Search results for: smart beta

Authors: Ali Mohammed Ali Lmbash

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The global refugee crisis points to the vital need for sustainable and resistant solutions to different kinds of problems for displaced persons all over the world. Among the myriads of sustainable concerns, however, there are diverse considerations including energy consumption, waste management, water access, and resiliency of structures. Our research aims to develop distinct ideas for sustainable architecture given the exigent problems in disaster-threatened areas starting with the Hatay Refugee camp in Turkey where the majority of the camp dwellers are Syrian refugees. Commencing community-based participatory research which focuses on the socio-environmental issues of displaced populations, this study will apply two approaches with a specific focus on the Hatay region. The initial experiment uses Richter's predictive model and simulations to forecast earthquake outcomes in refugee campers. The result could be useful in implementing architectural design tactics that enhance structural reliability and ensure the security and safety of shelters through earthquakes. In the second experiment a model is generated which helps us in predicting the quality of the existing water sources and since we understand how greatly water is vital for the well-being of humans, we do it. This research aims to enable camp administrators to employ forward-looking practices while managing water resources and thus minimizing health risks as well as building resilience of the refugees in the Hatay area. On the other side, this research assesses other sustainability problems of Hatay Refugee Camp as well. As energy consumption becomes the major issue, housing developers are required to consider energy-efficient designs as well as feasible integration of renewable energy technologies to minimize the environmental impact and improve the long-term sustainability of housing projects. Waste management is given special attention in this case by imposing recycling initiatives and waste reduction measures to reduce the pace of environmental degradation in the camp's land area. As well, study gives an insight into the social and economic reality of the camp, investigating the contribution of initiatives such as urban agriculture or vocational training to the enhancement of livelihood and community empowerment. In a similar fashion, this study combines the latest research with practical experience in order to contribute to the continuing discussion on sustainable architecture during disaster relief, providing recommendations and info that can be adapted on every scale worldwide. Through collaborative efforts and a dedicated sustainability approach, we can jointly get to the root of the cause and work towards a far more robust and equitable society.

Keywords: smart architecture, Hatay Camp, sustainability, machine learning.

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Authors: Alaa Hamed Habib

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The Coronavirus disease 2019 (COVID-19) is a viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated with systemic inflammation. Inflammation is an important process that follows infection and facilitates the repair of damaged tissue. Polyunsaturated fatty acids play an important role in the inflammatory process. These lipids can target transcription factors to modulate gene expression and protein function. Here, we evaluated whether differences in basal levels of different types of biomarkers can be detected in freshly frozen plasma samples from patients with and without COVID19. Fatty acid methyl ester (FAME) analysis showed a decrease in arachidic acid and myristic acid, but an increase in caprylic acid, palmitic acid, and eicosenoic acid in the plasma of COVID-19 patients compared to non-COVID19 patients. Multiple chemokines, including IP-10, MCP-1, and MIP-1 beta, were increased in the COVID-19 group compared to the non-COVID-19 group. Similarly, cytokines including IL-1 alpha and IL-8, and cell adhesion and inflammatory response markers including ICAM-1 and E-selectin were greater in the plasma of COVID-19 patients compared to non-COVID-19 patients. A baseline signature of specific polyunsaturated fatty acids, cytokines, and chemokines present in the plasma after COVID-19 viral infection may serve as biomarkers that can be useful in various applications, including determination of the severity of infection, an indication of disease prognosis and consideration for therapeutic options.

