Search results for: precision application

Authors: Andrei Tiberiu Cucuruz, Ecaterina Andronescu, Cristina Daniela Ghitulica, Andreia Cucuruz

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In modern dentistry, the application of resin-based composites continues to increase and in the majority of countries has completely replaced mercury amalgams. Alumina (Al2O3) is a representative bioinert ceramic with a variety of applications in industry as well as in medicine. Alumina has the potential to improve electrical resistivity and thermal conductivity of polymers. The application of poly(methacrylic acid) (PMAA) in medicine was poorly investigated in the past but can lead to good results by the incorporation of alumina particles that can bring bioinertness to the composite. However, because of the differences related to chemical bonding of these materials, the interaction is very weak at the interface leading to no significant values in practical situations. The aim of this work was to modify the structure of alumina with silane coupling agents and to study the influence of silanization on the physicomechanical properties of the resulting composite materials. Two silanes were used in this study: 3-aminopropyl-trimethoxysilane (APTMS) and dichlorodimethylsilane (DCDMS). Both silanes proved to have a significant effect on the overall performance of composites by establishing bonds with the polymer matrix and the filler. All these improvements in dental adhesive systems made for bonding resin composites to tooth structure have enhanced the clinical application of polymeric restorative materials to the position that they are now considered the material of choice for esthetic restoration.

Keywords: alumina, compressive strength, dental materials, silane coupling agents, poly(methacrylic acid)

Procedia PDF Downloads 351

Authors: A. E. Dumitriu

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The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

Procedia PDF Downloads 429

Authors: Panasbodee Thachaopas, Duangdorm Gamnerdsap, Waraporn Inthip, Arissara Pungpa

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LDD’s IM Farm or Land Development Department’s Integrated Management Farm is the agricultural simulation application developed by Land Development Department relies on actual data in simulation game to grow 12 cash crops which are rice, corn, cassava, sugarcane, soybean, rubber tree, oil palm, pineapple, longan, rambutan, durian, and mangosteen. Launching in simulation game, players could select preferable areas for cropping from base map or Orthophoto map scale 1:4,000. Farm management is simulated from field preparation to harvesting. The system uses soil group, and present land use database to facilitate player to know whether what kind of crop is suitable to grow in each soil groups and integrate LDD’s data with other agencies which are soil types, soil properties, soil problems, climate, cultivation cost, fertilizer use, fertilizer price, socio-economic data, plant diseases, weed, pest, interest rate for taking on loan from Bank for Agriculture and Agricultural Cooperatives (BAAC), labor cost, market prices. These mentioned data affect the cost and yield differently to each crop. After completing, the player will know the yield, income and expense, profit/loss. The player could change to other crops that are more suitable to soil groups for optimal yields and profits.

Keywords: agricultural simulation, smart farmer, web application, factors of agricultural production

Procedia PDF Downloads 199

Authors: Wahab Ali, Oyebade K. Oyedotun, Adnan Khashman

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Breast cancer remains a threat to the woman’s world in view of survival rates, it early diagnosis and mortality statistics. So far, research has shown that many survivors of breast cancer cases are in the ones with early diagnosis. Breast cancer is usually categorized into stages which indicates its severity and corresponding survival rates for patients. Investigations show that the farther into the stages before diagnosis the lesser the chance of survival; hence the early diagnosis of breast cancer becomes imperative, and consequently the application of novel technologies to achieving this. Over the year, mammograms have used in the diagnosis of breast cancer, but the inconclusive deductions made from such scans lead to either false negative cases where cancer patients may be left untreated or false positive where unnecessary biopsies are carried out. This paper presents the application of artificial neural networks in the prediction of severity of breast tumour (whether benign or malignant) using mammography reports and other factors that are related to breast cancer.

Keywords: breast cancer, intelligent classification, neural networks, mammography

Procedia PDF Downloads 491

Authors: X. S. Wu, H. Jia, P. H. Qian, Z. Zhang, H. L. Cai, F. M. Zhang

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A bipolar resistance switching behaviour is detected for a Ti/TiO2-x/Au memristor device, which is fabricated by a masked designed magnetic sputtering. The current dependence of voltage indicates the curve changes slowly and continuously. When voltage pulses are applied to the device, the set and reset processes maintains linearity, which is used to simulate the synapses. We argue that the conduction mechanism of the device is from the oxygen vacancy channel model, and the resistance of the device change slowly due to the reaction between the titanium electrode and the intermediate layer and the existence of a large number of oxygen vacancies in the intermediate layer. Then, Hopfield neural network is constructed to simulate the behaviour of neural network in image processing, and the accuracy rate is more than 98%. This shows that titanium dioxide memristor has a broad application prospect in high performance neural network simulation.

