Search results for: nano sensors

Authors: Yung C. Lin, Kung D. Wu, Wei C. Shih, Jui P. Hung

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High speed and high precision machining have become the most important technology in manufacturing industry. The surface roughness of high precision components is regarded as the important characteristics of the product quality. However, machining chatter could damage the machined surface and restricts the process efficiency. Therefore, selection of the appropriate cutting conditions is of importance to prevent the occurrence of chatter. In addition, vibration of the spindle tool also affects the surface quality, which implies the surface precision can be controlled by monitoring the vibration of the spindle tool. Based on this concept, this study was aimed to investigate the influence of the machining conditions on the surface roughness and the vibration of the spindle tool. To this end, a series of machining tests were conducted on aluminum alloy. In tests, the vibration of the spindle tool was measured by using the acceleration sensors. The surface roughness of the machined parts was examined using white light interferometer. The response surface methodology (RSM) was employed to establish the mathematical models for predicting surface finish and tool vibration, respectively. The correlation between the surface roughness and spindle tool vibration was also analyzed by ANOVA analysis. According to the machining tests, machined surface with or without chattering was marked on the lobes diagram as the verification of the machining conditions. Using multivariable regression analysis, the mathematical models for predicting the surface roughness and tool vibrations were developed based on the machining parameters, cutting depth (a), feed rate (f) and spindle speed (s). The predicted roughness is shown to agree well with the measured roughness, an average percentage of errors of 10%. The average percentage of errors of the tool vibrations between the measurements and the predictions of mathematical model is about 7.39%. In addition, the tool vibration under various machining conditions has been found to have a positive influence on the surface roughness (r=0.78). As a conclusion from current results, the mathematical models were successfully developed for the predictions of the surface roughness and vibration level of the spindle tool under different cutting condition, which can help to select appropriate cutting parameters and to monitor the machining conditions to achieve high surface quality in milling operation.

Keywords: machining parameters, machining stability, regression analysis, surface roughness

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Authors: Qianying Sun, Abdelhadi Kassiba, Guorong Li

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ZnO with wurtzite structure is a well-known semiconducting oxide (SCO), being applied in thermoelectric devices, varistors, gas sensors, transparent electrodes, solar cells, liquid crystal displays, piezoelectric and electro-optical devices. Intrinsically, ZnO is weakly n-type SCO due to native defects (Znⱼ, Vₒ). However, the substitutional doping by metallic elements as (Al, Ti) gives rise to a high n-type conductivity ensured by donor centers. Under CO+N₂ sintering atmosphere, Schottky barriers of ZnO ceramics will be suppressed by lowering the concentration of acceptors at grain boundaries and then inducing a large increase in the Hall mobility, thereby increasing the conductivity. The presented work concerns ZnO based ceramics, which are fabricated with doping by TiO₂ (0.50mol%), Al₂O₃ (0.25mol%) and MgO (1.00mol%) and sintering in different atmospheres (Air (A), N₂ (N), CO+N₂(C)). We obtained uniform, dense ceramics with ZnO as the main phase and Zn₂TiO₄ spinel as a secondary and minor phase. An important increase of the conductivity was shown for the samples A, N, and C which were sintered under different atmospheres. The highest conductivity (σ = 1.52×10⁵ S·m⁻¹) was obtained under the reducing atmosphere (CO). The role of doping was investigated with the aim to identify the local environment and valence states of the doping elements. Thus, Electron paramagnetic spectroscopy (EPR) determines the concentration of defects and the effects of charge carriers in ZnO ceramics as a function of the sintering atmospheres. The relation between conductivity and defects concentration shows the opposite behavior between these parameters suggesting that defects act as traps for charge carriers. For Al ions, nuclear magnetic resonance (NMR) technique was used to identify the involved local coordination of these ions. Beyond the six and forth coordinated Al, an additional NMR signature of ZnO based TCO requires analysis taking into account the grain boundaries and the conductivity through the Knight shift effects. From the thermal evolution of the conductivity as a function of the sintering atmosphere, we succeed in defining the conditions to realize ZnO based TCO ceramics with an important thermal coefficient of resistance (TCR) which is promising for electrical safety of devices.