Keywords: MARKS, COVID 19, UEVS NON COVIDS, kidneys, nanoparticles

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Authors: Soomal Hamza, Uzma Imran

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Organochlorine pesticides bio-accumulate into the fat of fish, birds, and animals through which it enters the human food cycle. Due to their persistence and stability in the environment, many health impacts are associated with them, most of which are carcinogenic in nature. In this study, the level of organochlorine pesticides has been detected in Keenjhar Lake and remediated using Rhizoremediation technique. 14 OC pesticides namely, Aldrin, Deldrin, Heptachlor, Heptachlor epoxide, Endrin, Endosulfun I and II, DDT, DDE, DDD, Alpha, Beta, Gamma BHC and two plants namely, Water Hyacinth and Slvinia Molesta were used in the system using pot experiment which processed for 11 days. A consortium was inoculated in both plants to increase its efficiency. Water samples were processed using liquide-liquid extraction. Sediments and roots samples were processed using Soxhlet method followed by clean-up and Gas Chromatography. Delta-BHC was the predominantly found in all samples with mean concentration (ppb) and standard deviation of 0.02 ± 0.14, 0.52 ± 0.68, 0.61 ± 0.06, in Water, Sediments and Roots samples respectively. The highest levels were of Endosulfan II in the samples of water, sediments and roots. Water Hyacinth proved to be better bioaccumulaor as compared to Silvinia Molesta. The pattern of compounds reduction rate by the end of experiment was Delta-BHC>DDD > Alpha-BHC > DDT> Heptachlor> H.Epoxide> Deldrin> Aldrin> Endrin> DDE> Endosulfun I > Endosulfun II. Not much significant difference was observed between the pots with the consortium and pots without the consortium addition. Phytoremediation is a promising technique, but more studies are required to assess the bioremediation potential of different aquatic plants and plant-endophyte relationship.

Keywords: aquatic plant, bio remediation, gas chromatography, liquid liquid extraction

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Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: Lebogang L. R. Mphahlele, Bruce B. Sithole

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Chicken meat is the highest consumed meat in south Africa, with a per capita consumption of >33 kg yearly. Hence, South Africa produces over 250 million kg of waste chicken feathers each year, the majority of which is landfilled or incinerated. The discarded feathers have caused environmental pollution and natural protein resource waste. Therefore, the valorisation of waste chicken feathers is measured as a more environmentally friendly and cost-effective treatment. Feather contains 91% protein, the main component being beta-keratin, a fibrous and insoluble structural protein extensively cross linked by disulfide bonds. Keratin is usually converted it into nanofibers via electrospinning for a variety of applications. keratin nanofiber composites have many potential biomedical applications for their attractive features, such as high surface-to-volume ratio and very high porosity. The application of nanofibers in the biomedical wound dressing requires antimicrobial properties for materials. One approach is incorporating inorganic nanoparticles, among which silver nanoparticles played an important alternative antibacterial agent and have been studied against many types of microbes. The objective of this study is to combine synthetic polymer, chicken feather keratin, and antibacterial nanoparticles to develop novel electrospun antibacterial nanofibrous composites for possible wound dressing application. Furthermore, this study will converting a two-dimensional electrospun nanofiber membrane to three-dimensional fiber networks that resemble the structure of the extracellular matrix (ECM)

Keywords: chicken feather keratin, nanofibers, nanoparticles, nanocomposites, wound dressing