Keywords: memristor fabrication, neuromorphic computing, bionic synaptic application, TiO₂-based

Procedia PDF Downloads 90

Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

Procedia PDF Downloads 420

Authors: Sujan Mahamud

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Purpose: A major challenge in radiotherapy treatment is to deliver precise dose of radiation to the tumor with minimum dose to the healthy normal tissues. Recently, gel dosimetry has emerged as a powerful tool to measure three-dimensional (3D) dose distribution for complex delivery verification and quality assurance. These dosimeters act both as a phantom and detector, thus confirming the versatility of dosimetry technique. The aim of the study is to know the application of Gel Dosimeters in Radiotherapy and find out the comparison with 1D and 2D dimensional dosimeters. Methods and Materials: The study is carried out from Gel Dosimeter literatures. Secondary data and images have been collected from different sources such as different guidelines, books, and internet, etc. Result: Analyzing, verifying, and comparing data from treatment planning system (TPS) is determined that gel dosimeter is a very excellent powerful tool to measure three-dimensional (3D) dose distribution. The TPS calculated data were in very good agreement with the dose distribution measured by the ferrous gel. The overall uncertainty in the ferrous-gel dose determination was considerably reduced using an optimized MRI acquisition protocol and a new MRI scanner. The method developed for comparing measuring gel data with calculated treatment plans, the gel dosimetry method, was proven to be a useful for radiation treatment planning verification. In 1D and 2D Film, the depth dose and lateral for RMSD are 1.8% and 2%, and max (Di-Dj) are 2.5% and 8%. Other side 2D+ ( 3D) Film Gel and Plan Gel for RMSDstruct and RMSDstoch are 2.3% & 3.6% and 1% & 1% and system deviation are -0.6% and 2.5%. The study is investigated that the result fined 2D+ (3D) Film Dosimeter is better than the 1D and 2D Dosimeter. Discussion: Gel Dosimeters is quality control and quality assurance tool which will used the future clinical application.

Keywords: gel dosimeters, phantom, rmsd, QC, detector

Procedia PDF Downloads 152

Authors: Mustafa Gulsen, Nihan Pekyavas, Emine Atıcı

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Purpose: The aim of this study is to investigate the effects of Kinesio taping on postural stability and in young soccer players. Subjects and Methods: 62 volunteered soccer players from Cayyolu Sports Club were included in our study. Permissions were also taken from the club directors about the inclusion of their players to our study. Soccer players between the age of 12 and 16 were included in our study. Players that had previous injury on lower extremities were excluded from the study. Players were randomly divided into two groups: Kinesio taping (KT) (n=31), and control group (n = 31). KT application including gastrocnemius and quadriceps femoris muscle facilitation techniques were applied to the first group. A rest time for 45 minutes was given in order to see the best effectiveness of the tape. The second group was set as the control group and no application was made. All participants were assessed before the application and 45 minutes later. In order to provide the double-blind design of the study, an experienced physiotherapist has done the assessments and another experienced physiotherapist has done the taping. The patients were randomly assigned to one of the two groups using an online random allocation software program. Postural stability was assessed by using Tetrax Interactive Balance System. Thermographic assessment was done by using FLIR E5 (FLIR Systems AB, Sweden) thermal camera in order to see which muscles have the most thermal activity while maintaining postural stability. Results: Statistically significant differences were found in all assessment parameters in both Kinesio Taping and control groups (all p<0.05) except thermal imaging of dominant gastrocnemius muscle results (p=0.668) (Table 1). In comparison of the two groups, statistically significant differences were found in all parameters (all p<0.05). Conclusion: In this study, we investigated the effects of Kinesio taping on postural stability in young soccer players and found that KT application on Quadriceps and Gastrocnemius muscles may have decreased the risk of falling more than the control group. According to thermal imaging assessments, both Quadriceps and Gastrocnemius muscles may be active in maintaining postural stability but in KT group, the temperature of these muscles are higher which leads us to think that they are more activated.

