Search results for: applied computing

Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: M. Abir Hossain, M. Shahjada Tarafder

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This paper deals with the analysis of potential flow past two-dimensional body by discretizing the body into panels where the Laplace equation was applied to each panel. The Laplace equation was solved at each panel by applying the boundary conditions. The boundary condition was applied at each panel to mathematically formulate the problem and then convert the problem into a computer-solvable problem. Kutta condition was applied at both the leading and trailing edges to see whether the condition is satisfied or not. Another approach that is applied for the analysis is Vortex Lattice Method (VLM). A vortex ring is considered at each control point. Using the Biot-Savart Law the strength at each control point is calculated and hence the pressure differentials are measured. For the comparison of the analytic result with the experimental result, different NACA section hydrofoil is used. The analytic result of NACA 0012 and NACA 0015 are compared with the experimental result of Abbott and Doenhoff and found significant conformity with the achieved result.

Keywords: Kutta condition, Law of Biot-Savart, pressure differentials, potential flow, vortex lattice method

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Authors: Suwimol Apapol, Punrapha Praditpong

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The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions as well as the types of figures of speech most commonly applied in captions. The relation between figures of speech and fragrance was also examined in order to analyze how figures of speech were used to represent fragrance. Thirty-five fragrance advertisements were randomly selected from the Internet. Content analysis was applied in order to consider the relation between figures of speech and fragrance. The results showed that figures of speech were found in almost every fragrance advertisement except one advertisement of several Goods service. Thirty-four fragrance advertising captions used at least one kind of figure of speech. Metaphor was most frequently found and also most frequently applied in fragrance advertising captions, followed by alliteration, rhyme, simile and personification, and hyperbole respectively which is in harmony with the research hypotheses as well.

Keywords: advertising captions, captions on internet, consumer purchasing decision, e-commerce

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Authors: Kwangmin Joo

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Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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Authors: Stephanie Elizabeth Talder

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Art therapy is a field that is growing exponentially with new groundbreaking discoveries that allow for embodying trauma and mental healing. Applied theatre and performance is a continuously growing and developing field that can help people who are struggling to work through traumatic experiences plaguing their life. By using performance, there is an ability to target sensitive topics in a manner that does not lead to re-traumatization. The use of theatre as a healing agent has been going on for centuries, with clear applications beginning in Greek theatre and tragedy. When working with complex mental illness, issues such as PTSD, anxiety, and depression can be managed and worked through. A central component of drama therapy is the connection to community and self. The ability to connect mind-body to stories as well as to other people allows for healing to occur. There is the opportunity for healing through emotional catharsis and community building. Applied theatre in connection to the medical field can allow for there to be a meaningful impact made on mental health. Though there is still a significant amount of progress to be made within the stigmatization of mental health problems, bringing in a varying option that allows for there to be movement and community building possesses a strong ability to impact people in a positive way.

Keywords: applied theatre, drama therapy, art therapy, performance, theatre

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Authors: Upal Barua

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Crash risk at intersections is a critical safety issue. This paper examines the effectiveness of removing an existing off-set at an intersection by realignment, in reducing crashes. Empirical Bayes method was applied to conduct a before-and-after study to assess the effect of this safety improvement. The Transportation Safety Improvement Program in Austin Transportation Department completed several safety improvement projects at high crash intersections with a view to reducing crashes. One of the common safety improvement techniques applied was the realignment of intersection approaches removing an existing off-set. This paper illustrates how this safety improvement technique is applied at a high crash intersection from inception to completion. This paper also highlights the significant crash reductions achieved from this safety improvement technique applying Empirical Bayes method in a before-and-after study. The result showed that realignment of intersection approaches removing an existing off-set can reduce crashes by 53%. This paper also features the state of the art techniques applied in planning, engineering, designing and construction of this safety improvement, key factors driving the success, and lessons learned in the process.