Procedia PDF Downloads 132

Authors: Toktam mehrabani

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Textiles, fashion, and architecture, though seemingly disparate fields, share a deep and evolving relationship. This paper explores the intersection of these disciplines, examining how the tactile, structural, and aesthetic qualities of textiles have influenced both fashion and architecture over time. By investigating historical and contemporary examples, this paper seeks to unravel the ways in which textiles and fashion have not only shaped architectural design but have also acted as a bridge between functionality, art, and human experience in the built environment.Textiles have been integral to human culture since the dawn of civilization. Their presence transcends mere functionality, serving as a medium for artistic expression, cultural identity, and social commentary. Fashion, derived from textiles, has long been associated with personal identity and societal trends, while architecture reflects human needs, environmental context, and cultural values. This paper posits that the relationship between textiles, fashion, and architecture is more interconnected than often perceived, with each influencing and inspiring the other across time. Textiles in Architectural Design: From ancient draperies in temples to tapestries in castles, textiles have adorned structures, softening rigid spaces and adding layers of warmth and luxury. Fabric screens and curtains have also served functional purposes, such as controlling light, acoustics, and temperature. Fashion as Architectural Expression: Renaissance and Baroque fashion used exaggerated forms, corsetry, and layers to mirror the grandiosity of architectural styles of the time. Clothing acted as wearable architecture, with structured garments mirroring the strong lines and curves of buildings..Structural Textiles in Architecture: In the 21st century, textiles are no longer just decorative; they have become integral to architectural innovation. Materials like tensile fabrics and smart textiles are used in creating flexible, lightweight structures. Iconic examples include Frei Otto’s work with tensile membranes, seen in the Munich Olympic Stadium.Technological advancements have drastically transformed the relationship between textiles, fashion, and architecture. Digital tools like 3D printing and laser cutting allow designers in both fields to push the limits of form and structure. Smart textiles that react to environmental stimuli are being explored for use in both wearable technology and adaptable architecture, such as facades that change in response to weather conditions. Textiles, fashion, and architecture are inextricably linked through their shared exploration of form, structure, and expression. This interdisciplinary relationship continues to evolve, driven by technological advancements and a growing emphasis on sustainability. As fashion becomes more architectural in its construction and architecture more fluid in its forms, the lines between these disciplines blur, offering new possibilities for creativity and functionality in both wearable and built environments.

Keywords: textiles in architecture, fashion and architecture, textile architecture, structural textiles, wearable architecture, architectural fashion

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Authors: Dorjana Nano

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Financial literacy has become on focus of many research studies. Family household is found to influence students’ financial literacy. The purpose of this study is to explore whether financial literacy of Albanian students is associated with their family household. The main objectives of this research are: i) firstly, to evaluate how financial literate are Albanian university students; ii) secondly, to examine whether the financial literacy differs based on the level of students family income; and iii) finally, to draw some conclusions and recommendations in order to improve student’s financial literacy. An instrument, comprised of personal finance and personal characteristics is administered to 637 students in Albania. The constituency of the survey is tested based on the dimension reduction and factor analyzing techniques. The One Way Welch ANOVA and multiple comparison techniques are utilized to analyze the data. The results indicate that student’s financial literacy is influenced by their family income.

Keywords: financial literacy, household income, smart decisions, university students

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Authors: Jiří Barta, Josef Krahulec, Jiří F. Urbánek

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Education and practical training crisis management members are a topical issue nowadays. The paper deals with the perspectives and possibilities of ‘smart solutions’ to education for crisis management staff. Currently, there are a large number of simulation tools, which notes that they are suitable for practical training of crisis management staff. The first part of the paper is focused on the introduction of the technology simulation tools. The simulators aim is to create a realistic environment for the practical training of extending units of crisis staff. The second part of the paper concerns the possibilities of using the simulation technology to the education process. The aim of this section is to introduce the practical capabilities and potential of the simulation programs for practical training of crisis management staff.

Keywords: crisis management staff, computer simulation, software, technological education

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 119

Authors: Lumindu Dilumka, Ranaweera I. D., Sudusinghe S. P., Sanduni Kanchana A. M. K.

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This study was motivated by the challenges experienced by parents and guardians in ensuring the safety of children in cyberspace. In the last two or three years, online education has become very popular all over the world due to the Covid 19 pandemic. Therefore, parents, guardians and teachers must ensure the safety of children in cyberspace. Children are more likely to go astray and there are plenty of online programs are waiting to get them on the wrong track and also, children who are engaging in the online education can be distracted at any moment. Therefore, parents should keep a close check on their children's online activity. Apart from that, due to the unawareness of children, they tempt to share their sensitive information, causing a chance of being a victim of phishing attacks from outsiders. These problems can be overcome through the proposed web-based system. We use feature extraction, web tracking and analysis mechanisms, image processing and name entity recognition to implement this web-based system.

