Search results for: adaptive traits

Authors: M. Bazin, I. Bouguir, D. Combe, V. Germain, G. Lassade

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The problem of managing a fleet of quad-rotor drones in a completely unknown environment is analyzed in the present paper. This work is following the footsteps of other studies about how should be managed the movements of a swarm of elements that have to stay gathered throughout their activities. In this paper we aim to demonstrate the limitations of a system where absolutely all the calculations and physical movements of our elements are done by one single external element. The strategy of control is an adaptive approach which takes into account the explored environment. This is made possible thanks to a set of command rules which can guide the drones through various missions with defined goal. The result of the mission is independent of the nature of environment and the number of drones in the fleet. This strategy is based on a simultaneous usage of different data: obstacles positions, real-time positions of all drones and relative positions between the different drones. The present work is made with the Robot Operating System and used several open-source projects on localization and usage of drones.

Keywords: cooperative guidance, distributed control, unmanned aerial vehicle, obstacle avoidance

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Authors: Azene Tesfaye, Yohannes Petros, Habtamu Zeleke

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To evaluate genetic variation among Ethiopian lentil, laboratory experiment were conducted to screen 12 accessions of lentil (Lens culinaris M.) for salt tolerance. Seeds of 12 Lentil accessions were grown at laboratory (Petri dish) condition with different levels of salinity (0, 2, 4, and 8 dSm-1 NaCl) for 4 weeks. The experimental design was completely randomized design (CRD) in factorial combination with three replications. Data analysis was carried out using SAS software. Average germination time, germination percentage, seedling shoot and root traits, seedling shoot and root weight were evaluated. The two way ANOVA for varieties revealed statistically significant variation among lentil accession, NaCl level and their interactions (p<0.001) with respect to the entire parameters. It was found that salt stress significantly delays germination rate and decreases germination percentage, shoot and root length, seedling shoot and root weight of lentil accessions. The degree of decrement varied with accessions and salinity levels. Accessions 36120, 9235 and 36004 were better salt tolerant than the other accessions. As the result, it is recommended to be used as a genetic resource for the development of lentil accession and other very salt sensitive crop with improved germination under salt stress condition.

Keywords: accession, germination, lentil, NaCl, screening, seedling stage

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Leidy M. Aldana, Jorge E. Camargo

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Adversarial Machine Learning has gained importance in recent years as Cybersecurity has gained too, especially malware, it has affected different entities and people in recent years. This paper shows a literature review about defense methods created to prevent adversarial machine learning attacks, firstable it shows an introduction about the context and the description of some terms, in the results section some of the attacks are described, focusing on detecting adversarial examples before coming to the machine learning algorithm and showing other categories that exist in defense. A method with five steps is proposed in the method section in order to define a way to make the literature review; in addition, this paper summarizes the contributions in this research field in the last seven years to identify research directions in this area. About the findings, the category with least quantity of challenges in defense is the Detection of adversarial examples being this one a viable research route with the adaptive approach in attack and defense.

Keywords: Malware, adversarial, machine learning, defense, attack

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Authors: V. Jamuna, A. K. Chakravarty, C. S. Patil, Vijay Kumar, M. A. Mir, Rakesh Kumar

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Intense selection of buffaloes for milk production at organized herds of the country without giving due attention to fertility traits viz. pregnancy rate has lead to deterioration in their performances. Aim of study is to develop an optimum model for predicting pregnancy rate and to assess the level of pregnancy rate with respect to milk production Murrah buffaloes. Data pertaining to 1224 lactation records of Murrah buffaloes spread over a period 21 years were analyzed and it was observed that pregnancy rate depicted negative phenotypic association with lactation milk yield (-0.08 ± 0.04). For developing optimum model for pregnancy rate in Murrah buffaloes seven simple and multiple regression models were developed. Among the seven models, model II having only Service period as an independent reproduction variable, was found to be the best prediction model, based on the four statistical criterions (high coefficient of determination (R 2), low mean sum of squares due to error (MSSe), conceptual predictive (CP) value, and Bayesian information criterion (BIC). For standardizing the level of fertility with milk production, pregnancy rate was classified into seven classes with the increment of 10% in all parities, life time and their corresponding average pregnancy rate in relation to the average lactation milk yield (MY).It was observed that to achieve around 2000 kg MY which can be considered optimum for Indian Murrah buffaloes, level of pregnancy rate should be in between 30-50%.

