Search results for: physiological sensors

Authors: Corbel Camille, Le Cerf Flora, Capriz Françoise, Vaillant-Ciszewicz Anne-Julie, Breaud Jean, Guerin Olivier, Corveleyn Xavier

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Background: The medical environment can generate stressful and anxiety-provoking situations for patients, particularly during painful care procedures for the older population. These stressful environments have deleterious effects on the quality of care and can even put the patient at risk and set the care team up for failure. The search for a solution is, therefore, imperative. The development of new technologies, such as virtual reality (VR), seems to be an answer to this problem. Objectives: The objective of this study is to compare the effects of virtual reality on pain and anxiety when caring for older hospitalized people with the effects of usual care. More precisely, different individual factors (age, cognitive level, individual preferences, etc.) and different virtual reality universes (personalized or non-personalized) are studied to understand the role of these factors in reducing pain and anxiety during care procedures. The aim of this study is to improve the quality of life of patients and caregivers in their work environment. Method: This mono-centered, randomized, controlled study was conducted from September 2023 to September 2024 on 120 participants recruited from the geriatric departments of the Cimiez Hospital, Nice, France. Participants are randomized into three groups: a control group, a personalized VR group and a non-personalized VR group. Each participant is followed during a painful care session. Data are collected before, during and after the care, using measures of pain (Algoplus and numerical scale) and anxiety (Hospital anxiety scale and numerical scale). Physiological assessments with an oximeter are also performed to collect both heart and respiratory rate measurements. The implementation of the care will be assessed among healthcare providers to evaluate its effects on the difficulty and fatigue associated with the care. Additionally, a questionnaire (System Usability Scale) will be administered at the conclusion of the study to determine the willingness of healthcare providers to integrate VR into their daily care practices. Result: The preliminary results indicate significant effects on anxiety (p=.001) and pain (p=<.001) following the VR intervention during care, as compared to the control group. Conclusion: The preliminary results suggest that VRI appears to be a suitable and effective method for reducing anxiety and pain among older hospitalized individuals compared with standard care. Finally, the experiences of healthcare professionals involved will also be considered to assess the impact of these interventions on working conditions and patient support.

Keywords: anxiety, care, pain, older adults, virtual reality

Procedia PDF Downloads 63

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Xiaoqian Zhang, Ping Zou, Pengcheng Li

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Salt stress is one of the most serious abiotic stresses, and it can lead to the reduction of agricultural productivity. High salt concentration makes it more difficult for roots to absorb water and disturbs the homeostasis of cellular ions resulting in osmotic stress, ion toxicity and generation of reactive oxygen species (ROS). Compared with the normal physiological conditions, salt stress could inhibit the photosynthesis, break metabolic balance and damage cellular structures, and ultimately results in the reduction of crop yield. Therefore it is vital to develop practical methods for improving the salt tolerance of plants. Chitooligomers (COS) is partially depolymerized products of chitosan, which is consisted of D-glucosamine and N-acetyl-D-glucosamine. In agriculture, COS has the ability to promote plant growth and induce plant innate immunity. The bioactivity of COS closely related to its degree of polymerization (DP) and acetylation (DA). However, most of the previous reports fail to mention the function of COS with different DP and DAs in improving the capacity of plants against salt stress. Accordingly, in this study, chitooligomers (COS) with different degrees of DAs were used to test wheat seedlings response to salt stress. In addition, the determined degrees of polymerization (DPs) COS(DP 4-12) and a heterogeneous COS mixture were applied to explore the relationship between the DP of COSs and its effect on the growth of wheat seedlings in response to salt stress. It showed that COSs, the exogenous elicitor, could promote the growth of wheat seedling, reduce the malondialdehyde (MDA) concentration, and increase the activities of antioxidant enzymes. The results of mRNA expression level test for salt stress-responsive genes indicated that COS keep plants away from being hurt by the salt stress via the regulation of the concentration and the increased antioxidant enzymes activities. Moreover, it was found that the activities of COS was closely related to its Das and COS (DA: 50%) displayed the best salt resistance activity to wheat seedlings. The results also showed that COS with different DP could promote the growth of wheat seedlings under salt stress. COS with a DP (6-8) showed better activities than the other tested samples, implied its activity had a close relationship with its DP. After treatment with chitohexaose, chitoheptaose, and chitooctaose, the photosynthetic parameters were improved obviously. The soluble sugar and proline contents were improved by 26.7%-53.3% and 43.6.0%-70.2%, respectively, while the concentration of malondialdehyde (MDA) was reduced by 36.8% - 49.6%. In addition, the antioxidant enzymes activities were clearly activated. At the molecular level, the results revealed that they could obviously induce the expression of Na+/H+ antiporter genes. In general, these results were fundamental to the study of action mechanism of COS on promoting plant growth under salt stress and the preparation of plant growth regulator.

Keywords: chitooligomers (COS), degree of polymerization (DP), degree of acetylation (DA), salt stress

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Authors: S. Cowley, M. Lawrance, D. Bick, R. McCord

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Technology that automates manual handling (musculoskeletal disorder or MSD) risk assessments is increasingly available to ergonomists, engineers, generalist health and safety practitioners alike. The risk assessment process is generally based on the use of wearable motion sensors that capture information about worker movements for real-time or for posthoc analysis. Traditionally, MSD risk assessment is undertaken with the assistance of a checklist such as that from the SafeWork Australia code of practice, the expert assessor observing the task and ideally engaging with the worker in a discussion about the detail. Automation enables the non-expert to complete assessments and does not always require the assessor to be there. This clearly has cost and time benefits for the practitioner but is it an improvement on the assessment by the human. Human risk assessments draw on the knowledge and expertise of the assessor but, like all risk assessments, are highly subjective. The complexity of the checklists and models used in the process can be off-putting and sometimes will lead to the assessment becoming the focus and the end rather than a means to an end; the focus on risk control is lost. Automated risk assessment handles the complexity of the assessment for the assessor and delivers a simple risk score that enables decision-making regarding risk control. Being machine-based, they are objective and will deliver the same each time they assess an identical task. However, the WHS professional needs to know that this emergent technology asks the right questions and delivers the right answers. Whether it improves the risk assessment process and results or simply distances the professional from the task and the worker. They need clarity as to whether automation of manual task risk analysis and reporting leads to risk control or to a focus on the worker. Critically, they need evidence as to whether automation in this area of hazard management leads to better risk control or just a bigger collection of assessments. Practitioner experienced determinants of this automated manual task risk analysis and reporting being a benefit or distraction will address an understanding of emergent risk assessment technology, its use and things to consider when making decisions about adopting and applying these technologies.

