Search results for: hybrid bridge

Authors: Filipa Lancastre, Carmen Lages, Filipe Santos

Abstract:

The concept of social entrepreneurship (SE) remains ambiguous and deprived of a widely accepted operational definition. We argue that an awareness about the consensual constituent elements of SE from all key players from its ecosystem as well as a deeper understanding of apparently divergent perspectives will allow the different stakeholders (social entrepreneurs, corporations, investors, policymakers, the beneficiaries themselves) to bridge and cooperate for societal value co-creation in trying to solve our most pressing societal issues. To address our research question –what are the dimensions of SE that are consensual and controversial across existing perspectives? – We designed a two-step qualitative study. In a first step, we conducted an extensive literature review, collecting and analyzing 155 different SE definitions. From this initial step, we extracted and characterized three consensual and six controversial dimensions of the SE concept. In a second step, we conducted 20 semi-structured interviews with practitioners that are actively involved in the SE field. The goal of this second step was to verify if the literature did not capture any key dimension, understand how the dimensions related to each other and to understand the rationale behind them. The dimensions of the SE concept were extracted based on the relevance of each theme and on the theoretical relationship among them. To identify the relevance, we used as a proxy the frequency of each theme was referred to in our sample of definitions. To understand relationships, as identified in the previous section, we included concepts from both the management and psychology literature, such as the Entrepreneurial Orientation concept from the entrepreneurship literature, the Subjective Well Being construct from psychology literature, and the Resource-Based Theory from the strategy literature. This study has two main contributions; First, the identification of (consensual and controversial) dimensions of SE that exist across scattered definitions from the academic and practitioner literature. Second, a framework that parsimoniously synthesizes four dominant perspectives of SE and relates them with the SE dimensions. Assuming the contested nature of the SE concept, it is not expected that these views will be reconciled at the academic or practitioner field level. In future research, academics can, however, be aware of the existence of different understandings of SE and avoid bias towards a single view, developing holistic studies on SE phenomena or comparing differences by studying their underlying assumptions. Additionally, it is important that researchers make explicit the perspective they are embracing to ensure consistency among the research question, sampling procedures and implications of results. At the practitioner level, individuals or groups following different logics are predictably mutually suspicious and might benefit from taking stock of other perspectives on SE, building bridges and fostering cross-fertilization to the benefit of the SE ecosystem for which all contribute.

Keywords: social entrepreneurship, conceptualization, dimensions, perspectives

Procedia PDF Downloads 175

Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

Abstract:

Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

Procedia PDF Downloads 115

Authors: Uzaira Rafique, Kousar Parveen

Abstract:

The discharge volume and composition of Textile effluents gains scientific concern due to its hazards and biotoxcity of azo dyes. Azo dyes are non-biodegradable due to its complex molecular structure and recalcitrant nature. Serious attempts have been made to synthesize and develop new materials to combat the environmental problems. The present study is designed for removal of a range of azo dyes (Methyl orange, Congo red and Basic fuchsine) from synthetic aqueous solutions and real textile effluents. For this purpose, Metal (cobalt) doped alumina hybrids are synthesized and applied as adsorbents in the batch experiment. Two different aluminium precursor (aluminium nitrate and spent aluminium foil) and glucose are mixed following sol gel method to get hybrids. The synthesized materials are characterized for surface and bulk properties using FTIR, SEM-EDX and XRD techniques. The characterization of materials under FTIR revealed that –OH (3487-3504 cm-1), C-H (2935-2985 cm-1), Al-O (~ 800 cm-1), Al-O-C (~1380 cm-1), Al-O-Al (659-669 cm-1) groups participates in the binding of dyes onto the surface of hybrids. Amorphous shaped particles and elemental composition of carbon (23%-44%), aluminium (29%-395%), and oxygen (11%-20%) is demonstrated in SEM-EDX micrograph. Time-dependent batch-experiments under identical experimental parameters showed 74% congo red, 68% methyl orange and 85% maximum removal of basic fuchsine onto the surface of cobalt doped alumina hybrids probably through the ion-exchange mechanism. The experimental data when treated with adsorption models is found to have good agreement with pseudo second order kinetic and freundlich isotherm for adsorption process. The present study concludes the successful synthesis of novel and efficient cobalt doped alumina hybrids providing environmental friendly and economical alternative to the commercial adsorbents for the treatment of industrial effluents.

Keywords: alumina hybrid, adsorption, dopant, isotherm, kinetic

Procedia PDF Downloads 192

Authors: Weldeabrha Kiros Kidanemaryam, DepaTesfay Kelali Gidey, Yikaalo Welu Kidanemariam

Abstract:

Dairy services are considered as sources of income, employment, nutrition and health for smallholder rural and urban farmers. The main objective of this study is to assess the interlinkage of dairy farms and small-scale dairy processing in Mekelle, Tigray. To achieve the stated objective, a descriptive research approach was employed where data was collected from 45 dairy farmers and 40 small-scale processors and analyzed by calculating the mean values and percentages. Findings show that the dairy business in the study area is characterized by a shortage of feed and water for the farm. The dairy farm is dominated by breeds of hybrid type, followed by the so called ‘begait’. Though the farms have access to medication and vaccination for the cattle, they fell short of hygiene practices, reliable shade for the cattle and separate space for the claves. The value chain at the milk production stage is characterized by a low production rate, selling raw milk without adding value and a very meager traditional processing practice. Furthermore, small-scale milk processors are characterized by collecting milk from farmers and producing cheese, butter, ghee and sour milk. They do not engage in modern milk processing like pasteurized milk, yogurt and table butter. Most small-scale milk processors are engaged in traditional production systems. Additionally, the milk consumption and marketing part of the chain is dominated by the informal market (channel), where market problems, lack of skill and technology, shortage of loans and weak policy support are being faced as the main challenges. Based on the findings, recommendations and future research areas are forwarded.