Keywords: Kinesio taping, fall risk, muscle temperature, postural stability

Procedia PDF Downloads 241

Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

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In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: ¹⁷⁷Lu, breast cancer, compartmental modeling, dosimetry

Procedia PDF Downloads 151

Authors: Hala A. Alrumaih

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It is widely believed that mobile device is a promising technology for lending the opportunity for the third wave of electronic commerce. Mobile devices have changed the way companies do business. Many applications are under development or being incorporated into business processes. In this day, mobile applications are a vital component of any industry strategy. One of the greatest benefits of selling merchandise and providing services on a mobile application is that it widens a company’s customer base significantly. Mobile applications are accessible to interested customers across regional and international borders in different electronic business (e-business) area. But there is a dark side to this success story. The security risks associated with mobile devices and applications are very significant. This paper introduces a broad risk analysis for the various threats, vulnerabilities, and risks in mobile e-business applications and presents some important risk mitigation approaches. It reviews and compares two different frameworks for security assurance in mobile e-business applications. Based on the comparison, the paper suggests some recommendations for applications developers and business owners in mobile e-business application development process.

Keywords: e-business, mobile applications, risk mitigations, security assurance

Procedia PDF Downloads 295

Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

Procedia PDF Downloads 149

Authors: Meryem Aydin, Serdar Karadas, Ercan Ceyhan

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The research was conducted to determine effects of salt concentrations on emergence of cowpea genotypes. Trials were performed during the year of 2014 on the laboratory of Agricultural Faculty, Selcuk University. Emergency trial was set up according to “Randomized Plots Design” by two factors and four replications with three replications. Samandag, Akkiz-86, Karnikara and Sarigobek cowpea genotypes have been used as trial material in this study. Effects of the five doses of salt concentrations (control, 30 mM, 60 mM, 90 mM and 120 mM) on the ratio of emergency, speed of emergency, average time for emergency, index of sensibility were evaluated. Responses of the cowpea genotypes for salt concentrations were found different. Comparing to the control, all of the investigated characteristics on the cowpea genotypes showed significant reduction by depending on the increasing salt application. According to the effects of salt application, the cowpea genotypes Samandag and Karnikara were the most tolerant in respect to index of sensibility while the Sarigobek genotypes was the most sensitive.

Keywords: cowpea, Vigna sinensis, emergence, salt tolerant

Procedia PDF Downloads 268

Authors: Á. L. Bendes

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By the end of the second decade of the 21st century, artificial intelligence (AI) has become an unavoidable part of everyday life and has necessarily aroused the interest of researchers in almost every field of science. This is no different in the case of jurisprudence, whose main task is not only to create its own theoretical paradigm related to AI. Perhaps the biggest impact on digital crime is artificial intelligence. In addition, the need to create legal frameworks suitable for the future application of the law has a similar importance. The prognosis according to which AI can reshape the practical application of law and, ultimately, the entire legal life is also of considerable importance. In the past, criminal law was basically created to sanction the criminal acts of a person, so the application of its concepts with original content to AI-related violations is not expected to be sufficient in the future. Taking this into account, it is necessary to rethink the basic elements of criminal law, such as the act and factuality, but also, in connection with criminality barriers and criminal sanctions, several new aspects have appeared that challenge both the criminal law researcher and the legislator. It is recommended to continuously monitor technological changes in the field of criminal law as well since it will be timely to re-create both the legal and scientific frameworks to correctly assess the events related to them, which may require a criminal law response. Artificial intelligence has completely reformed the world of digital crime. New crimes have appeared, which the legal systems of many countries do not or do not adequately regulate. It is considered important to investigate and sanction these digital crimes. The primary goal is prevention, for which we need a comprehensive picture of the intertwining of artificial intelligence and digital crimes. The goal is to explore these problems, present them, and create comprehensive proposals that support legal certainty.

Keywords: artificial intelligence, chat forums, defamation, international criminal cooperation, social networking, virtual sites

Procedia PDF Downloads 89

Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan

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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.

Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water

Procedia PDF Downloads 198

Authors: Aron Witkowski, Andrzej Wodecki

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Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

Procedia PDF Downloads 52

Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

Procedia PDF Downloads 183

Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad

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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.

Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments

Procedia PDF Downloads 96

Authors: M. Lesage, G. Raîche, M. Riopel, F. Fortin, D. Sebkhi

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This paper describes a Web server implementation of the hierarchical aggregate assessment process in the field of education. This process describes itself as a field of teamwork assessment where teams can have multiple levels of hierarchy and supervision. This process is applied everywhere and is part of the management, education, assessment and computer science fields. The E-Assessment website named “Cluster” records in its database the students, the course material, the teams and the hierarchical relationships between the students. For the present research, the hierarchical relationships are team member, team leader and group administrator appointments. The group administrators have the responsibility to supervise team leaders. The experimentation of the application has been performed by high school students in geology courses and Canadian army cadets for navigation patrols in teams. This research extends the work of Nance that uses a hierarchical aggregation process similar as the one implemented in the “Cluster” application.

Keywords: e-learning, e-assessment, teamwork assessment, hierarchical aggregate assessment

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Authors: Rajeshkumar Kanubhai Patel, Neha Sudhirkumar Mochi

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A simple and accurate stability-indicating, reversed-phase high-performance liquid chromatography (RP-HPLC) method was developed and validated for the simultaneous quantitation of Evogliptin tartrate and Metformin HCl in pharmaceutical dosage forms, following ICH guidelines. Forced degradation was performed under various stress conditions including acid, base, oxidation, thermal, and photodegradation. The method utilized an Eclipse C18 column (250 mm × 4.6 mm, 5 µm) with a mobile phase of 5 mM 1-hexane sulfonic acid sodium salt in water and 0.2% v/v TEA (45:55 %v/v), adjusted to pH 3.0 with OPA, at a flow rate of 1.0 mL/min. Detection at 254.4 nm using a PDA detector showed good resolution of degradation products and both drugs. Linearity was observed within 1-5 µg/mL for Evogliptin tartrate and 100-500 µg/mL for Metformin HCl, with % recovery between 99-100% and precision within acceptable limits (%RSD < 2%). The method proved to be specific, precise, accurate, and robust for routine analysis of these drugs.

Keywords: stability indicating RP-HPLC, evogliptin tartrate, metformin HCl, validation

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Authors: Rossy G. Olan Villegas, Gerardo Acosta Garcia, Aurea Bernardino Nicanor, Leopoldo Gonzalez Cruz, Humberto Ramirez Medina

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Capsicum annuum is a crop of agricultural and economic importance in Mexico and other countries. The fruit (pepper) contains bioactive components such as carotenoids, phenolic compounds and capsaicinoids that improve health. However, pepper cultivation is affected by biotic and abiotic factors that decrease yield. Some phytohormones like gibberellins and auxins induce the formation and development of fruit in several plants. In this study, we evaluated the effect of the exogenous application of phytohormones like gibberellic acid and indolbutyric acid on fruit development of jalapeno pepper plants, the protein profile of plant tissues, the accumulation of bioactive compounds and antioxidant activity in the pericarp and seeds. For that, plants were sprinkled with these phytohormones. The fruit collection for the control, indolbutyric acid and gibberellic acid treatments was 7 peppers per plant; however, for the treatment that combines indolbutyric acid and gibberellic acid, a fruit with the shortest length (1.52 ± 1.00 cm) and weight (0.41 ± 1.0 g) was collected compared to fruits of plants grown under other treatments. The length (4,179 ± 0,130 cm) and weight of the fruit (8,949 ± 0.583 g) increased in plants treated with indolbutyric acid, but these characteristics decreased with the application of GA3 (length of 3,349 ± 0.127 cm and a weight 4,429 ± 0.144 g). The content of carotenes and phenolic compounds increased in plants treated with GA3 (1,733 ± 0.092 and 1,449 ± 0.009 mg / g, respectively) or indolbutyric acid (1,164 ± 0.042 and 0.970 ± 0.003 mg / g). However, this effect was not observed in plants treated with both phytohormones (0.238 ± 0.021 and 0.218 ± 0.004 mg / g). Capsaicin content was higher in all treatments; but it was more noticeable in plants treated with both phytohormones, the value being 0.913 ± 0.001 mg / g (three times greater in amount). The antioxidant activity was measured by 3 different assays, 2,2-diphenyl-1-picrylhydrazyl (DPPH), antioxidant power of ferric reduction (FRAP) and 2,2'-Azinobis-3-ethyl-benzothiazoline-6-sulfonic acid ( ABTS) to find the minimum inhibitory concentration of the reducing radical (IC50 and EC50). Significant differences were observed from the application of the phytohormone, being the fruits treated with gibberellins, which had a greater accumulation of bioactive compounds. Our results suggest that the application of phytohormones modifies the development of fruit and its content of bioactive compounds.

