Search results for: hybrid thinking

Authors: Lei Xue, Liye Zhao, Jundong Wang, Yu Xue

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A hybrid energy conversion system composed of a floating offshore wind turbine (FOWT) and wave energy converters (WECs) may possibly reduce the levelized cost of energy, improving the platform dynamics and increasing the capacity to harvest energy. This paper investigates the aerodynamic performance and dynamic responses of the combined semi-submersible FOWT and point-absorber WECs in frequency and time domains using synthetic optimizing control under turbulent wind and irregular wave conditions. Individual pitch control is applied to the FOWT part, while spring–damping control is used on the WECs part, as well as the synergistic control effect of both are studied. The effect of the above control optimization is analyzed under several typical working conditions, such as below-rated wind speed, rated wind speed, and above-rated wind speed by OpenFAST and WEC-Sim software. Particularly, the wind-wave misalignment is also comparatively investigated, which has demonstrated the importance of applying proper integrated optimal control in this hybrid energy system. More specifically, the combination of individual pitch control and spring–damping control is able to mitigate the platform pitch motion and improve output power. However, the increase in blade root load needs to be considered which needs further investigations in the future.

Keywords: floating offshore wind turbine, wave energy converters, control optimization, individual pitch control, dynamic response

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Authors: Roba Zakariah Shaheen

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In the 21st-century Interior, design pedagogy has developed rapidly due to social and economical factors. Socially, this paper presents research findings that shows a significant relationship between educators and students in interior design education. It shows that students’ personal traits, design process, and thinking process are significantly interrelated. Constructively, this paper presented how personal traits can guide educators in the interior design education domain to develop students’ thinking process. In the same time, it demonstrated how students should use their own personal traits to create their own design process. Constructivism was the theory underneath this research, as it supports the grounded theory, which is the methodological approach of this research. Moreover, Mayer’s Briggs Type Indicator strategy was used to investigate the personality traits scientifically, as a psychological strategy that related to cognitive ability. Conclusions from this research strongly recommends that educators and students should utilize their personal traits to foster interior design education.

Keywords: interior design, pedagogy, constructivism, grounded theory, personality traits, creativity

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Authors: Yenni Kurniawati

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Students Prediction Skill in chemistry experiments is an important skill for pre-service chemistry students to stimulate students reflective thinking at each stage of many chemistry experiments, qualitatively and quantitatively. A Virtual Chemistry Laboratory was designed to give students opportunities and times to practicing many kinds of chemistry experiments repeatedly, everywhere and anytime, before they do a real experiment. The Virtual Chemistry Laboratory content was constructed using the Model of Educational Reconstruction and developed to enhance students ability to predicted the experiment results and analyzed the cause of error, calculating the accuracy and precision with carefully in using chemicals. This research showed students changing in making a decision and extremely beware with accuracy, but still had a low concern in precision. It enhancing students level of reflective thinking skill related to their prediction skill 1 until 2 stage in average. Most of them could predict the characteristics of the product in experiment, and even the result will going to be an error. In addition, they take experiments more seriously and curiously about the experiment results. This study recommends for a different subject matter to provide more opportunities for students to learn about other kinds of chemistry experiments design.

Keywords: virtual chemistry laboratory, chemistry experiments, prediction skill, pre-lab experiences

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Authors: L. I. Izhar, T. Stathaki, K. Howell

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Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. In this paper, a novel system is proposed to improve diagnosis and monitoring of morphoea skin disorder based on integration with the published lines of Blaschko. In the proposed system, image registration based on global and local registration methods are found inevitable. This paper presents a modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images that are represented by smooth gray edge maps is proposed for the global registration approach. This method is improved further by incorporating an iterative-based normalized cross-correlation coefficient (NCC) method. It is found that by replacing the final registration part of the NGC method where translational differences are solved in the spatial Fourier domain with the NCC method performed in the spatial domain, the performance and robustness of the NGC method can be greatly improved. It is shown in this paper that the hybrid NGC method not only outperforms phase correlation (PC) method but also improved misregistration due to translation, suffered by the modified NGC method alone for thermograms with ill-defined jawline. This also demonstrates that by using the gradients of the gray edge maps and a hybrid technique, the performance of the PC based image registration method can be greatly improved.

