Search results for: hybrid perovskite

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

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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

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

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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

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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Authors: A. Q. Sobia, M. S. Hamidah, I. Azmi, S. F. A. Rafeeqi

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Fibre-reinforced polymer (FRP) strengthened reinforced concrete (RC) structures are susceptible to intense deterioration when exposed to elevated temperatures, particularly in the incident of fire. FRP has the tendency to lose bond with the substrate due to the low glass transition temperature of epoxy; the key component of FRP matrix.  In the past few decades, various types of high performance cementitious composites (HPCC) were explored for the protection of RC structural members against elevated temperature. However, there is an inadequate information on the influence of elevated temperature on the ultra high performance fibre-reinforced cementitious composites (UHPFRCC) containing ground granulated blast furnace slag (GGBS) as a replacement of high alumina cement (HAC) in conjunction with hybrid fibres (basalt and polypropylene fibres), which could be a prospective fire resisting material for the structural components. The influence of elevated temperatures on the compressive as well as flexural strength of UHPFRCC, made of HAC-GGBS and hybrid fibres, were examined in this study. Besides control sample (without fibres), three other samples, containing 0.5%, 1% and 1.5% of basalt fibres by total weight of mix and 1 kg/m³ of polypropylene fibres, were prepared and tested. Another mix was also prepared with only 1 kg/m³ of polypropylene fibres. Each of the samples were retained at ambient temperature as well as exposed to 400, 700 and 1000 °C followed by testing after 28 and 56 days of conventional curing. Investigation of results disclosed that the use of hybrid fibres significantly helped to improve the ambient temperature compressive and flexural strength of UHPFRCC, which was found to be 80 and 14.3 MPa respectively. However, the optimum residual compressive strength was marked by UHPFRCC-CP (with polypropylene fibres only), equally after both curing days (28 and 56 days), i.e. 41%. In addition, the utmost residual flexural strength, after 28 and 56 days of curing, was marked by UHPFRCC– CP and UHPFRCC– CB2 (1 kg/m³ of PP fibres + 1% of basalt fibres) i.e. 39% and 48.5% respectively.

Keywords: fibre reinforced polymer materials (FRP), ground granulated blast furnace slag (GGBS), high-alumina cement, hybrid, fibres

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Authors: M. R. Vijayakumar, K. Priyanka, Ramoji Kosuru, Lakshmi, Sanjay Singh

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Trans resveratrol (RES) is a non-flavonoid poly-phenolic compound proved for its therapeutic and preventive effect against various types of cancer. However, the practical application of RES in cancer treatment is limited because of its higher dose (up to 7.5 g/day in humans), low biological half life, rapid metabolism and faster elimination in mammals. PEGylated core-shell type lipid polymer hybrid nanoparticles are the novel drug delivery systems for long circulation and improved anti cancer effect of its therapeutic payloads. Therefore, the main objective of this study is to extend the biological half life (long circulation) and improve the therapeutic efficacy of RES through core shell type of nanoparticles. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS), a novel surfactant is applied for the preparation of PEGylated lipid polymer hybrid nanoparticles. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Entrapment efficiency and invitro drug release were determined by ultracentrifugation method and dialysis bag method, respectively. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies after i.v administration were performed in sprague dawley rats. The prepared NPs were found to be spherical in shape with smooth surfaces. Particle size and zeta potential of prepared NPs were found to be in the range of 179.2±7.45 to 266.8±9.61 nm and -0.63 to -48.35 mV, respectively. DSC revealed absence of potential interaction. XRD study revealed presence of amorphous form in nanoparticles. Entrapment efficiency was found to be 83.7 % and drug release was found to be in controlled manner. MTT assay showed low MEC and pharmacokinetic studies showed higher AUC of nanoformulaition than its pristine drug. All these studies revealed that the RES loaded PEG modified core-shell type lipid polymer hybrid nanoparticles can be an alternative tool for chemopreventive and therapeutic application of RES in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating nanoparticles, bioavailability enhancement, core shell nanoparticles, lipid polymer hybrid nanoparticles

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Authors: Gautam, Gurcharan Singh, Mandeep Kaur, Yogesh Aggarwal, Sanjeev Naval

