Search results for: improved sparrow search algorithm

Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

Abstract:

Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

Procedia PDF Downloads 494

Authors: Razwan Ahmed Tanvir, Greg Speegle

Abstract:

Collaborative blockchain ecosystems allow diverse groups to cooperate on tasks while providing properties such as decentralization and transaction security. We provide a model that uses a repository blockchain to manage hard forks within a collaborative system such that a single process (assuming that it has knowledge of the requirements of each fork) can access all of the blocks within the system. The repository blockchain replaces the need for Inter Blockchain Communication (IBC) within the ecosystem by navigating the networks. The resulting construction resembles a tree instead of a chain. A proof-of-concept implementation performs a depth-first search on the new structure.

Keywords: hard fork, shared governance, inter blockchain communication, blockchain ecosystem, regular research paper

Procedia PDF Downloads 17

Authors: Maryam Kiani

Abstract:

This study focuses on the development of composite nanomaterials based on SiO2 and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO2/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO2 into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO2 facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO2/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: oxygen reduction reaction, batteries, fuel cells, electrrocatalyst

Procedia PDF Downloads 117

Authors: Felipe Haleyson Ribeiro dos Santos, Edson Ronaldo Guarido Filho

Abstract:

This article aims to review the literature on performance in police organizations. For that, the inOrdinatio method was adopted, which defines the form of selection and classification of articles. The search was carried out in databases, which resulted in a total of 619 documents that were cataloged and classified with the support of the Mendeley software. The theoretical scope intended here is to identify how performance in police organizations has been studied. After deepening the analysis and focusing on management, it was possible to classify the articles into three levels: individual, organizational, and institutional. However, to our best knowledge, no studies were found that addressed the performance relationship between the levels, which can be seen as a suggestion for further research.

Keywords: police management, performance, management, multi-level

Procedia PDF Downloads 109

Authors: Mathieu Le Cam, Tejaswinee Darure, Mateusz Pawlucki

Abstract:

Climate control of cabin aircraft is traditionally conditioned as a single unit by the environmental control system. Cabin temperature is controlled by the crew while passengers of the aircraft have control on the gaspers providing fresh air from the above head area. The small nozzles are difficult to reach and adjust to meet the passenger’s needs in terms of flow and direction. More dedicated control over the near environment of each passenger can be beneficial in many situations. The European project COCOON, funded under Clean Sky 2, aims at developing and demonstrating a microclimate conditioning module (MCM) integrated into a standard economy 3-seat row. The system developed will lead to improved passenger comfort with more control on their personal thermal area. This study focuses on the assessment of thermal comfort of passengers in the cabin aircraft through simulation on the TAITherm modelling platform. A first analysis investigates thermal comfort and sensation of passengers in varying cabin environmental conditions: from cold to very hot scenarios, with and without MCM installed in the seats. The modelling platform is also used to evaluate the impact of different physiologies of passengers on their thermal comfort as well as different seat locations. Under the current cabin conditions, a passenger of a 50th percentile body size is feeling uncomfortably cool due to the high velocity cabin air ventilation. The simulation shows that the in-seat MCM developed in COCOON project improves the thermal comfort of the passenger.

Keywords: cabin aircraft, in-seat HVAC, microclimate conditioning module, thermal comfort

Procedia PDF Downloads 200

Authors: Marcela de Oliveira, Guilherme Giacomini, Allan Felipe Fattori Alves, Ana Luiza Menegatti Pavan, Maria Eugenia Dela Rosa, Fernando Antonio Bacchim Neto, Diana Rodrigues de Pina

Abstract:

It is estimated that each year one death every 10 seconds (about 2 million deaths) in the world is attributed to tuberculosis (TB). Even after effective treatment, TB leaves sequelae such as, for example, pulmonary fibrosis, compromising the quality of life of patients. Evaluations of the aforementioned sequel are usually performed subjectively by radiology specialists. Subjective evaluation may indicate variations inter and intra observers. The examination of x-rays is the diagnostic imaging method most accomplished in the monitoring of patients diagnosed with TB and of least cost to the institution. The application of computational algorithms is of utmost importance to make a more objective quantification of pulmonary impairment in individuals with tuberculosis. The purpose of this research is the use of computer algorithms to quantify the pulmonary impairment pre and post-treatment of patients with pulmonary TB. The x-ray images of 10 patients with TB diagnosis confirmed by examination of sputum smears were studied. Initially the segmentation of the total lung area was performed (posteroanterior and lateral views) then targeted to the compromised region by pulmonary sequel. Through morphological operators and the application of signal noise tool, it was possible to determine the compromised lung volume. The largest difference found pre- and post-treatment was 85.85% and the smallest was 54.08%.