Keywords: value-chain, dairy, milk production, milk processing

Procedia PDF Downloads 31

Authors: Olivia A. Wilson, Hannah E. Power, Murray Kendall

Abstract:

Sydney Harbour is an iconic location with a dense population and low-lying development. On the east coast of Australia, facing the Pacific Ocean, it is exposed to several tsunamigenic trenches. This paper presents a component of the most detailed assessment of the potential for earthquake-generated tsunami impact on Sydney Harbour to date. Models in this study use dynamic tides to account for tide-tsunami interaction. Sydney Harbour’s tidal range is 1.5 m, and the spring tides from January 2015 that are used in the modelling for this study are close to the full tidal range. The tsunami wave trains modelled include hypothetical tsunami generated from earthquakes of magnitude 7.5, 8.0, 8.5, and 9.0 M_W from the Puysegur and New Hebrides trenches as well as representations of the historical 1960 Chilean and 2011 Tohoku events. All wave trains are modelled for the peak wave to coincide with both a low tide and a high tide. A single wave train, representing a 9.0 M_W earthquake at the Puysegur trench, is modelled for peak waves to coincide with every hour across a 12-hour tidal phase. Using the hydrodynamic model ANUGA, results are compared according to the impact parameters of inundation area, depth variation and current speeds. Results show that both maximum inundation area and depth variation are tide dependent. Maximum inundation area increases when coincident with a higher tide, however, hazardous inundation is only observed for the larger waves modelled: NH90high and P90high. The maximum and minimum depths are deeper on higher tides and shallower on lower tides. The difference between maximum and minimum depths varies across different tidal phases although the differences are slight. Maximum current speeds are shown to be a significant hazard for Sydney Harbour; however, they do not show consistent patterns according to tide-tsunami phasing. The maximum current speed hazard is shown to be greater in specific locations such as Spit Bridge, a narrow channel with extensive marine infrastructure. The results presented for Sydney Harbour are novel, and the conclusions are consistent with previous modelling efforts in the greater area. It is shown that tide must be a consideration for both tsunami modelling and emergency management planning. Modelling with peak tsunami waves coinciding with a high tide would be a conservative approach; however, it must be considered that maximum current speeds may be higher on other tides.

Keywords: emergency management, sydney, tide-tsunami interaction, tsunami impact

Procedia PDF Downloads 239

Authors: Shoury Gupta

Abstract:

Chatbots are a rapidly growing technological trend that has revolutionized the way businesses interact with their customers. With the advancements in artificial intelligence, chatbots can now mimic human-like conversations and provide instant and efficient responses to customer inquiries. In this research paper, we aim to explore the implications of chatbots on the future of globalization for both businesses and consumers. The paper begins by providing an overview of the current state of chatbots in the global market and their growth potential in the future. The focus is on how chatbots have become a valuable tool for businesses looking to expand their global reach, especially in areas with high population density and language barriers. With chatbots, businesses can engage with customers in different languages and provide 24/7 customer service support, creating a more accessible and convenient customer experience. The paper then examines the impact of chatbots on cross-cultural communication and how they can help bridge communication gaps between businesses and consumers from different cultural backgrounds. Chatbots can potentially facilitate cross-cultural communication by offering real-time translations, voice recognition, and other innovative features that can help users communicate effectively across different languages and cultures. By providing more accessible and inclusive communication channels, chatbots can help businesses reach new markets and expand their customer base, making them more competitive in the global market. However, the paper also acknowledges that there are potential drawbacks associated with chatbots. For instance, chatbots may not be able to address complex customer inquiries that require human input. Additionally, chatbots may perpetuate biases if they are programmed with certain stereotypes or assumptions about different cultures. These drawbacks may have significant implications for businesses and consumers alike. To explore the implications of chatbots on the future of globalization in greater detail, the paper provides a thorough review of existing literature and case studies. The review covers topics such as the benefits of chatbots for businesses and consumers, the potential drawbacks of chatbots, and how businesses can mitigate any risks associated with chatbot use. The paper also discusses the ethical considerations associated with chatbot use, such as privacy concerns and the need to ensure that chatbots do not discriminate against certain groups of people. The ethical implications of chatbots are particularly important given the potential for chatbots to be used in sensitive areas such as healthcare and financial services. Overall, this research paper provides a comprehensive analysis of chatbots and their implications for the future of globalization. By exploring both the potential benefits and drawbacks of chatbot use, the paper aims to provide insights into how businesses and consumers can leverage this technology to achieve greater global reach and improve cross-cultural communication. Ultimately, the paper concludes that chatbots have the potential to be a powerful tool for businesses looking to expand their global footprint and improve their customer experience, but that care must be taken to mitigate any risks associated with their use.