Keywords: online education, cyber bullying, social media, face recognition, web tracker, privacy data

Procedia PDF Downloads 88

Authors: Hemendra Singh Rathod

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Frequency is, among other factors, one of the governing parameters for maintaining electrical grid stability. The quality of an electrical transmission and supply system is mainly described by the stability of the grid frequency. Over the past few decades, energy generation by intermittent sustainable sources like wind and solar has seen a significant increase globally. Consequently, controlling the associated deviations in grid frequency within safe limits has been gaining momentum so that the balance between demand and supply can be maintained. Lithium-ion battery energy storage system (Li-Ion BESS) has been a promising technology to tackle the challenges associated with grid instability. BESS is, therefore, an effective response to the ongoing debate whether it is feasible to have an electrical grid constantly functioning on a hundred percent renewable power in the near future. In recent years, large-scale manufacturing and capital investment into battery production processes have made the Li-ion battery systems cost-effective and increasingly efficient. The Li-ion systems require very low maintenance and are also independent of geographical constraints while being easily scalable. The paper highlights the use of stationary and moving BESS for balancing electrical energy, thereby maintaining grid frequency at a rapid rate. Moving BESS technology, as implemented in the selected railway network in Germany, is here considered as an exemplary concept for demonstrating the same functionality in the electrical grid system. Further, using certain applications of Li-ion batteries, such as self-consumption of wind and solar parks or their ancillary services, wind and solar energy storage during low demand, black start, island operation, residential home storage, etc. offers a solution to effectively integrate the renewables and support Europe’s future smart grid. EMT software tool DIgSILENT PowerFactory has been utilised to model an electrical transmission system with 100% renewable energy penetration. The stability of such a transmission system has been evaluated together with BESS within a defined frequency band. The transmission system operators (TSO) have the superordinate responsibility for system stability and must also coordinate with the other European transmission system operators. Frequency control is implemented by TSO by maintaining a balance between electricity generation and consumption. Li-ion battery systems are here seen as flexible, controllable loads and flexible, controllable generation for balancing energy pools. Thus using Li-ion battery storage solution, frequency-dependent load shedding, i.e., automatic gradual disconnection of loads from the grid, and frequency-dependent electricity generation, i.e., automatic gradual connection of BESS to the grid, is used as a perfect security measure to maintain grid stability in any case scenario. The paper emphasizes the use of stationary and moving Li-ion battery storage for meeting the demands of maintaining grid frequency and stability for near future operations.

Keywords: frequency control, grid stability, li-ion battery storage, smart grid

Procedia PDF Downloads 150

Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

Procedia PDF Downloads 149

Authors: P. Chaipanya, R. Keawchai, W. Sombatsanongkhun, S. Jantaramporn

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To manage the demand of wireless communication that has been dramatically increased, switched beam antenna in smart antenna system is focused. Implementation of switched beam antennas at mobile terminals such as notebook or mobile handset is a preferable choice to increase the performance of the wireless communication systems. This paper proposes the low complexity switched beam antenna using single element of antenna which is suitable to implement at mobile terminal. Main beam direction is switched by changing the positions of short circuit on the radiating patch. There are four cases of switching that provide four different directions of main beam. Moreover, the performance in terms of Signal to Interference Ratio when utilizing the proposed antenna is compared with the one using omni-directional antenna to confirm the performance improvable.

Keywords: switched beam, shorted circuit, single element, signal to interference ratio

Procedia PDF Downloads 171

Authors: Lydia Foucan, Christine Rambhojan, Rachel Billy, Christophe Armand, Carl-Thony Michel, Jean-Marc Lacorte, Laurent Larifla