Keywords: algorithm, radiology, tuberculosis, x-rays exam

Procedia PDF Downloads 419

Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

Abstract:

This paper aims at developing a multi-objective model for supplier selection and order allocation problem in stochastic environment, where purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. In this regard, dependent chance programming is used which maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. The abovementioned stochastic multi-objective programming problem is then transformed into a stochastic single objective programming problem using minimum deviation method. In the next step, the further problem is solved applying a genetic algorithm, which performs a simulation process in order to calculate the stochastic objective function as its fitness function. Finally, the impact of stochastic parameters on the given solution is examined via a sensitivity analysis exploiting coefficient of variation. The results show that whatever stochastic parameters have greater coefficients of variation, the value of the objective function in the stochastic single objective programming problem is deteriorated.

Keywords: supplier selection, order allocation, dependent chance programming, genetic algorithm

Procedia PDF Downloads 313

Authors: L. F. Tamele Jr., G. Buonocore, H. F. Muiambo

Abstract:

Asphalt binders play an essential role in the performance and properties of asphalt mixtures. The increase in heavy loads, greater traffic volume, and high tire pressure, combined with a substantial variation in daily and seasonal pavement temperatures, are the main responsible for the failure of asphalt pavements. To avoid or mitigate these failures, the present research proposes the use of thermoplastic polymers, HDPE and LLDPE, and nanoclay Dellite 43B for modification of asphalt in order to improve its thermomechanical and rheological properties. The nanocomposites were prepared by the solution intercalation method in a high shear mixer for a mixing time of 2 h, at 180℃ and 5000 rpm. The addition of Dellite 43B improved the physical, rheological, and thermal properties of asphalt, either separated or in the form of polymer/bitumen blends. The results of the physical characterization showed a decrease in penetration and an increase in softening point, thermal susceptibility, viscosity, and stiffness. On the other hand, thermal characterization showed that the nanocomposites have greater stability at higher temperatures by exhibiting greater amounts of residues and improved initial and final decomposition temperatures. Thus, the modification of asphalt by polymers and nanoclays seems to be a suitable solution for road pavement in countries which experiment with high temperatures combined with long heavy rain seasons.

Keywords: asphalt, nanoclay dellite 43B, polymer modified asphalt, thermal and rheological properties

Procedia PDF Downloads 147

Authors: Jianan Li, Lusen Shi, Haiqiao Du, Wei Chen, Qian Wang, Shuoshuo Kang, Shiming Yang

Abstract:

Background: Follow-up of cochlear implant effectiveness is mainly focused on 3 years postoperatively, and studies with more than 5 years of observation are rare, especially for local Chinese brands. Objectives: Nurotron (Chinese domestic cochlear implant brand) CI recipients who participated in the clinical trial in 2009 were followed-up for 10 years prospectively, providing data to guide doctors and patients. Material and Methods: From December 2009 to April 2010, 57 subjects underwent Nurotron Venus CI surgery at multiple centers and were continued to be followed up and assessed at 1, 2, 3, 4, 5, and 10 years after switching on. Results: All recipients were successfully implanted with CIs with no difficulty in subsequent use, with one reported case of re-implantation 9 years after implantation. The aided hearing thresholds were significantly improved one month after switching on (p<0.0001) and remained stable afterward for 10 years. Speech recognition scores were significantly higher than pre-operative results (p<0.05) and continued to improve till 3 years after switching on. At 10 years of post-operation, most subjects had improved QOL scores in most sub-items. Conclusions and Significance: Nurotron Venus CI System provides long-term, stable results in hearing speech assistance capabilities and can improve the quality of life of CI recipients.