Keywords: ceramics, conductivity, defects, TCO, ZnO

Procedia PDF Downloads 173

Authors: Ankita Srivastava, Bhupendra S. Butola, Abhijit Majumdar

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Application of shear thickening fluid (STF) has been proved to increase the impact resistance performance of the textile structures to further use it as a body armor material. In the present research, STF was applied on Kevlar woven fabric to make the structure lightweight and flexible while improving its impact resistance performance. It was observed that getting a fair amount of add-on of STF on Kevlar fabric is difficult as Kevlar fabric comes with a pre-coating of PTFE which hinders its absorbency. Hence, a method termed as sequential padding is developed in the present study to improve the add-on of STF on Kevlar fabric. Contrary to the conventional process, where Kevlar fabric is treated with STF once using any one pressure, in sequential padding method, the Kevlar fabrics were treated twice in a sequential manner using combination of two pressures together in a sample. 200 GSM Kevlar fabrics were used in the present study. STF was prepared by adding PEG with 70% (w/w) nano-silica concentration. Ethanol was added with the STF at a fixed ratio to reduce viscosity. A high-speed homogenizer was used to make the dispersion. Total nine STF treated Kevlar fabric samples were prepared by using varying combinations and sequences of three levels of padding pressure {0.5, 1.0 and 2.0 bar). The fabrics were dried at 80°C for 40 minutes in a hot air oven to evaporate ethanol. Untreated and STF treated fabrics were tested for add-on%. Impact resistance performance of samples was also tested on dynamic impact tester at a fixed velocity of 6 m/s. Further, to observe the impact resistance performance in actual condition, low velocity ballistic test with 165 m/s velocity was also performed to confirm the results of impact resistance test. It was observed that both add-on% and impact energy absorption of Kevlar fabrics increases significantly with sequential padding process as compared to untreated as well as single stage padding process. It was also determined that impact energy absorption is significantly better in STF treated Kevlar fabrics when 1st padding pressure is higher, and 2nd padding pressure is lower. It is also observed that impact energy absorption of sequentially padded Kevlar fabric shows almost 125% increase in ballistic impact energy absorption (40.62 J) as compared to untreated fabric (18.07 J).The results are owing to the fact that the treatment of fabrics at high pressure during the first padding is responsible for uniform distribution of STF within the fabric structures. While padding with second lower pressure ensures the high add-on of STF for over-all improvement in the impact resistance performance of the fabric. Therefore, it is concluded that sequential padding process may help to improve the impact performance of body armor materials based on STF treated Kevlar fabrics.

Keywords: body armor, impact resistance, Kevlar, shear thickening fluid

Procedia PDF Downloads 223

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

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

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

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Authors: Tomasz Łęga, Marta Sosnowska, Mirosława Panasiuk, Lilit Hovhannisyan, Beata Gromadzka, Marcin Olszewski, Sabina Zoledowska, Dawid Nidzworski