Keywords: life time, pregnancy rate, production, service period, standardization

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Authors: Bernard Vaernes

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Creativity is thought to be of importance for educational success. Educational institutions vary greatly in regard to socioeconomic status (SES) and curricular emphasis on creativity. Research is needed to clarify the effects of age and SES on creativity. The objective of this study will be to compare the creative performance of children with different SES, low or high, and age. It is hypothesized that younger children will score higher than older children, independent of their SES. Children aged 15, 12, and 9 from four different junior and secondary schools in Warsaw, Poland, will participate in the study. The schools will differ in terms of socioeconomic, geographic localization. To assess creative performance, a Polish adaptation of the Torrance Test of Creative Thinking (TTCT) will be used. In order to select low and high SES individuals for SES grouping, a Polish adaptation of the MacArthur Scale of Subjective Social Status will be given to all participants. To control for individual differences in personality traits, a Polish adaptation of the Big Five Questionnaire for Children (BFQ-C) will be used. These measures will allow to compare the creative performance of children with different age and SES and eliminate confound variables. It is predicted that younger children, as well as high SES children, will score higher on the TTCT than older children, and low SES children. The findings of this study may provide useful insight into socioeconomic and age differences in creativity, as well as facilitating teacher’s adjustment of learning styles and emphasis on creativity in relation to the SES and age of their students.

Keywords: big five questionnaire for children, children, creativity, socioeconomic status, Torrance test of creative thinking, TTCT

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Authors: Sun-Ki Hong, Yong-Ho Cho, Ki-Seok Kim, Tae-Sam Kang

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Piezoelectric actuator is treated as RC load when it is modeled electrically. For some piezoelectric actuator applications, arbitrary voltage is required to actuate. Especially for unidirectional arbitrary voltage driving like as sine wave, some special inverter with circuit that can charge and discharge the capacitive energy can be used. In this case, the difference between power supply level and the object voltage level for RC load is varied. Because the control gain is constant, the controlled output is not uniform according to the voltage difference. In this paper, for charge and discharge circuit for unidirectional arbitrary voltage driving for piezoelectric actuator, the controller gain is controlled according to the voltage difference. With the proposed simple idea, the load voltage can have controlled smoothly although the voltage difference is varied. The appropriateness is proved from the simulation of the proposed circuit.

Keywords: analog voltage inverter, capacitive load, gain control, dc-dc converter, piezoelectric, voltage waveform

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Authors: Kurotimi M. Fems, Francis D. W. Poazi, Helen Opigo

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Entrepreneurship education and graduate entrepreneurship have taken centre stage in many countries as a 21st century strategy for economic growth and development. Entrepreneurship education has been viewed as a pre-requisite tool for a more effective and successful business operation. The purpose of this study is to ascertain if entrepreneurship education is a foundational requirement for graduate entrepreneurial engagement or, if other factors such as personality trait, need for achievement, situational circumstances or experience and competence played a more vital role in stimulating graduate entrepreneurial engagement. The scope of the research study is entrepreneurs within Yenagoa metropolis in Bayelsa state, Nigeria. The sample target is graduates engaged in entrepreneurship activities (graduates who own and run businesses). Stratified sampling technique was used and 101 responses were gotten from a total of 300 questionnaires issued. Bar chart, tables, and percentages were used to analyze the data collected. Findings: The findings revealed that personality traits, situational circumstance, need for achievement and experience/competence were the foundational factors stimulating graduate entrepreneurs to engage in entrepreneurial pursuits. Of all, personality trait showed the highest score with 73 (73%) out of 101 entrepreneurs agreeing. Experience/Competence and situational circumstances followed behind with 66 (65%) and 63 (62.4%) respectively. Entrepreneurship education revealed the least score with 33 (32.3%) out of 101 participating entrepreneurs. All hope, however, is not lost, as this shows that something can be done to increase the impact of entrepreneurship education on graduate entrepreneurship.