Keywords: cochlear implantation, hearing loss, post lingual, follow up

Procedia PDF Downloads 16

Authors: Bastien Batardière, Joon Kwon

Abstract:

For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

Procedia PDF Downloads 71

Authors: Lara A. Alshawawreh, R. Sean Smith, John B. Wood

Abstract:

This study focuses on the sheltering response in the Middle East, specifically through reviewing two Syrian refugee camps in Jordan, involving Zaatari and Azraq. Zaatari camp involved the rapid deployment of tents and shelters over a very short period of time and Azraq was purpose built and pre-planned over a longer period. At present, both camps collectively host more than 133,000 occupants. Field visits were taken to both camps and the main issues and problems in the sheltering response were highlighted through focus group discussions with camp occupants and inspection of shelter habitats. This provided both subjective and objective research data sources. While every case has its own significance and deployment to meet humanitarian needs, there are some common requirements irrespective of geographical region. The results suggest that there is a gap in the suitability of the required habitat needs and what has been provided. It is recommended that the global international response and support could be improved in relation to the habitat form, construction type, layout, function and critically the cultural aspects. Services, health and hygiene are key elements to the shelter habitat provision. The study also identified the amendments to shelters undertaken by the beneficiaries providing insight into their key main requirements. The outcomes from this study could provide an important learning opportunity to develop improved habitat response for future shelters.

Keywords: culture, post-disaster, refugees, shelters

Procedia PDF Downloads 488

Authors: Jenny Fairthorne, Yuka Mori, Helen Leonard

Abstract:

Background: Primary care-givers of children with autism spectrum disorder (ASD) or intellectual disability (ID) have poorer health and quality of life (QoL) than primary care-givers (hereafter referred to as just care-givers) of typically developing children. We aimed to review original research which described factors impacting the health of care-givers of children with ASD or ID and to discuss how these factors might influence care-giver health. Methods: We searched Web of Knowledge, Medline, Scopus and Google Scholar using selections of words from each of three groups. The first comprised terms associated with ASD and ID and included autism, pervasive development disorder, intellectual disability, mental retardation, disability, disabled, Down and Asperger. The second included terms related to health such as depression, physical, mental, psychiatric, psychological and well-being. The third was terms related to care-givers such as mother, parent and care-giver. We included an original paper in our review if it was published between 1st January 1990 and 31st December, 2016, described original research in a peer-reviewed journal and was written in English. Additional criteria were that the research used a study population of 15 persons or more; described a risk or protective factor for the health of care-givers of a child with ASD, ID or a sub-type (such as ASD with ID or Down syndrome). Using previous research, we developed a simple and objective five-level tool to assess the strength of evidence provided by the reviewed papers. Results: We retained 33 papers. Factors impacting primary care-giver health included child behaviour, level of support, socio-economic status (SES) and diagnostic issues. Challenging child behaviour, the most commonly identified risk factor for poorer care-giver health and QoL was reported in ten of the studies. A higher level of support was associated with improved care-giver health and QoL. For example, substantial evidence indicated that family support reduced care-giver burden in families with a child with ASD and that family and neighbourhood support was associated with improved care-giver mental health. Higher socio-economic status (SES) was a protective factor for care-giver health and particularly maternal health. Diagnostic uncertainty and an unclear prognosis are factors which can cause the greatest concern to care-givers of children with ASD and those for whom a cause of their child’s ID has not been identified. We explain how each of these factors might impact caregiver health and how they might act differentially in care-givers of children with different types of ASD or ID (such as Down syndrome and ASD without ID). Conclusion: Care-givers of children with ASD may be more likely to experience many risk factors and less likely to experience the protective factors we identified for poorer mental health. Interventions to reduce risk factors and increase protective factors could pave the way for improved care-giver health. For example, workshops to train care-givers to better manage challenging child behaviours and earlier diagnosis of ASD (and particularly ASD without ID) would seem likely to improve care-giver well-being. Similarly, helping to expand support networks might reduce care-giver burden and stress leading to improved health.