Keywords: Blaschko’s lines, image registration, morphoea, thermal imaging

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Authors: Mohammed Ahmed, Ziba Nazarlou

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Mild steels have a limited alloying content which makes them vulnerable to excessive corrosion rates in the harsh medium. To overcome this issue, some protective coatings are used to prevent corrosion on the steel surface. The use of specialized coatings, mainly organic coatings (such as epoxies, polyurethanes, and acrylics) and inorganic coatings (such as Polysiloxanes) is the most common method of mitigating corrosion of carbon steel. Incorporating the benefits of organic and inorganic hybrid (OIH) compounds for the designing of hybrid protective coatings is still challenging for industrial applications. There are advantages of inorganic coatings have, but purely inorganic siloxane-based coatings are difficult to use on industrial applications unless they are used at extremely low thicknesses (< 1-2 microns). Hence, most industrial applications try to have a combination of Polysiloxanes with organic compounds.  A hybrid coating possesses an organic section, which transports flexibility and impact resistance, and an inorganic section, which usually helps in the decreasing of porosity and increasing thermal stability and hardness. A number of polymers including polyethylene glycol and polyvinyl pyrrolidone have been reported to inhibit the corrosion mild steel in acidic media. However, reports on the effect of polyethylene oxide (PEO) or its blends on corrosion inhibition of metals is very scarce. Different composition of OIH coatings was synthesized by using silica sol-gel, epoxy, and PEO. The effect of different coating types on the corrosion behavior of carbon steel in harsh solution has been studied by weight loss and electrochemical measurements using Gamry 1000 Interface Potentiostat. Coating structures were investigated by SEM. İt revealed a considerable reduction in corrosion rate for coated sample. Based on these results, OIH coating prepared by epoxy-silica sol gel-PEO and epoxy-silica sol-gel exhibit had a %99.5 and %98 reduction of (Corrosion rate) CR compares to baseline. Cathodic Tafel constant (βc) shows that coatings change both Tafel constants but had more effect on the cathodic process. The evolution of the Potentiostatic scan with time displays stability in potential, some of them in a high value while the other in a low value which can be attributed to the formation of an oxide film covering substrate surface. The coated samples with the group of epoxy coating have a lower potential along with the time test, while the silica group shows higher in potential with respect to time.

Keywords: electrostatic, hybrid coating, corrosion tests, silica sol gel

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid Tabu Search (TS) algorithm is suggested for the multi-objective job shop scheduling problems (MO-JSSPs). The algorithm integrates several shifting bottleneck based neighborhood structures with the Giffler & Thompson algorithm, which improve efficiency of the search. Diversification and intensification are provided with local and global left shift algorithms application and also new semi-active, active, and non-delay schedules creation. The suggested algorithm is tested in the MO-JSSPs benchmarks from the literature based on the Pareto optimality concept. Different performances criteria are used for the multi-objective algorithm evaluation. The proposed algorithm is able to find the Pareto solutions of the test problems in shorter time than other algorithm of the literature.

Keywords: tabu search, heuristics, job shop scheduling, multi-objective optimization, Pareto optimality

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Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning

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Authors: Manlika Ratchagit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, Lyapunov functional, linear matrix inequalities

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Pozzaglio Carolina

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This work analyses the term sect or religious cult and the general traits of those groups and the people involved so as to better understand this unexpectedly popular reality. Some translations taken from research papers as well as academic articles are likewise taken into consideration. We have carried out an in-depth analysis of the topics presented. Firstly we defined magic related to religion and all the similarities and differences between magical thinking and religious thinking, religion, and superstition. Secondly, the term “sect” was defined, and the phenomenon was dealt with, along with the listing of all kinds of existing groups. Then we studied the recruitment process in general and recruitment according to the brainwashing theory. We then analysed the criminological aspects that entail their harmfulness with a particular focus on the structure of those religious communities and the theories regarding the people involved: leader, members, and the group, as it has its own pattern of behaviour and its conformism. Finally, we studied the ideology and the techniques of manipulation used, such as brainwashing, which got already introduced in previous chapters trying to explain this reality not only in theory but studying and trying to understand some of the most famous religious cults.