Keywords: chatbots, conversational AI, globalization, businesses

Procedia PDF Downloads 96

Authors: Karima Adilla

Abstract:

Aceh province, into which Islam convinced to have entered Indonesia in the 12th Century before spreading throughout the archipelago and the rest of Southeast Asia, has several early Islamic mosques that still exist until today. However, due to some circumstances, the restoration and rehabilitation towards those mosques have been made in some periods, while the background was diverse. Concerning this, the research will examine the physical changing aspects of 3 prominent historical mosques in Aceh Besar and Banda Aceh; those are, Indrapuri Mosque, Baiturrahman Grand Mosque, and Baiturrahim Mosque built coincided with the beginning of Islam’s development in Aceh and regarded as eventful mosques. The existence of Indrapuri Mosque built on the remains of the Lamuri Kingdom’s temple is a historical trace that there was Hindu-Buddhist civilization in Aceh before Islam entered and became the majority religion about 98% from Aceh total population. Also, there was the Dutch who colonialized Aceh behind the existence of two famous mosques in Aceh, namely Baiturrahman Grand Mosque and Baiturrahim Mosque, as the colonizer also assisted to rebuild those 2 sacred Mosques to quell the anger of the Acehnese people because their mosque was burnt by the Dutch. Interestingly, despite underwent a long history successively since the rise of Islam after the Hindu-Buddhist kingdom had collapsed, colonialization, conflict, in Aceh, and even experienced the earthquake and tsunami disaster in 2004, those mosques still exist. Therefore, those mosques have been considered as historical silent witnesses. However, it was not merely those reasons that led the mosques underwent several physical changes, otherwise economic, political, social, cultural and religious factors were also highly influential. Instead of directly illustrating the physical changing of those three mosques, this research intends to identify under what condition the physical appearance continuously changing during the sultanate era, the colonial period until post-independent in terms of the architectural style, detail elements, design philosophy, and how the remnants buildings act as medium to bridge the history. A framework will use qualitative research methods by collecting actual data of the mosque's physical change figures through field studies, investigations, library studies and interviews. This research aims to define every trace of historical issues embedded in the physical changing of those mosques as they are intertwined in collecting historical proof. Thus, the result will reveal the characteristic interrelation between history, the mosque architectural style in a certain period, the physical changes background and its impact. Eventually, this research will also explicate a clear inference of each mosque’s role in representing history in Aceh Besar and Banda Aceh specifically, as well as Aceh generally through architectural design concepts.

Keywords: Aceh ancient mosques, Aceh history, Islamic architecture, physical changing

Procedia PDF Downloads 134

Authors: Fadi Saleh, Çığdem Sezer Zhmurov

Abstract:

Biopharmaceuticals represent one of the wildest developing fields within biotechnology, and the biological macromolecules being produced inside cells have a variety of applications for therapies. In the past, mammalian cells, especially CHO cells, have been employed in the production of biopharmaceuticals. This is because these cells can achieve human-like completion of PTM. These systems, however, carry apparent disadvantages like high production costs, vulnerability to contamination, and limitations in scalability. This research is focused on the utilization of microalgae as a bioreactor system for the synthesis of biopharmaceutical glycoproteins in relation to PTMs, particularly N-glycosylation. The research points to a growing interest in microalgae as a potential substitute for more conventional expression systems. A number of advantages exist in the use of microalgae, including rapid growth rates, the lack of common human pathogens, controlled scalability in bioreactors, and the ability of some PTMs to take place. Thus, the potential of microalgae to produce recombinant proteins with favorable characteristics makes this a promising platform in order to produce biopharmaceuticals. The study focuses on the examination of the N-glycosylation pathways across different species of microalgae. This investigation is important as N-glycosylation—the process by which carbohydrate groups are linked to proteins—profoundly influences the stability, activity, and general performance of glycoproteins. Additionally, bioinformatics methodologies are employed to explain the genetic pathways implicated in N-glycosylation within microalgae, with the intention of modifying these organisms to produce glycoproteins suitable for human consumption. In this way, the present comparative analysis of the N-glycosylation pathway in humans and microalgae can be used to bridge both systems in order to produce biopharmaceuticals with humanized glycosylation profiles within the microalgal organisms. The results of the research underline microalgae's potential to help improve some of the limitations associated with traditional biopharmaceutical production systems. The study may help in the creation of a cost-effective and scale-up means of producing quality biopharmaceuticals by modifying microalgae genetically to produce glycoproteins with N-glycosylation that is compatible with humans. Improvements in effectiveness will benefit biopharmaceutical production and the biopharmaceutical sector with this novel, green, and efficient expression platform. This thesis, therefore, is thorough research into the viability of microalgae as an efficient platform for producing biopharmaceutical glycoproteins. Based on the in-depth bioinformatic analysis of microalgal N-glycosylation pathways, a platform for their engineering to produce human-compatible glycoproteins is set out in this work. The findings obtained in this research will have significant implications for the biopharmaceutical industry by opening up a new way of developing safer, more efficient, and economically more feasible biopharmaceutical manufacturing platforms.

Keywords: microalgae, glycoproteins, post-translational modification, genome

Procedia PDF Downloads 23

Authors: Makhlouf Mourad, Messabih Sidi Mohamed, Bouchher Omar, Houali Farida, Benrachedi Khaled

Abstract:

Mesoporous materials are very commonly used as adsorbent materials for removing phenolic compounds. However, the adsorption mechanism of these compounds is still poorly controlled. However, understanding the interactions mesoporous materials/adsorbed molecules is very important in order to optimize the processes of liquid phase adsorption. The difficulty of synthesis is to keep an orderly and cubic pore structure and achieve a homogeneous surface modification. The grafting of Si(CH₃)₃ was chosen, to transform hydrophilic surfaces hydrophobic surfaces. The aim of this work is to study the kinetics and thermodynamics of two volatile organic compounds VOC phenol (PhOH) and P hydroxy benzoic acid (4AHB) on a mesoporous material of type MCM-48 grafted with an organosilane of the Trimethylchlorosilane (TMCS) type, the material thus grafted or functionalized (hereinafter referred to as MCM-48-G). In a first step, the kinetic and thermodynamic study of the adsorption isotherms of each of the VOCs in mono-solution was carried out. In a second step, a similar study was carried out on a mixture of these two compounds. Kinetic models (pseudo-first order, pseudo-second order) were used to determine kinetic adsorption parameters. The thermodynamic parameters of the adsorption isotherms were determined by the adsorption models (Langmuir, Freundlich). The comparative study of adsorption of PhOH and 4AHB proved that MCM-48-G had a high adsorption capacity for PhOH and 4AHB; this may be related to the hydrophobicity created by the organic function of TMCS in MCM-48-G. The adsorption results for the two compounds using the Freundlich and Langmuir models show that the adsorption of 4AHB was higher than PhOH. The values ​​obtained by the adsorption thermodynamics show that the adsorption interactions for our sample with the phenol and 4AHB are of a physical nature. The adsorption of our VOCs on the MCM-48 (G) is a spontaneous and exothermic process.