Keywords: automated, manual-handling, risk-assessment, machine-based

Procedia PDF Downloads 111

Authors: Sara R. Knigge, Sugat R. Tuladhar, Hans-Klaus HöFfler, Tobias Schilling, Tim Kaufeld, Axel Haverich

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Tissue engineered (TE) heart valves based on degradable electrospun fiber scaffold represent a promising approach to overcome the known limitations of mechanical or biological prostheses. But the mechanical stress in the high-pressure system of the human circulation is a severe challenge for the delicate materials. Hence, the prediction of the scaffolds` in vivo degradation kinetics must be as accurate as possible to prevent fatal events in future animal or even clinical trials. Therefore, this study investigates whether long-term testing in full blood provides more meaningful results regarding the degradation behavior than conventional tests in simulated body fluids (SBF) or Phosphate Buffered Saline (PBS). Fiber mats were produced from a polycaprolactone (PCL)/tetrafluoroethylene solution by electrospinning. The morphology of the fiber mats was characterized via scanning electron microscopy (SEM). A maximum physiological degradation environment utilizing a test set-up with porcine full blood was established. The set-up consists of a reaction vessel, an oxygenator unit, and a roller pump. The blood parameters (pO2, pCO2, temperature, and pH) were monitored with an online test system. All tests were also carried out in the test circuit with SBF and PBS to compare conventional degradation media with the novel full blood setting. The polymer's degradation is quantified by SEM picture analysis, differential scanning calorimetry (DSC), and Raman spectroscopy. Tensile and cyclic loading tests were performed to evaluate the mechanical integrity of the scaffold. Preliminary results indicate that PCL degraded slower in full blood than in SBF and PBS. The uptake of water is more pronounced in the full blood group. Also, PCL preserved its mechanical integrity longer when degraded in full blood. Protein absorption increased during the degradation process. Red blood cells, platelets, and their aggregates adhered on the PCL. Presumably, the degradation led to a more hydrophilic polymeric surface which promoted the protein adsorption and the blood cell adhesion. Testing degradable implants in full blood allows for developing more reliable scaffold materials in the future. Material tests in small and large animal trials thereby can be focused on testing candidates that have proven to function well in an in-vivo-like setting.

Keywords: Electrospun scaffold, full blood degradation test, long-term polymer degradation, tissue engineered aortic heart valve

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Manuel Palma Oliveira

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The decline in employment rates across sectors like industry and construction is exacerbated by an aging workforce. This has far-reaching implications for the economy, including skills gaps, labour shortages, productivity challenges due to physical limitations, and workplace safety concerns. To sustain the workforce and pension systems, technology plays a pivotal role. Robots provide valuable support to human workers, and effective human-robot interaction is essential. FORTIS, a Horizon project, aims to address these challenges by creating a comprehensive Human-Robot Interaction (HRI) solution. This solution focuses on multi-modal communication and multi-aspect interaction, with a primary goal of maintaining a human-centric approach. By meeting the needs of both human workers and robots, FORTIS aims to facilitate efficient and safe collaboration. The project encompasses three key activities: 1) A Human-Centric Approach involving data collection, annotation, understanding human behavioural cognition, and contextual human-robot information exchange. 2) A Robotic-Centric Focus addressing the unique requirements of robots during the perception and evaluation of human behaviour. 3) Ensuring Human-Robot Trustworthiness through measures such as human-robot digital twins, safety protocols, and resource allocation. Factor Social, a project partner, will analyse psycho-physiological signals that influence human factors, particularly in hazardous working conditions. The analysis will be conducted using a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. However, the adoption of novel technologies, particularly those involving human-robot interaction, often faces hurdles related to acceptance. To address this challenge, FORTIS will draw upon insights from Social Sciences and Humanities (SSH), including risk perception and technology acceptance models. Throughout its lifecycle, FORTIS will uphold a human-centric approach, leveraging SSH methodologies to inform the design and development of solutions. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No 101135707 (FORTIS).

Keywords: skills gaps, productivity challenges, workplace safety, human-robot interaction, human-centric approach, social sciences and humanities, risk perception

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Authors: Rami Faraj, Cezary Graczykowski, Błażej Popławski, Grzegorz Mikułowski, Rafał Wiszowaty

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Progress in the field of sensors, electronics and computing results in more and more often applications of adaptive techniques for dynamic response mitigation. When it comes to systems excited with mechanical impacts, the control system has to take into account the significant limitations of actuators responsible for system adaptation. The paper provides a comprehensive discussion of the problem of appropriate design and implementation of adaptation techniques and mechanisms. Two case studies are presented in order to compare completely different adaptation schemes. The first example concerns a double-chamber pneumatic shock absorber with a fast piezo-electric valve and parameters corresponding to the suspension of a small unmanned aerial vehicle, whereas the second considered system is a safety air cushion applied for evacuation of people from heights during a fire. For both systems, it is possible to ensure adaptive performance, but a realization of the system’s adaptation is completely different. The reason for this is technical limitations corresponding to specific types of shock-absorbing devices and their parameters. Impact mitigation using a pneumatic shock absorber corresponds to much higher pressures and small mass flow rates, which can be achieved with minimal change of valve opening. In turn, mass flow rates in safety air cushions relate to gas release areas counted in thousands of sq. cm. Because of these facts, both shock-absorbing systems are controlled based on completely different approaches. Pneumatic shock-absorber takes advantage of real-time control with valve opening recalculated at least every millisecond. In contrast, safety air cushion is controlled using the semi-passive technique, where adaptation is provided using prediction of the entire impact mitigation process. Similarities of both approaches, including applied models, algorithms and equipment, are discussed. The entire study is supported by numerical simulations and experimental tests, which prove the effectiveness of both adaptive impact mitigation techniques.