Keywords: crash risk, intersection, off-set, safety improvement technique, before-and-after study, empirical Bayes method

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Authors: Panprae Bunyapukkna

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This study investigated figures of speech used in fragrance advertising captions on the Internet. The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions and the types of figures of speech most commonly applied in captions. The relation between figures of speech and fragrance was also examined in order to analyze how figures of speech were used to represent fragrance. Thirty-five fragrance advertisements were randomly selected from the Internet. Content analysis was applied in order to consider the relation between figures of speech and fragrance. The results showed that figures of speech were found in almost every fragrance advertisement except one advertisement of Lancôme. Thirty-four fragrance advertising captions used at least one kind of figure of speech. Metaphor was most frequently found and also most frequently applied in fragrance advertising captions, followed by alliteration, rhyme, simile and personification, and hyperbole respectively.

Keywords: advertising speech, fragrance advertisements, figures of speech, metaphor

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Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz

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Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.

Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Sonja Gögele, Petra Kletzenbauer

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International strategies are ranked as one of the core activities in the development plans of Austrian universities. This has led to numerous promising activities in terms of internationalization (i.e. development of international degree programmes, increased staff and student mobility, and blended international projects). The latest innovative approach in terms of Erasmus+ are so called Blended Intensive Programmes (BIP) which combine jointly delivered teaching and learning elements of at least three participating ERASMUS universities in a virtual and short-term mobility setup. Students who participate in BIP can maintain their study plans at their home institution and include BIP as a parallel activity. This paper presents the experiences of this programme on the topic of sustainable computing hosted by the University of Applied Sciences FH JOANNEUM. By means of an online survey and face-to-face interviews with all stakeholders (20 students, 8 professors), the empirical study addresses the challenges of hosting an international blended learning programme (i.e. virtual phase and on-site intensive phase) and discusses the impact of such activities in terms of internationalization and Englishization. In this context, key roles are assigned to the development of future transnational and transdisciplinary curricula by considering innovative aspects for learning and teaching (i.e. virtual collaboration, research-based learning).

Keywords: internationalization, englishization, short-term mobility, international teaching and learning

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Noemi Schneider, Richard Blaese, Pietro Morandi, Brigitte Liebig

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While women are increasingly frequent among the founders of innovative companies and advanced researchers in many university research institutes today, they are still an exception among initiators of research-based spin-offs. This also applies to countries such as Switzerland, which does have a leading position in international innovation rankings. Starting from a gender-sensitive neo-institutionalist perspective, this paper examines formal and non-formal institutional framework conditions for academic spin-offs at Swiss universities of applied sciences. This field, which stresses vocational education and practice-oriented research, seems to conserve the gender gap in the area of establishing research-based spin-offs spin-off rates strongly. The analysis starts from a survey conducted in 2017 and 2018 at all seven public universities of applied sciences in Switzerland as well as on an evaluation of expert interviews performed with heads of start-up centers, where also spin-offs from universities of applied sciences get support. The results show the mechanisms, which contribute to gender gaps in academic entrepreneurship in higher education. University's female employees have hardly been discovered as target groups. Thus, only 10.5% of universities of applied sciences offer specific support measures for women in academia. And only 1 out of 7 universities of applied sciences offer mentoring programs for female entrepreneurs while in addition there are no financial resources available to support female founders in academia. Moreover, the awareness of the gender gap in academic entrepreneurship is low among founding commissioners. A consistent transfer strategy might be key for bringing in line the formal and non-formal preconditions relevant for the formation of research-based spin-offs and for providing an effective incentive structure to promote women.

Keywords: gender, science-based spin-off, universities of applied sciences, knowledge transfer strategy

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram

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With the increase of prevailing non-traditional rivalry, mobile banking experiences an ever changing commercial backdrop. Substantial customer demands have established to be more intricate as customers request more expediency and superintend over their banking services. To enterprise advance and modernization in mobile banking applications, it is gradually obligatory to deeply leapfrog the scuffle using business model transformation. The dramaturgical vicissitudes taking place in mobile banking entail advanced traditions to exploit security. By reforming and transforming older back office into integrated mobile banking applications, banks can engender a supple and nimble banking environment that can rapidly respond to new business requirements over cloud computing. Cloud computing is transfiguring ecosystems in numerous industries, and mobile banking is no exemption providing services innovation, greater flexibility to respond to improved security and enhanced business intelligence with less cost. Cloud technology offer secure deployment possibilities that can provision banks in developing new customer experiences, empower operative relationship and advance speed to efficient banking transaction. Cloud adoption is escalating quickly since it can be made secured for commercial mobile banking transaction through backend as a service in scrutinizing the security strategies of the cloud service provider along with the antiquity of transaction details and their security related practices.