Keywords: creative destruction, entrepreneurs, entrepreneurship education, graduate entrepreneurship, pre-requisite

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Authors: Hamed Saremi, Suzan Taghavy, Seyed Mohammad Hanif Sanjari, Mostafa Kahali

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study, the identified indicators of brand equity are based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: brand, cosmetic product, ANFIS, DEMATEL

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Authors: Elena Selezneva

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Over the last two decades, an unprecedented growth in uncertainty and volatility in all aspects of the business environment has caused major global supply chain disruptions and malfunctions. The effects of one failed company in a supply chain can ripple up and down the chain, causing a number of entities or an entire supply chain to collapse. The complicating factor is that an increasingly unstable and unpredictable business environment fuels the growing complexity of global supply chain networks. That makes supply chain operations extremely unpredictable and hard to manage with the established methods and strategies. It has caused the premature demise of many companies around the globe as they could not withstand or adapt to the storm of change. Solutions to this problem are not easy to come by. There is a lack of new empirically tested theories and practically viable supply chain resilience strategies. The mainstream organizational approach to managing supply chain resilience is rooted in well-established theories developed in the 1960-1980s. However, their effectiveness is questionable in currently extremely volatile business environments. The systems thinking approach offers an alternative view of supply chain resilience. Still, it is very much in the development stage. The aim of this explorative research is to investigate supply chain management strategies that are successful in taming complexity in volatile business environments and creating resilience in supply chains. The design of this research methodology was guided by an interpretivist paradigm. A literature review informed the selection of the systems thinking approach to supply chain resilience. Therefore, an explorative single case study of Ventilator Challenge UK was selected as a case study for its extremely resilient performance of its supply chain during a period of national crisis. Ventilator Challenge UK is intensive care ventilators supply project for the NHS. It ran for 3.5 months and finished in 2020. The participants moved on with their lives, and most of them are not employed by the same organizations anymore. Therefore, the study data includes documents, historical interviews, live interviews with participants, and social media postings. The data analysis was accomplished in two stages. First, data were thematically analyzed. In the second stage, pattern matching and pattern identification were used to identify themes that formed the findings of the research. The findings from the Ventilator Challenge UK case study supply management practices demonstrated all the features of an adaptive dynamic system. They cover all the elements of supply chain and employ an entire arsenal of adaptive dynamic system strategies enabling supply chain resilience. Also, it is not a simple sum of parts and strategies. Bonding elements and connections between the components of a supply chain and its environment enabled the amplification of resilience in the form of systemic emergence. Enablers are categorized into three subsystems: supply chain central strategy, supply chain operations, and supply chain communications. Together, these subsystems and their interconnections form the resilient supply chain system framework conceptualized by the author.

Keywords: enablers of supply chain resilience, supply chain resilience strategies, systemic approach in supply chain management, resilient supply chain system framework, ventilator challenge UK

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Authors: Rattanan Tippayaphalapholgul, Yasothorn Sapsathiarn

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Composites of piezoelectric materials are widely use in practical applications such as nondestructive testing devices, smart adaptive structures and medical devices. A thorough understanding of coupled electro-elastic response and properties of piezocomposite are crucial for the development and design of piezoelectric composite materials used in advanced applications. The micromechanics analysis is employed in this paper to determine the response and engineering properties of the piezocomposite. A mechanical imperfect interface bonding between piezoelectric inclusion and polymer matrix is taken into consideration in the analysis. The micromechanics analysis is based on the Boundary Element Method (BEM) together with the periodic micro-field micromechanics theory. A selected set of numerical results is presented to investigate the influence of volume ratio and interface bonding condition on effective piezocomposite material coefficients and portray basic features of coupled electroelastic response within the domain of piezocomposite unit cell.

Keywords: effective engineering properties, electroelastic response, imperfect interface, piezocomposite

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Authors: Nagaletchumi Balasubramaniam, A. Mohd Isa

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Engineers have a leading role in planning, designing, building and ensuring a sustainable future. Universiti Tenaga Nasional (UNITEN) acknowledges this role by assigning sustainable development as one of the expected traits that a UNITEN student should have upon graduation, formalized as the Programme Outcomes 7 (PO7): Students graduating from the Bachelor of Electrical and Electronics (BEEE) program will have the ability to demonstrate knowledge of the impact of professional engineering solutions in environmental contexts and the need for sustainable development. This paper explores how PO7 is integrated within the BEEE (Hons) program in UNITEN under the framework of Outcome Base Education (OBE). Five technical core courses were specifically assigned by UNITEN to reflect attainment of PO7. Under UNITEN’s definition, the attainment criterion of a PO is set as 70/40. This means that 70% of the students taking the course achieve at least 40% of the full marks. The paper first gives an overview of the overall OBE system as applied in UNITEN, particularly describing the key and supporting courses approach adopted for each PO. Then, the paper reviews the mechanism in which PO7 is taught and assessed in the five assigned courses. Data on PO7 attainment from four of the five courses are collected and analyzed for two student cohorts to investigate the interrelationship between the courses assigned to PO7. It was found that the five courses have different mechanisms for assessing PO7, and that generally PO7 is attained for the assigned courses. This reflects positively on the UNITEN method for integrating sustainable development within the engineering undergraduate programme.