Keywords: adsorption, kinetics, isotherm, mesoporous materials, Phenol, P-hydroxy benzoique acid

Procedia PDF Downloads 206

Authors: Rui Wu

Abstract:

In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

Procedia PDF Downloads 106

Authors: Jihuai Wu, Zeyu Song, Zhang Lan, Liuxue Sun

Abstract:

Solar energy is clean, open, and infinite, but solar radiation on the earth is fluctuating, intermittent, and unstable. So, the sustainable utilization of solar energy requires a combination of high-efficient energy conversion and low-loss energy storage technologies. Hence, a photo capacitor integrated with photo-electrical conversion and electric-chemical storage functions in single device is a cost-effective, volume-effective and functional-effective optimal choice. However, owing to the multiple components, multi-dimensional structure and multiple functions in one device, especially the mismatch of the functional modules, the overall conversion and storage efficiency of the photocapacitors is less than 13%, which seriously limits the development of the integrated system of solar conversion and energy storage. To this end, two typical photocapacitors were studied. A three-terminal photocapacitor was integrated by using perovskite solar cell as solar conversion module and symmetrical supercapacitor as energy storage module. A function portfolio management concept was proposed the relationship among various efficiencies during photovoltaic conversion and energy storage process were clarified. By harmonizing the energy matching between conversion and storage modules and seeking the maximum power points coincide and the maximum efficiency points synchronize, the overall efficiency of the photocapacitor surpassed 18 %, and Joule efficiency was closed to 90%. A voltage adjustable hybrid supercapacitor (VAHSC) was designed as energy storage module, and two Si wafers in series as solar conversion module, a three-terminal photocapacitor was fabricated. The VAHSC effectively harmonizes the energy harvest and storage modules, resulting in the current, voltage, power, and energy match between both modules. The optimal photocapacitor achieved an overall efficiency of 15.49% and Joule efficiency of 86.01%, along with excellent charge/discharge cycle stability. In addition, the Joule efficiency (ηJoule) was defined as the energy ratio of discharge/charge of the devices for the first time.

Keywords: joule efficiency, perovskite solar cell, photocapacitor, silicon solar cell, supercapacitor

Procedia PDF Downloads 85

Authors: Ayman M. Mansour, Bilal Hawashin, Hesham Alsalem

Abstract:

Faster delivery of laboratory test results is one of the most noticeable signs of good laboratory service and is often used as a key performance indicator of laboratory performance. Despite the availability of technology, the delivery time of clinical laboratory test results continues to be a cause of customer dissatisfaction which makes patients feel frustrated and they became careless to get their laboratory test results. The Medical Clinical Laboratory test results are highly sensitive and could harm patients especially with the severe case if they deliver in wrong time. Such results affect the treatment done by physicians if arrived at correct time efforts should, therefore, be made to ensure faster delivery of lab test results by utilizing new trusted, Robust and fast system. In this paper, we proposed a distributed Multi-Agent System to enhance and faster the process of laboratory test results delivery using SMS. The developed system relies on SMS messages because of the wide availability of GSM network comparing to the other network. The software provides the capability of knowledge sharing between different units and different laboratory medical centers. The system was built using java programming. To implement the proposed system we had many possible techniques. One of these is to use the peer-to-peer (P2P) model, where all the peers are treated equally and the service is distributed among all the peers of the network. However, for the pure P2P model, it is difficult to maintain the coherence of the network, discover new peers and ensure security. Also, security is a quite important issue since each node is allowed to join the network without any control mechanism. We thus take the hybrid P2P model, a model between the Client/Server model and the pure P2P model using GSM technology through SMS messages. This model satisfies our need. A GUI has been developed to provide the laboratory staff with the simple and easy way to interact with the system. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: multi-agent system, delivery process, GSM technology, clinical laboratory results

Procedia PDF Downloads 248

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 70

Authors: D. Berg, N. Hartley, L. Nasr

Abstract:

This paper presents a conceptual model of human-robot interaction within service encounters and the effect on the well-being of both consumers and service providers. In this paper, service providers are those employees who work alongside frontline service robots. The significance of this paper lies in the knowledge created which outlines how frontline service robots can be effectively utilized in service encounters for the benefit of organizations and society as a whole. As this paper is conceptual in nature, the main methodologies employed are theoretical, namely problematization and theory building. The significance of this paper is underpinned by the shift of service robots from manufacturing plants and factory floors to consumer-facing service environments. This service environment places robots in direct contact with frontline employees and consumers creating a hybrid workplace where humans work alongside service robots. This change from back-end to front-end roles may have implications not only on the physical environment, servicescape, design, and strategy of service offerings and encounters but also on the human parties of the service encounter itself. Questions such as ‘how are frontline service robots impacting and changing the service encounter?’ and ‘what effect are such changes having on the well-being of the human actors in a service encounter?’ spring to mind. These questions form the research question of this paper. To truly understand social service robots, an interdisciplinary perspective is required. Besides understanding the function, system, design or mechanics of a service robot, it is also necessary to understand human-robot interaction. However not simply human-robot interaction, but particularly what happens when such robots are placed in commercial settings and when human-robot interaction becomes consumer-robot interaction and employee-robot interaction? A service robot in this paper is characterized by two main factors; its social characteristics and the consumer-facing environment within which it operates. The conceptual framework presented in this paper contributes to interdisciplinary discussions surrounding social robotics, service, and technology’s impact on consumer and service provider well-being, and hopes that such knowledge will help improve services, as well as the prosperity and well-being of society.