Keywords: cloud adoption, backend as a service, business intelligence, secured mobile banking

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Authors: Andrew Youssef, David Matthews, Jie Pan

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Identifying the magnitude and direction of a force on an elastic solid is highly desirable, as this allows for investigation and continual monitoring of the dynamic loading. This was traditionally conducted by connecting the solid to the supporting structure by multi-axial force transducer, providing that the transducer will not change the mounting conditions. Polyvinylidene fluoride (PVDF) film is a versatile force transducer that can be easily embedded in structures. Here a PVDF sensor array is embedded inside a simple structure in an effort to determine the force vector applied to the structure is an inverse problem. In this paper, forces of different magnitudes and directions where applied to the structure with an impact hammer, and the output of the PVDF was captured and processed to gain an estimate of the forces applied by the hammer. The outcome extends the scope of application of PVDF sensors for measuring the external or contact force vectors.

Keywords: embedded sensor, monitoring, PVDF, vibration

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Authors: Md. Shah Alam

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Mushfiq Ahmad has defined a Mixed Number, which is the sum of a scalar and a Cartesian vector. He has also defined the elementary group operations of Mixed numbers i.e. the norm of Mixed numbers, the product of two Mixed numbers, the identity element and the inverse. It has been observed that Mixed Number is consistent with Pauli matrix algebra and a handy tool to work with Dirac electron theory. Its use as a mathematical method in Physics has been studied. (1) We have applied Mixed number in Quantum Mechanics: Mixed Number version of Displacement operator, Vector differential operator, and Angular momentum operator has been developed. Mixed Number method has also been applied to Klein-Gordon equation. (2) We have applied Mixed number in Electrodynamics: Mixed Number version of Maxwell’s equation, the Electric and Magnetic field quantities and Lorentz Force has been found. (3) An associative transformation of Mixed Number numbers fulfilling Lorentz invariance requirement is developed. (4) We have applied Mixed number algebra as an extension of Complex number. Mixed numbers and the Quaternions have isomorphic correspondence, but they are different in algebraic details. The multiplication of unit Mixed number and the multiplication of unit Quaternions are different. Since Mixed Number has properties similar to those of Pauli matrix algebra, Mixed Number algebra is a more convenient tool to deal with Dirac equation.

Keywords: mixed number, special relativity, quantum mechanics, electrodynamics, pauli matrix

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Authors: Zviad Ghadua, Biswa Bhattacharya

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The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina

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Authors: Zahoor Hussain

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Creasing is a physiological disorder of rind in sweet orange [Citrus sinensis (L.) Osbeck] fruit and causes serious economic losses in various countries of the world. The reversible inhibitor of ethylene, aminoethoxyvinylglycine (AVG) with the effects of different concentrations (0, 20, 40 and 60 mgL⁻¹) AVG with 0.05% ‘Tween 20’ as a surfactant applied at the fruit set, the golf ball or at the colour break stage on controlling creasing, rheological properties of fruit and rind as well as fruit quality in of Washington Navel and Lane Late sweet orange was investigated. Creasing was substantially reduced and fruit quality was improved with the exogenous application of AVG depending upon its concentration and stage of application in both cultivars. The spray application of AVG (60 mgL⁻¹) at the golf ball stage was effective in reducing creasing (27.86% and 24.29%) compared to the control (52.14 and 51.53%) in cv. Washington Navel during 2011 and 2012, respectively. Whilst, in cv. Lane Late lowest creasing was observed When AVG was applied at fruit set stage (22.86%) compared to the control (51.43%) during 2012. In cv. Washington Navel, AVG treatment (60 mgL⁻¹) was more effective to increase the fruit firmness (318.97 N) and rind hardness (25.94 N) when applied at fruit set stage. However, rind tensile strength was higher, when AVG was applied at the golf ball stage (54.13 N). In cv. Lane Late, the rind harness (28.61 N), rind tensile strength (78.82 N) was also higher when AVG was sprayed at fruit set stage. Whilst, the fruit compression force (369.68 N) was higher when AVG was applied at the golf ball stage. Similarly, the treatment AVG (60 mgL⁻¹) was more effective in improving fruit weight (281.00 and 298.50 g) and fruit diameter (87.30 and 82.69 mm), rind thickness (5.56 and 5.38 mm) and total sugars (15.27 mg.100ml⁻¹) when AVG was applied at the fruit golf ball stage in cv. Washington Navel and Lane Late, respectively. Similarly, rind harness (25.94 and 28.61 N), total antioxidants (45.30 and 46.48 mM trolox 100ml⁻¹), total sugars (13.64 and 15.27 mg.100ml⁻¹), citric acid (1.66 and 1.32 mg100ml⁻¹), malic acid (0.36 and 0.63 mg.100ml⁻¹) and succinic acid (0.35 and 0.38 mg100ml⁻¹) were also higher, when AVG was applied at the fruit set stage in both cultivars. In conclusion, the exogenous applications of AVG substantially reduces the creasing incidence, improves rheological properties of fruit and rind as well as fruit quality in Washington Navel and Lane Late sweet orange fruit.

