Search results for: invasive techniques

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

Abstract:

To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

Procedia PDF Downloads 409

Authors: Valery Gulyayev, Sergey Glazunov, Elena Andrusenko, Nataliya Shlyun

Abstract:

Enhancement of technology and techniques for drilling deep directed oil and gas bore-wells are of essential industrial significance because these wells make it possible to increase their productivity and output. Generally, they are used for drilling in hard and shale formations, that is why their drivage processes are followed by the emergency and failure effects. As is corroborated by practice, the principal drilling drawback occurring in drivage of long curvilinear bore-wells is conditioned by the need to obviate essential force hindrances caused by simultaneous action of the gravity, contact and friction forces. Primarily, these forces depend on the type of the technological regime, drill string stiffness, bore-hole tortuosity and its length. They can lead to the Eulerian buckling of the drill string and its sticking. To predict and exclude these states, special mathematic models and methods of computer simulation should play a dominant role. At the same time, one might note that these mechanical phenomena are very complex and only simplified approaches (‘soft string drag and torque models’) are used for their analysis. Taking into consideration that now the cost of directed wells increases essentially with complication of their geometry and enlargement of their lengths, it can be concluded that the price of mistakes of the drill string behavior simulation through the use of simplified approaches can be very high and so the problem of correct software elaboration is very urgent. This paper deals with the problem of simulating the regimes of drilling deep curvilinear bore-wells with prescribed imperfect geometrical trajectories of their axial lines. On the basis of the theory of curvilinear flexible elastic rods, methods of differential geometry, and numerical analysis methods, the 3D ‘stiff-string drag and torque model’ of the drill string bending and the appropriate software are elaborated for the simulation of the tripping in and out regimes and drilling operations. It is shown by the computer calculations that the contact and friction forces can be calculated and regulated, providing predesigned trouble-free modes of operation. The elaborated mathematic models and software can be used for the emergency situations prognostication and their exclusion at the stages of the drilling process design and realization.

Keywords: curvilinear drilling, drill string tripping in and out, contact forces, resistance forces

Procedia PDF Downloads 146

Authors: Yangzhi Li

Abstract:

Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 86

Authors: Vimal Kumar Dewangan, T. S. Sampath Kumar, Mukesh Doble, Viju Daniel Varghese

Abstract:

The apatite-based, i.e., calcium-deficient hydroxyapatite (CDHAp) bone cement is well-known potential bone graft/substitute in orthopaedics due to its similar chemical composition with natural bone minerals. Therefore, an easy approach was attempted to fabricate the apatite-based (CDHAp) bone cement with improved injectability, bioresorbability, and macroporosity. In this study, the desired bone cement was developed by mixing the solid phase (consisting of wet chemically synthesized nanocrystalline hydroxyapatite and commercially available (synthetic) tricalcium phosphate) and the liquid phase (consisting of cement binding accelerator with few biopolymers in a dilute acidic solution) along with a liquid porogen as polysorbate or a solid porogen as mannitol (for comparison) in an optimized liquid-to-powder ratio. The fabricated cement sets within clinically preferred setting time (≤20 minutes) are better injectable (>70%) and also stable at ~7.3-7.4 (physiological pH). The CDHAp phased bone cement was resulted by immersing the fabricated after-set cement in phosphate buffer solution and other similar artificial body fluids and incubated at physiological conditions for seven days, confirmed through the X-ray diffraction and Fourier transform-infrared spectroscopy analyses. The so-formed synthetic apatite-based bone cement holds the acceptable compressive strength (within the range of trabecular bone) with average interconnected pores size falls in a macropores range (~50-200μm) inside the cement, verified by scanning electron microscopy (SEM), mercury intrusion porosimetry and micro-CT analysis techniques. Also, it is biodegradable (degrades ~19-22% within 10-12 weeks) when incubated in artificial body fluids under physiological conditions. The biocompatibility study of the bone cement, when incubated with MG63 cells, shows a significant increase in the cell viability after 3rd day of incubation compared with the control, and the cells were well-attached and spread completely on the surface of the bone cement, confirmed through SEM and fluorescence microscopy analyses. With this all, we can conclude that the developed synthetic macroporous apatite-based bone cement may have the potential to become promising material used as a trabecular bone substitute.

Keywords: calcium deficient hydroxyapatite, synthetic apatite-based bone cement, injectability, macroporosity, trabecular bone substitute

Procedia PDF Downloads 86

Authors: Prudhvinath Reddy Ankireddy, Narasimha Mangadoddy

Abstract:

Spiral concentrators are commonly used in various industries, including mineral and coal processing, to efficiently separate materials based on their density and size. In these concentrators, a mixture of solid particles and fluid (usually water) is introduced as feed at the top of a spiral channel. As the mixture flows down the spiral, centrifugal and gravitational forces act on the particles, causing them to stratify based on their density and size. Spiral flows exhibit complex fluid dynamics, and interactions involve multiple phases and components in the process. Understanding the behavior of these phases within the spiral concentrator is crucial for achieving efficient separation. An experimental bi-component particle interaction study is conducted in this work utilizing magnetite (heavier density) and silica (lighter density) with different proportions processed in the spiral concentrator. The observation separation reveals that denser particles accumulate towards the inner region of the spiral trough, while a significant concentration of lighter particles are found close to the outer edge. The 5th turn of the spiral trough is partitioned into five zones to achieve a comprehensive distribution analysis of bicomponent particle segregation. Samples are then gathered from these individual streams using an in-house sample collector, and subsequent analysis is conducted to assess component segregation. Along the trough, there was a decline in the concentration of coarser particles, accompanied by an increase in the concentration of lighter particles. The segregation pattern indicates that the heavier coarse component accumulates in the inner zone, whereas the lighter fine component collects in the outer zone. The middle zone primarily consists of heavier fine particles and lighter coarse particles. The zone-wise results reveal that there is a significant fraction of segregation occurs in inner and middle zones. Finer magnetite and silica particles predominantly accumulate in outer zones with the smallest fraction of segregation. Additionally, numerical simulations are also carried out using the computational fluid dynamics (CFD) model based on the volume of fluid (VOF) approach incorporating the RSM turbulence model. The discrete phase model (DPM) is employed for particle tracking, thereby understanding the particle segregation of magnetite and silica along the spiral trough.

Keywords: spiral concentrator, bi-component particle segregation, computational fluid dynamics, discrete phase model

Procedia PDF Downloads 67

Authors: Abdul Mutolib, Yonariza Mahdi, Hanung Ismono

Abstract:

The existence of forests is essential to human lives on earth, but its existence is threatened by forest deforestations and degradations. Forest deforestations and degradations in Indonesia is not only caused by the illegal activity by the company or the like, even today many cases in Indonesia forest damage caused by human activities, one of which cut down forests for agriculture and plantations. In West Sumatra, community forest management are the result supported the enactment of customary land tenure, including ownership of land within the forest. Indigenous forest management have a positive benefit, which gives the community an opportunity to get livelihood and income, but if forest management practices by indigenous peoples is not done wisely, then there is the destruction of forests and cause adverse effects on the environment. Based on intensive field works in Dhamasraya District employing some data collection techniques such as key informant interviews, household surveys, secondary data analysis, and satellite image interpretation. This paper answers the following questions; how the impact of forest management by local communities on forest conditions (foccus in Forest Production and Limited Production Forest) and knowledge of the local community on the benefits of forests. The site is a Nagari Bonjol, Dharmasraya District, because most of the forest in Dharmasraya located and owned by Nagari Bonjol community. The result shows that there is damage to forests in Dharmasraya because of forest management activities by local communities. Damage to the forest area of 33,500 ha in Dharmasraya because forests are converted into oil palm and rubber plantations with monocultures. As a result of the destruction of forests, water resources are also diminishing, and the community has experienced a drought in the dry season due to forest cut down and replaced by oil palm plantations. Knowledge of the local community on the benefits of low forest, the people considered that the forest does not have better benefits and cut down and converted into oil palm or rubber plantations. Local people do not understand the benefits of ecological and environmental services that forests. From the phenomena in Dharmasraya on land ownership, need to educate the local community about the importance of protecting the forest, and need a strategy to integrate forests management to keep the ecological functions that resemble the woods and counts the economic benefits for the welfare of local communities. One alternative that can be taken is to use forest management models agroforestry smallholders in accordance with the characteristics of the local community who still consider the economic, social and environmental.

Keywords: community, customary land, farmer plantations, and forests

Procedia PDF Downloads 335

Authors: Xiao-Hua Zhu, Xin Yuan, Yi-Ran Zhao

Abstract:

High-cadmium pollution in rice is a serious problem in many parts of China. Many kinds of remediation technologies have been tested and applied in many farmlands. Because of the productive function of the farmland, most technologies are inappropriate due to their destruction to the tillage soil layer. And the large labours and expensive fees of many technologies are also the restrictive factors for their applications. The conception of 'Root Micro-Geochemical Barrier' was proposed to reduce cadmium (Cd) bioavailability and the concentration of the cadmium in rice. Remediation and mitigation techniques were demonstrated on contaminated farmland in the downstream of some mine. According to the rule of rice growth, Cd would be absorbed by the crops in every growth stage, and the plant-absorb efficiency in the first stage of the tillering stage is almost the highest. We should create a method to protect the crops from heavy metal pollution, which could begin to work from the early growth stage. Many materials with repair property get our attention. The materials will create a barrier preventing Cd from being absorbed by the crops during all the growing process because the material has the ability to adsorb soil-Cd and making it losing its migration activity. And we should choose a good chance to put the materials into the crop-growing system cheaply as soon as early. Per plant, rice has a little root system scope, which makes the roots reach about 15cm deep and 15cm wide. So small root radiation area makes it possible for all the Cd approaching the roots to be adsorbed with a small amount of adsorbent. Mixing the remediation materials with the seed-raising soli and adding them to the tillage soil in the process of transplanting seedlings, we can control the soil-Cd activity in the range of roots to reduce the Cd-amount absorbed by the crops. Of course, the mineral materials must have enough adsorptive capacity and no additional pollution. More than 3000 square meters farmlands have been remediated. And on the application of root micro-geochemical barrier, the Cd-concentration in rice and the remediation-cost have been decreased by 90% and 80%, respectively, with little extra labour brought to the farmers. The Cd-concentrations in rice from remediated farmland have been controlled below 0.1 ppm. The remediation of one acre of contaminated cropland costs less than $100. The concept has its advantage in the remediation of paddy field contaminated by Cd, especially for the field with outside pollution sources.