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Toxic heavy metal ion contamination of industrial wastewater has recently become a significant environmental concern in many regions of the world. Although the majority of heavy metals are naturally occurring elements found on the earth's surface, anthropogenic activities such as mining and smelting, industrial production, and agricultural use of metals and metal-containing compounds are responsible for the majority of environmental contamination and human exposure. The permissible limits (ppm) for heavy metals in food, water and soil are frequently exceeded and considered hazardous to humans, other organisms, and the environment as a whole. Human exposure to highly nickel-polluted environments causes a variety of pathologic effects. In 2008, nickel received the shameful name of “Allergen of the Year” (GILLETTE 2008). According to the dermatologist, the frequency of nickel allergy is still growing, and it can’t be explained only by fashionable piercing and nickel devices used in medicine (like coronary stents and endoprostheses). Effective remediation methods for removing heavy metal ions from soil and water are becoming increasingly important. Among others, methods such as chemical precipitation, micro- and nanofiltration, membrane separation, conventional coagulation, electrodialysis, ion exchange, reverse and forward osmosis, photocatalysis and polymer or carbon nanocomposite absorbents have all been investigated so far. The importance of environmentally sustainable industrial production processes and the conservation of dwindling natural resources has highlighted the need for affordable, innovative biosorptive materials capable of recovering specific chemical elements from dilute aqueous solutions. The use of combinatorial phage display techniques for selecting and recognizing material-binding peptides with a selective affinity for any target, particularly inorganic materials, has gained considerable interest in the development of advanced bio- or nano-materials. However, due to the limitations of phage display libraries and the biopanning process, the accuracy of molecular recognition for inorganic materials remains a challenge. This study presents the isolation, identification and characterisation of metal binding phage clones that preferentially recover nickel.

Keywords: Heavy metal recovery, cleaning water, phage display, nickel

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Authors: He Zhang, Jianxin Yi

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As a clean energy, hydrogen shows many advantages such as renewability, high heat value, and extensive sources and may play an important role in the future society. However, hydrogen is a combustible gas because of its low ignition energy (0.02mJ) and wide explosive limit (4% ~ 74% in air). It is very likely to cause fire hazard or explosion once leakage is happened and not detected in time. Mixed-potential type sensor has attracted much attention in monitoring and detecting hydrogen due to its high response, simple support electronics and long-term stability. Typically, this kind of sensor is consisted of a sensing electrode (SE), a reference electrode (RE) and a solid electrolyte. The SE and RE materials usually display different electrocatalytic abilities to hydrogen. So hydrogen could be detected by measuring the EMF change between the two electrodes. Previous reports indicate that a high-performance sensing electrode is important for improving the sensing characteristics of the sensor. In this report, a planar type mixed-potential hydrogen sensor using La₀.₈Sr₀.₂Cr₀.₅Mn₀.₅O₃₋δ (LSCM) as SE, Pt as RE and yttria-stabilized zirconia (YSZ) as solid electrolyte was developed. The reason for selecting LSCM as sensing electrode is that it shows the high electrocatalytic ability to hydrogen in solid oxide fuel cells. The sensing performance of the fabricated LSCM/YSZ/Pt sensor was tested systemically. The experimental results show that the sensor displays high response to hydrogen. The response values for 100ppm and 1000ppm hydrogen at 450 ºC are -70 mV and -118 mV, respectively. The response time is an important parameter to evaluate a sensor. In this report, the sensor response time decreases with increasing hydrogen concentration and get saturated above 500ppm. The steady response time at 450 ºC is as short as 4s, indicating the sensor shows great potential in practical application to monitor hydrogen. An excellent response repeatability to 100ppm hydrogen at 450 ˚C and a good sensor reproducibility among three sensors were also observed. Meanwhile, the sensor exhibits excellent selectivity to hydrogen compared with several interfering gases such as NO₂, CH₄, CO, C₃H₈ and NH₃. Polarization curves were tested to investigate the sensing mechanism and the results indicated the sensor abide by the mixed-potential mechanism.

Keywords: fire hazard, H₂ sensor, mixed-potential, perovskite

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Authors: Mingjiang Dai, Qian Shi, Fang Hu, Songsheng Lin, Huijun Hou, Chunbei Wei