Keywords: frontline service robots, human-robot interaction, service encounters, well-being

Procedia PDF Downloads 207

Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

Abstract:

This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

Procedia PDF Downloads 136

Authors: Orit Baruth, Anat Cohen

Abstract:

Online courses have become common in many learning programs and various learning environments, particularly in higher education. Social distancing forced in response to the COVID-19 pandemic has increased the demand for these courses. Yet, despite the frequency of use, online learning is not free of limitations and may not suit all learners. Hence, the growth of online learning alongside with learners' diversity raises the question: is online learning, as it currently offered, meets the needs of each learner? Fortunately, today's technology allows to produce tailored learning platforms, namely, personalization. Personality influences learner's satisfaction and therefore has a significant impact on learning effectiveness. A better understanding of personality can lead to a greater appreciation of learning needs, as well to assists educators ensure that an optimal learning environment is provided. In the context of online learning and personality, the research on learning design according to personality traits is lacking. This study explores the relations between personality traits (using the 'Big-five' model) and students' satisfaction with five techno-pedagogical learning solutions (TPLS): discussion groups, digital books, online assignments, surveys/polls, and media, in order to provide an online learning process to students' satisfaction. Satisfaction level and personality identification of 108 students who participated in a fully online learning course at a large, accredited university were measured. Cluster analysis methods (k-mean) were applied to identify learners’ clusters according to their personality traits. Correlation analysis was performed to examine the relations between the obtained clusters and satisfaction with the offered TPLS. Findings suggest that learners associated with the 'Neurotic' cluster showed low satisfaction with all TPLS compared to learners associated with the 'Non-neurotics' cluster. learners associated with the 'Consciences' cluster were satisfied with all TPLS except discussion groups, and those in the 'Open-Extroverts' cluster were satisfied with assignments and media. All clusters except 'Neurotic' were highly satisfied with the online course in general. According to the findings, dividing learners into four clusters based on personality traits may help define tailor learning paths for them, combining various TPLS to increase their satisfaction. As personality has a set of traits, several TPLS may be offered in each learning path. For the neurotics, however, an extended selection may suit more, or alternatively offering them the TPLS they less dislike. Study findings clearly indicate that personality plays a significant role in a learner's satisfaction level. Consequently, personality traits should be considered when designing personalized learning activities. The current research seeks to bridge the theoretical gap in this specific research area. Establishing the assumption that different personalities need different learning solutions may contribute towards a better design of online courses, leaving no learner behind, whether he\ she likes online learning or not, since different personalities need different learning solutions.

Keywords: online learning, personality traits, personalization, techno-pedagogical learning solutions

Procedia PDF Downloads 102

Authors: Heiko Weiß, Andreas Meister, Christoph Ament, Nils Dreifke

Abstract:

Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.

Keywords: force variations, linear direct drive, modeling and system identification, variable excitation flux

Procedia PDF Downloads 368

Authors: Robert Prohaska, Arnaud Konan, Kenneth Kelly, Adam Ragatz, Adam Duran

Abstract:

In an effort to evaluate the in-use performance of electrified Power Take-off (PTO) usage on bucket utility trucks operating under real-world conditions, data from 20 medium- and heavy-duty vehicles operating in California, USA were collected, compiled, and analyzed by the National Renewable Energy Laboratory's (NREL) Fleet Test and Evaluation team. In this paper, duty-cycle statistical analyses of class 5, medium-duty quick response trucks and class 8, heavy-duty material handler trucks are performed to examine and characterize vehicle dynamics trends and relationships based on collected in-use field data. With more than 100,000 kilometers of driving data collected over 880+ operating days, researchers have developed a robust methodology for identifying PTO operation from in-field vehicle data. Researchers apply this unique methodology to evaluate the performance and utilization of the conventional and electric PTO systems. Researchers also created custom representative drive-cycles for each vehicle configuration and performed modeling and simulation activities to evaluate the potential fuel and emissions savings for hybridization of the tractive driveline on these vehicles. The results of these analyses statistically and objectively define the vehicle dynamic and kinematic requirements for each vehicle configuration as well as show the potential for further system optimization through driveline hybridization. Results are presented in both graphical and tabular formats illustrating a number of key relationships between parameters observed within the data set that relates specifically to medium- and heavy-duty utility vehicles operating under real-world conditions.