Keywords: adaptive control, adaptive system, impact mitigation, pneumatic system, shock-absorber

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: Nardjes Hamini, Mohamed Bachir Yagoubi

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Precision agriculture has revolutionized farming by enabling farmers to monitor their crops remotely in real-time. By utilizing technologies such as sensors, farmers can detect the state of growth, hydration levels, and nutritional status and even identify diseases affecting their crops. With this information, farmers can make informed decisions regarding irrigation, fertilization, and pesticide application. Automated agricultural tasks, such as plowing, seeding, planting, and harvesting, are carried out by autonomous robots and have helped reduce costs and increase production. Despite the advantages of precision agriculture, its high cost makes it inaccessible to small and medium-sized farms. To address this issue, this paper presents an open-source guidance system for an autonomous planter robot. The system is composed of a Raspberry Pi-type nanocomputer equipped with Wi-Fi, a GPS module, a gyroscope, and a power supply module. The accompanying application allows users to enter and calibrate maps with at least four coordinates, enabling the localized contour of the parcel to be captured. The application comprises several modules, such as the mission entry module, which traces the planting trajectory and points, and the action plan entry module, which creates an ordered list of pre-established tasks such as loading, following the plan, returning to the garage, and entering sleep mode. A remote control module enables users to control the robot manually, visualize its location on the map, and use a real-time camera. Wi-Fi coverage is provided by an outdoor access point, covering a 2km circle. This open-source system offers a low-cost alternative for small and medium-sized farms, enabling them to benefit from the advantages of precision agriculture.

Keywords: autonomous robot, guidance system, low-cost, medium farms, open-source system, planter robot, precision agriculture, real-time monitoring, remote control, small farms

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Authors: Umer Malik, David Armstrong, Mark Ashworth, Alex Dregan, Veline L'Esperance, Lucy McDonnell, Mariam Molokhia, Patrick White

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Introduction: The microbiota lining epithelial surfaces is thought to play an important role in many human physiological functions including defense against pathogens and modulation of immune response. The microbiota is susceptible to disruption from external influences such as exposure to antibiotic medication. It is thought that antibiotic-induced disruption of the microbiota could predispose to pathogen overgrowth and invasion. We hypothesized that antibiotic use would be associated with increased risk of future infections. We carried out a systematic review of evidence of associations between antibiotic use and subsequent risk of community-acquired infections. Methods: We conducted a review of the literature for observational studies assessing the association between antibiotic use and subsequent community-acquired infection. Eligible studies were published before April 29th, 2016. We searched MEDLINE, EMBASE, and Web of Science and screened titles and abstracts using a predefined search strategy. Infections caused by Clostridium difficile, drug-resistant organisms and fungal organisms were excluded as their association with prior antibiotic use has been examined in previous systematic reviews. Results: Eighteen out of 21,518 retrieved studies met the inclusion criteria. The association between past antibiotic exposure and subsequent increased risk of infection was reported in 16 studies, including one study on Campylobacter jejuni infection (Odds Ratio [OR] 3.3), two on typhoid fever (ORs 5.7 and 12.2), one on Staphylococcus aureus skin infection (OR 2.9), one on invasive pneumococcal disease (OR 1.57), one on recurrent furunculosis (OR 16.6), one on recurrent boils and abscesses (Risk ratio 1.4), one on upper respiratory tract infection (OR 2.3) and urinary tract infection (OR 1.1), one on invasive Haemophilus influenzae type b (Hib) infection (OR 1.51), one on infectious mastitis (OR 5.38), one on meningitis (OR 2.04) and five on Salmonella enteric infection (ORs 1.4, 1.59, 1.9, 2.3 and 3.8). The effect size in three studies on Salmonella enteric infection was of marginal statistical significance. A further two studies on Salmonella infection did not demonstrate a statistically significant association between prior antibiotic exposure and subsequent infection. Conclusion: We have found an association between past antibiotic exposure and subsequent risk of a diverse range of infections in the community setting. Our findings provide evidence to support the hypothesis that prior antibiotic usage may predispose to future infection risk, possibly through antibiotic-induced alteration of the microbiota. The findings add further weight to calls to minimize inappropriate antibiotic prescriptions.

Keywords: antibiotic, infection, risk factor, side effect

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Authors: Sonu Rana, Jyoti Verma, A. K. Gautam

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In most developing countries like India, the majority of the population heavily relies on agriculture for their livelihood. The yield of agriculture is heavily dependent on uncertain weather conditions like a monsoon, soil fertility, availability of irrigation facilities and fertilizers as well as support from the government. The agricultural yield is quite less compared to the effort put in due to inefficient agricultural facilities and obsolete farming practices on the one hand and lack of knowledge on the other hand, and ultimately agricultural community does not prosper. It is therefore essential for the farmers to improve their harvest yield by the acquisition of related data such as soil condition, temperature, humidity, availability of irrigation facilities, availability of, manure, etc., and adopt smart farming techniques using modern agricultural equipment. Nowadays, using IOT technology in agriculture is the best solution to improve the yield with fewer efforts and economic costs. The primary focus of this work-related is IoT technology in the agriculture field. By using IoT all the parameters would be monitored by mounting sensors in an agriculture field held at different places, will collect real-time data, and could be transmitted by a transmitting device like an antenna. To improve the system, IoT will interact with other useful systems like Wireless Sensor Networks. IoT is exploring every aspect, so the radio frequency spectrum is getting crowded due to the increasing demand for wireless applications. Therefore, Federal Communications Commission is reallocating the spectrum for various wireless applications. An antenna is also an integral part of the newly designed IoT devices. The main aim is to propose a new antenna structure used for IoT agricultural applications and compatible with this new unlicensed frequency band. The main focus of this paper is to present work related to these technologies in the agriculture field. This also presented their challenges & benefits. It can help in understanding the job of data by using IoT and correspondence advancements in the horticulture division. This will help to motivate and educate the unskilled farmers to comprehend the best bits of knowledge given by the huge information investigation utilizing smart technology.