Keywords: psychological manipulation, brainwashing, love bombing, magic and religion

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Authors: Vibha Sinha, Sumedha Chakma

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Arsenic (As) contamination in drinking water is a serious concern worldwide resulting in severe health maladies. To tackle this problem, several hydrogel based matrix which selectively uptake toxic metals from contaminated water has increasingly been examined as a potential practical method for metal removal. The major concern in hydrogels is low stability of matrix, resulting in poor performance. In this study, the potential of hybrid hydrogel-biochar matrix synthesized from natural plant polymers, specific for As removal was explored. Various compositional and functional group changes of the elements contained in the matrix due to the adsorption of As were identified. Moreover, to resolve the stability issue in hydrogel matrix, optimum and effective mixing of hydrogel with biochar was studied. Mixing varied proportions of matrix components at the time of digestion process was tested. Preliminary results suggest that partial premixing methods may increase the stability and reduce cost. Addition of nanoparticles and specific catalysts with different concentrations of As(III) and As(V) under batch conditions was performed to study their role in performance enhancement of the hydrogel matrix. Further, effect of process parameters, optimal uptake conditions and detailed mechanism derived from experimental studies were suitably conducted. This study provides an efficient, specific and a low-cost As removal method that offers excellent regeneration abilities which can be reused for value.

Keywords: arsenic, catalysts, hybrid hydrogel-biochar, water purification

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Authors: Wing Cheuk Chan

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It is well-known that Heidegger was highly critical of Sartre’s existential philosophy. In his famous “Letter on Humanism,” Heidegger not only draw a clear cutline between his thinking of Being and Sartre’s existentialism but also introduced a kind of anti-humanism. Such a hostile attitude towards Sartre’sExistentialism as Humanism seems to have created an unbridgeable gap between these them. Indeed, already in his Being and Nothingness, Sartre complained: Heidegger “has completely avoided any appeal to consciousness in his description of Dasein.”In reality, Sartre was mainly faithful to Husserlianphenomenology, in spite of his rejection of Husserl’s idealism. Thanks to the Japanese Buddhist scholar Yoshifumi Ueda’s work on the Old School of Yogācāra Buddhismas represented by Sthiramati and Paramārtha, we learn that in additional to thethesis of transforming vijñāna (knowing consciousness) into jñāna (wisdom), there is an idea of pṛṣṭa-labdha-jñāna (the subsequently acquired wisdom). According to Ueda, the latter is a “non-discriminative discrimination.” This gives rise to a possibility of synthesizing Heidegger’s thinking of Being and Sartre’s existential phenomenology. Structurally, this paper will firstshow that Heidegger focuses on the side of non-discrimination, whereas Sartre concentrates on the side of discrimination. It will then clarify in what sense thateach of them, in itself, remains incomplete. Finally, it will demonstratehow to synthesize them in term of the notion of “non-discriminative discrimination.”

Keywords: heidegger, sartre, phenomenology, yogācāra buddhism

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Authors: Manlika Rajchakit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, lyapunov functional, linear matrix inequalities

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Authors: B. Oji, O. Olaniran

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The prospect of improving the corrosion property of Al 6063 alloy based hybrid composites reinforced with cassava peel ash (CPA) and silicon carbide (SiC) is the target of this research. It seeks to determine the viability of using locally sourced material (CPA) as a complimentary reinforcement for SiC to produce low cost high performance aluminum matrix composite. The CPA was mixed with the SiC in the ratios 0:1, 1:3, 1:1, 3:1 and 1:0 for 8 wt % reinforcement in the produced composites by double stir-casting method. The microstructures of the composites were studied before and after corrosion using the scanning electron microscopy which reveals the matrix (dark region) and eutectic phase (lamellar region). The corrosion rate was studied in accordance with ASTM G59-97 (2014) using an AutoLab potentiostat (Versa STAT 400) with versaSTUDIO electrochemical software which analyses the results obtained. The result showed that Al 6063 alloy exhibited good corrosion resistance in 0.3M H₂SO₄ and 3.5 wt. % NaCl solutions with sample C containing the 25% wt CPA showing the highest resistance to corrosion with corrosion rate of 0.0046 mmpy as compared to the control sample which has a value of 13.233 mmpy. Sample B, D, E, and F also showed a corrosion rate of 3.9502, 2.6903, 2.1223, and 5.7344 mmpy which indicated a better corrosion rate than the control in the acidic environment. The corrosion rate in the saline medium shows that sample E with 75% wt CPA has the lowest corrosion rate of 0.0422 mmpy as compared to the control sample with 0.0873 mmpy corrosion rate.