Keywords: direct assessment, engineering education, outcome base education, programme outcome, sustainable development

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Authors: Inês Ramalhete, Hugo Farias, Rui da Silva Pinto

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Adequate housing has been a widely discussed theme in academic circles related to low-cost housing, whereas its physical features are easy to deal with, overcrowding (related to social, cultural and economic aspects) is still ambiguous, particularly regarding the set of indicators that can accurately reflect and measure it. This paper develops research on low-cost housing models for developing countries and what is the best method to embed overcrowding as an important parameter for adaptability. A critical review of international overcrowding indicators and their application in two developing countries, Cape Verde and Angola, is presented. The several rationales and the constraints for an accurate assessment of overcrowding are considered, namely baseline data (statistics), which can induce misjudgments, as well as social and cultural factors (such as personal choices of residents). This paper proposes a way to tackle overcrowding through housing adaptability, considering factors such as physical flexibility, functional ambiguity, and incremental expansion schemes. Moreover, a case-study is presented to establish a framework for the theoretical application of the proposed approach.

Keywords: adaptive housing, low cost housing, overcrowding, housing model

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

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Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: I. S. R. Butswat, D. Zahraddeen

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This study identified and described some skill-based and necessity-driven entrepreneurship in animal agriculture (AA). AA is an integral segment of the world food industry, and provides a good and rapid source of income. The contribution of AA to the Sub-Saharan economy is quite significant, and there are still large opportunities that remain untapped in the sector. However, it is imperative to understand, simplify and package the various components of AA in order to pave way for rapid wealth creation, poverty eradication and women empowerment programmes in sub-Saharan Africa and other developing countries. The entrepreneurial areas of AA highlighted were animal breeding, livestock fattening, dairy production, poultry farming, meat production (beef, mutton, chevon, etc.), rabbit farming, wool/leather production, animal traction, animal feed industry, commercial pasture management, fish farming, sport animals, micro livestock production, private ownership of abattoirs, slaughter slabs, animal parks and zoos, among others. This study concludes that reproductive biotechnology such as oestrous synchronization, super-/multiple ovulation, artificial insemination and embryo transfer can be employed as a tool for improvement of genetic make-up of low-yielding animals in terms of milk, meat, egg, wool, leather production and other economic traits that will necessitate sustainable job and wealth creations.

Keywords: animal, agriculture, entreprenurship, wealth

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

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Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

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Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

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To address the problem that the FM continuous-wave radar (FMCW) extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a new detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a BP neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise and accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal-to-noise ratio of the sign signals.

Keywords: frequency modulated continuous wave radar, ICEEMDAN, BP neural network, vital signs signal

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: adaptive filtering, sparse system identification, TD-LMS algorithm, VSSLMS algorithm

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Authors: Eduardo F. Mello, Peter H. Bauer

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The primary focus of this paper is the generation of energy-optimal speed trajectories for heterogeneous electric vehicle platoons in urban driving conditions. Optimal speed trajectories are generated for individual vehicles and for an entire platoon under the assumption that they can be executed without errors, as would be the case for self-driving vehicles. It is then shown that the optimization for the “average vehicle in the platoon” generates similar transportation energy savings to optimizing speed trajectories for each vehicle individually. The introduced approach only requires the lead vehicle to run the optimization software while the remaining vehicles are only required to have adaptive cruise control capability. The achieved energy savings are typically between 30% and 50% for stop-to-stop segments in cities. The prime motivation of urban platooning comes from the fact that urban platoons efficiently utilize the available space and the minimization of transportation energy in cities is important for many reasons, i.e., for environmental, power, and range considerations.