Keywords: auxins, capsaicinoids, carotenoids, gibberellins

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Authors: Khavieya Anandhan, Soundarapandian Santhanakrishnan, Vijayaraghavan Laxmanan

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In general, measurement of surfaces is carried out by using traditional methods such as contact type stylus instruments. This prevalent approach is challenged by using non-contact instruments such as optical profiler, co-ordinate measuring machine, laser triangulation sensors, machine vision system, etc. Recently, confocal sensor is trying to be used in the surface metrology field. This sensor, such as a confocal sensor, is explored in this study to determine the surface roughness value for various turned surfaces. Turning is a crucial machining process to manufacture products such as grooves, tapered domes, threads, tapers, etc. The roughness value of turned surfaces are in the range of range 0.4-12.5 µm, were taken for analysis. Three instruments were used, namely, perthometer, optical profiler, and confocal sensor. Among these, in fact, a confocal sensor is least explored, despite its good resolution about 5 nm. Thus, such a high-precision sensor was used in this study to explore the possibility of measuring turned surfaces. Further, using this data, measurement uncertainty was also studied.

Keywords: confocal sensor, optical profiler, surface roughness, turned surfaces

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Authors: Donato Maniello, Alessandra Cirafici, Valeria Amoretti

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This paper aims to present a new method that consists in the use of video mapping techniques – that is a particular form of augmented reality, which could produce new tools - different from the ones that are actually in use - for an interactive Museum experience. With the words 'augmented reality', we mean the addition of more information than what the visitor would normally perceive; this information is mediated by the use of computer and projector. The proposed application involves the creation of a documentary that depicts and explains the history of the artifact and illustrates its features; this must be projected on the surface of the faithful copy of the freeze (obtained in full-scale with a 3D printer). This mode of operation uses different techniques that allow passing from the creation of the model to the creation of contents through an accurate historical and artistic analysis, and finally to the warping phase, that will permit to overlap real and virtual models. The ultimate step, that is still being studied, includes the creation of interactive contents that would be activated by visitors through appropriate motion sensors.

Keywords: augmented reality, multimedia, parthenon frieze, video mapping

Procedia PDF Downloads 387

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

Procedia PDF Downloads 151

Authors: Reza M. Rudd, Ali Saeedi, Colin Wood

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In this article, the latest advancements made in the applications of polymers in the enhanced hydrocarbon recovery technologies are investigated. For this purpose, different classes of polymers are reviewed and the latest progresses made in making them suitable for application under harsh reservoir conditions are discussed. The main reservoir conditions whose effects are taken into account include the temperature, rock mineralogy and brine salinity and composition. For profile modification and blocking the thief zones, polymers are used in the form of nanocomposite hydrogels. Polymers are also used as thickeners during CO2 flooding. Also, they are used in enhanced gas recovery, to inhibit the mixing of injection gas with the in-situ natural gas. This review covers the main types of polymers, their functions and the challenges in their applications, some of which are mentioned above. Included in this review are also the latest progresses made in the development of new polymeric surfactants used for surfactant flooding.

Keywords: EOR, EGR, polymer flooding, profile modification, mobility control, nanocomposite hydrogels, CO2 flooding, polymeric surfactants

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Authors: Camilo Souza, Lidia Melo, Fernanda Terra, Francisco Caio, Marcelo Reis

Abstract:

SIDIA is a research and development (R&D) institute that belongs to Samsung’s global software development process. The SIDIA’s Model Team (MT) is a part of Samsung’s Mobile Division Area, which is responsible for the development of Android releases embedded in Samsung mobile devices. Basically, in this software development process, the kickoff occurs in some strategic countries (e.g., South Korea) where some software requirements are applied and the initial software tests are performed. When the software achieves a more mature level, a new branch is derived, and the development continues in subsidiaries from other strategic countries (e.g., SIDIA-Brazil). However, even in the newly created branches, there are several interactions between developers from different nationalities in order to fix bugs reported during test activities, apply some specific requirements from partners and develop new features as well. Despite the GSD strategy contributes to improving software development, some challenges are also introduced as well. In this paper, we share the initial results about the application of the failure modes and effect analysis (FMEA) concept in the software development process followed by the SIDIA’s model team. The main goal was to identify and mitigate the process potential failures through the application of recommended actions. The initial results show that the application of the FMEA concept allows us to identify the potential failures in our GSD process as well as to propose corrective actions to mitigate them. Finally, FMEA encouraged members of different teams to take actions that contribute to improving our GSD process.

Keywords: global software development, potential failures, FMEA, recommended actions

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Authors: Stephen Barnes, Ian Mills, Frances Cleary

Abstract:

Augmented and virtual reality-based applications offer many benefits for the heritage and tourism sector. This technology provides a platform to showcase the regions of interest to people without the need for them to be physically present, which has had a positive impact on enticing tourists to visit those locations. However, the technology also provides the opportunity to present historical artefacts in a form that accurately represents their original, intended appearance. Three sites of interest were identified in the Lingaun Valley in South East Ireland, wherein virtual representations of site-specific artefacts of interest were created via a multidisciplinary team encompassing archaeology, art history, 3D modelling, design, and software development. The collated information has been presented to users via an augmented reality mobile-based application that provides information in an engaging manner that encourages an interest in history as well as visits to the sites in the Lingaun Valley.

Keywords: augmented reality, virtual heritage, 3D modelling, archaeology, virtual representation

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Authors: Ahmet Yetik, Seyit Ali Kara, Cevat Özarpa

Abstract:

Load changes occur on natural gas and oil pipelines due to natural disasters. The displacement of the soil around the natural gas and oil pipes due to situations that may cause erosion, such as earthquakes, landslides, and floods, is the source of this load change. The exposure of natural gas and oil pipes to variable loads causes deformation, cracks, and breaks in these pipes. Cracks and breaks on the pipes cause damage to people and the environment due to reasons such as explosions. Especially with the examinations made after natural disasters, it can be easily understood which of the pipes has more damage in the regions followed. It has been determined that the earthquakes in Turkey caused permanent damage to the pipelines. This project was designed and realized because it was determined that there were cracks and gas leaks in the insulation gaskets placed in the pipelines, especially at the junction points. In this study, A new SCADA (Supervisory Control and Data Acquisition) application has been developed to monitor load changes caused by natural disasters. The newly developed SCADA application monitors the changes in the x, y, and z axes of the stresses occurring in the pipes with the help of strain gauge sensors placed on the pipes. For the developed SCADA system, test setups in accordance with the standards were created during the fieldwork. The test setups created were integrated into the SCADA system, and the system was followed up. Thanks to the SCADA system developed with the field application, the load changes that will occur on the natural gas and oil pipes are instantly monitored, and the accumulations that may create a load on the pipes and their surroundings are immediately intervened, and new risks that may arise are prevented. It has contributed to energy supply security, asset management, pipeline holistic management, and sustainability.

Keywords: earthquake, natural gas pipes, oil pipes, strain measurement, stress measurement, landslide

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Authors: Bitewulign Mekonnen

Abstract:

Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: A. A. Behroozpoor, M. M. Mazarei

Abstract:

In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: Mihai Duguleana, Florin Girbacia, Cristian Postelnicu, Raffaello Brodi, Marcello Carrozzino

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Augmented Reality (AR) has taken a big leap with the introduction of mobile applications which co-locate bi-dimensional (e.g. photo, video, text) and tridimensional information with the location of the user enriching his/her experience. This study presents the advantages of using Mobile Augmented Reality (MAR) technologies in traveling applications, improving cultural heritage exploration. We propose a location-based AR application which combines co-location with the augmented visual information about Pisa monuments to establish a friendly navigation in this historic city. AR was used to render contextual visual information in the outdoor environment. The developed Android-based application offers two different options: it provides the ability to identify the monuments positioned close to the user’s position and it offers location information for getting near the key touristic objectives. We present the process of creating the monuments’ 3D map database and the navigation algorithm.

Keywords: augmented reality, electronic compass, GPS, location-based service

Procedia PDF Downloads 286