Keywords: Al-Mg-Si alloy, AutoLab potentiostat, Cassava Peel Ash, CPA, hybrid composite, stir-cast method

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Authors: Peeranan Wisanskoonwong, Sumitta Sawangtook

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Practicum in Midwifery II is the subject that affects most students to be stressed and anxious because they lack of experiences and self-confidence in delivery baby. This study is a qualitative research. That research objectives were (1) to study learning through reflective practice of nursing students (2) to explain the effects of learning through reflective practice of nursing students in the delivery room. The selected key informant method was criterion-based selection. Thirty-two of fourth-year nursing students in Kuakarun Faculty of nursing who practiced in Delivery room at Taksin Hospital in academic year 2014 were selected. Data collection was data triangulation which consisted of in-depth interview, group discussion and reading students’ reflective practice journal. The research instruments were students’ reflective practice journal, semi-structured questionnaires for in-depth interview, group discussion. Data analysis was thematic analysis. The research result found that: The learning method through reflective practice of nursing students in the delivery room were (1) reflective practice journal (2) dialogue (3) critical thinking and problem solving (4) incident analysis (5) self-criticism (6) observation and evaluation of practice. There were eight issues that students learned through their reflective practice were that (1) students' ethics and morality. (2) students' knowledge and comprehension (3) creative thinking of students (4) communications and collaboration (5) experiential learning of students (6) students’memories and impressions (7) students’experience in delivery baby (8) self-learning of students. Learning through reflective practice supported students’ awareness in improving knowledge and learning continuously and systematically. It helped to adjust the attitude to learning and leadership to be careful which help develop their skills, including critical thinking and understand themselves and understand others. Recommendation for applying research results: midwifery and nursing lecturers can apply these results to be a guide for development their clinical teaching in delivery rooms and other wards.

Keywords: learning, reflection, birth, qualitative research

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Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

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Authors: Asma’a Mahfoud, Abu Bakar Md. Sultan, Abdul Azim Abd, Norhayati Mohd Ali, Novia Admodisastro

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Obfuscation is a practice to make something difficult and complicated. Programming code is ordinarily obfuscated to protect the intellectual property (IP) and prevent the attacker from reverse engineering (RE) a copyrighted software program. Obfuscation may involve encrypting some or all the code, transforming out potentially revealing data, renaming useful classes and variables (identifiers) names to meaningless labels, or adding unused or meaningless code to an application binary. Obfuscation techniques were not performing effectively recently as the reversing tools are able to break the obfuscated code. We propose in this paper a hybrid obfuscation technique that contains three approaches of renaming. Experimentation was conducted to test the effectiveness of the proposed technique. The experimentation has presented a promising result, where the reversing tools were not able to read the code.

Keywords: intellectual property, obfuscation, software security, reverse engineering

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Authors: David Ompong, Jai Singh

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A better understanding of the open-circuit voltage (Voc) related losses in organic solar cells (OSCs) is desirable in order to assess the photovoltaic performance of these devices. We have derived Voc as a function of charge carrier mobilities (μe and μh) for organic and hybrid solar cells by optimizing the drift-diffusion current density. The optimum Voc thus obtained depends on the energy difference between the highest occupied molecular orbital (HOMO) level and the quasi-Fermi level of holes of the donor material. We have found that the Voc depends on the ratio of the electron (μe) and hole (μh) mobilities and when μh > μe the Voc increases. The most important loss term in the Voc arises from the energetics of the donor and acceptor materials, which will be discussed in detail in this paper.