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A diamond-like carbon (DLC) is considered as a promising protective film since its high hardness and excellent tribological properties. However, DLC films are very sensitive to the environmental condition, its friction coefficient could dramatic change in high humidity, therefore, limited their further application in aerospace, the watch industry, and micro/nano-electromechanical systems. Therefore, most studies focus on the low friction coefficient of DLC films at a high humid environment. However, this is out of satisfied in practical application. An important thing was ignored is that the DLC coated components are usually used in the diversed environment, which means its friction coefficient may evidently change in different humid condition. As a result, the invalidation of DLC coated components or even sometimes disaster occurred. For example, DLC coated minisize gears were used in the watch industry, and the customer may frequently transform their locations with different weather and humidity even in one day. If friction coefficient is not stable in dry and high moisture conditions, the watch will be inaccurate. Thus, it is necessary to investigate the stable tribological behavior of DLC films in various environments. In this study, a-C:H:Si films were deposited by multi-function magnetron sputtering system, containing one ion source device and a pair of SiC dual mid-frequent targets and two direct current Ti/C targets. Hydrogenated carbon layers were manufactured by sputtering the graphite target in argon and methane gasses. The silicon was doped in DLC coatings by sputtering silicon carbide targets and the doping content were adjusted by mid-frequent sputtering current. The microstructure of the film was characterized by Raman spectrometry, X-ray photoelectron spectroscopy, and transmission electron microscopy while its friction behavior under different humidity conditions was studied using a ball-on-disc tribometer. The a-C:H films with Si content from 0 to 17at.% were obtained and the influence of Si content on the structure and tribological properties under the relative humidity of 50% and 85% were investigated. Results show that the a-C:H:Si film has typical diamond-like characteristics, in which Si mainly existed in the form of Si, SiC, and SiO2. As expected, the friction coefficient of a-C:H films can be effectively changed after Si doping, from 0.302 to 0.176 in RH 50%. The further test shows that the friction coefficient value of a-C:H:Si film in RH 85% is first increase and then decrease as a function of Si content. We found that the a-C:H:Si films with a Si content of 3.75 at.% show a stable friction coefficient of 0.13 in different humidity environment. It is suggestion that the sp3/sp2 ratio of a-C:H films with 3.75 at.% Si was higher than others, which tend to form the silica-gel-like sacrificial layers during friction tests. Therefore, the films deliver stable low friction coefficient under controlled RH value of 50 and 85%.

Keywords: diamond-like carbon, Si doping, moisture environment, table low friction coefficient

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Authors: Daniel Osieko Okach, Joseph Otieno Ondier, Gerhard Rambold, John Tenhunen, Bernd Huwe, Dennis Otieno

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Increased human activities such as grazing, logging, and agriculture alongside unpredictable rainfall patterns have been detrimental to the ecosystem service delivery, therefore compromising its productivity potential. This study aimed at simulating the impact of drought (50%) and enhanced rainfall (150%) on the future herbaceous CO2 uptake, biomass production and soil C:N dynamics in a humid savanna ecosystem influenced by livestock grazing. Rainfall pattern was predicted using manipulation experiments set up to reduce (50%) and increase (150%) ambient (100%) rainfall amounts in grazed and non-grazed plots. The impact of manipulated rainfall regime on herbaceous CO2 fluxes, biomass production and soil C:N dynamics was measured against volumetric soil water content (VWC) logged every 30 minutes using the 5TE (Decagon Devices Inc., Washington, USA) soil moisture sensors installed (at 20 cm soil depth) in every plots. Herbaceous biomass was estimated using destructive method augmented by standardized photographic imaging. CO2 fluxes were measured using the ecosystem chamber method and the gas analysed using LI-820 gas analyzer (USA). C:N ratio was calculated from the soil carbon and Nitrogen contents (analyzed using EA2400CHNS/O and EA2410 N elemental analyzers respectively) of different plots under study. The patterning of VWC was directly influenced by the rainfall amount with lower VWC observed in the grazed compared to the non-grazed plots. Rainfall variability, grazing and their interaction significantly affected changes in VWC (p < 0.05) and subsequently total biomass and CO2 fluxes. VWC had a strong influence on CO2 fluxes under 50% rainfall reduction in the grazed (r2 = 0.91; p < 0.05) and ambient rainfall in the ungrazed (r2 = 0.77; p < 0.05). The dependence of biomass on VWC across plots was enhanced under grazed (r2 = 0.78 - 0.87; p < 0.05) condition as compared to ungrazed (r2 = 0.44 - 0.85; p < 0.05). The C:N ratio was however not correlated to VWC across plots. This study provides insight on how the predicted trends in humid savanna will respond to changes influenced by rainfall variability and livestock grazing and consequently the sustainable management of such ecosystems.