Keywords: electric vehicles, energy efficiency, optimization, platooning, self-driving vehicles, urban traffic

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Authors: Othman Elmahdy Othman

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The objectives of this study were to identify polymorphisms in the STAT5A using Restriction Fragment Length Polymorphism and DGAT1 using Single-Strand Conformation Polymorphism genes among three Egyptian goat breeds (Barki, Zaraibi, and Damascus) as well as investigate the effect of their genotypes on milk composition traits of Zaraibi goats. One hundred and fifty blood samples were collected for DNA extraction, 60 from Zaraibi, 40 from Damascus and 50 from Barki breeds. Fat, protein and lactose percentages were determined in Zaraibi goat milk using an automatic milk analyzer. Two genotypes, CC and CT (for STAT5A) and C-C- and C-C+ (for DGAT1), were identified in the three Egyptian goat breeds with different frequencies. The associations between these genotypes and milk fat, protein and lactose were determined in Zaraibi breed. The results showed that the STAT5A genotypes had significant effects on milk yield, protein, fat and lactose with the superiority of CT genotype over CC. Regarding DGAT1 polymorphism, the result showed the only association between it with milk fat where the animals with C-C+ genotype had greater milk fat than animals possess C-C- genotype. The association of combined genotypes with milk trait declared that the does with heterozygous genotypes for both genes are preferred than does with homozygous genotypes where the animals with CTC-C+ have more milk yield, fat and protein than those with CCC-C- genotype. In conclusion, the result showed that C/T and C-/C+ SNPs of STAT5A and DGAT1 genes respectively may be useful markers for assisted selection programs to improve goat milk composition

Keywords: DGAT1, genetic polymorphism, milk trait, STAT5A

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Authors: Hue Dinh, Binh Nguyen, Vivian Mendez, Phillip W. Taylor, Fleur Ponton

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Better understanding of how parental diet affects offspring traits is an important ecological and evolutionary question. In this study, we explored how maternal diet influences offspring physiology and resistance to infection using Bactrocera tryoni (Q-fly) as a system model. Female Q-flies were fed one of six single diets varying in their yeast-to-sugar ratio yielding six protein-to-carbohydrate ratios. As controls, we used females that were given a choice between yeast and sugar. Males were reared on a choice diet and allowed to mate with females 14 days post-emergence. Results showed that while maternal diet does not influence offspring developmental time, it has a strong effect on larval body weight. Mother fed either high-protein or high-sugar diet produced larger progeny. By challenging offspring with the bacterium Serratia marcescens, we found that female offspring from mothers fed high-sugar diet survived better the infection compared to those from mothers fed low-sugar diet. In contrast, male offspring produced by mother fed high-protein diet showed better resistance to the infection compared to those produced by mother fed low-protein diet. These results suggested sex-dependent transgenerational effects of maternal nutrition on offspring physiology and immunity.

Keywords: bacterial infection, Bactrocera tryoni, maternal diet, offspring, Serretia marcescens

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Authors: Mohamed A. Moustafa Hassan, Omnia S .S. Hussian, Hany M. Elsaved

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This paper introduces the application of Fuzzy Logic Controller (FLC) to extract the Maximum Power Point Tracking (MPPT) from the PV panel. In addition, the proportional integral (PI) controller is used to be the strategy for battery charge control according to acceptable performance criteria. The parameters of the PI controller have been tuned via Modified Adaptive Accelerated Coefficient Particle Swarm Optimization (MAACPSO) technique. The simulation results, using MATLAB/Simulink tools, show that the FLC technique has advantages for use in the MPPT problem, as it provides a fast response under changes in environmental conditions such as radiation and temperature. In addition, the use of PI controller based on MAACPSO results in a good performance in terms of controlling battery charging with constant voltage and current to execute rapid charging.

Keywords: battery charging, fuzzy logic control, maximum power point tracking, PV system, PI controller, evolutionary technique

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Authors: Jessica Beck

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Despite efforts to address the issue through prevention and education, sexual assault remains an issue within the military. Rape supportive beliefs have been identified as a risk factor linked to sexually aggressive and coercive behaviours. Rape myth acceptance is part of a wider cognitive framework of attitudes which perpetuate negative sociocultural norms about the male role. Notwithstanding the established links between rape myth acceptance, attitudinal variables, and rape proclivity, relatively little research has been conducted with military samples. In this study, 151 British military veterans completed an online survey measuring their rape myth acceptance, attitudes towards women, belief in male role norms and basic personality traits. Consistent with previous research, male veterans had higher levels of rape myth acceptance, more negative attitudes towards women, and subscribed to more traditional notions of masculinity. The types of myths endorsed also varied by gender, with male veterans significantly more likely to blame rape victims or believe women regularly lie about being raped. A relationship between rape myth acceptance, negative attitudes towards women, and adherence to male norms was found, which explained a significant proportion of the variance in rape myth acceptance. Implications for sexual assault prevention programmes are discussed.