Keywords: autism, caregivers, health, intellectual disability, mothers, review

Procedia PDF Downloads 160

Authors: John K. Avor, Choong-Koo Chang

Abstract:

The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

Procedia PDF Downloads 171

Authors: Oxana Lukoshus

Abstract:

The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

Procedia PDF Downloads 314

Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

Abstract:

We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

Procedia PDF Downloads 132

Authors: Chalise Kiran

Abstract:

The learning difficulties of children with disabilities are always a matter of concern when we talk about educational needs and quality education of children with disabilities. This paper is the outcome of the review of the literatures based on the literatures on the educational needs and learning difficulties of children with disabilities. For the paper, different studies written on children with disabilities and their education were collected through search engines. The literature put together was analyzed from the angle of learning difficulties faced by children with disabilities and the same were used as a precursor to arrive at the findings on the learning of the children. The analysis showed that children with disabilities face learning difficulties. The reasons for these difficulties could be attributed to factors in terms of authority, structure, school environment, and behaviors of teachers and parents, and the society as a whole.

Keywords: children with disabilities, learning difficulties, education, disabled children

Procedia PDF Downloads 114

Authors: Bashar Tarawneh, Yasser Hakam

Abstract:

Rapid Impact Compaction (RIC) is a modern dynamic compaction device mainly used to compact sandy soils, where silt and clay contents are low. The device uses the piling hammer technology to increase the bearing capacity of soils through controlled impacts. The RIC device uses "controlled impact compaction" of the ground using a 9-ton hammer dropped from the height between 0.3 m to 1.2 m onto a 1.5 m diameter steel patent foot. The delivered energy is about 26,487 to 105,948 Joules per drop. To evaluate the performance of this technique, three project sites in the United Arab Emirates were improved using RIC. In those sites, a loose to very loose fine to medium sand was encountered at a depth ranging from 1.0m to 4.0m below the ground level. To evaluate the performance of the RIC, Cone Penetration Tests (CPT) were carried out before and after improvement. Also, load tests were carried out post-RIC work to assess the settlements and bearing capacity. The soil was improved to a depth of about 5.0m below the ground level depending on the CPT friction ratio (the ratio between sleeve friction and tip resistance). CPT tip resistance was significantly increased post ground improvement work. Load tests showed enhancement in the soil bearing capacity and reduction in the potential settlements. This study demonstrates the successful application of the RIC for middle-deep improvement and compaction of the ground. Foundation design criteria were achieved in all site post-RIC work.

Keywords: compaction, RIC, ground improvement, CPT

Procedia PDF Downloads 366

Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

Abstract:

Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

Procedia PDF Downloads 112

Authors: Elizabeth F. Rodrigues, Julia da R. Mattos, Naira Q. Leitão, Roberta T. da Cunha

Abstract:

The business strategy of many companies has two factors in common: the search for the competitive edge and its long term maintenance. The thing that differentiates the companies’ performance in their abilities to set the right strategy, which depends on their capacity to analyze and apply all sort of management support tools. In this context, the sponsorship of events stands out as an important way to increase brand awareness, especially when it is a worldwide event, such as Rio 2016 Olympic and Paralympic Games. This paper will present the case of a car maker company, which chose to invest on sponsorship as a way to reach its goals and grow in the brazilian market.

Keywords: strategy, sponsorship, events, management

Procedia PDF Downloads 497

Authors: Sonia Saddiqui, Maya Marcus

Abstract:

UTS STEAMpunk Girls is an educational program for young women (aged 12-16), to empower them to be more informed and active members of the 21st century workforce. With the number of STEM graduates on the decline, especially among young women, an additional aim of the program is to trial a STEAM (Science, Technology, Engineering, Arts/Humanities/Social Sciences, Mathematics), inter-disciplinary approach to improving STEM engagement. In-line with UNESCO’s recent focus on promoting ‘transversal competencies’ in future graduates, the program utilised co-design, project-based learning, entrepreneurial processes, and inter-disciplinary learning. The program consists of two phases. Taking a participatory design approach, the first phase (co-design workshops) provided valuable insight into student perspectives around engaging young women in STEM and inter-disciplinary thinking. The workshops positioned 26 young women from three schools as subject matter experts (SMEs), providing a platform for them to share their opinions, experiences and findings around the STEAM disciplines. The second (pilot) phase put the co-design phase findings into practice, with 64 students from four schools working in groups to articulate problems with real-world implications, and utilising design-thinking to solve them. The pilot phase utilised project-based learning to engage young women in entrepreneurial and STEAM frameworks and processes. Scalable program design and educational resources were trialed to determine appropriate mechanisms for engaging young women in STEM and in STEAM thinking. Across both phases, data was collected via longitudinal surveys to obtain pre-program, baseline attitudinal information, and compare that against post-program responses. Preliminary findings revealed students’ improved understanding of the STEM disciplines, industries and professions, improved awareness of STEAM as a concept, and improved understanding regarding inter-disciplinary and design thinking. Program outcomes will be of interest to high-school educators in both STEM and the Arts, Humanities and Social Sciences fields, and will hopefully inform future programmatic approaches to introducing inter-disciplinary STEAM learning in STEM curriculum.