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Leptin, an adipocyte-derived hormone, modulates insulin secretion and action via the leptin receptor (LEPR) that is expressed in pancreatic beta cells, adipose tissue, and muscle. Several polymorphisms have been described in the human LEPR gene including p.K109R (rs1137100), p.Q223R (rs1137101) and p.K656N (rs1805094) polymorphisms. The role of these polymorphisms is not yet studied in Guadeloupian population. Our aim was to explore the association of LEPR polymorphisms (K109R, Q223R and K656N) with leptin levels and obesity in non-diabetic Afro-Caribbean subjects. Genotypic analysis of the three polymorphisms was performed in 425 subjects using TaqMan and KASPar Assays. Serum leptin was measured with ELISA kits Biovendor® (RD191001100). Logistic regressions were used for assessment of statistical associations. Mean age was 47.6 ± 12.7 years. Among the participants, 238 (56 %) were women, 124 (30%) were obese and 155 (36.5%) had abdominal obesity. Carriers of LEPR K656N rs1805094 rare allele had significant higher frequencies of obesity (P = 0.007), abdominal obesity (P = 0.004) and metabolic syndrome (P = 0.021) but mean leptin level was not significantly different between both groups (P = 0.075). Odds ratios, adjusted for age and sex associated with presence of rs1805094 rare allele were 1.8 (1.1-2.9), P = 0.012 for obesity, 2.0 (1.2-3.3), P = 0.008 for abdominal obesity and 1.8 (1.1-3.0), P = 0.031 for MetS. No significant association was found with K109R, Q223R. These findings suggest that the K656N polymorphism (but not the K109R or Q223R polymorphism) of LEPR is associated with obesity, abdominal obesity and metabolic syndrome in this Afro-Caribbean non-diabetic population.

Keywords: Afro-Caribbean, leptin levels, leptin receptor gene polymorphisms, obesity

Procedia PDF Downloads 377

Authors: C. Benjbara, A. Habbani

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Wireless networks are getting more and more used in every new technology or feature, especially those without infrastructure (Ad hoc mode) which provide a low cost alternative to the infrastructure mode wireless networks and a great flexibility for application domains such as environmental monitoring, smart cities, precision agriculture, and so on. These application domains present a common characteristic which is the need of coexistence and intercommunication between modules belonging to different types of ad hoc networks like wireless sensor networks, mesh networks, mobile ad hoc networks, vehicular ad hoc networks, etc. This vision to bring to life such heterogeneous networks will make humanity duties easier but its development path is full of challenges. One of these challenges is the communication complexity between its components due to the lack of common or compatible protocols standard. This article proposes a new patented routing protocol based on the OLSR standard in order to resolve the heterogeneous ad hoc networks communication issue. This new protocol is applied on a specific network architecture composed of MANET, VANET, and FANET.

Keywords: Ad hoc, heterogeneous, ID-Node, OLSR

Procedia PDF Downloads 215

Authors: Arunporn Itharat, Kamonmas Srikwan, Srisopa Ruangnoo, Pakakrong Thongdeeying

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Background: The rhizomes of Smilax glabra (SG) has long been used in Traditional Chinese and Thai herbal medicine to treat a variety of infectious diseases and immunological disorders. Objective: To investigate the in vitro anti-allergic activities of crude extracts and pure isolated flavonoid compounds from SG by determination of inhibitory effects on antigen-induced release of β-hexosaminidase from RBL-2H3 cells. Methods: The in vitro inhibitory effects of crude aqueous and organic extracts on beta-hexosaminidase release in RBL-2H3 cells were evaluated as an in vitro indication of possible anti-allergic activity in vivo. Bioassay-guided fractionation of extracts was used to isolate flavonoid compounds from the ethanolic extracts. Results: The 95% and 50% ethanolic extracts of SG showed remarkably high anti-allergic activity, with IC50 values of 5.74 ± 2.44 and 23.54 ± 4.75 μg/ml, much higher activity than that for Ketotifen (IC50 58.90 μM). The water extract had negligible activity (IC50 > 100 μg/ml). The two isolated flavonols, Engeletin and Astilbin, showed weak anti-allergic activity, IC50 values 97.46 ± 2.04 and > 100 μg/ml, respectively. Conclusions: The 95% and 50% ethanolic extracts of SG showed strong anti-allergic activity but two flavonol constituents did not show any significant anti-allergic activity. These findings suggest that a combination of effects of various phytochemicals in crude extracts used in traditional medicine are responsible for the purported anti-allergic activity of SG herbal preparations. The plethora of constituents in crude extracts, as yet unidentified, are likely to be acting synergistically to account for the strong observed anti-allergic in vitro activity.