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The present ground reality scenario of suffering of humanity shows the evidence of failure to take wrong decisions to shape the civilization with Irresponsibilities in the history. A strong positive will of right responsibilities make the right civilization structure which affects itself and the whole world. Present suffering of humanity shows and reflect the failure of past decisions taken to shape the true culture with right social structure of society, due to unplanned system of Indian civilization and its rapid disaster of population make the failure to face all kind of problems which make the society sufferer. Our India is still suffering from disaster like earthquake, floods, droughts, tsunamis etc. and we face the uncountable disaster of deaths from the beginning of humanity at the present time. In this research paper our focus is to make a Disaster Resistance Structure having the solution of dense populated urban cities area by high vertical expansion HYBRID STRUCTURE. Our efforts are to analyse the Reinforced Concrete Hybrid Structure at different seismic zones, these concrete frames were analyzed using the response spectrum method to calculate and compare the different seismic displacement and drift. Seismic analysis by this method generally is based on dynamic analysis of building. Analysis results shows that the Reinforced Concrete Building at seismic Zone V having maximum peak story shear, base shear, drift and node displacement as compare to the analytical results of Reinforced Concrete Building at seismic Zone III and Zone IV. This analysis results indicating to focus on structural drawings strictly at construction site to make a HYBRID STRUCTURE. The study case is deal with the 10 story height of a vertical expansion Hybrid frame structure at different zones i.e. zone III, zone IV and zone V having the column 0.45x0.36mt and beam 0.6x0.36mt. with total height of 30mt, to make the structure more stable bracing techniques shell be applied like mage bracing and V shape bracing. If this kind of efforts or structure drawings are followed by the builders and contractors then we save the lives during earthquake disaster at Bhuj (Gujarat State, India) on 26th January, 2001 which resulted in more than 19,000 deaths. This kind of Disaster Resistance Structure having the capabilities to solve the problems of densely populated area of cities by the utilization of area in vertical expansion hybrid structure. We request to Government of India to make new plans and implementing it to save the lives from future disasters instead of unnecessary wants of development plans like Bullet Trains.

Keywords: history, irresponsibilities, unplanned social structure, humanity, hybrid structure, response spectrum analysis, DRIFT, and NODE displacement

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Authors: Bambang Heliyanto, Rully Dyah Purwati, Hasnam, Fadjry Djufry

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Jatropha curcas L., a drought tolerant and monoecious perennial shrub, has received attention worldwide during the past decade. Realizing the facts, the Indonesian government has decided to option for Jatropha and palm oil for in country biofuel production. To support the program development of high yielding jatropha varieties is necessary. This paper reviews Jatropha improvement program in Indonesia using mass selection and hybrid development. To start with, at the end of 2005, in-country germplasm collection was mobilized to Lampung and Nusa Tenggara Barat (NTB) provinces and successfully collected 15 provenances/sub-provenances which serves as a base population for selection. A significant improvement has been achieved through a simple recurrent breeding selection during 2006 to 2007. Seed yield productivity increased more than double, from 0.36 to 0.97 ton dry seed per hectare during the first selection cycle (IP-1), and then increased to 2.2 ton per hectare during the second cycles (IP-2) in Lampung provenance. Similar result was also observed in NTB provenance. Seed yield productivity increased from 0.43 ton to 1 ton dry seed per hectare in the first cycle (IP-1), and then 1.9 ton in the second cycle (IP-2). In 2008, the population IP-3 resulted from the third cycle of selection have been identified which were capable of producing 2.2 to 2.4 ton seed yield per hectare. To improve the seed yield per hectare, jatropha hybrid varieties was developed involving superior provenances. As a result a Jatropha Energy Terbarukan (JET) variety-2 was released in 2017 with seed yield potential of 2.6 ton per hectare. The use of this high yielding genotypes for biofuel is discussed.

Keywords: Jatropha curcas, provenance, biofuel, improve population, hybrid

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Authors: Adel. M. Sharaf, Foad H. Gandoman

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Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PV-hybrid-Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid-Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6-pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, smart grid, stabilization, PV-battery storage, Switched Filter-Compensation (SFC)

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Authors: J. Tamosaitiene

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The article focuses on the identification and classification of key risk management criteria that represent the most important sustainability aspects of the construction industry. The construction sector is one of the most important sectors in Lithuania. Nowadays, the assessment of the risk level of a construction project is especially important for the quality of construction projects, the growth of enterprises and the sector. To establish the most important criteria for successful growth of the sector, a questionnaire for experts was developed. The analytic hierarchy process (AHP), the expert judgement method and other multicriteria decision making (MCDM) methods were used to develop the hybrid model. The results were used to develop an integrated knowledge system for the measurement of a risk level particular to construction projects. The article presents a practical case that details the developed system, sustainable aspects, and risk assessment.