Keywords: AVG, creasing, ethylene inhibitor, sweet orange

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Authors: Andres Zuñiga Orozco

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Green manure fertilizers have special importance in the development of organic and sustainable agriculture as a substitute or complement to chemical fertilization. They have many advantages, but they have application limitations in greenhouse crops and in open field crops that have low growing size. On the other hand, the logistics of sowing, harvesting and applying have been difficult for producers to adopt. For this reason, a pelletized presentation was designed in conjunction with Trichoderma harzianum. The biopellet was applied in pineapple as the first experience, managing to improve carbon levels in the soil and some nutrients. Then it was applied to tomatoes where it was proven that, nutritionally, it is possible to nourish the crop up to day 60 only with the biopellet, improve carbon levels in soil and control the fungus Fusarium oxysporum. Subsequently, it was applied to coffee seedlings with an organo-mineral formulation. Here, the improvement in the growth and nutrition of the plants was notable, as well as the increase in the microbial activity of the soil. M. pruriens biopellets allow crops to be nourished, allow biocontrolers to be added, improve soil conditions to promote greater microbial activity, reincorporate carbon and CO2 into the soil, are easily applicable, allow dosing and have a favorable shelf-life. They can be applied to all types of crops, both in the greenhouse and in the field.

Keywords: Mucuna pruriens, pellets, carbon, Trichoderma, Fusarium

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Authors: Pin Xiu Chen, Shang Liang Chen

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A virtualized software controller is developed in this research to replace traditional hardware control units. This virtualized software controller transfers motion interpolation calculations from the motion control units of end devices to edge computing platforms, thereby reducing the end devices' computational load and hardware requirements and making maintenance and updates easier. The study also applies the concept of microservices, dividing the control system into several small functional modules and then deploy into a cloud data server. This reduces the interdependency among modules and enhances the overall system's flexibility and scalability. Finally, with containerization technology, the system can be deployed and started in a matter of seconds, which is more efficient than traditional virtual machine deployment methods. Furthermore, this virtualized software controller communicates with end control devices via wireless networks, making the placement of production equipment or the redesign of processes more flexible and no longer limited by physical wiring. To handle the large data flow and maintain low-latency transmission, this study integrates 5G technology, fully utilizing its high speed, wide bandwidth, and low latency features to achieve rapid and stable remote machine control. An experimental setup is designed to verify the feasibility and test the performance of this framework. This study designs a smart manufacturing site with a 5G communication architecture, serving as a field for experimental data collection and performance testing. The smart manufacturing site includes one robotic arm, three Computer Numerical Control machine tools, several Input/Output ports, and an edge computing architecture. All machinery information is uploaded to edge computing servers and cloud servers via 5G communication and the Internet of Things framework. After analysis and computation, this information is converted into motion control commands, which are transmitted back to the relevant machinery for motion control through 5G communication. The communication time intervals at each stage are calculated using the C++ chrono library to measure the time difference for each command transmission. The relevant test results will be organized and displayed in the full-text.