Keywords: drive cycle, heavy-duty (HD), hybrid, medium-duty (MD), PTO, utility

Procedia PDF Downloads 395

Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

Abstract:

The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

Procedia PDF Downloads 147

Authors: Hossam E. Emam

Abstract:

Metal–organic frameworks (MOFs) are new hybrid materials investigated from 15 years ago; they synthesized from metals as inorganic center joined with multidentate organic linkers to form a 1D, 2D or 3D network structure. MOFs have unique properties such as pore crystalline structure, large surface area, chemical tenability and luminescent characters. These significant properties enable MOFs to be applied in many fields such like gas storage, adsorption/separation, drug delivery/biomedicine, catalysis, polymerization, magnetism and luminescence applications. Recently, many of published reports interested in superiority of MOFs for functionalization of textiles to exploit the unique properties of MOFs. Incorporation of MOFs is found to acquire the textiles some additional formidable functions to be used in considerable fields such like water treatment and fuel purification. Modification of textiles with MOFs could be easily performed by two main techniques; Ex-situ (preparation of MOFs then applied onto textiles) and in-situ (ingrowth of MOFs within textiles networks). Uniqueness of MOFs could be assimilated in acquirement of decorative color, antimicrobial character, anti-mosquitos character, ultraviolet radiation protective, self-clean, photo-luminescent and sensor character. Additionally, textiles treatment with MOFs make it applicable as filter in the adsorption of toxic gases, hazardous materials (such as pesticides, dyes and aromatics molecules) and fuel purification (such as removal of oxygenated, nitrogenated and sulfur compounds). Also, the porous structure of MOFs make it mostly utilized in control release of insecticides from the surface of the textile. Moreover, MOF@textiles as recyclable materials lead it applicable as photo-catalyst composites for photo-degradation of different dyes in the day light. Therefore, MOFs is extensively considered for imparting textiles with formidable properties as ingeniousness way for textile functionalization.

Keywords: MOF, functional textiles, water treatment, fuel purification, environmental applications

Procedia PDF Downloads 144

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 72

Authors: Wafeek Mohamed Ibrahim Mohamed

Abstract:

In the era of globalization, the camera of the cinematographic film plays a very important role in terms of monitoring and documenting what it was and distinguished the built environment of architectural and Urbanism. Moving the audience to the out-going backward through the cinematographic film and its stereophonic screen by which the picture appears at its best and its coexistence reached now its third dimension. The camera has indicated to the city shape with its paths, (alley) lanes, buildings and its architectural style. We have seen the architectural styles in its cinematic scenes which remained a remembrance in its history, in spite of the fact that some of which has been disappearing as what happened to ‘Boulak Bridge’ in Cairo built by ‘Eiffel’ and it has been demolished, but it remains a remembrance we can see it in the films of ’Usta Hassan’and A Crime in the Quiet Neighborhood. The purpose of the fundamental research is an attempt to reach a critical view of the idea of criticism and theorizing for Architecture and Urbanism in the cinematographic film and their relationship and reflection on the ‘audience’ understanding of the public opinion related to our built environment of Architectural and Urbanism with its problems and hardness. It is like as a trial to study the Architecture and Urbanism of the built environment in the cinematographic film and hooking up (linking) a realistic view of the governing conceptual significance thereof. The aesthetic thought of our traditional environment, in a psychological and anthropological framework, derives from the cinematic concept of the Architecture and Urbanism of the place and the dynamics of the space. The architectural space considers the foundation stone of the cinematic story and the main background of the events therein, which integrate the audience into a romantic trip to the city through its symbolized image of the spaces, lanes [alley], etc. This will be done through two main branches: firstly, Reviewing during time pursuit of the Architecture and Urbanism in the cinematographic films the thirties ago in the Egyptian cinema [onset from the film ‘Bab El Hadid’ to the American University at a film of ‘Saidi at the American University’]. The research concludes the importance of the need to study the cinematic films which deal with our societies, their architectural and Urbanism concerns whether the traditional ones or the contemporary and their crisis (such as the housing crisis in the film of ‘Krakoun in the street’, etc) to study the built environment with its architectural dynamic spaces through a modernist view. In addition, using the cinema as an important Media for spreading the ideas, documenting and monitoring the current changes in the built environment through its various dramas and comedies, etc. The cinema is considered as a mirror of the society and its built environment over the epochs. It assured the unique case constituted by cinema with the audience (public opinion) through a sense of emptiness and forming the mental image related to the city and the built environment.

Keywords: architectural and urbanism, cinematographic architectural, film, space in the film, media

Procedia PDF Downloads 237

Authors: Ji-Won Park, Jong-Wha Kim

Abstract:

Triploid L. lancifolium have a wide geographic distribution. By contrast, diploid L. lancifolium have limited distributions in the islands and coastal regions of the South and West Korean Peninsula and northern Tsushima Island, Japan. L. lancifolium diploids and triploids are not sympatrically distributed with other lily species or ploidy lines in West Sea and South Sea Islands of the Korean Peninsula. This observation raises the following questions: 'Why have autotriploid L. lancifolium never been observed in those isolated islands?', 'What mechanism excludes the occurrence of autotriploids, if they arise?'. To determine the occurrence and survival of triploid plants in natural diploid populations of tiger lily (Lilium lancifolium), ploidy analysis was conducted on natural open-pollinated seeds produced from plants grown on isolated islands, and on hybrid seeds produced by artificial crossing between plant populations originating on different Korean islands. Normal seeds were classified into five grades depending on the ratio of embryo/endosperm lengths, including 5/5, 4/5, 3/5, 2/5, and 1/5. Triploids were not observed among seedlings produced from natural open pollinations on isolated islands. Triploids were detected only in seedlings of underdeveloped seed grades(3/5 and 2/5) from artificial crosses between populations from different isolated islands. The triploid occurrence frequency was calculated as 0.0 for natural open-pollinated seedlings and 0.000582 for artificial crosses(6 triploids from 10,303 seedlings). Triploids were produced from crosses between isolated populations located at least 70 km apart; no triploids were detected in inter-population crosses of plants originating on the same islands. Triploid seedlings have very low viability in soil. We analyzed factors affecting triploid occurrence and survival in natural diploid populations of L. lancifolium. The results suggest that triploids originate from fertilization between plants that are genetically isolated due to geographical isolation and/or genotypic differences.