Keywords: smart agriculture, IoT, agriculture technology, data analytics, smart technology

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Abdullah Faqihi, John Hedley

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Biosensors play a significant role in the healthcare sectors, scientific and technological progress. Developing electrodes that are easy to manufacture and deliver better electrochemical performance is advantageous for diagnostics and biosensing. They can be implemented extensively in various analytical tasks such as drug discovery, food safety, medical diagnostics, process controls, security and defence, in addition to environmental monitoring. Development of biosensors aims to create high-performance electrochemical electrodes for diagnostics and biosensing. A biosensor is a device that inspects the biological and chemical reactions generated by the biological sample. A biosensor carries out biological detection via a linked transducer and transmits the biological response into an electrical signal; stability, selectivity, and sensitivity are the dynamic and static characteristics that affect and dictate the quality and performance of biosensors. In this research, a developed experimental study for laser scribing technique for graphene oxide inside a vacuum chamber for processing of graphene oxide is presented. The processing of graphene oxide (GO) was achieved using the laser scribing technique. The effect of the laser scribing on the reduction of GO was investigated under two conditions: atmosphere and vacuum. GO solvent was coated onto a LightScribe DVD. The laser scribing technique was applied to reduce GO layers to generate rGO. The micro-details for the morphological structures of rGO and GO were visualised using scanning electron microscopy (SEM) and Raman spectroscopy so that they could be examined. The first electrode was a traditional graphene-based electrode model, made under normal atmospheric conditions, whereas the second model was a developed graphene electrode fabricated under a vacuum state using a vacuum chamber. The purpose was to control the vacuum conditions, such as the air pressure and the temperature during the fabrication process. The parameters to be assessed include the layer thickness and the continuous environment. Results presented show high accuracy and repeatability achieving low cost productivity.

Keywords: laser scribing, lightscribe DVD, graphene oxide, scanning electron microscopy

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Authors: Adolfo Martucci, Iulian Mihai

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By means of the expansion through a Conical Nozzle and the low pressure inside the Test Chamber, a large hypersonic stable flow takes place for a duration of up to 30 minutes. Downstream the Test Chamber, the diffuser has the function of reducing the flow velocity to subsonic values, and as a consequence, the temperature increases again. In order to cool down the flow, a heat exchanger is present at the end of the diffuser. The Vacuum System generates the necessary vacuum conditions for the correct hypersonic flow generation, and the DeNOx system, which follows the Vacuum System, reduces the nitrogen oxide concentrations created inside the plasma flow behind the limits imposed by Italian law. This very large, powerful, and complex facility allows researchers and engineers to reproduce entire re-entry trajectories of space vehicles into the atmosphere. One of the most important parameters for a hypersonic flowfield representative of re-entry conditions is the specific total enthalpy. This is the whole energy content of the fluid, and it represents how severe could be the conditions around a spacecraft re-entering from a space mission or, in our case, inside a hypersonic wind tunnel. It is possible to reach very high values of enthalpy (up to 45 MJ/kg) that, together with the large allowable size of the models, represent huge possibilities for making on-ground experiments regarding the atmospheric re-entry field. The maximum nozzle exit section diameter is 1950 mm, where values of Mach number very much higher than 1 can be reached. The specific total enthalpy is evaluated by means of a number of measurements, each of them concurring with its value and its uncertainty. The scope of the present paper is the evaluation of the sensibility of the uncertainty of the specific total enthalpy versus all the parameters and measurements involved. The sensors that, if improved, could give the highest advantages have so been individuated. Several simulations in Python with the METAS library and by means of Monte Carlo simulations are presented together with the obtained results and discussions about them.

Keywords: hypersonic, uncertainty, enthalpy, simulations

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Wei-Chou Hsu, Ching-Sung Lee, Han-Yin Liu

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This work uses H2O2 oxidation technique to improve the pH sensitivity of the AlGaN/GaN-based ion-sensitive field-effect transistors (ISFETs). 10-nm-thick Al2O3 was grown on the surface of the AlGaN. It was found that the pH sensitivity was improved from 41.6 mV/pH to 55.2 mV/pH. Since the H2O2-grown Al2O3 was served as a passivation layer and the problem of Fermi-level pinning was suppressed for the ISFET with the H2O2 oxidation process. Hysteresis effect in the ISFET with the H2O2 treatment also became insignificant. The hysteresis effect was observed by dipping the ISFETs into different pH value solutions and comparing the voltage difference between the initial and final conditions. The hysteresis voltage (Vhys) of the ISFET with the H2O2 oxidation process was improved from 8.7 mV to 4.8 mV. The hysteresis effect is related to the buried binding sites which are related to the material defects like threading dislocations in the AlGaN/GaN heterostructure which was grown by the hetero-epitaxy technique. The H2O2-grown Al2O3 passivate these material defects and the Al2O3 has less material defects. The long-term stability of the ISFET is estimated by the drift effect measurement. The drift measurement was conducted by dipping the ISFETs into a specific pH value solution for 12 hours and the ISFETs were operating at a specific quiescent point. The drift rate is estimated by the drift voltage divided by the total measuring time. It was found that the drift rate of the ISFET was improved from 10.1 mV/hour to 1.91 mV/hour in the pH 7 solution, from 14.06 mV/hour to 6.38 mV/pH in the pH 2 solution, and from 12.8 mV/hour to 5.48 mV/hour in the pH 12 solution. The drift effect results from the capacitance variation in the electric double layer. The H2O2-grown Al2O3 provides an additional capacitance connection in series with the electric double layer. Therefore, the capacitance variation of the electric double layer became insignificant. Generally, the H2O2 oxidation process is a simple, fast, and cost-effective method for the AlGaN/GaN-based ISFET. Furthermore, the performance of the AlGaN/GaN ISFET was improved effectively and the non-ideal effects were suppressed.