Keywords: Smilax glabra, anti-allergic activity, RBL-2H3 cells, flavonoid compounds

Procedia PDF Downloads 667

Authors: Maha Aladdin, Khaled Nagaty, Abeer Hamdy

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The rapid advancement cellular networks and wireless networks have laid a solid basis for the Internet of Things. IoT has evolved into a unique standard that allows diverse physical devices to collaborate with one another. A service provider gives a variety of services that may be accessed via smart apps anywhere, at any time, and from any location over the Internet. Because of the public environment of mobile communication and the Internet, these services are highly vulnerable to a several malicious attacks, such as unauthorized disclosure by hostile attackers. As a result, the best option for overcoming these vulnerabilities is a strong authentication method. In this paper, a lightweight authentication scheme that is based on numerical series cryptography is proposed for the IoT environments. It allows mutual authentication between IoT devices Parametric study and formal proofs are utilized to illustrate that the pro-posed approach is resistant to a variety of security threats.

Keywords: internet of things, authentication, cryptography, security protocol

Procedia PDF Downloads 120

Authors: Habib Ur Rahman Habib

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Renewable energy resources are being realized as suitable options in hybrid energy planning for on-grid and micro grid. In this paper, operation, planning and optimal design of on-grid distributed energy resources based hybrid system are investigated. The aim is to minimize the cost of the overall energy system keeping in view the environmental emission and minimum penetration of conventional energy resources. Seven grid connected different case studies including diesel only, diesel-renewable based, and renewable based only are designed to perform economic analysis, operational planning and emission. Sensitivity analysis is implemented to investigate the impact of different parameters on the performance of energy resources.

Keywords: data management, renewable energy, distributed energy, smart grid, micro-grid, modeling, energy planning, design optimization

Procedia PDF Downloads 460

Authors: Alexander N. Savostyanov, Tatiana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Tatiana A. Golovko, Yulia V. Kovas

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EEG correlates of mathematical and trait anxiety level were studied in 52 healthy Russian-speakers during execution of error-recognition tasks with lexical, arithmetic and algebraic conditions. Event-related spectral perturbations were used as a measure of brain activity. The ERSP plots revealed alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three conditions. The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-20 Hz) frequency bands. In theta band the effects of mathematical anxiety were stronger expressed in lexical, than in arithmetic and algebraic condition. The mathematical anxiety effects in theta band were associated with differences between anterior and posterior cortical areas, whereas the effects of trait anxiety were associated with inter-hemispherical differences. In beta1 and beta2 bands effects of trait and mathematical anxiety were directed oppositely. The trait anxiety was associated with increase of amplitude of desynchronization, whereas the mathematical anxiety was associated with decrease of this amplitude. The effect of mathematical anxiety in beta2 band was insignificant for lexical condition but was the strongest in algebraic condition. EEG correlates of anxiety in theta band could be interpreted as indexes of task emotionality, whereas the reaction in beta2 band is related to tension of intellectual resources.

Keywords: EEG, brain activity, lexical and numerical error-recognition tasks, mathematical and trait anxiety

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Authors: Abdollah Kavousi Fard

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This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

Procedia PDF Downloads 271

Authors: Kashif Laeeq, Zubair A. Shaikh

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The paradigm of education is drastically changing from conventional to e-learning model. Due to ease of learning with various other benefits, several educational institutions are adopting the e-learning models. Some institutions are still willing to transform their educational system on to e-learning, but due to limited resources, they are still compromising on the old traditional system. The cloud computing could be one of the best solutions to overcome this problem by providing hardware, software, and infrastructure resources with cost efficient manner. The adoption of cloud computing in education will bring revolution in this paradigm. This paper introduces various positive features of e-learning and presents a way how cloud computing technology can be provisioned e-learning model. This paper also investigates the numerous challenges and opportunities that would be observed in cloud computing adoption in e-learning domain. The concept and knowledge present in this paper may create a new direction of research in the domain of cloud-based e-learning.