Keywords: charge carrier mobility, open-circuit voltage, organic solar cells, quasi-fermi levels

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Authors: Daly M. J, Condron C, Mulhall C, Eppich W, O'Neill J.

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Introduction: In contemporary clinical cardiology, comprehensive and holistic bedside evaluation including accurate cardiac auscultation is in decline despite having positive effects on patients and their outcomes. Methods: Scripted histories and scoring checklists for three clinical scenarios in cardiology were co-created and refined through iterative consensus by a panel of clinical experts; these were then paired with recordings of auscultatory findings from three actual patients with known valvular heart disease. A wearable vest with embedded pressure-sensitive panel speakers was developed to transmit these recordings when examined at the standard auscultation points. RCSI medical students volunteered for a series of three formative long case examinations in cardiology (LC1 – LC3) using this hybrid simulation. Participants were randomised into two groups: Group 1 received individual teaching from an expert trainer between LC1 and LC2; Group 2 received the same intervention between LC2 and LC3. Each participant’s long case examination performance was recorded and blindly scored by two peer participants and two RCSI examiners. Results: Sixty-eight participants were included in the study (age 27.6 ± 0.1 years; 74% female) and randomised into two groups; there were no significant differences in baseline characteristics between groups. Overall, the median total faculty examiner score was 39.8% (35.8 – 44.6%) in LC1 and increased to 63.3% (56.9 – 66.4%) in LC3, with those in Group 1 showing a greater improvement in LC2 total score than that observed in Group 2 (p < .001). Using the novel checklist, intraclass correlation coefficients (ICC) were excellent between examiners in all cases: ICC .994 – .997 (p < .001); correlation between peers and examiners improved in LC2 following peer grading of LC1 performances: ICC .857 – .867 (p < .001). Conclusion: Hybrid simulation and quantitative grading improve learning, standardisation of assessment, and direct comparisons of both performance and acumen in clinical cardiology.

Keywords: cardiology, clinical skills, long case examination, hybrid simulation, checklist

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Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic

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Authors: Tarek Aboueldahab, Hanan Farag

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Cost minimization of Multiple Vehicle Routing Problem becomes a critical issue in the field of transportation because it is NP-hard optimization problem and the search space is complex. Many researches use the hybridization of artificial intelligence (AI) models to solve this problem; however, it can not guarantee to reach the best solution due to the difficulty of searching the whole search space. To overcome this problem, we introduce the hybrid model of Discrete Particle Swarm Optimization (DPSO) with a passive congregation which enable searching the whole search space to compromise between both local and global search. The practical experiment shows that our model obviously outperforms other hybrid models in cost minimization.

Keywords: cost minimization, multi-vehicle routing problem, passive congregation, discrete swarm, passive congregation

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Authors: Ali Heydarimoghim

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In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

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Authors: Rajesh Kumar G

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A challenging aspect of any clinical trial is to carefully plan the study design to meet the study objective in optimum way and to validate the assumptions made during protocol designing. And when it is a pediatric study, there is the added challenge of stringent guidelines and difficulty in recruiting the necessary subjects. Unlike adult trials, there is not much historical data available for pediatrics, which is required to validate assumptions for planning pediatric trials. Typically, pediatric studies are initiated as soon as approval is obtained for a drug to be marketed for adults, so with the adult study historical information and with the available pediatric pilot study data or simulated pediatric data, the pediatric study can be well planned. Generalizing the historical adult study for new pediatric study is a tedious task; however, it is possible by integrating various statistical techniques and utilizing the advantage of hybrid study design, which will help to achieve the study objective in a smoother way even with the presence of many constraints. This research paper will explain how well the hybrid study design can be planned along with integrated technique (SEV) to plan the pediatric study; In brief the SEV technique (Simulation, Estimation (using borrowed adult data and applying Bayesian methods)) incorporates the use of simulating the planned study data and getting the desired estimates to Validate the assumptions.This method of validation can be used to improve the accuracy of data analysis, ensuring that results are as valid and reliable as possible, which allow us to make informed decisions well ahead of study initiation. With professional precision, this technique based on the collected data allows to gain insight into best practices when using data from historical study and simulated data alike.