Keywords: cadmium pollution, growth stage, cost, root micro-geochemistry barrier

Procedia PDF Downloads 84

Authors: Lin Po-Hsi, Sheu Ming-Thau

Abstract:

Urea cycle disorders (UCD) are rare genetic metabolic disorders that compromise the body's urea cycle. Sodium phenylbutyrate (SPB) is a medication commonly administered in tablet or powder form to lower ammonia levels. Nonetheless, its high sodium content poses risks to sodium-sensitive UCD patients. This necessitates the creation of an alternative drug formulation to mitigate sodium load and optimize drug delivery for UCD patients. This study focused on crafting a novel oral drug formulation for UCD, leveraging choline bicarbonate and phenylbutyric acid. The active pharmaceutical ingredient-ionic liquids (API-ILs) and therapeutic deep eutectic systems (THEDES) were formed by combining these with choline chloride. These systems display characteristics like maintaining a liquid state at room temperature and exhibiting enhanced solubility. This in turn amplifies drug dissolution rate, permeability, and ultimately oral bioavailability. Incorporating choline-based phenylbutyric acid as a substitute for traditional SPB can effectively curtail the sodium load in UCD patients. Our in vitro dissolution experiments revealed that the ILs and DESs, synthesized using choline bicarbonate and choline chloride with phenylbutyric acid, surpassed commercial tablets in dissolution speed. Pharmacokinetic evaluations in SD rats indicated a notable uptick in the oral bioavailability of phenylbutyric acid, underscoring the efficacy of choline salt ILs in augmenting its bioavailability. Additional in vitro intestinal permeability tests on SD rats authenticated that the ILs, formulated with choline bicarbonate and phenylbutyric acid, demonstrate superior permeability compared to their sodium and acid counterparts. To conclude, choline salt ILs developed from choline bicarbonate and phenylbutyric acid present a promising avenue for UCD treatment, with the added benefit of reduced sodium load. They also hold merit in formulation engineering. The sustained-release capabilities of DESs position them favorably for drug delivery, while the low toxicity and cost-effectiveness of choline chloride signal potential in formulation engineering. Overall, this drug formulation heralds a prospective therapeutic avenue for UCD patients.

Keywords: phenylbutyric acid, sodium phenylbutyrate, choline salt, ionic liquids, deep eutectic systems, oral bioavailability

Procedia PDF Downloads 115

Authors: Sushil Pradhan

Abstract:

Biotechnology contributes to sustainable development in several ways such as biofertilizer production, biopesticide production and management of environmental pollution, tissue culture and biodiversity conservation in vitro, in vivo and in situ, Insectivorous medicinal plant Drosera burmannii Vahl belongs to the Family-Droseraceae under Order-Caryophyllales, Dicotyledoneae, Angiospermeae which has 31 (thirty one) living genera and 194 species besides 7 (seven) extinct (fossil) genera. Locally it is known as “Patkanduri” in Odia. Its Hindi name is “Mukhajali” and its English name is “Sundew”. The earliest species of Drosera was first reported in 1753 by Carolous Linnaeus called Drosera indica L (Indian Sundew). The latest species of Drosera reported by Fleisch A, Robinson, AS, McPherson S, Heinrich V, Gironella E and Madulida D.A. (2011) is Drosera ultramafica from Malaysia. More than 50 % species of Drosera have been reported from Australia and next to Australia is South Africa. India harbours only 3 species such as D. indica L, Drosera burmannii Vahl and D. peltata L. From our Odisha only D. burmannii Vahl is being reported for the first time from the district of Subarnapur near Sonepur (Arjunpur Reserve Forest Area). Drosera plant is autotrophic but to supplement its Nitrogen (N2) requirement it adopts heterotrophic mode of nutrition (insectivorous/carnivorous) as well. The colour of plant in mostly red and about 20-30cm in height with beautiful pink or white pentamerous flowers. Plants grow luxuriantly during November to February in shady and moist places near small water bodies of running water stream. Medicinally it is a popular herb in the locality for the treatment of cold and cough in children in rainy season by the local Doctors (Kabiraj and Baidya). In the present field investigation an attempt has been made to understand the unique reproductive phase and life cycle of the plant thereby planning for its conservation and propagation through various techniques of tissue culture and biotechnology. More importantly besides morphological and anatomical studies, cytological investigation is being carried out to find out the number of chromosomes in the cell and its genomics as there is no such report as yet for Drosera burmannii Vahl. The ecological significance and biodiversity conservation of Drosera with special reference to energy, environmental and chemical engineering has been discussed in the research paper presentation.