Keywords: AlGaN/GaN, Al2O3, hysteresis effect, drift effect, reliability, passivation, pH sensors

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Authors: Asowata Osamede, Christo Pienaar, Johan Bekker

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Mismatch in electrical energy (power) or outage from commercial providers, in general, does not promote development to the public and private sector, these basically limit the development of industries. The necessity for a well-structured photovoltaic (PV) system is of importance for an efficient and cost-effective monitoring system. The major renewable energy potential on earth is provided from solar radiation and solar photovoltaics (PV) are considered a promising technological solution to support the global transformation to a low-carbon economy and reduction on the dependence on fossil fuels. Solar arrays which consist of various PV module should be operated at the maximum power point in order to reduce the overall cost of the system. So power regulation and conditioning circuits should be incorporated in the set-up of a PV system. Power regulation circuits used in PV systems include maximum power point trackers, DC-DC converters and solar chargers. Inappropriate choice of power conditioning device in a basic off-grid PV system can attribute to power loss, hence the need for a right choice of power conditioning device to be coupled with the system of the essence. This paper presents the design and implementation of a power conditioning devices in order to improve the overall yield from the availability of solar energy and the system’s total efficiency. The power conditioning devices taken into consideration in the project includes the Buck and Boost DC-DC converters as well as solar chargers with MPPT. A logging interface circuit (LIC) is designed and employed into the system. The LIC is designed on a printed circuit board. It basically has DC current signalling sensors, specifically the LTS 6-NP. The LIC is consequently required to program the voltages in the system (these include the PV voltage and the power conditioning device voltage). The voltage is structured in such a way that it can be accommodated by the data logger. Preliminary results which include availability of power as well as power loss in the system and efficiency will be presented and this would be used to draw the final conclusion.

Keywords: tilt and orientation angles, solar chargers, PV panels, storage devices, direct solar radiation

Procedia PDF Downloads 128

Authors: Jacob Lewis Watts, Adam F. A. Pellegrini

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Prairies, grasslands, and forests cover an expansive portion of the world’s surface and contribute significantly to Earth’s carbon cycle. The largest driver of carbon dynamics in some of these ecosystems is fire. As the global climate changes, most fire-dominated ecosystems will experience increased fire frequency and intensity, leading to increased carbon flux into the atmosphere and soil nutrient depletion. The plant communities associated with different fire regimes are important for reassimilation of carbon lost during fire and soil recovery. More frequent fires promote conservative plant functional traits aboveground; however, belowground fine root traits are poorly explored and arguably more important drivers of ecosystem function as the primary interface between the soil and plant. The root economic spectrum (RES) hypothesis describes single-dimensional covariation between important fine-root traits along a range of plant strategies from acquisitive to conservative – parallel to the well-established leaf economic spectrum (LES). However, because of the paucity of root trait data, the complex nature of the rhizosphere, and the phylogenetic conservatism of root traits, it is unknown whether the RES hypothesis accurately describes plant nutrient and water acquisition strategies. This project utilizesplants grown in common garden conditions in the Cambridge University Botanic Garden and a meta-analysis of long-term fire manipulation experiments to examine the belowground physiological traits of fire-adapted and non-fire-adapted herbaceous species to 1) test the RES hypothesis and 2) describe the effect of fire regimes on fine root functional traits – which in turn affect carbon and nutrient cycling. A suite of morphological, chemical, and biological root traits (e.g. root diameter, specific root length, percent N, percent mycorrhizal colonization, etc.) of 50 herbaceous species were measuredand tested for phylogenetic conservatism and RES dimensionality. Fire-adapted and non-fire-adapted plants traits were compared using phylogenetic PCA techniques. Preliminary evidence suggests that phylogenetic conservatism may weaken the single-dimensionality of the RES, suggesting that there may not be a single way that plants optimize nutrient and water acquisition and storage in the complex rhizosphere; additionally, fire-adapted species are expected to be more conservative than non-fire-adapted species, which may be indicative of slower carbon cycling with increasing fire frequency and intensity.

Keywords: climate change, fire regimes, root economic spectrum, fine roots

Procedia PDF Downloads 109

Authors: Muhammad Naeem Chaudhry, Fahim Nawaz, Rana Nauman Shabbir

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New strategies aimed at increasing the resilience of crop plants to the negative effects of climate change represent important research priorities of plant scientists. The use of soil microorganisms to alleviate abiotic stresses like drought has gained particular importance in recent past. A field experiment was planned to investigate the effect of phosphorous solubilizing bacteria on yield and seed quality of Camelina (Camelina sativa L.) under water deficit conditions. The study was conducted at Agronomic Research Farm, University College of Agriculture and Environmental Sciences, The Islamia University Bahawalpur, during 4th week of November, 2013. The available seeds of Camelina sativa were inoculated with two bacterial strains (pseudomonas and Bacillus spp.) and grown under various water stress levels i.e. D0, (four irrigations), D3 (three irrigation), D2 (two irrigations), and D1 (one irrigation). The results revealed that drought stress significantly reduced the plant growth and yield, consequently reducing protein contents and oil concentration in camelina. The exposure to drought stress decreased plant height (16%), plant population (27%), number of fertile branches (41-59%), number of pods per plant (35%) and seed per pod (33%). Drought stress also exerted a negative impact on yield characteristics by reducing the 1000-seed weight (65%), final seed yield (52%), biological yield (22%) and harvest index (39%) of camelina. However, the inoculation of seeds with Pseudomonas and Bacillus spp. promoted the plant growth characterized by increased plant height and enhanced plant population. It was noted that inoculation of seeds with Pseudomonas resulted in the maximum plant population (113.4 cm), primary branches (19 plant-1), and number of pods (664 plant-1), whereas Bacillus inoculation resulted in maximum plant height (113.4 cm), seeds per pod (15.9), 1000-seed weight (1.85 g), and seed yield (3378.8 kg ha-1). Moreover, the inoculation with Bacillus also significantly improved the quality attributes of camelina and gave 3.5% and 2.1% higher oil contents than Pseudomonas and control (no-inoculation), respectively. Similarly, the same strain also resulted in maximum protein contents (33.3%). Our results confirmed the hypothesis that inoculation of seeds with phosphorous solubilizing bacterial strains is an effective, viable and environment-friendly approach to improve yield and quality of camelina under water deficit conditions. However, further studies are suggested to investigate the physiological and molecular processes, stimulated by bacterial strains, for increasing drought tolerance in food crops.