Keywords: risk, system, model, construction

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Authors: A. Selmi, A. Bettaibi, H. Rahmouni, R. M’nassri, N. Chniba Boudjada, A. Chiekhrouhou, K. Khirouni

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Investigation of magnetic and magnetocaloric properties of Pr₀.₇Ca₀.₃Mn₀.₉M₀.₁O₃ perovskite manganites (M=Cr and Ni) has been carried out. Our compounds were prepared by the conventional solid-state reaction method at high temperatures. Rietveld refinement of X-ray diffraction pattern using FULLPROF method shows that all compounds adopt the orthorhombic structure with Pnma space group. The partial substitution of Mn-site drives the system from charge order state to ferromagnetic one with a Curie temperature T𝒸=150K, 118k and 116K for M=Cr and Ni, respectively. Magnetization measurements versus temperature in a magnetic applied field of 0.05T show that all our samples exhibit a paramagnetic–ferromagnetic transition with decreasing temperature. From M(H) isotherms, we have deduced the magnetic entropy change, which present maximum values of 2.37 J/kg.K and 2.94 J/kg.K, in a magnetic field change of 5T for M=Cr and Ni, respectively.

Keywords: manganites, magnetocaloric, magnetic, refrigeration

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Authors: C. Shalini Devi

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This work describes the stress concentration in a rectangular specimen with a circular hole made up of hybrid composite material with the combination of glass/carbon with epoxy. The arrangements of cross ply lamina in the sequence of alternative carbon and glass, using carbon fiber in panel, gives more strength to the structure as the carbon properties are higher when compared to glass. Typical aircraft and automobile components are with cut-outs, and such cut-outs reduce the weight of the aircraft according to the weight reduction law and also they reduce the bulking load carrying capacity. Experimental investigations were carried out using three specimens as per ASTM D5766 and three specimens as per ASTM D3039 in the Universal Testing Machine. Stress concentration in the rectangular specimen with a hole is also analysed using FEA and comparing the results.

Keywords: composite, stress concentration, finite element analysis, tensile strength

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Authors: Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

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Authors: Maria Ledinskaya

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This paper examines the Morris Collection Conservation Project at the Sainsbury Centre for Visual Arts in the context of Agile, Lean, and Hybrid project management. It is part case study and part literature review. To date, relatively little has been written about non-traditional project management approaches in heritage conservation. This paper seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation, by referencing their practical application on a recent museum-based conservation project. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre for Visual Arts by private collectors Michael and Joyce Morris. The first part introduces the chronological timeline and key elements of the project. It describes a medium-size conservation project of moderate complexity, which was planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown condition and materials, unconfirmed budget. The project was also impacted by the unknown unknowns of the COVID-19 pandemic, such as indeterminate lockdowns, and the need to accommodate social distancing and remote communications. The author, a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Collection Conservation Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. Subsequent sections examine the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment, due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Collection Conservation Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, as well as the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics, particularly with respect to change management, bespoke ethics, shared decision-making, and value-based cost-benefit conservation strategy. The author concludes that the Morris Collection Conservation Project had multiple Agile and Lean features which were instrumental to the successful delivery of the project. These key features are identified as distributed decision making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point largely in favour of a Hybrid model which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: project management, conservation, waterfall, agile, lean, hybrid

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Authors: Fatma Keskin Arabul, Ibrahim Senol, Ahmet Yigit Arabul, Ali Rifat Boynuegri

Abstract:

On account of the concern of the fossil fuel is depleting and its negative effects on the environment, interest in alternative energy sources is increasing day by day. However, considering the importance of transportation in human life, instead of oil and its derivatives fueled vehicles with internal combustion engines, electric vehicles which are sensitive to the environment and working with electrical energy has begun to develop. In this study, simulation was carried out for providing energy management and recovering regenerative braking in fuel cell-battery hybrid electric vehicle. The main power supply of the vehicle is fuel cell on the other hand not only instantaneous power is supplied by the battery but also the energy generated due to regenerative breaking is stored in the battery. Obtained results of the simulation is analyzed and discussed.

Keywords: electric vehicles, fuel cell, battery, regenerative braking, energy management

Procedia PDF Downloads 694

Authors: M. Assaad, J. Mäkiö, T. Mäkelä, M. Kankaanranta, N. Fachantidis, V. Dagdilelis, A. Reid, C. R. del Rio, E. V. Pavlysh, S. V. Piashkun

Abstract:

To bring science and society together in Europe, thus increasing the continent’s international competitiveness, STEM (science, technology, engineering and mathematics) education must be more relatable to European youths in their everyday life. STIMEY (Science, Technology, Innovation, Mathematics, Engineering for the Young) project researches and develops a hybrid educational environment with multi-level components that is being designed and developed based on a well-researched pedagogical framework, aiming to make STEM education more attractive to young people aged 10 to 18 years in this digital era. This environment combines social media components, robotic artefacts, and radio to educate, engage and increase students’ interest in STEM education and careers from a young age. Additionally, it offers educators the necessary modern tools to deliver STEM education in an attractive and engaging manner in or out of class. Moreover, it enables parents to keep track of their children’s education, and collaborate with their teachers on their development. Finally, the open platform allows businesses to invest in the growth of the youths’ talents and skills in line with the economic and labour market needs through entrepreneurial tools. Thus, universities, schools, teachers, students, parents, and businesses come together to complete a circle in which STEM becomes part of the daily life of youths through a hybrid educational environment that also prepares them for future careers.