Keywords: insectivorous, medicinal, drosera, biotechnology, chromosome, genome

Procedia PDF Downloads 383

Authors: Chul Hyun Park

Abstract:

Background:Repair using the Achillon deviceis a representative mini-open repair technique;however, the limitations of this technique includethe need for special instruments and decreasedrepair strength.A modifiedmini-open repair using ring forcepsmight overcome these limitations. Purpose:This study was performed to compare the Achillon device with ring forceps in mini-open repairsof acute Achilles tendon rupture. Study Design:This was a retrospective cohort study, and the level of evidence was3. Methods:Fifty patients (41 men and 9 women), withacute Achilles tendon rupture on one foot, were consecutively treated using mini-open repair techniques. The first 20 patients were treated using the Achillon device (Achillon group) and the subsequent 30 patients were treated using a ring forceps (Forcep group). Clinical, functional, and isokinetic results,and postoperative complications were compared between the two groups at the last follow-up. Clinical evaluations wereperformed using the American Orthopedic Foot and Ankle Society (AOFAS) score, Achilles tendon Total Rupture Score (ATRS), length of incision, and operation time. Functional evaluationsincludedactive range of motion (ROM) of the ankle joint, maximum calf circumference (MCC), hopping test, and single limb heel-rise (SLHR) test. Isokinetic evaluations were performed using the isokinetic test for ankle plantar flexion. Results:The AOFAS score (p=0.669), ATRS (p=0.753), and length of incision (p=0.305) were not significantly different between the groups. Operative times in the Achillon group were significantly shorter than that in the Forcep group (p<0.001).The maximum height of SLHR (p=0.023) and number of SLHRs (p=0.045) in the Forcep group were significantly greater than that in the Achillon group. No significant differences in the mean peak torques for plantar flexion at angular speeds of 30°/s (p=0.219) and 120°/s (p=0.656) were detected between the groups. There was no significant difference in the occurrence of postoperative complications between the groups (p=0.093). Conclusion:The ring forceps technique is comparable with the Achillon technique with respect to clinical, functional, and isokinetic results and the postoperative complications. Given that no special instrument is required, the ring forceps technique could be a better option for acute Achilles tendon rupture repair.

Keywords: achilles tendon, acute rupture, repair, mini-open

Procedia PDF Downloads 81

Authors: Gianmaria Califano, Júlio Augusto Lucena Maciel, Olfa Zarrouk, Miguel Damasio, Jose Silvestre, Ana Margarida Fortes

Abstract:

Global warming, with rapid and sudden changes in meteorological conditions, is one of the major constraints to ensuring agricultural and crop resilience in the Mediterranean regions. Several strategies are being adopted to reduce the pressure of drought stress on grapevines at regional and local scales: improvements in the irrigation systems, adoption of interline cover crops, and adaptation of pruning techniques. However, still, more can be achieved if also microbial compartments associated with plants are considered in crop management. It is known that the microbial community change according to several factors such as latitude, plant variety, age, rootstock, soil composition and agricultural management system. Considering the increasing pressure of the biotic and abiotic stresses, it is of utmost necessity to also evaluate the effects of drought on the microbiome associated with the grapevine, which is a commercially important crop worldwide. In this study, we characterize the diversity and the structure of the microbial community under three long-term irrigation levels (100% ETc, 50% ETc and rain-fed) in a drought-tolerant grapevine cultivar present worldwide, Syrah. To avoid the limitations of culture-dependent methods, amplicon sequencing with target primers for bacteria and fungi was applied to the same soil samples. The use of the DNeasy PowerSoil (Qiagen) extraction kit required further optimization with the use of lytic enzymes and heating steps to improve DNA yield and quality systematically across biological treatments. Target regions (16S rRNA and ITS genes) of our samples are being sequenced with Illumina technology. With bioinformatic pipelines, it will be possible to obtain a characterization of the bacterial and fungal diversity, structure and composition. Further, the microbial communities will be assessed for their functional activity, which remains an important metric considering the strong inter-kingdom interactions existing between plants and their associated microbiome. The results of this study will lay the basis for biotechnological applications: in combination with the establishment of a bacterial library, it will be possible to explore the possibility of testing synthetic microbial communities to support plant resistance to water scarcity.

Keywords: microbiome, metabarcoding, soil, vinegrape, syrah, global warming, crop sustainability

Procedia PDF Downloads 123

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

Abstract:

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

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

Procedia PDF Downloads 136

Authors: Erick C. Valverde, Wansu Lim

Abstract:

Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

Procedia PDF Downloads 118

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

Abstract:

Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

Procedia PDF Downloads 54

Authors: Temitayo Tosin Alawiye

Abstract:

Plant disease control is important in maintaining plant vigour, grain quantity, abundance of food, feed, and fibre produced by farmers all over the world. Farmers make use of different methods in controlling these diseases but one of the commonly used method is the use of chemicals. However, the continuous and excessive usages of these agrochemicals pose a danger to the environment, man and wildlife. The more the population growth the more the food security challenge which leads to more pressure on agronomic growth. Agricultural waste also known as green waste are the residues from the growing and processing of raw agricultural products such as fruits, vegetables, rice husk, corn cob, mushroom growth medium waste, coconut husk. They are widely used in land bioremediation, crop production and protection which include disease control. These agricultural wastes help the crop by improving the soil fertility, increase soil organic matter and reduce in many cases incidence and severity of disease. The objective was to review the agricultural waste that has worked effectively against certain soil-borne diseases such as Fusarium oxysporum, Pythiumspp, Rhizoctonia spp so as to help minimize the use of chemicals. Climate change is a major problem of agriculture and vice versa. Climate change and agriculture are interrelated. Change in climatic conditions is already affecting agriculture with effects unevenly distributed across the world. It will increase the risk of food insecurity for some vulnerable groups such as the poor in Sub Saharan Africa. The food security challenge will become more difficult as the world will need to produce more food estimated to feed billions of people in the near future with Africa likely to be the biggest hit. In order to surmount this hurdle, smallholder farmers in Africa must embrace climate-smart agricultural techniques and innovations which includes the use of green waste in agriculture, conservative agriculture, pasture and manure management, mulching, intercropping, etc. Training and retraining of smallholder farmers on the use of green energy to mitigate the effect of climate change should be encouraged. Policy makers, academia, researchers, donors, and farmers should pay more attention to the use of green energy as a way of reducing incidence and severity of soilborne plant diseases to solve looming food security challenges.