Keywords: CO2 fluxes, rainfall manipulation, soil properties, sustainability

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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: 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

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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: 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: 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: Alice Robba, Renaud Bouchet, Celine Barchasz, Jean-Francois Colin, Erik Elkaim, Kristina Kvashnina, Gavin Vaughan, Matjaz Kavcic, Fannie Alloin

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With their high theoretical energy density (~2600 Wh.kg-1), lithium/sulfur (Li/S) batteries are highly promising, but these systems are still poorly understood due to the complex mechanisms/equilibria involved. Replacing S8 by Li2S as the active material allows the use of safer negative electrodes, like silicon, instead of lithium metal. S8 and Li2S have different conductivity and solubility properties, resulting in a profoundly changed activation process during the first cycle. Particularly, during the first charge a high polarization and a lack of reproducibility between tests are observed. Differences observed between raw Li2S material (micron-sized) and that electrochemically produced in a battery (nano-sized) may indicate that the electrochemical process depends on the particle size. Then the major focus of the presented work is to deepen the understanding of the Li2S material charge mechanism, and more precisely to characterize the effect of the initial Li2S particle size both on the mechanism and the electrode preparation process. To do so, Li2S nanoparticles were synthetized according to two ways: a liquid path synthesis and a dissolution in ethanol, allowing Li2S nanoparticles/carbon composites to be made. Preliminary chemical and electrochemical tests show that starting with Li2S nanoparticles could effectively suppress the high initial polarization but also influence the electrode slurry preparation. Indeed, it has been shown that classical formulation process - a slurry composed of Polyvinylidone Fluoride polymer dissolved in N-methyle-2-pyrrolidone - cannot be used with Li2S nanoparticles. This reveals a complete different Li2S material behavior regarding polymers and organic solvents when going at the nanometric scale. Then the coupling between two operando characterizations such as X-Ray Diffraction (XRD) and X-Ray Absorption and Emission Spectroscopy (XAS/XES) have been carried out in order to interpret the poorly understood first charge. This study discloses that initial particle size of the active material has a great impact on the working mechanism and particularly on the different equilibria involved during the first charge of the Li2S based Li-ion batteries. These results explain the electrochemical differences and particularly the polarization differences observed during the first charge between micrometric and nanometric Li2S-based electrodes. Finally, this work could lead to a better active material design and so to more efficient Li2S-based batteries.

Keywords: Li-ion/Sulfur batteries, Li2S nanoparticles effect, Operando characterizations, working mechanism

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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: Ahmed Tamer AlMotasem, Jens Bergström, Anders Gåård, Pavel Krakhmalev, Thijs Jan Holleboom