Keywords: 5G, MEC, microservices, virtualized software controller, smart manufacturing

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Authors: Kang Huang, Wanting Zhou, Shiwei Yuan, Lei Li

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Since information technology develops rapidly, the security issue has become an increasingly critical for computer system. In particular, as cloud computing and the Internet of Things (IoT) continue to gain widespread adoption, computer systems need to new security threats and attacks. The Root of Trust (RoT) is the foundation for providing basic trusted computing, which is used to verify the security and trustworthiness of other components. Design a reliable Root of Trust and guarantee its own security are essential for improving the overall security and credibility of computer systems. In this paper, we discuss the implementation of self-security technology based on the RISC-V Root of Trust at the hardware level. To effectively safeguard the security of the Root of Trust, researches on security safeguard technology on the Root of Trust have been studied. At first, a lightweight and secure boot framework is proposed as a secure mechanism. Secondly, two kinds of memory protection mechanism are built to against memory attacks. Moreover, hardware implementation of proposed method has been also investigated. A series of experiments and tests have been carried on to verify to effectiveness of the proposed method. The experimental results demonstrated that the proposed approach is effective in verifying the integrity of the Root of Trust’s own boot rom, user instructions, and data, ensuring authenticity and enabling the secure boot of the Root of Trust’s own system. Additionally, our approach provides memory protection against certain types of memory attacks, such as cache leaks and tampering, and ensures the security of root-of-trust sensitive information, including keys.

Keywords: root of trust, secure boot, memory protection, hardware security

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Authors: Alla Levina, Sergey Taranov

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The classical approach to the providing noise immunity and integrity of information that process in computing devices and communication channels is to use linear codes. Linear codes have fast and efficient algorithms of encoding and decoding information, but this codes concentrate their detect and correct abilities in certain error configurations. To protect against any configuration of errors at predetermined probability can robust codes. This is accomplished by the use of perfect nonlinear and almost perfect nonlinear functions to calculate the code redundancy. The paper presents the error-correcting coding scheme using biorthogonal wavelet transform. Wavelet transform applied in various fields of science. Some of the wavelet applications are cleaning of signal from noise, data compression, spectral analysis of the signal components. The article suggests methods for constructing linear codes based on wavelet decomposition. For developed constructions we build generator and check matrix that contain the scaling function coefficients of wavelet. Based on linear wavelet codes we develop robust codes that provide uniform protection against all errors. In article we propose two constructions of robust code. The first class of robust code is based on multiplicative inverse in finite field. In the second robust code construction the redundancy part is a cube of information part. Also, this paper investigates the characteristics of proposed robust and linear codes.

Keywords: robust code, linear code, wavelet decomposition, scaling function, error masking probability

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Authors: Ashkan Vatani, Peter Woodfield, Nam-Trung Nguyen, Dzung Dao

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Thermomagnetic convection of a ferrofluid flow induced by the non-uniform magnetic field around a current-carrying wire was theoretically analyzed and experimentally tested. To show this phenomenon, the temperature rise of a hot wire, immersed in DIW and Ferrofluid, as a result of joule heating has been measured using a transient hot-wire technique. When current is applied to the wire, a temperature gradient is imposed on the magnetic fluid resulting in non-uniform magnetic susceptibility of the ferrofluid that results in a non-uniform magnetic body force which makes the ferrofluid flow as a bulk suspension. For the case of the wire immersed in DIW, free convection is the only means of cooling, while for the case of ferrofluid a combination of both free convection and thermomagnetic convection is expected to enhance the heat transfer from the wire beyond that of DIW. Experimental results at different temperatures and for a range of constant currents applied to the wire show that thermomagnetic convection becomes effective for the currents higher than 1.5A at all temperatures. It is observed that the onset of thermomagnetic convection is directly proportional to the current applied to the wire and that the thermomagnetic convection happens much faster than the free convection. Calculations show that a 35% enhancement in heat transfer can be expected for the ferrofluid compared to DIW, for a 3A current applied to the wire.