Keywords: agricultural waste, climate change, green energy, soil borne plant disease

Procedia PDF Downloads 269

Authors: Lucero Gonzalez, Salvador Alfaro

Abstract:

Carbon dioxide (CO2) and methane (CH4) are considered as the compounds with higher abundance among the greenhouse gases (CO2, NOx, SOx, CxHx, etc.), due to its higher concentration, this two gases have a greater impact in the environment pollution and provokes global warming. So, recovery, disposal and subsequent reuse, are of great interest, especially from the ecological and health perspective. By one hand, porous inorganic materials are good candidates to capture gases, because these type of materials are higher stability from the point view of thermal, chemical and mechanical under adsorption gas processes. By another hand, during the design and the synthetic preparation of the porous materials is possible add other intrinsic properties (physicochemical and structural) by adding chemical compounds as dopants or using structured directed agents or surfactants to improve the porous structure, the above features allow to have alternative materials for separation, capture and storage of greenhouse gases. In this work, ordered mesoporous materials base silica were prepared using Surfynol as surfactant. The surfactant micelles are commonly used as self-assembly templates for the development of new structure porous silica’s, adding a variety of textures and structures. By another hand, the Surfynol is a commercial surfactant, is non-ionic, for that is necessary determine its critical micelles concentration (cmc) by the pyrene I1/I3 ratio method, before to prepare silica particles. One time known the CMC, a precursor gel was prepared via sol-gel process at room temperature using TEOS as silica precursor, NH4OH as catalyst, Surfynol as template and H2O as solvent. Then, the gel precursor was treatment hydrothermally in a Teflon-lined stainless steel autoclave with a volume of 100 mL and kept at 100 ºC for 24 h under static conditions in a convection oven. After that, the porous silica particles obtained were impregnated with lithium to improve the CO2 adsorption capacity. Then the silica particles were characterized physicochemical, morphology and structurally, by XRD, FTIR, BET and SEM techniques. The thermal stability and the CO2 adsorption capacity was evaluated by thermogravimetric analysis (TGA). According the results, we found that the Surfynol is a good candidate to prepare silica particles with an ordered structure. Also the TGA analysis shown that the particles has a good thermal stability in the range of 250 °C and 800 °C. The best materials had, the capacity to adsorbing 70 and 90 mg per gram of silica particles and its CO2 adsorption capacity depends on the way to thermal pretreatment of the porous silica before of the adsorption experiments and of the concentration of surfactant used during the synthesis of silica particles. Acknowledgments: This work was supported by SIP-IPN through project SIP-20161862.

Keywords: CO2 adsorption, lithium as dopant, porous silica, surfynol as surfactant, thermogravimetric analysis

Procedia PDF Downloads 268

Authors: Bahaa Eldin A. Fouda, Khaled N. Yossef, Mohamed Elhosseny, Ahmed Lotfy, Mohamed Salama, Mohamed Sobh

Abstract:

Developmental neurotoxicity (DNT) entails the toxic effects imparted by various chemicals on the brain during the early childhood period. As human brains are vulnerable during this period, various chemicals would have their maximum effects on brains during early childhood. Some toxicants have been confirmed to induce developmental toxic effects on CNS e.g. lead, however; most of the agents cannot be identified with certainty due the defective nature of predictive toxicology models used. A novel alternative method that can overcome most of the limitations of conventional techniques is the use of 3D neurospheres system. This in-vitro system can recapitulate most of the changes during the period of brain development making it an ideal model for predicting neurotoxic effects. In the present study, we verified the possible DNT of epoxomicin which is a naturally occurring selective proteasome inhibitor with anti-inflammatory activity. Rat neural progenitor cells were isolated from rat embryos (E14) extracted from placental tissue. The cortices were aseptically dissected out from the brains of the fetuses and the tissues were triturated by repeated passage through a fire-polished constricted Pasteur pipette. The dispersed tissues were allowed to settle for 3 min. The supernatant was, then, transferred to a fresh tube and centrifuged at 1,000 g for 5 min. The pellet was placed in Hank’s balanced salt solution cultured as free-floating neurospheres in proliferation medium. Two doses of epoxomicin (1µM and 10µM) were used in cultured neuropsheres for a period of 14 days. For proliferation analysis, spheres were cultured in proliferation medium. After 0, 4, 5, 11, and 14 days, sphere size was determined by software analyses. The diameter of each neurosphere was measured and exported to excel file further to statistical analysis. For viability analysis, trypsin-EDTA solution were added to neurospheres for 3 min to dissociate them into single cells suspension, then viability evaluated by the Trypan Blue exclusion test. Epoxomicin was found to affect proliferation and viability of neuropsheres, these effects were positively correlated to doses and progress of time. This study confirms the DNT effects of epoxomicin on 3D neurospheres model. The effects on proliferation suggest possible gross morphologic changes while the decrease in viability propose possible focal lesion on exposure to epoxomicin during early childhood.