Keywords: Camelina, drought stress, phosphate solubilizing bacteria, seed quality

Procedia PDF Downloads 255

Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

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Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

Procedia PDF Downloads 275

Authors: H. Tavakoli, S. S. Mohtasebi, R. Alimardani, R. Gebbers

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Nitrogen (N) is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. N demand of crops varies spatially across fields due to spatial differences in soil conditions. In addition, the response of a crop to the fertilizer applications is heavily reliant on plant available water. Matching N supply to water availability is thus essential to achieve an optimal crop response. The objective of this study was to determine effect of drought stress on estimation of nitrogen status of winter wheat by some vegetation indices. During the 2012 growing season, a field experiment was conducted at the Bundessortenamt (German Plant Variety Office) Marquardt experimental station which is located in the village of Marquardt about 5 km northwest of Potsdam, Germany (52°27' N, 12°57' E). The experiment was designed as a randomized split block design with two replications. Treatments consisted of four N fertilization rates (0, 60, 120 and 240 kg N ha-1, in total) and two water regimes (irrigated (Irr) and non-irrigated (NIrr)) in total of 16 plots with dimension of 4.5 × 9.0 m. The indices were calculated using readings of a spectroradiometer made of tec5 components. The main parts were two “Zeiss MMS1 nir enh” diode-array sensors with a nominal rage of 300 to 1150 nm with less than 10 nm resolutions and an effective range of 400 to 1000 nm. The following vegetation indices were calculated: NDVI, GNDVI, SR, MSR, NDRE, RDVI, REIP, SAVI, OSAVI, MSAVI, and PRI. All the experiments were conducted during the growing season in different plant growth stages including: stem elongation (BBCH=32-41), booting stage (BBCH=43), inflorescence emergence, heading (BBCH=56-58), flowering (BBCH=65-69), and development of fruit (BBCH=71). According to the results obtained, among the indices, NDRE and REIP were less affected by drought stress and can provide reliable wheat nitrogen status information, regardless of water status of the plant. They also showed strong relations with nitrogen status of winter wheat.

Keywords: nitrogen status, drought stress, vegetation indices, precision agriculture

Procedia PDF Downloads 310

Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

Procedia PDF Downloads 71

Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 382

Authors: Nabila Dwi Agustin, Ria Septitis Mentari, Nugroho Adi Sasongko

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Indonesia is experiencing a crisis in the development of defense equipment. Most of Indonesia's defense equipment must import its parts from other countries. Moreover, the area of Indonesia is 2/3 of its territory is the sea areas. For the protection of marine areas, Indonesia relies solely on submarines in monitoring conditions and whether or not intruders enter their territory. In fact, we know the submarine has a large size so that the expenses are getting bigger, the time it takes longer and needs a big maneuver to operate the submarine. Indeed, the submarine can only be operated for deeper seas. Many other countries enter the underwater world of Indonesia but Indonesia could not do anything due to the limitations of underwater monitoring system. At the same time, reconnaissance and monitor for shallow seas cannot be done by submarine. Equipment that can be used for surveillance of shallow underwater areas shall be made. This study reviewed the current research and development initiative of the submarine unmanned vehicle (SUV) or unmanned undersea vehicle (UUV) in Indonesia. This can explore underwater without the need for an operator to operate in it, but we can monitor it from a long distance. UUV has several advantages that size can be reduced as we desired, rechargeable ship batteries, has a detection sonar commonly found on a submarine and agile movement to detect at shallow sea depth. In the sonar sensors consisted of MEMS (Micro Electro Mechanical System), the sonar system runs more efficiently and effectively to monitor the target. UUV that has been developed will be very useful if the equipment is used around the outlying islands and outer from Indonesia especially the island frequented by foreign submarines without us know. The impact of this may not be felt now but it will allow foreign countries to attack Indonesia from within for the future. In addition, UUV needs to be equipped with a anti-radar system so that submarines of other countries crossing borders cannot detect it and Indonesia anti-submarine vessels can take further security measures. As the recommendation, Indonesia should take decisive steps in the state border rules, especially submarines of other countries that deliberately cross the borders of the state. This decisive action not only by word alone but also action as well. Indonesia government should show the strength and sovereignty as the entire society unites and applies the principle of universal peace.

Keywords: submarine unmanned vehicle, submarine, development of defense equipment, the border of Indonesia