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In sheet metal forming processes, accumulation and transfer of sheet material to tool surfaces, often referred to as galling, is the major cause of tool failure. Initiation of galling is assumed to occur due to local adhesive wear between two surfaces. Therefore, reducing adhesion between the tool and the work sheet has a great potential to improve the tool materials galling resistance. Experimental observations and theoretical studies show that the presence of primary micro-sized carbides and/or nitrides in alloyed steels may significantly improve galling resistance. Generally, decreased adhesion between the ceramic precipitates and the sheet material counter-surface are attributed as main reason to the latter observations. On the other hand, adhesion processes occur at an atomic scale and, hence, fundamental understanding of galling can be obtained via atomic scale simulations. In the present study, molecular dynamics simulations are used, with utilizing second nearest neighbor embedded atom method potential to investigate the influence of nano-sized cementite precipitates embedded in tool atoms. The main aim of the simulations is to gain new fundamental knowledge on galling initiation mechanisms. Two tool/work piece configurations, iron/iron and iron-cementite/iron, are studied under dry sliding conditions. We find that the average frictional force decreases whereas the normal force increases for the iron-cementite/iron system, in comparison to the iron/iron configuration. Moreover, the average friction coefficient between the tool/work-piece decreases by about 10 % for the iron-cementite/iron case. The increase of the normal force in the case of iron-cementite/iron system may be attributed to the high stiffness of cementite compared to bcc iron. In order to qualitatively explain the effect of cementite on adhesion, the adhesion force between self-mated iron/iron and cementite/iron surfaces has been determined and we found that iron/cementite surface exhibits lower adhesive force than that of iron-iron surface. The variation of adhesion force with temperature was investigated up to 600 K and we found that the adhesive force, generally, decreases with increasing temperature. Structural analyses show that plastic deformation is the main deformation mechanism of the work-piece, accompanied with dislocations generation.

Keywords: adhesion, cementite, galling, molecular dynamics

Procedia PDF Downloads 286

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

Procedia PDF Downloads 219

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 117

Authors: Sayed M. Ahmed, Sawsan S. Darwish, Nagib A. Elmarzugi, Mohammad A. Al-Dosari, Mahmoud A. Adam, Nadia A. Al-Mouallimi

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Historical stone surfaces and architectural heritage may undergo unwanted changes due to the exposure to many physical and chemical deterioration factors, the innovative properties of the nano - materials can have advantageous application in the restoration and conservation of the cultural heritage with relation to the tailoring of new products for protection and consolidation of stone. The current work evaluates the effectiveness of inorganic compatible treatments; based on nanosized particles of silica (SiO2) dispersed in silicon based product, commonly used as a water-repellent/ consolidation for the construction materials affected by different kinds of decay. The nanocomposites obtained by dispersing the silica nanoparticles in polymeric matrices SILRES® BS OH 100 (solventless mixtures of ethyl silicates), in order to obtain a new nanocomposite, with hydrophobic and consolidation properties, to improve the physical and mechanical properties of the stone material. The nanocomposites obtained and pure SILRES® BS OH 100 were applied by brush Experimental stone blocks. The efficacy of the treatments has been evaluated after consolidation and artificial Thermal aging, through capillary water absorption measurements, Ultraviolet-light exposure to evaluate photo-induced and the hydrophobic effects of the treated surface, Scanning electron microscopy (SEM) examination is performed to evaluate penetration depth, re-aggregating effects of the deposited phase and the surface morphology before and after artificialaging. Sterio microscopy investigation is performed to evaluate the resistant to the effects of the erosion, acids and salts. Improving of stone mechanical properties were evaluated by compressive strength tests, colorimetric measurements were used to evaluate the optical appearance. All the results get together with the apparent effect that, silica/polymer nanocomposite is efficient material for the consolidation of artistic and architectural sandstone monuments, completely compatible, enhanced the durability of sandstone toward thermal and UV aging. In addition, the obtained nanocomposite improved the stone mechanical properties and the resistant to the effects of the erosion, acids and salts compared to the samples treated with pure SILRES® BS OH 100 without silica nanoparticles.

Keywords: colorimetric measurements, compressive strength, nanocomposites, porous stone consolidation, silica nanoparticles, sandstone

Procedia PDF Downloads 241

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

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Authors: Mehrnaz Mostafavi, Jalaledin Ghanavi