Keywords: neural progentor cells, epoxomicin, neurosphere, medical and health sciences

Procedia PDF Downloads 426

Authors: I. Poot-Ocejo, H. Silva-Poot, J. C. Cruz, A. Yeladaqui-Tello

Abstract:

Mexico has remarkable archaeological remains mainly in the Maya area, which are critical to the preservation of our cultural heritage, so the authorities have an interest in preserving and restoring these vestiges of the most original way, by employing techniques traditional, which has advantages such as compatibility, durability, strength, uniformity and chemical composition. Recent studies have confirmed the addition of natural resins extracted from the bark of trees, of which Brosium alicastrum (Ramon) has been the most evaluated, besides being one of the most abundant species in the vicinity of the archaeological sites, like that Manilkara Zapota (Chicozapote). Therefore, the objective is to determine if these resins are capable of being employed in archaeological restoration. This study shows the results of the chemical composition and physical-mechanical behavior of mortar mixtures eight made with commercial lime and off by hand, calcium sand, resins added with Brosium alicastrum (Ramon) and Manilkara zapota (Chicozapote), where determined and quantified properties and chemical composition of the resins by X-Ray Fluorescence (XRF), the pH of the material was determined, indicating that both resins are acidic (3.78 and 4.02), and the addition rate maximum was obtained from resins in water by means of ultrasonic baths pulses, being in the case of 10% Manilkara zapota, because it contains up to 40% rubber and for 40% alicastrum Brosium contain less rubber. Through quantitative methodology, the compressive strength 96 specimens of 5 cm x 5 cm x 5 cm of mortar binding, 72 with partial substitution of water mixed with natural resins in proportions 5 to 10% in the case was evaluated of Manilkara Zapota, for Brosium alicastrum 20 and 40%, and 12 artificial resin and 12 without additive (mortars witnesses). 24 specimens likewise glued brick with mortar, for testing shear adhesion was found where, then the microstructure more conducive additions was determined by SEM analysis were prepared sweep. The test results indicate that the addition Manilkara zapota resin in the proportion of 10% 1.5% increase in compressive strength and 1% with respect to adhesion, compared to the control without addition mortar; In the case of Brosium alicastrum results show that compressive strengths and adhesion were insignificant compared to those made with registered by Manilkara zapota mixtures. Mortars containing the natural resins have improvements in physical properties and increase the mechanical strength and adhesion, compared to those who do not, in addition to the components are chemically compatible, therefore have considered that can be employed in Archaeological restoration.

Keywords: lime, mortar, natural resins, Manilkara zapota mixtures, Brosium alicastrum

Procedia PDF Downloads 371

Authors: Bryan Clark B. Hernandez, Eugene C. Herrera, Kazuo Nadaoka

Abstract:

Mangrove forests thriving in intertidal zones in tropical and subtropical regions of the world offer a range of ecosystem services including carbon storage and sequestration. They can regulate the detrimental effects of climate change due to carbon releases two to four times greater than that of mature tropical rainforests. Moreover, they are effective natural defenses against storm surges and tsunamis. However, their proliferation depends significantly on the prevailing hydroperiod at the coast. In the Philippines, these coastal ecosystems have been severely threatened with a 50% decline in areal extent observed from 1918 to 2010. The highest decline occurred in 1950 - 1972 when national policies encouraged the development of fisheries and aquaculture. With the intensive land use conversion upstream, changes in the freshwater-saltwater envelope at the coast may considerably impact mangrove growth conditions. This study investigates a developing urban watershed in Kalibo, Aklan province with a 220-hectare mangrove forest replanted for over 30 years from coastal mudflats. Since then, the mangrove forest was sustainably conserved and declared as protected areas. Hybrid land cover classification technique was used to classify Landsat images for years, 1990, 2010, and 2017. Digital elevation model utilized was Interferometric Synthetic Aperture Radar (IFSAR) with a 5-meter resolution to delineate the watersheds. Using numerical modelling techniques, the hydrologic and hydraulic analysis of the influence of land cover change to flow and sediment dynamics was simulated. While significant land cover change occurred upland, thereby increasing runoff and sediment loads, the mangrove forests abundance adjacent to the coasts for the urban watershed, was somehow sustained. However, significant alteration of the coastline was observed in Kalibo through the years, probably due to the massive land-use conversion upstream and significant replanting of mangroves downstream. Understanding the hydrologic-hydraulic response of these watersheds to change land cover is essential to helping local government and stakeholders facilitate better management of these mangrove ecosystems.