Keywords: cloud-based e-learning, e-learning, cloud computing application, smart learning

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Samad Lotfollahzadeh

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To evaluate the effect of intramuscular administration of vitamin A during dry period in pregnant dairy cows, which already received it in their daily ration, on vitamin A status of neonatal calves, a total of 30 cows were randomly selected and divided to two main groups; treatment and control group. Animals in the treatment group were subdivided into two groups. Single intramuscular injection of 2000000 IU vitamin A; was carried in 10 dairy cows at 7 months of pregnancy (group 1). In the second group of treated animals (10 cows) the injection was performed in 8 months of pregnancy (group 2). Ten pregnant dairy cows were received saline injection as placebo and selected as the control group. Blood samples were collected from experimental dairy cows at 7 and 8 months of pregnancy as well as their newborn calves’ pre and after colostrum intake. There was no significant difference between vitamin A and β- carotene concentration of dairy cows of three groups in two last months of pregnancy (P > 0.05). Vitamin A concentration of calves of two treatment groups before and after receiving of colostrum were significantly higher than that in the control group (P < 0.05). There was no significant difference between serum concentrations of vitamin A in calves of two treated groups (P > 0.05). β- Carotene concentration of serum samples of dairy cows and neonatal calves of three groups were not significantly different as compared with together. From results of the present study it can be concluded that daily supplementation of vitamin A in late pregnancy in dairy cows may not compensate the calves need for vitamin A and single injection of this vitamin A during dry either in 7 or 8 months of pregnancy can significantly increase level of vitamin A in their colostrum and neonatal calves.

Keywords: dry cow, beta carotene, newborn calves, vitamin A, dry cows

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Authors: Saleh Abu Hashanah, Abirami Radhakrishnan, Dessa David

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Sustainable practices in the supply chain have been an area of focus that require consideration of environmental, economic, and social sustainability practices. This paper aims to examine the use of blockchain as a disruptive technology to promote sustainable supply chains. Content analysis was used to analyze the uses of blockchain technology in sustainable supply chains. The results showed that blockchain technology features such as traceability, transparency, smart contracts, accountability, trust, immutability, anti-fraud, and decentralization promote sustainable supply chains. It is found that these features have impacted organizational efficiency in operations, transportation, and production, minimizing costs and reducing carbon emissions. In addition, blockchain technology has been found to elicit customer trust in the products.

Keywords: blockchain technology, sustainability, supply chains, economic sustainability, environmental sustainability, social sustainability

Procedia PDF Downloads 106

Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Tobias Wissing, Peter Burggräf, Johannes Wagner

Abstract:

Cost pressure, competitiveness and the increasing turbulence of globalized saturated markets has been the driver for a variety of research activities in the field of production planning and control (PPC) during the past decades. For some time past an increasing awareness for innovative technologies in terms of Industry 4.0 can be noticed. Although there are many promising approaches a solely installation of those smart solutions will not maximize the PPC performance. To accelerate the successful digital transformation the cooperation between employee and technology also has to be adapted. The existing processes and organizational structures might be not sufficient to maximize the utilization of technological innovations. This paper presents the key results of an extensive study which was conducted by the Laboratory for Machine Tools and Production Engineering (WZL) of the RWTH Aachen University to evaluate the current situation and examine the organizational readiness for this digital transformation.