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This research investigates the production of nanoring structures through a chemical reduction approach, exploring gradual reduction processes assisted by reductant agents, leading to the formation of these specialized nanorings. The study focuses on the controlled reduction of metal atoms within these agents, crucial for shaping these nanoring structures over time. The paper commences by highlighting the wide-ranging applications of metal nanostructures across fields like Nanomedicine, Nanobiotechnology, and advanced spectroscopy methods such as Surface Enhanced Raman Spectroscopy (SERS) and Surface Enhanced Infrared Absorption Spectroscopy (SEIRA). Particularly, gold nanoparticles, especially in the nanoring configuration, have gained significant attention due to their distinctive properties, offering accessible spaces suitable for sensing and spectroscopic applications. The methodology involves utilizing human serum albumin as a reducing agent to create gold nanoparticles through a chemical reduction process. This process involves the transfer of electrons from albumin's carboxylic groups, converting them into carbonyl, while AuCl4− acquires electrons to form gold nanoparticles. Various characterization techniques like Ultraviolet–visible spectroscopy (UV-Vis), Atomic-force microscopy (AFM), and Transmission electron microscopy (TEM) were employed to examine and validate the creation and properties of the gold nanoparticles and nanorings. The findings suggest that precise and gradual reduction processes, in conjunction with optimal pH conditions, play a pivotal role in generating nanoring structures. Experiments manipulating optical properties revealed distinct responses in the visible and infrared spectrums, demonstrating the tunability of these nanorings. Detailed examinations of the morphology confirmed the formation of gold nanorings, elucidating their size, distribution, and structural characteristics. These nanorings, characterized by an empty volume enclosed by uniform walls, exhibit promising potential in the realms of Nanomedicine and Nanobiotechnology. In summary, this study presents a chemical synthesis approach using organic reducing agents to produce gold nanorings. The results underscore the significance of controlled and gradual reduction processes in crafting nanoring structures with unique optical traits, offering considerable value across diverse nanotechnological applications.

Keywords: nanoring structures, chemical reduction approach, gold nanoparticles, spectroscopy methods, nano medicine applications

Procedia PDF Downloads 91

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

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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 63

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 373

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 132

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

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Authors: Luminita Marin, Dalila Belei, Carmen Dumea

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Aggregation induced emission (AIE) is an intriguing optical phenomenon recently evidenced by Tang and his co-workers, for which aggregation works constructively in the improving of light emission. The AIE challenging phenomenon is quite opposite to the notorious aggregation caused quenching (ACQ) of light emission in the condensed phase, and comes in line with requirements of photonic and optoelectronic devices which need solid state emissive substrates. This paper reports a series of ten new aggregation induced emission (AIE) low molecular weight compounds based on triazole and pyridine-N-oxide heterocyclic units bonded by short flexible chains, obtained by a „click” chemistry reaction. The compounds present extremely weak luminescence in solution but strong light emission in solid state. To distinguish the influence of the crystallinity degree on the emission efficiency, the photophysical properties were explored by UV-vis and photoluminescence spectroscopy in solution, water suspension, amorphous and crystalline films. On the other hand, the compound morphology of the up mentioned states was monitored by dynamic light scattering, scanning electron microscopy, atomic force microscopy and polarized light microscopy methods. To further understand the structural design – photophysical properties relationship, single crystal X-ray diffraction on some understudy compounds was performed too. The UV-vis absorption spectra of the triazole water suspensions indicated a typical behaviour for nanoparticle formation, while the photoluminescence spectra revealed an emission intensity enhancement up to 921-fold higher of the crystalline films compared to solutions, clearly indicating an AIE behaviour. The compounds have the tendency to aggregate forming nano- and micro- crystals in shape of rose-like and fibres. The crystals integrity is kept due to the strong lateral intermolecular forces, while the absence of face-to-face forces explains the enhanced luminescence in crystalline state, in which the intramolecular rotations are restricted. The studied flexible triazoles draw attention to a new structural design in which small biologically friendly luminophore units are linked together by small flexible chains. This design enlarges the variety of the AIE luminogens to the flexible molecules, guiding further efforts in development of new AIE structures for appropriate applications, the biological ones being especially envisaged.

Keywords: aggregation induced emission, pyridine-N-oxide, triazole

Procedia PDF Downloads 441