Keywords: cooling, ferrofluid, thermomagnetic convection, magnetic field

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Alexandre M. Brighenti

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The experiment was carried out in Valença, Rio de Janeiro State, Brazil, to evaluate the selectivity and weed control of carotenoid biosynthesis inhibiting herbicides applied alone or in combination with atrazine in elephant grass crop. The treatments were as follows: mesotrione (0.072 and 0.144 kg ha^-1 + 0.5% v/v mineral oil - Assist®), tembotrione (0.075 and 0.100 kg ha^-1 + 0.5% v/v mineral oil - Aureo®), atrazine + mesotrione (1.25 + 0.072 kg ha^-1 + 0.5% v/v mineral oil - Assist®), atrazine + tembotrione (1.25 + 0.100 kg ha^-1 + 0.5% v/v mineral oil - Aureo®), atrazine + mesotrione (1.25 + 0.072 kg ha^-1), atrazine + tembotrione (1.25 + 0.100 kg ha^-1) and two controls (hoed and unhoed check). Two application rates of mesotrione with the addition of mineral oil or the tank mixture of atrazine plus mesotrione, with or without the addition of mineral oil, did not provide injuries capable to reduce elephant grass forage yield. Tembotrione was phytotoxic to elephant grass when applied with mineral oil. Atrazine and tembotrione in a tank-mix, with or without mineral oil, were also phytotoxic to elephant grass. All treatments provided satisfactory weed control.

Keywords: forage, Napier grass, pasture, Pennisetum purpureum, weeds

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Lingzhi Li, Jiankun Zhang, Tiantian Gu

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Hazard management that can prevent fatal accidents and property losses is a fundamental process during the buildings’ construction stage. However, due to lack of safety supervision resources and operational pressures, the conduction of hazard management is poor and ineffective in China. In order to improve the quality of construction safety management, it is critical to explore the use of information technologies to ensure that the process of hazard management is efficient and effective. After exploring the existing problems of construction hazard management in China, this paper develops the griddization management model for construction hazard management. First, following the knowledge grid infrastructure, the griddization computing infrastructure for construction hazards management is designed which includes five layers: resource entity layer, information management layer, task management layer, knowledge transformation layer and application layer. This infrastructure will be as the technical support for realizing grid management. Second, this study divides the construction hazards into grids through city level, district level and construction site level according to grid principles. Last, a griddization management process including hazard identification, assessment and control is developed. Meanwhile, all stakeholders of construction safety management, such as owners, contractors, supervision organizations and government departments, should take the corresponding responsibilities in this process. Finally, a case study based on actual construction hazard identification, assessment and control is used to validate the effectiveness and efficiency of the proposed griddization management model. The advantage of this designed model is to realize information sharing and cooperative management between various safety management departments.

Keywords: construction hazard, griddization computing, grid management, process

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Authors: Yousef Sharrab, Dimah Al-Fraihat, Monther Tarawneh, Aysh Alhroob, Ala’ Khalifeh, Nabil Sarhan

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This paper explores the evolution of Electrical Engineering (EE) and Computer Science (CS) education in higher learning, examining the feasibility of unifying them into Electrical Engineering and Computer Science (EECS) for the technology industry. It delves into the historical reasons for their separation and underscores the need for integration. Emerging technologies such as AI, Virtual Reality, IoT, Cloud Computing, and Cybersecurity demand an integrated EE and CS program to enhance students' understanding. The study evaluates curriculum integration models, drawing from prior research and case studies, demonstrating how integration can provide students with a comprehensive knowledge base for industry demands. Successful integration necessitates addressing administrative and pedagogical challenges. For academic institutions considering merging EE and CS programs, the paper offers guidance, advocating for a flexible curriculum encompassing foundational courses and specialized tracks in computer engineering, software engineering, bioinformatics, information systems, data science, AI, robotics, IoT, virtual reality, cybersecurity, and cloud computing. Elective courses are emphasized to keep pace with technological advancements. Implementing this integrated approach can prepare students for success in the technology industry, addressing the challenges of a technologically advanced society reliant on both EE and CS principles. Integrating EE and CS curricula is crucial for preparing students for the future.

Keywords: electrical engineering, computer science, EECS, curriculum integration of EE and CS

Procedia PDF Downloads 47