non micronized spray dried fat powders as hardstock. Manufacturers do not need to store structuring fats at 80-90°C and even high in winter, instead, they can adapt their processes to use fat powders which need to be stored at 25 °C. The developed process method used one scrape surface heat exchanger instead of the four to five currently used in votator based plants. The use of a single scraped surface heat exchanger translated to about 61% energy savings i.e., 23 kW per ton of product. Furthermore, it was found that the energy saved by implementing separate pasteurization was calculated to be 6.5 kW per ton of product produced.

Keywords: margarine emulsion, votator technology, margarine processing, scraped sur, fat powders

Procedia PDF Downloads 85

Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

Procedia PDF Downloads 59

Authors: E. Vlachopapadopoulou, E. Dikaiakou, E. Anagnostou, I. Panagiotopoulos, E. Kaloumenou, M. Kafetzi, A. Fotinou, S. Michalacos

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Aim: To investigate the relation and impact of Body Mass Index (BMI), Waist Circumference (WC) and Body Fat Weight (BFW) on insulin resistance (MATSUDA INDEX < 2.5) in children and adolescents. Methods: Data from 95 overweight and obese children (47 boys and 48 girls) with mean age 10.7 ± 2.2 years were analyzed. ROC analysis was used to investigate the predictive ability of BMI, WC and BFW for insulin resistance and find the optimal cut-offs. The overall performance of the ROC analysis was quantified by computing area under the curve (AUC). Results: ROC curve analysis indicated that the optimal-cut off of WC for the prediction of insulin resistance was 97 cm with sensitivity equal to 75% and specificity equal to 73.1%. AUC was 0.78 (95% CI: 0.63-0.92, p=0.001). The sensitivity and specificity of obesity for the discrimination of participants with insulin resistance from those without insulin resistance were equal to 58.3% and 75%, respectively (AUC=0.67). BFW had a borderline predictive ability for insulin resistance (AUC=0.58, 95% CI: 0.43-0.74, p=0.101). The predictive ability of WC was equivalent with the correspondence predictive ability of BMI (p=0.891). Obese subjects had 4.2 times greater odds for having insulin resistance (95% CI: 1.71-10.30, p < 0.001), while subjects with WC more than 97 had 8.1 times greater odds for having insulin resistance (95% CI: 2.14-30.86, p=0.002). Conclusion: BMI and WC are important clinical factors that have significant clinical relation with insulin resistance in children and adolescents. The cut off of 97 cm for WC can identify children with greater likelihood for insulin resistance.

Keywords: body fat weight, body mass index, insulin resistance, obese children, waist circumference

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Authors: Rahul Paul, Kedar Nath Das

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The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.

Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques

Procedia PDF Downloads 69