Keywords: co-design, STEM, STEAM, project-based learning, inter-disciplinary

Procedia PDF Downloads 199

Authors: Exa Heydemans, Jessica Sjah, Dwinanti Rika Marthanty

Abstract:

This paper presents numerical simulations using an open boundary algorithm with modified dynamic boundary condition (mDBC) for weakly compressible smoothed particle hydrodynamics models from particle-based code Dualsphysics. The problems of piping erosion in dams and dikes are aimed for studying the algorithm. The case 2D model of unsteady fluid flow past around a fixed cylinder is simulated, where various values of Reynold’s numbers (Re40, Re60, Re80, and Re100) and different model’s resolution are considered. A constant velocity with different values of viscosity for generating various Reynold’s numbers and different numbers of particles over a cylinder for the resolution are modeled. The interaction between solid particles of the cylinder and fluid particles is concerned. The cylinder is affected by the hydrodynamics force caused by the flow of fluid particles. The solid particles of the cylinder are the observation points to obtain force and pressure due to the hydrodynamics forces. As results of the simulation, which is to show the capability to model 2D unsteady with various Reynold’s numbers, the pressure coefficient, drag coefficient, lift coefficient, and Strouhal number are compared to the previous work from literature.

Keywords: hydrodynamics, internal erosion, dualsphysics, viscous fluid flow

Procedia PDF Downloads 165

Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

Abstract:

Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

Procedia PDF Downloads 476

Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

Procedia PDF Downloads 327

Authors: Suriya

Abstract:

Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

Procedia PDF Downloads 48

Authors: Yskak Nabi, Onolkan Umankulova, Ilyas Seitov

Abstract:

Tempus project about “Central Asian network for quality assurance – CANQA” had been implemented in 2009-2012. As the result of the project, two accreditation agencies were established: the agency for quality assurance in the field of education, “EdNet” in Kyrgyzstan, center of progressive technologies in Tajikistan. The importance of the research studies of the project is supported by the idea that the creation of Central-Asian network for quality assurance in education is still relevant, and results of the International forum “Global in regional: Kazakhstan in Bologna process and EU projects,” that was held in Nur-Sultan in October 2020, proves this. At the same time, the previous experience of the partnership between accreditation agencies of Central Asia shows that recommendations elaborated within the CANQA project were not theoretically justified. But there are a number of facts and arguments that prove the practical appliance of these recommendations. In this respect, joint activities of accreditation agencies of Kyrgyzstan and Kazakhstan are representative. For example, independent Kazakh agency of accreditation and rating successfully conducts accreditation of Kyrgyz universities; based on the memorandum about joint activity between the agency for quality assurance in the field of education “EdNet” (Kyrgyzstan) and Astana accreditation agency (Kazakhstan), the last one provides its experts for accreditation procedures in EdNet. Exchange of experience among the agencies shows an effective approach towards adaptation of European standards to the reality of education systems of Central Asia with consideration of not only a legal framework but also from the point of European practices view. Therefore, the relevance of the research is identified as there is a practical partnership between accreditation agencies of Central Asian countries, but the absence of theoretical justification of integrational processes in the accreditation field. As a result, the following hypothesis was put forward: “if to develop theoretical aspects for harmonization of accreditation standards, then integrational processes would be improved since the implementation of Bologna process principles would be supported with wider possibilities, and particularly, students and academic mobility would be improved.” Indeed, for example, in Kazakhstan, the total share of foreign students was 5,04% in 2020, and most of them are coming from Kyrgyzstan, Tajikistan, and Uzbekistan, and if integrational processes will be improved, then this share can increase.