Keywords: rape myths, rape myth acceptance, military sexual assault, sexual assault beliefs

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Authors: Irene T. Ho

Abstract:

Students with Autism Spectrum Disorder (ASD) studying in mainstream schools often face difficulties adjusting to school life and teachers often find it challenging to meet the needs of these students. The Hong Kong Jockey Club Autism Support Network (JC A-Connect) is an initiative launched in 2015 to enhance support for students with ASD as well as their families and schools. The School Support Programme of the Project aims at building the capacity of schools to provide quality education for these students. The present report provides a summary of the main features of the support model and the related evaluation results. The school support model was conceptualized in response to four observed needs: (1) inadequate teacher expertise in dealing with the related challenges, (2) the need to promote evidence-based practices in schools, (3) less than satisfactory home-school collaboration and whole-school participation, and (4) lack of concerted effort by different parties involved in providing support to schools. The resulting model had partnership and capacity building as two guiding tenets for the School Support Programme. There were two levels of partnership promoted in the project. At the programme support level, a platform that enables effective collaboration among major stakeholders was established, including the funding body that provides the necessary resources, the Education Bureau that helps to engage schools, university experts who provide professional leadership and research support, as well as non-governmental organization (NGO) professionals who provide services to the schools. At the programme implementation level, tripartite collaboration among teachers, parents and professionals was emphasized. This notion of partnership permeated efforts at capacity building targeting students with ASD, school personnel, parents and peers. During 2015 to 2018, school-based programmes were implemented in over 400 primary and secondary schools with the following features: (1) spiral Tier 2 (group) training for students with ASD to enhance their adaptive skills, led by professionals but with strong teacher involvement to promote transfer of knowledge and skills; (2) supplementary programmes for teachers, parents and peers to enhance their capability to support students with ASD; and (3) efforts at promoting continuing or transfer of learning, on the part of both students and teachers, to Tier 1 (classroom practice) and Tier 3 (individual training) contexts. Over 5,000 students participated in the Programme, representing about 50% of students diagnosed with ASD in mainstream public sector schools in Hong Kong. Results showed that the Programme was effective in helping students improve to various extents at three levels: achievement of specific training goals, improvement in adaptive skills in school, and change in ASD symptoms. The sense of competence of teachers and parents in dealing with ASD-related issues, measured by self-report rating scales, was also significantly enhanced. Moreover, effects on enhancing the school system to provide support for students with ASD, assessed according to indicators of inclusive education, were seen. The process and results of this Programme illustrate how obstacles to inclusive education for students with ASD could be overcome by strengthening the necessary partnerships and building the required capabilities of all parties concerned.

Keywords: autism, school support, skills training, teacher development, three-tier model

Procedia PDF Downloads 88

Authors: Amir Bastani

Abstract:

The result of the research in the field of human behavioural genetics demonstrates a genetic contribution of behavioural differences in aggression, violence, drug and substance abuse, antisocial personality disorder and other related traits. As the field of human behavioural genetics progresses and achieves credibility, the criminal accused continue to use its types of evidence into the criminal law. One of the most important genetic factors which controls certain neurotransmitters like dopamine and serotonin is the Monoamine Oxidase Acid A (MAOA) gene, known as the 'warrior gene'. The high-profile study by Caspi and colleagues in 2002 showed that the combination between one type of variation of the MAOA gene and childhood maltreatment noticeably predisposes a person to antisocial behaviour. Moreover, further scientific research shows that individuals with the MAOA gene have to some degree difficulties in controlling their impulses. Based on the evidence of MAOA, some criminal accused claimed difficulties in self-control. In the first case – the famous case of Mobley – the court rejected the MAOA evidence on the ground of the lack of scientific support. In contrast, in other cases after the Mobley trial, courts accepted the evidence of MAOA. In this paper, the issue of lack of impulse control produced by the MAOA gene and cases which relied on the MAOA evidence and successfully being accepted will be reviewed in detail. Finally, the anticipation of the paper for the future use of the MAOA evidence in criminal cases will be presented.

Keywords: genetic defence, criminal responsibility, MAOA, self-control

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Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

Abstract:

Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Keywords: adaptive complex systems, X-Events, risk management, antifragility, banking antifragility index, triangular fuzzy number

Procedia PDF Downloads 172