Keywords: cyber-physical production system, digital transformation, industry 4.0, production planning and control

Procedia PDF Downloads 353

Authors: A. Elnady

Abstract:

This paper presents an improved Direct Power Control (DPC) scheme applied to the multilevel inverter that forms a Distributed Generation Unit (DGU). This paper demonstrates the performance of active and reactive power injected by the DGU to the smart grid. The DPC is traditionally operated by the hysteresis controller with the Space Vector Modulation (SVM) which is applied on the 2-level inverters or 3-level inverters. In this paper, the DPC is operated by the PI controller with the Phase-Disposition Pulse Width Modulation (PD-PWM) applied to the 5-level diode clamped inverter. The new combination of the DPC, PI controller, PD-PWM and multilevel inverter proves that its performance is much better than the conventional hysteresis-SVM based DPC. Simulations results have been presented to validate the performance of the suggested control scheme in the grid-connected mode.

Keywords: direct power control, PI controller, PD-PWM, and power control

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Authors: Mohammad Rahman, Guy Burton, Megan Mathias

Abstract:

Strategic management as an organizational practice was adopted by the public sector in the New Public Management (NPM) era that began in most parts of the world in the 1980s. Strategy as a new public management concept was subscribed by governments in both developed and developing world, as they were persuaded that clearly defined vision, mission and goals, as well as programs and projects - aligned with the goals - could potentially help achieve government vision at the national level and organizational goals at the service-delivery level. The advocates for strategic management in the public sector saw an inherent link between strategy and performance, claiming that the implementation of organizational strategy has an effect on the overall performance of an organization. Arguably, many government entities that have failed in enhancing team and individual performance had poorly-designed strategy or weak strategy implementation. Another key argument about low-level performance is linked with lack of strategic sense-making and orientation by middle managers in particular. Scholars maintain that employees at all levels need to understand strategic management plan in order to facilitate its implementation. Therefore, involving employees (particularly the middle managers) from the beginning potentially helps an organization avoid the drop in performance, and on the contrary would increase their commitment. The United Arab Emirates (UAE) is well known for adopting public sector reform strategies and tools since the 1990s. This observation is contextually pertinent in the case of the Government of Dubai, which has provided a Strategy Execution Guide to all of its entities to achieve high level strategic success in service delivery. The Dubai public sector also adopts road maps for e-Government, Smart Dubai, Expo 2020, investment, environment, education, health and other sectors. Evidently, some of these strategies are bringing tangible (e.g. Smart Dubai transformation) results in a transformational manner. However, the amount of academic research and literature on the strategy process vis-à-vis staff performance in the Government of Dubai is limited. In this backdrop, this study examines how individual performance of public sector employees in Dubai is linked with their sense-making, engagement and orientation with strategy development and implementation processes. Based on a theoretical framework, this study will undertake a sample-based questionnaire survey amongst middle managers in Dubai public sector to (a) measure the level of engagement of middle managers in strategy development and implementation processes as perceived by them; (b) observe the organizational landscape in which role expectations are placed on middle managers; and (c) examine the impact of employee engagement in strategy development process and the conditions for role expectations on individual performance. The paper is expected to provide new insights on the interface between strategic sense-making and performance in order to contribute a better understanding of the current culture/practices of staff engagement in strategic management in the public sector of Dubai.

Keywords: employee performance, government of Dubai, middle managers, strategic sense-making

Procedia PDF Downloads 197

Authors: Bekkem Chakradhar Reddy, Y. Soni Priya, Mathivanan G., L. K. Joshila Grace, N. Srinivasan, Asha P.

Abstract:

Currently, there are a lot of problems related to marking attendance in schools, offices, or other places. Organizations tasked with collecting daily attendance data have numerous concerns. There are different ways to mark attendance. The most commonly used method is collecting data manually by calling each student. It is a longer process and problematic. Now, there are a lot of new technologies that help to mark attendance automatically. It reduces work and records the data. We have proposed to implement attendance marking using the latest technologies. We have implemented a system based on face identification and analyzing faces. The project is developed by gathering faces and analyzing data, using deep learning algorithms to recognize faces effectively. The data is recorded and forwarded to the host through mail. The project was implemented in Python and Python libraries used are CV2, Face Recognition, and Smtplib.

Keywords: python, deep learning, face recognition, CV2, smtplib, Dlib.

Procedia PDF Downloads 57