Procedia PDF Downloads 140

Authors: Aarti Sharma, Sarita Kumar, Pushplata Tripathi

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Aedes aegypti L. is one of the most important insect vectors in the world transmitting several diseases of concern; dengue fever, dengue haemorrhagic fever and yellow fever. Though since ages the control of dengue vector is primarily relied upon the use of synthetic chemical insecticides, the continued and indiscriminate use of insecticides for their control has received wide public apprehension because of multifarious problems including insecticide resistance, resurgence of pest species, environmental pollution, toxic hazards to humans and non-target organisms. These problems have necessitated the need to explore and develop alternative strategies using eco-friendly and bio-degradable plant products. Bio-insecticides, despite being the focus of research nowadays, have not been investigated much regarding their physiological effects on the mosquitoes. Thus, the present studies were carried out to investigate the anti-mosquito potential of the leaf and stem hexane extracts of Achyranthes aspera against early fourth instars of Aedes aegypti L and their effects on the histological architecture of their midgut. The larvicidal bioassays conducted with the A. aspera leaf hexane extracts revealed the respective LC30, LC50 and LC90 values of 66.545 ppm, 82.555 ppm, 139.817 ppm while the assays with stem hexane extracts resulted in respective values of 54.982 ppm, 68.133 ppm, 115.075 ppm. The studies clearly indicate the efficacy of extracts as larvicidal agents against Ae. aegypti, the stem extracts being found more effective than the leaf extracts. When the larvae assayed with extracts were investigated for the modifications in the histo-architecture of the midgut, the studies showed significant damage, shrinkage, distortion and vacuolization of gut tissues and peritrophic membrane causing disintegration of epithelial cells and cytoplasmic organelles; extent of toxicity and damage varied depending upon the concentration and exposure time period. These changes revealed appreciable stomach poison potential of A. aspera extracts against Ae. aegypti larvae, which may have also caused adverse impact on the growth and development of larvae. These effects were also found to be more pronounced with the stem extract than the leaf extract. Our findings may prove significant suggesting the use of A. aspera extract as a bio-insecticide against early fourth instar larvae of Ae. aegypti. Further studies are needed to identify the bioactive component in the extracts and to ascertain the use of component in the fields as anti-mosquito control agent.

Keywords: Achyranthes aspera, Aedes aegypti, histological architecture, larvicidal, midgut, stomach poison

Procedia PDF Downloads 283

Authors: Kougioumtzis Konstantin, Rylander Pär, Karlsteen Magnus

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Ball skills as a subset of fundamental motor skills are predictors for performance in sports. Currently, most tools evaluate ball skills utilizing subjective ratings. The aim of this study was to examine the psychometric properties of a newly developed instrument to objectively measure ball handling skills (BHS-test) utilizing digital instrument. Participants were a convenience sample of 213 adolescents (age M = 17.1 years, SD =3.6; 55% females, 45% males) recruited from upper secondary schools and invited to a sports hall for the assessment. The 8-item instrument incorporated both accuracy-based ball skill tests and repetitive-performance tests with a ball. Testers counted performance manually in the four tests (one throwing and three juggling tasks). Furthermore, assessment was technologically enhanced in the other four tests utilizing a ball machine, a Kinect camera and balls with motion sensors (one balancing and three rolling tasks). 3D printing technology was used to construct equipment, while all results were administered digitally with smart phones/tablets, computers and a specially constructed application to send data to a server. The instrument was deemed reliable (α = .77) and principal component analysis was used in a random subset (53 of the participants). Furthermore, latent variable modeling was employed to confirm the structure with the remaining subset (160 of the participants). The analysis showed good factorial-related validity with one factor explaining 57.90 % of the total variance. Four loadings were larger than .80, two more exceeded .76 and the other two were .65 and .49. The one factor solution was confirmed by a first order model with one general factor and an excellent fit between model and data (χ² = 16.12, DF = 20; RMSEA = .00, CI90 .00–.05; CFI = 1.00; SRMR = .02). The loadings on the general factor ranged between .65 and .83. Our findings indicate good reliability and construct validity for the BHS-test. To develop the instrument further, more studies are needed with various age-groups, e.g. children. We suggest using the BHS-test for diagnostic or assessment purpose for talent development and sports participation interventions that focus on ball games.

Keywords: ball-handling skills, ball-handling ability, technologically-enhanced measurements, assessment

Procedia PDF Downloads 81

Authors: Mursleen Yasin, Sunil Panchal, Michelle Mak, Zhonghua Chen

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“The use of agricultural and horticultural waste to obtain beneficial products. Thus reduce its environmental impact and help the general population.” Every year 20 billion dollars of food is wasted in the world. All the energy, resources, nutrients and metabolites are lost to the landfills as well. On farm production losses are a main issue in agriculture. Almost 25% vegetables never leave the farm because they are not considered perfect for supermarkets and treated as waste material along with the rest of the plant parts. For capsicums, this waste is 56% of the total crop. Capsicum genus is enriched with a group of compounds called capsaicinoids which are a source of spiciness of these fruits. Capsaicin and dihydrocapsaicin are the major members comprising almost 90% of this group. The major production and accumulation site is the non-edible part of fruit i.e., placenta. Other parts of the plant, like stem, leaves, pericarp and seeds, also contain these pungent compounds. Capsaicinoids are enriched with properties like analgesic, antioxidants, anti-inflammatory, antibacterial, anti-virulence anti-carcinogenic, chemo preventive, chemotherapeutic, antidiabetic etc. They are also effective in treating problems related to gastrointestinal tract, lowering cholesterol and triglycerides in obesity. The aim of the study is to develop a standardised technique for capsaicinoids extraction and to identify better nutrient treatment for fruit and capsaicinoids yield. For research 3 capsicum and 2 chilli varieties were grown in a high-tech glass house facility in Sydney, Australia. Plants were treated with three levels of nutrient treatments i.e., EC 1.8, EC 2.8 and EC 3.8 in order to check its effect on fruit yield and capsaicinoids concentration. Solvent extraction procedure is used with 75% ethanol to extract these secondary metabolites. Physiological, post-harvest and waste biomass measurement and metabolomic analysis are also performed. The results showed that EC 2.8 gave the better fruit yield of capsicums, and those fruits have the higher capsaicinoids concentration. For chillies, higher EC levels had better results than lower treatment. The UHPLC analysis is done to quantify the compounds, and a decrease in capsaicin concentration is observed with the crop maturation. The outcome of this project is a sustainable technique for extraction of capsaicinoids which can easily be adopted by farmers. In this way, farmers can help in value adding of waste by extracting and selling capsaicinoids to nutraceutical and pharmaceutical industries and also earn some secondary income from the 56% waste of capsicum crop.