Keywords: coastal mangroves, hydrologic model, land cover change, Philippines

Procedia PDF Downloads 122

Authors: Ortega Ivan, De La Plaza Edurne

Abstract:

Background: Spain and other European countries have implemented Uncontrolled Donation after Cardiac Death (uDCD) programs. After 15 years of experience in Spain, many things have changed. Recent evidence and technical breakthroughs achieved in resuscitation are relevant for uDCD programs and raise some ethical concerns related to these protocols. Aim: To rethink current uDCD programs in the light of recent evidence on available therapeutic procedures applicable to victims of out-of-hospital cardiac arrest (OHCA). To address the following question: What is the current standard of treatment owed to victims of OHCA before including them in an uDCD protocol? Materials and Methods: Review of the scientific and ethical literature related to both uDCD programs and innovative resuscitation techniques. Results: 1) The standard of treatment received and the chances of survival of victims of OHCA depend on whether they are classified as Non-Heart Beating Patients (NHBP) or Non-Heart-Beating-Donors (NHBD). 2) Recent studies suggest that NHBPs are likely to survive, with good quality of life, if one or more of the following interventions are performed while ongoing CPR -guided by suspected or known cause of OHCA- is maintained: a) direct access to a Cath Lab-H24 or/and to extra-corporeal life support (ECLS); b) transfer in induced hypothermia from the Emergency Medical Service (EMS) to the ICU; c) thrombolysis treatment; d) mobile extra-corporeal membrane oxygenation (mini ECMO) instituted as a bridge to ICU ECLS devices. 3) Victims of OHCA who cannot benefit from any of these therapies should be considered as NHBDs. Conclusion: Current uDCD protocols do not take into account recent improvements in resuscitation and need to be adapted. Operational criteria to distinguish NHBDs from NHBP should seek a balance between the technical imperative (to do whatever is possible), considerations about expected survival with quality of life, and distributive justice (costs/benefits). Uncontrolled DCD protocols can be performed in a way that does not hamper the legitimate interests of patients, potential organ donors, their families, the organ recipients, and the health professionals involved in these processes. Families of NHBDs’ should receive information which conforms to the ethical principles of respect of autonomy and transparency.

Keywords: uncontrolled donation after cardiac death resuscitation, refractory cardiac arrest, out of hospital cardiac, arrest ethics

Procedia PDF Downloads 237

Authors: Emilio Galdeano-Gómez, Ángeles Godoy-Durán, Juan C. Pérez-Mesa, Laura Piedra-Muñoz

Abstract:

Eco-efficiency is receiving ever-increasing interest as an indicator of sustainability, as it links environmental and economic performances in productive activities. In agriculture, these indicators and their determinants prove relevant due to the close relationships in this activity between the use of natural resources, which is generally limited, and the provision of basic goods to society. In this context, various analyses have focused on eco-efficiency by considering individual family farms as the basic production unit. However, not only must the measure of efficiency be taken into account, but also the existence of a series of factors which constitute socio-economic, political-institutional, and environmental determinants. Said factors have been studied to a lesser extent in the literature. The present work analyzes eco-efficiency at a micro level, focusing on small-scale family farms as the main decision-making units in horticulture in southeast Spain, a sector which represents about 30% of the fresh vegetables produced in the country and about 20% of those consumed in Europe. The objectives of this study are a) to obtain a series of eco-efficiency indicators by estimating several pressure ratios and economic value added in farming, b) to analyze the influence of specific social, economic and environmental variables on the aforementioned eco-efficiency indicators. The present work applies the method of Data Envelopment Analysis (DEA), which calculates different combinations of environmental pressures (water usage, phytosanitary contamination, waste management, etc.) and aggregate economic value. In a second stage, an analysis is conducted on the influence of the socio-economic and environmental characteristics of family farms on the eco-efficiency indicators, as endogeneous variables, through the use of truncated regression and bootstrapping techniques, following Simar-Wilson methodology. The results reveal considerable inefficiency in aspects such as waste management, while there is relatively little inefficiency in water usage and nitrogen balance. On the other hand, characteristics, such as product specialization, the adoption of quality certifications and belonging to a cooperative do have a positive impact on eco-efficiency. These results are deemed to be of interest to agri-food systems structured on small-scale producers, and they may prove useful to policy-makers as regards managing public environmental programs in agriculture.

Keywords: data envelopment analysis, eco-efficiency, family farms, horticulture, socioeconomic features

Procedia PDF Downloads 193

Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles

Abstract:

The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.

Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite

Procedia PDF Downloads 228

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 125

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 80

Authors: D. Signore, M. Ferraiuolo, P. Caramuta, O. Petrella, C. Toscano

Abstract:

The Digital Image Correlation (DIC) is a newly developed optical technique that is spreading in all engineering sectors because it allows the non-destructive estimation of the entire surface deformation without any contact with the component under analysis. These characteristics make the DIC very appealing in all the cases the global deformation state is to be known without using strain gages, which are the most used measuring device. The DIC is applicable to any material subjected to distortion caused by either thermal or mechanical load, allowing to obtain high-definition mapping of displacements and deformations. That is why in the civil and the transportation industry, DIC is very useful for studying the behavior of metallic materials as well as of composite materials. DIC is also used in the medical field for the characterization of the local strain field of the vascular tissues surface subjected to uniaxial tensile loading. DIC can be carried out in the two dimension mode (2D DIC) if a single camera is used or in a three dimension mode (3D DIC) if two cameras are involved. Each point of the test surface framed by the cameras can be associated with a specific pixel of the image, and the coordinates of each point are calculated knowing the relative distance between the two cameras together with their orientation. In both arrangements, when a component is subjected to a load, several images related to different deformation states can be are acquired through the cameras. A specific software analyzes the images via the mutual correlation between the reference image (obtained without any applied load) and those acquired during the deformation giving the relative displacements. In this paper, a metrological characterization of the digital image correlation is performed on aluminum and composite targets both in static and dynamic loading conditions by comparison between DIC and strain gauges measures. In the static test, interesting results have been obtained thanks to an excellent agreement between the two measuring techniques. In addition, the deformation detected by the DIC is compliant with the result of a FEM simulation. In the dynamic test, the DIC was able to follow with a good accuracy the periodic deformation of the specimen giving results coherent with the ones given by FEM simulation. In both situations, it was seen that the DIC measurement accuracy depends on several parameters such as the optical focusing, the parameters chosen to perform the mutual correlation between the images and, finally, the reference points on image to be analyzed. In the future, the influence of these parameters will be studied, and a method to increase the accuracy of the measurements will be developed in accordance with the requirements of the industries especially of the aerospace one.