Keywords: e-learning, entrepreneurship, pedagogy, robotics, serious gaming, social media, STEM education

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Authors: Ye Ling, Ruan Haihui

Abstract:

Aqueous Zn-ion hybrid supercapacitors (AZHSCs) pertain to a new type of electrochemical energy storage device that has received considerable attention. They integrate the advantages of high-energy Zn-ion batteries and high-power supercapacitors to meet the demand for low-cost, long-term durability, and high safety. Nevertheless, the challenge caused by the finite ion adsorption/desorption capacity of carbon electrodes gravely limits their energy densities. This work describes titanium nitride@nitrogen-doped carbon nanocage (TiN@NCNC) composite cathodes for AZHSCs to achieve a greatly improved energy density, and the composites can be facile synthesized based on the calcination of a mixture of tetrabutyl titanate and zeolitic imidazolate framework-8 in argon atmosphere. The resulting composites are featured by the ultra-fine TiN particles dispersed uniformly on the NCNC surfaces, enhancing the Zn2+ storage capabilities. Using TiN@NCNC cathodes, the AZHSCs can operate stably with a high energy density of 154 Wh kg-¹ at a specific power of 270 W kg-¹ and achieve a remarkable capacity retention of 88.9% after 104 cycles at 5 A g-¹. At an extreme specific power of 8.7 kW kg-1, the AZHSCs can retain an energy density of 97.2 Wh kg-1. With these results, we stress that the TiN@NCNC cathodes render high-performance AZHSCs, and the facile one-pot method can easily be scaled up, which enables AZHSCs a new energy-storage component for managing intermitted renewable energy sources.

Keywords: Zn-ion hybrid supercapacitors, ion absorption/desorption reactions, titanium nitride, zeolitic imidazolate framework-8

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Authors: Redouane Krini, Lutz Nuhn, Hicham El Mard Cheol Woo Ha, Yoondeok Han, Kwang-Sup Lee, Dong-Yol Yang, Jinsoo Joo, Rudolf Zentel

Abstract:

To use Quantum Dots (QDs) in the two photon initiated polymerization technique (TPIP) for 3D patternings, QDs were modified on the surface with photosensitive end groups which are able to undergo a photopolymerization. We were able to fabricate fluorescent 3D lattice structures using photopatternable QDs by TPIP for photonic devices such as photonic crystals and metamaterials. The QDs in different diameter have different emission colors and through mixing of RGB QDs white light fluorescent from the polymeric structures has been created. Metamaterials are capable for unique interaction with the electrical and magnetic components of the electromagnetic radiation and for manipulating light it is crucial to have a negative refractive index. In combination with QDs via TPIP technique polymeric structures can be designed with properties which cannot be found in nature. This makes these artificial materials gaining a huge importance for real-life applications in photonic and optoelectronic. Understanding of interactions between nanoparticles and biological systems is of a huge interest in the biomedical research field. We developed a synthetic strategy of polymer functionalized nanoparticles for biomedical studies to obtain hybrid systems of QDs and copolymers with a strong binding network in an inner shell and which can be modified in the end through their poly(ethylene glycol) functionalized outer shell. These hybrid systems can be used as models for investigation of cell penetration and drug delivery by using measurements combination between CryoTEM and fluorescence studies.

Keywords: biomedical study models, lithography, photo induced polymerization, quantum dots

Procedia PDF Downloads 504

Authors: Kanta Maan Sangwan, Neetu Ahlawat, Rajender Singh Kundu

Abstract:

BaZrTiO3 ceramics having high dielectric constant and low dielectric loss are interesting material for being used as commercial capacitor applications. BZT (BaZrTiO3) has attracted attentions for their many applications for the microwave technology as the doping of Zr4+ on Ti4+ has advantage to the stability of the system. In the present work, co-doping of Zr and V with BaTiO3 ceramics was synthesized by the conventional solid state reaction technique and sintered at 1200 K for 6 hours, and their structural and ferroelectric properties were studied. The XRD (x-ray diffraction) pattern of BZT (BaZrTiO3) ceramics shows that the crystalline sample is single phase tetragonal structure with P4mm space group. The result revealed that Zr ion enters the unit cell maintaining the perovskite structure of BZT ceramics and the impedance spectroscopy of the sample performed in selected frequency and temperature range.

Keywords: ferroelectric, impedance spectroscopy, space group, tetragonal

Procedia PDF Downloads 188