Keywords: Lilium lancifolium, autotriploid, natural population, genetic distance, 2n female gamete

Procedia PDF Downloads 519

Authors: Misagh Ghobadi, Rich Crane, Karen Hudson-Edwards, Clemens Vinzenz Ullmann

Abstract:

Lithium is recognized as the critical energy metal of the 21st century, comparable in importance to coal in the 19th century and oil in the 20th century, often termed 'white gold'. Current global demand for lithium, estimated at 0.95-0.98 million metric tons (Mt) of lithium carbonate equivalent (LCE) annually in 2024, is projected to rise to 1.87 Mt by 2027 and 3.06 Mt by 2030. Despite anticipated short-term stability in supply and demand, meeting the forecasted 2030 demand will require the lithium industry to develop an additional capacity of 1.42 Mt of LCE annually, exceeding current planned and ongoing efforts. Brine resources constitute nearly 65% of global lithium reserves, underscoring the importance of exploring lithium recovery from underutilized sources, especially geothermal brines. However, conventional lithium extraction from brine deposits faces challenges due to its time-intensive process, low efficiency (30-50% lithium recovery), unsuitability for low lithium concentrations (<300 mg/l), and notable environmental impacts. Addressing these challenges, direct lithium extraction (DLE) methods have emerged as promising technologies capable of economically extracting lithium even from low-concentration brines (>50 mg/l) with high recovery rates (75-98%). However, most studies (70%) have predominantly focused on synthetic brines instead of native (natural/real), with limited application of these approaches in real-world case studies or industrial settings. This study aims to bridge this gap by investigating a geothermal brine sample collected from a real case study site in the UK. A Mn-based lithium-ion sieve (LIS) adsorbent was synthesized and employed to selectively extract lithium from the sample brine. Adsorbents with a Li:Mn molar ratio of 1:1 demonstrated superior lithium selectivity and adsorption capacity. Furthermore, the pristine Mn-based adsorbent was modified through transition metals doping, resulting in enhanced lithium selectivity and adsorption capacity. The modified adsorbent exhibited a higher separation factor for lithium over major co-existing cations such as Ca, Mg, Na, and K, with separation factors exceeding 200. The adsorption behaviour was well-described by the Langmuir model, indicating monolayer adsorption, and the kinetics followed a pseudo-second-order mechanism, suggesting chemisorption at the solid surface. Thermodynamically, negative ΔG° values and positive ΔH° and ΔS° values were observed, indicating the spontaneity and endothermic nature of the adsorption process.

Keywords: adsorption, critical minerals, DLE, geothermal brines, geochemistry, lithium, lithium-ion sieves

Procedia PDF Downloads 44

Authors: Ionelia Taranu, Gina Cecilia Pistol, Mihai Alexandru Gras, Mihai Laurentiu Palade, Mariana Stancu, Veronica Sanda Chedea

Abstract:

In the last decade bioactive compounds from grape waste are investigated as new therapeutic agents for the inhibition of carcinogenesis and other diseases. The objective of this study was to characterize several bioactive compounds (polyphenols and polyunsaturated fatty acids) of a dried grape pomace (GP) derived from a Romanian winery and further to evaluate their effect on inflammation and oxidative markers in liver of pig used as animal model. The total polyphenol concentration of pomace was 36.2g gallic acid equiv /100g. The pomace was rich in polyphenols from the flavonoids group, the main class being flavanols (epicatechins, catechin, epigallocatechin, procyanidins) and antocyanins (Malvidin 3-O-glucoside). The highest concentration was recorded for epicatechin (51.96g/100g) and procyanidin dimer (22.79g/100g). A high concentration of total polyunsaturated fatty acids (PUFA) especially ω-6 fatty acids (59.82 g/100g fat) was found in grape pomace. 20 crossbred TOPIG hybrid fattening pigs were randomly assigned (n = 10) to two experimental treatments: a normal diet (control group) and a diet included 5% grape pomace (GP group) for 24 days. The GP diet lowered the gene expression and protein concentration of IL-1β, IL-8, TNF-α and IFN-γ cytokines in liver suggesting an anti-inflammatory effect of GP diet. Concentration of hepatic TBARS also decreased, but the total antioxidant capacity (liver TEAC) and activity and gene expression of antioxidant enzymes (superoxide dismutase, catalase and glutathione peroxidase) did not differ between the GP and control diet. The results showed that GP diet exerted an anti-inflammatory effect, but the 5% dietary inclusion modulated only partially the oxidative stress.

Keywords: animal model, inflammation, grape waste, immune organs

Procedia PDF Downloads 338

Authors: Bekir Turedi

Abstract:

Exploiting the potential of perovskite single-crystal solar cells in optoelectronic applications necessitates overcoming a significant challenge: the low charge collection efficiency at increased thickness, which has restricted their deployment in radiation detectors and nuclear batteries. Our research details a promising approach to this problem, wherein we have successfully fabricated single-crystal MAPbI3 solar cells employing a space-limited inverse temperature crystallization (ITC) methodology. Remarkably, these cells, up to 400-fold thicker than current-generation perovskite polycrystalline films, maintain a high charge collection efficiency even without external bias. The crux of this achievement lies in the long electron diffusion length within these cells, estimated to be around 0.45 mm. This extended diffusion length ensures the conservation of high charge collection and power conversion efficiencies, even as the thickness of the cells increases. Fabricated cells at 110, 214, and 290 µm thickness manifested power conversion efficiencies (PCEs) of 20.0, 18.4, and 14.7% respectively. The single crystals demonstrated nearly optimal charge collection, even when their thickness exceeded 200 µm. Devices of thickness 108, 214, and 290 µm maintained 98.6, 94.3, and 80.4% of charge collection efficiency relative to their maximum theoretical short-circuit current value, respectively. Additionally, we have proposed an innovative, self-consistent technique for ascertaining the electron-diffusion length in perovskite single crystals under operational conditions. The computed electron-diffusion length approximated 446 µm, significantly surpassing previously reported values for this material. In conclusion, our findings underscore the feasibility of fabricating halide perovskite single-crystal solar cells of hundreds of micrometers in thickness while preserving high charge extraction efficiency and PCE. This advancement paves the way for developing perovskite-based optoelectronics necessitating thicker active layers, such as X-ray detectors and nuclear batteries.

Keywords: perovskite, solar cell, single crystal, diffusion length

Procedia PDF Downloads 50

Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

Abstract:

Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

Procedia PDF Downloads 429

Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 104

Authors: Katherine O'Grady-Bray

Abstract:

For some deaf children, reading books can be a challenge. Frank Barnes School (FBS) provides guided reading time with Teachers of the Deaf, in which they read books with deaf children using a bilingual approach. The vocabulary and context of the story is explained to deaf children in BSL so they develop skills bridging English and BSL languages. However, the success of this practice is only achieved if the person is fluent in both languages. FBS piloted a scheme to convert an Oxford Reading Tree (ORT) book into an e-book that can be read using tablets. Deaf readers at FBS have access to both languages (BSL and English) during lessons and outside the classroom. The pupils receive guided reading sessions with a Teacher of the Deaf every morning, these one to one sessions give pupils the opportunity to learn how to bridge both languages e.g. how to translate English to BSL and vice versa. Generally, due to our pupils’ lack of access to incidental learning, gaining new information about the world around them is limited. This highlights the importance of quality time to scaffold their language development. In some cases, there is a shortfall of parental support at home due to poor communication skills or an unawareness of how to interact with deaf children. Some families have a limited knowledge of sign language or simply don’t have the required learning environment and strategies needed for language development with deaf children. As the majority of our pupils’ preferred language is BSL we use that to teach reading and writing English. If this is not mirrored at home, there is limited opportunity for joint reading sessions. Development of the e-Book required planning and technical development. The overall production took time as video footage needed to be shot and then edited individually for each page. There were various technical considerations such as having an appropriate background colour so not to draw attention away from the signer. Appointing a signer with the required high level of BSL was essential. The language and pace of the sign language was an important consideration as it was required to match the age and reading level of the book. When translating English text to BSL, careful consideration was given to the nonlinear nature of BSL and the differences in language structure and syntax. The e-book was produced using Apple’s ‘iBook Author’ software which allowed video footage of the signer to be embedded on pages opposite the text and illustration. This enabled BSL translation of the content of the text and inferences of the story. An interpreter was used to directly ‘voice over’ the signer rather than the actual text. The aim behind the structure and layout of the e-book is to allow parents to ‘read’ with their deaf child which helps to develop both languages. From observations, the use of e-books has given pupils confidence and motivation with their reading, developing skills bridging both BSL and English languages and more effective reading time with parents.

Keywords: bilingual book, e-book, BSL and English, bilingual e-book

Procedia PDF Downloads 166

Authors: Arjun Goutham, Chaitanya Sridhar, Sunita Maheshwari, Robin Uthappa, Prasanna Gopinath

Abstract:

In alignment with the growth in the sporting industry, a number of people playing and competing in sports are growing exponentially across the globe. However, the number of sports psychology experts are not growing at a similar rate, especially in the Asian and more so, Indian context. Hence, the access to actionable mental training solutions specific to individual athletes is limited. Also, the time constraint an athlete faces due to their intense training schedule makes one-on-one sessions difficult. One of the means to bridge that gap is through technology. Technology makes individualization possible. It allows for easy access to specific-qualitative content/information and provides a medium to place individualized assessments, analysis, solutions directly into an athlete's hands. This enables mental training awareness, education, and real-time actionable solutions possible for athletes in-spite of the limitation of available sports psychology experts in their region. Furthermore, many athletes are hesitant to seek support due to the stigma of appearing weak. Such individuals would prefer a more discreet way. Athletes who have strong mental performance tend to produce better results. The mobile application helps to equip athletes with assessing and developing their mental strategies directed towards improving performance on an ongoing basis. When an athlete understands their strengths and limitations in their mental application, they can focus specifically on applying the strategies that work and improve on zones of limitation. With reports, coaches get to understand the unique inner workings of an athlete and can utilize the data & analysis to coach them with better precision and use coaching styles & communication that suits better. Systematically capturing data and supporting athletes(with individual-specific solutions) or teams with assessment, planning, instructional content, actionable tools & strategies, reviewing mental performance and the achievement of objectives & goals facilitate for a consistent mental skills development at all levels of sporting stages of an athlete's career. The mobile application will help athletes recognize and align with their stable attributes such as their personalities, learning & execution modalities, challenges & requirements of their sport, etc and help develop dynamic attributes like states, beliefs, motivation levels, focus etc. with practice and training. It will provide measurable analysis on a regular basis and help them stay aligned to their objectives & goals. The solutions are based on researched areas of influence on sporting performance individually or in teams.

Keywords: athletes, mental training, mobile application, performance, sports

Procedia PDF Downloads 267