Keywords: adaptive design, simulation, borrowing data, bayesian model

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Hiba S. Ahmed, Abbas A. Allawi, Riyadh A. Hindi

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Pultruded materials made of fiber-reinforced polymer (FRP) come in a broad range of shapes, such as bars, I-sections, C-sections, and other structural sections. These FRP materials are starting to compete with steel as structural materials because of their great resistance, low self-weight, and cheap maintenance costs-especially in corrosive conditions. This study aimed to evaluate the effectiveness of Glass Fiber Reinforced Polymer (GFRP) of the hybrid columns built by combining (GFRP) profiles with concrete columns because of their low cost and high structural efficiency. To achieve the aims of this study, nine circular columns with a diameter of (150 mm) and a height of (1000mm) were cast using normal concrete with compression strength equal to (35 MPa). The research involved three different types of reinforcement: hybrid circular columns type (IG) with GFRP I-section and 1% of the reinforcement ratio of steel bars, hybrid circular columns type (IS) with steel I-section and 1% of the reinforcement ratio of steel bars, (where the cross-section area of I-section for GFRP and steel was the same), compared with reference column (R) without I-section. To investigate the ultimate capacity, axial and lateral deformation, strain in longitudinal and transverse reinforcement, and failure mode of the circular column under different loading conditions (concentric and eccentric) with eccentricities of 25 mm and 50 mm, respectively. In the second part, an analytical finite element model will be performed using ABAQUS software to validate the experimental results.

Keywords: composite, columns, reinforced concrete, GFRP, axial load

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Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: W. Hasan, H. Farhat, A. Alhilo, L. Tamimi

Abstract:

Oil in water (O/W) emulsions are utilized extensively for cooling and lubricating cutting tools during parts machining. A robust Lattice Boltzmann (LBM) thermal-surfactants model, which provides a useful platform for exploring complex emulsions’ characteristics under variety of flow conditions, is used here for the study of the fluid behavior during conventional tools cooling. The transient thermal capabilities of the model are employed for simulating the effects of the flow conditions of O/W emulsions on the cooling of cutting tools. The model results show that the temperature outcome is slightly affected by reversing the direction of upper plate (workpiece). On the other hand, an important increase in effective viscosity is seen which supports better lubrication during the work.

Keywords: hybrid lattice Boltzmann method, Gunstensen model, thermal, surfactant-covered droplet, Marangoni stress

Procedia PDF Downloads 285

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

Procedia PDF Downloads 130

Authors: Satu Lautamäki

Abstract:

This paper presents findings from a multidisciplinary course (bachelor level) implemented at Seinäjoki University of Applied Sciences, Finland. The course aims to develop innovative thinking of students, by having projects given by companies, using design thinking methods as a tool for creativity and by integrating students into multidisciplinary teams working on the given projects. The course is obligatory for all first year bachelor students across four faculties (business and culture, food and agriculture, health care and social work, and technology). The course involves around 800 students and 30 pedagogical coaches, and it is implemented as an intensive one-week course each year. The paper discusses the pedagogy, structure and coordination of the course. Also, reflections on methods for the development of creative skills are given. Experts in contemporary, global context often work in teams, which consist of people who have different areas of expertise and represent various professional backgrounds. That is why there is a strong need for new training methods where multidisciplinary approach is at the heart of learning. Creative learning takes place when different parties bring information to the discussion and learn from each other. When students in different fields are looking for professional growth for themselves and take responsibility for the professional growth of other learners, they form a mutual learning relationship with each other. Multidisciplinary team members make decisions both individually and collectively, which helps them to understand and appreciate other disciplines. Our results show that creative and multidisciplinary project learning can develop diversity of knowledge and competences, for instance, students’ cultural knowledge, teamwork and innovation competences, time management and presentation skills as well as support a student’s personal development as an expert. It is highly recommended that higher education curricula should include various studies for students from different study fields to work in multidisciplinary teams.

Keywords: multidisciplinary learning, creative skills, innovative thinking, project-based learning

Procedia PDF Downloads 93

Authors: Boon Yih Mah

Abstract:

Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

Procedia PDF Downloads 542