Keywords: accuracy, deformation, image correlation, mechanical analysis

Procedia PDF Downloads 311

Authors: Huinan Zhang, Wenjie Jiang

Abstract:

Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

Procedia PDF Downloads 63

Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

Abstract:

In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

Procedia PDF Downloads 417

Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

Abstract:

Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

Procedia PDF Downloads 267

Authors: Nadezhda Kvatashidze, Elena Kharabadze

Abstract:

It is broadly known that lease is a flexible means of funding enterprises. Lease reduces the risk related to access and possession of assets, as well as obtainment of funding. Therefore, it is important to refine lease accounting. The lease accounting regulations under the applicable standard (International Accounting Standards 17) make concealment of liabilities possible. As a result, the information users get inaccurate and incomprehensive information and have to resort to an additional assessment of the off-balance sheet lease liabilities. In order to address the problem, the International Financial Reporting Standards Board decided to change the approach to lease accounting. With the deficiencies of the applicable standard taken into account, the new standard (IFRS 16 ‘Leases’) aims at supplying appropriate and fair lease-related information to the users. Save certain exclusions; the lessee is obliged to recognize all the lease agreements in its financial report. The approach was determined by the fact that under the lease agreement, rights and obligations arise by way of assets and liabilities. Immediately upon conclusion of the lease agreement, the lessee takes an asset into its disposal and assumes the obligation to effect the lease-related payments in order to meet the recognition criteria defined by the Conceptual Framework for Financial Reporting. The payments are to be entered into the financial report. The new lease accounting standard secures supply of quality and comparable information to the financial information users. The International Accounting Standards Board and the US Financial Accounting Standards Board jointly developed IFRS 15: ‘Revenue from Contracts with Customers’. The standard allows the establishment of detailed revenue recognition practical criteria such as identification of the performance obligations in the contract, determination of the transaction price and its components, especially price variable considerations and other important components, as well as passage of control over the asset to the customer. IFRS 15: ‘Revenue from Contracts with Customers’ is very similar to the relevant US standards and includes requirements more specific and consistent than those of the standards in place. The new standard is going to change the recognition terms and techniques in the industries, such as construction, telecommunications (mobile and cable networks), licensing (media, science, franchising), real property, software etc.

Keywords: assessment of the lease assets and liabilities, contractual liability, division of contract, identification of contracts, contract price, lease identification, lease liabilities, off-balance sheet, transaction value

Procedia PDF Downloads 319

Authors: Elif Tugce Aksun Tumerkan, Chris Lowe, Hannah Krupa

Abstract:

Fluorescent proteins are self-sufficient in forming chromophores with a visible wavelength from 3 amino acids sequence within their own polypeptide structure. This chromophore – a molecule that absorbs a photon of light and exhibits an energy transition equal to the energy of the absorbed photon. Fluorescent proteins (FPs) consisted of a chain of 238 amino acid residues and composed of 11 beta strands shaped in a cylinder surrounding an alpha helix structure. A better understanding of the system of the chromospheres and the increasing advance in protein engineering in recent years, the properties of FPs offers the potential for new applications. They have used sensors and probes in molecular biology and cell-based research that giving a chance to observe these FPs tagged cell localization, structural variation and movement. For clarifying functional uses of fluorescent proteins, electrophoretic properties of these proteins are one of the most important parameters. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) analysis is used for determining electrophoretic properties commonly. While there are many techniques are used for determining the functionality of protein-based research, SDS-PAGE analysis can only provide a molecular level assessment of the proteolytic fragments. Before SDS-PAGE analysis, fluorescent proteins need to successfully purified. Due to directly purification of the target, FPs is difficult from the animal, gene expression is commonly used which must be done by transformation with the plasmid. Furthermore, used gel within electrophoresis and staining agents properties have a key role. In this review, the different factors that have the impact on the electrophoretic properties of fluorescent proteins explored. Fluorescent protein separation and purification are the essential steps before electrophoresis that should be done very carefully. For protein purification, gene expression process and following steps have a significant function. For successful gene expression, the properties of selected bacteria for expression, used plasmid are essential. Each bacteria has own characteristics which are very sensitive to gene expression, also used procedure is the important factor for fluorescent protein expression. Another important factors are gel formula and used staining agents. Gel formula has an effect on the specific proteins mobilization and staining with correct agents is a key step for visualization of electrophoretic bands of protein. Visuality of proteins can be changed depending on staining reagents. Apparently, this review has emphasized that gene expression and purification have a stronger effect than electrophoresis protocol and staining agents.

Keywords: cell biology, gene expression, staining agents, SDS-page

Procedia PDF Downloads 194