Keywords: capsaicinoids, plant waste, capsicum, solvent extraction, waste biomass

Procedia PDF Downloads 71

Authors: Gul Rahim Rahimi

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The IoT-based soil moisture monitoring system for indoor plants is designed to address the challenges of maintaining optimal moisture levels in soil for plant growth and health. The system utilizes sensor technology to collect real-time data on soil moisture levels, which is then processed and analyzed using machine learning algorithms. This allows for accurate and timely monitoring of soil moisture levels, ensuring plants receive the appropriate amount of water to thrive. The main objectives of the system are twofold: to keep plants fresh and healthy by preventing water deficiency and to provide users with comprehensive insights into the water content of the soil on a daily and hourly basis. By monitoring soil moisture levels, users can identify patterns and trends in water consumption, allowing for more informed decision-making regarding watering schedules and plant care. The scope of the system extends to the agriculture industry, where it can be utilized to minimize the efforts required by farmers to monitor soil moisture levels manually. By automating the process of soil moisture monitoring, farmers can optimize water usage, improve crop yields, and reduce the risk of plant diseases associated with over or under-watering. Key technologies employed in the system include the Capacitive Soil Moisture Sensor V1.2 for accurate soil moisture measurement, the Node MCU ESP8266-12E Board for data transmission and communication, and the Arduino framework for programming and development. Additionally, machine learning algorithms are utilized to analyze the collected data and provide actionable insights. Cloud storage is utilized to store and manage the data collected from multiple sensors, allowing for easy access and retrieval of information. Overall, the IoT-based soil moisture monitoring system offers a scalable and efficient solution for indoor plant care, with potential applications in agriculture and beyond. By harnessing the power of IoT and machine learning, the system empowers users to make informed decisions about plant watering, leading to healthier and more vibrant indoor environments.

Keywords: IoT-based, soil moisture monitoring, indoor plants, water management

Procedia PDF Downloads 40

Authors: Khaled Al-Badani, Andrew Norbury, Essam Elmshawet, Glynn Rotwell, Ian Jenkinson , James Ren

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Micro welding procedures are widely used for joining materials, developing duplex components or functional surfaces, through various methods such as Micro Discharge Welding or Spot Welding process, which can be found in the engineering, aerospace, automotive, biochemical, biomedical and numerous other industries. The relationship between the material properties, structure and processing is very important to improve the structural integrity and the final performance of the welded joints. This includes controlling the shape and the size of the welding nugget, state of the heat affected zone, residual stress, etc. Nowadays, modern high volume productions require the welding of much versatile shapes/sizes and material systems that are suitable for various applications. Hence, an improved understanding of the micro welding process and the digital tools, which are based on computational numerical modelling linking key welding parameters, dimensional attributes and functional performance of the weldment, would directly benefit the industry in developing products that meet current and future market demands. This paper will introduce recent work on developing an integrated experimental and numerical modelling code for micro welding techniques. This includes similar and dissimilar materials for both ferrous and non-ferrous metals, at different scales. The paper will also produce a comparative study, concerning the differences between the micro discharge welding process and the spot welding technique, in regards to the size effect of the welding zone and the changes in the material structure. Numerical modelling method for the micro welding processes and its effects on the material properties, during melting and cooling progression at different scales, will also be presented. Finally, the applications of the integrated numerical modelling and the material development for the digital manufacturing of welding, is discussed with references to typical application cases such as sensors (thermocouples), energy (heat exchanger) and automotive structures (duplex steel structures).

Keywords: computer modelling, droplet formation, material distortion, materials forming, welding

Procedia PDF Downloads 248

Authors: Neha Batra Bali, Monika Tomar, Vinay Gupta

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A reagentless biosensor for detection of urea based on ZnO-CuO composite thin film is presented in following work. Biosensors have immense potential for varied applications ranging from environmental to clinical testing, health care, and cell analysis. Immense growth in the field of biosensors is due to the huge requirement in today’s world to develop techniques which are both cost effective and accurate for prevention of disease manifestation. The human body comprises of numerous biomolecules which in their optimum levels are essential for functioning. However mismanaged levels of these biomolecules result in major health issues. Urea is one of the key biomolecules of interest. Its estimation is of paramount significance not only for healthcare sector but also from environmental perspectives. If level of urea in human blood/serum is abnormal, i.e., above or below physiological range (15-40mg/dl)), it may lead to diseases like renal failure, hepatic failure, nephritic syndrome, cachexia, urinary tract obstruction, dehydration, shock, burns and gastrointestinal, etc. Various metal nanoparticles, conducting polymer, metal oxide thin films, etc. have been exploited to act as matrix to immobilize urease to fabricate urea biosensor. Amongst them, Zinc Oxide (ZnO), a semiconductor metal oxide with a wide band gap is of immense interest as an efficient matrix in biosensors by virtue of its natural abundance, biocompatibility, good electron communication feature and high isoelectric point (9.5). In spite of being such an attractive candidate, ZnO does not possess a redox couple of its own which necessitates the use of electroactive mediators for electron transfer between the enzyme and the electrode, thereby causing hindrance in realization of integrated and implantable biosensor. In the present work, an effort has been made to fabricate a matrix based on ZnO-CuO composite prepared by pulsed laser deposition (PLD) technique in order to incorporate redox properties in ZnO matrix and to utilize the same for reagentless biosensing applications. The prepared bioelectrode Urs/(ZnO-CuO)/ITO/glass exhibits high sensitivity (70µAmM⁻¹cm⁻²) for detection of urea (5-200 mg/dl) with high stability (shelf life ˃ 10 weeks) and good selectivity (interference ˂ 4%). The enhanced sensing response obtained for composite matrix is attributed to the efficient electron exchange between ZnO-CuO matrix and immobilized enzymes, and subsequently fast transfer of generated electrons to the electrode via matrix. The response is encouraging for fabricating reagentless urea biosensor based on ZnO-CuO matrix.

Keywords: biosensor, reagentless, urea, ZnO-CuO composite

Procedia PDF Downloads 285