Keywords: accreditation standards in education, Central Asian countries, pedagogical theory, model

Procedia PDF Downloads 199

Authors: Muqdad Al-Juboori, Bithin Datta

Abstract:

Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

Procedia PDF Downloads 224

Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

Abstract:

With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

Procedia PDF Downloads 112

Authors: Yuan-Lin Liu, Ye Li, Tian Xia

Abstract:

Taxi-calling APPs have been used widely, while brought both benefits and a variety of issues for the taxi market. Many countries do not know whether the benefits are remarkable than the issues or not. This paper established a comparison between the basic scenario (2009-2012) and a taxi-calling software usage scenario (2012-2015) to explain the impact of taxi-calling APPs. The impacts of taxi-calling APPs illustrated by the comparison results are: 1) The supply and demand distribution is more balanced, extending from the city center to the suburb. The availability of taxi service has been improved in low density areas, thin market attribute has also been improved; 2)The ratio of short distance taxi trip decreased, long distance service increased, the utilization of mileage increased, and the rate of empty decreased; 3) The popularity of taxi-calling APPs was able to reduce the average empty distance, cruise time, empty mileage rate and average times of loading passengers, can also enhance the average operating speed, improve the taxi operating level, and reduce social cost although there are some disadvantages. This paper argues that the taxi industry and government can establish an integrated third-party credit information platform based on credit evaluated by the data of the drivers’ driving behaviors to supervise the drivers. Taxi-calling APPs under fully covered supervision in the mobile Internet environment will become a new trend.

Keywords: taxi, taxi-calling APPs, credit, scenario comparison

Procedia PDF Downloads 254

Authors: Abigail Ekeigwe, Bethany McGowan, Loran C. Parker, Stephen Byrn, Kari L. Clase

Abstract:

There are growing calls in the literature to develop and implement competency-based regulatory sciences education (CBRSE) in sub-Saharan Africa to expand and create a pipeline of a competent workforce of regulatory scientists. A defined competence framework is an essential component in developing competency-based education. However, such a competence framework is not available for regulatory scientists in sub-Saharan Africa. The purpose of this research is to identify entry-level competencies for inclusion in a competency framework for regulatory scientists in sub-Saharan Africa as a first step in developing CBRSE. The team systematically reviewed the literature following the PRISMA guidelines for systematic reviews and based on a pre-registered protocol on Open Science Framework (OSF). The protocol has the search strategy and the inclusion and exclusion criteria for publications. All included publications were coded to identify entry-level competencies for regulatory scientists. The team deductively coded the publications included in the study using the 'framework synthesis' model for systematic literature review. The World Health Organization’s conceptualization of competence guided the review and thematic synthesis. Topic and thematic codings were done using NVivo 12™ software. Based on the search strategy in the protocol, 2345 publications were retrieved. Twenty-two (n=22) of the retrieved publications met all the inclusion criteria for the research. Topic and thematic coding of the publications yielded three main domains of competence: knowledge, skills, and enabling behaviors. The knowledge domain has three sub-domains: administrative, regulatory governance/framework, and scientific knowledge. The skills domain has two sub-domains: functional and technical skills. Identification of competencies is the primal step that serves as a bedrock for curriculum development and competency-based education. The competencies identified in this research will help policymakers, educators, institutions, and international development partners design and implement competence-based regulatory science education in sub-Saharan Africa, ultimately leading to access to safe, quality, and effective medical products.

Keywords: competence-based regulatory science education, competencies, systematic review, sub-Saharan Africa

Procedia PDF Downloads 197

Authors: Khadri Sihem, Abbaci Nafissa, Zerari Labiba

Abstract:

In the context of the search for new bioactive natural products, we were interested in evaluating some antibacterial properties of two plant extracts: total phenols and flavonoids of Algerian medicinal plant. Our study occurs in two axes: The first concerns the extraction of phenolic compounds and flavonoids with methanol by liquid-liquid extraction, followed by quantification of the levels of these compounds in the end the analysis of the chemical composition of extracts. In the second axis, we studied the antibacterial power of the studied plant extracts.

Keywords: antibacterial activity, flavonoids, medicinal plants, polyphenols

Procedia PDF Downloads 554