Search results for: electronic intelligence

Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: P. Suchismita Behera, V. G. Sathe, A. K. Nigam, P. A. Bhobe

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Co-existence of long-range ferromagnetism and semi-conductivity with correlated behavior of structural, magnetic, optical and electrical properties in various sites doping at CdCr2Se4 makes it a most promising candidate for spin-based electronic applications and magnetic devices. It orders ferromagnetically below TC = 130 K with a direct band gap of ~ 1.5 eV. The magnetic ordering is believed to result from strong competition between the direct antiferromagnetic Cr-Cr spin couplings and the ferromagnetic Cr-Se-Cr exchange interactions. With an aim of understanding the influence of crystal structure on its magnetic properties without disturbing the magnetic site, we investigated four compositions with 3%, 5%, 7% and 10% of Sn-substitution at Cd-site. Partial substitution of Cd2+ (0.78Å) by small sized nonmagnetic ion, Sn4+ (0.55Å), is expected to bring about local lattice distortion as well as a change in electronic charge distribution. The structural disorder would affect the Cd/Sn – Se bonds thus affecting the Cr-Cr and Cr-Se-Cr bonds. Whereas, the charge imbalance created due to Sn4+ substitution at Cd2+ leads to the possibility of Cr mixed valence state. Our investigation of the local crystal structure using the EXAFS, Raman spectroscopy and magnetic properties using SQUID magnetometry of the Cd1-xSnxCr2Se4 series reflects this premise. All compositions maintain the Fd3m cubic symmetry with tetrahedral distribution of Sn at Cd-site, as confirmed by XRD analysis. Lattice parameters were determined from the Rietveld refinement technique of the XRD data and further confirmed from the EXAFS spectra recorded at Cr K-edge. Presence of five Raman-active phonon vibrational modes viz. (T2g (1), T2g (2), T2g (3), Eg, A1g) in the Raman spectra further confirms the crystal symmetry. Temperature dependence of the Raman data provides interesting insight to the spin– phonon coupling, known to dominate the magneto-capacitive properties in the parent compound. Below the magnetic ordering temperature, the longitudinal damping of Eg mode associated with Se-Cd/Sn-Se bending and T2g (2) mode associated to Cr-Se-Cr interaction, show interesting deviations with respect to increase in Sn substitution. Besides providing the estimate of TC, the magnetic measurements recorded as a function of field provide the values of total magnetic moment for all the studied compositions indicative of formation of multiple Cr valences.

Keywords: exchange interactions, EXAFS, ferromagnetism, Raman spectroscopy, spinel chalcogenides

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Driss Kettani

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ICT4D actors are naturally attempted to include AI in the range of enabling technologies and tools that could support and boost the Development process, and to refer to these as AI4D. But, doing so, assumes that AI complies with the very specific features of ICT4D context, including, among others, affordability, relevance, openness, and ownership. Clearly, none of these is fulfilled, and the enthusiastic posture that AI4D is a natural part of ICT4D is not grounded and, to certain extent, does not serve the purpose of Technology for Development at all. In the context of Development, it is important to emphasize and prioritize ICT4D, in the national digital transformation strategies, instead of borrowing "trendy" waves of the IT Industry that are motivated by business considerations, with no specific care/consideration to Development.

Keywords: AI, ICT4D, technology for development, position paper

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Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

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With the fast growth of integrated circuits and the trend towards making electronic devices smaller, the heat dissipation load of electronic devices has continued to go over the limit. The high heat flux element would not only harm the operation and lifetime of the equipment but would also impede the performance upgrade brought about by the iteration of technological updates, which would have a direct negative impact on the economic and production cost benefits of rising industries. Hence, in high-tech industries like radar, information and communication, electromagnetic power, and aerospace, the development and implementation of effective heat dissipation technologies were urgently required. Pool boiling is favored over other cooling methods because of its capacity to dissipate a high heat flux at a low wall superheat without the usage of mechanical components. Enhancing the pool boiling performance by increasing the heat transfer coefficient via surface modification techniques has received a lot of attention. There are several surface modification methods feasible today, but the stability and durability of surface modification are the greatest priority. Thus, laser machining is an interesting choice for surface modification due to its low production cost, high scalability, and repeatability. In this study, different patterns of laser-processed copper surfaces are fabricated to investigate the nucleate pool boiling heat transfer performance of distilled water. The investigation showed that there is a significant enhancement in the pool boiling heat transfer performance of the laser-processed surface compared to the reference surface due to the notable increase in nucleation frequency and nucleation site density. It was discovered that the heat transfer coefficients increased when both the surface area ratio and the ratio of peak-to-valley height of the microstructure were raised. It is believed that the development of microstructures on the surface as a result of laser processing is the primary factor in the enhancement of heat transfer performance.

Keywords: heat transfer coefficient, laser processing, micro structured surface, pool boiling

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Authors: Dulani Jayasuriya

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This study outlines the developmental steps of a chatbot for administrative purposes of a large undergraduate course. The chatbot is able to handle student queries about administrative details, including assessment deadlines, course documentation, how to navigate the course, group formation, etc. The development window screenshots are that of a free account on the Snatchbot platform such that this can be adopted by the wider public. While only one connection to an answer based on possible keywords is shown here, one needs to develop multiple connections leading to different answers based on different keywords for the actual chatbot to function. The overall flow of the chatbot showing connections between different interactions is depicted at the end.

Keywords: chatbots, education, technology, snatch bot, artificial intelligence

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Authors: N. Ben Si Ali, N. Benalia, N. Zerzouri

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Many electronic drivers for the induction motor control are based on sensorless technologies. Speed and torque control is usually attained by application of a speed or position sensor which requires the additional mounting space, reduce the reliability and increase the cost. This paper seeks to analyze dynamical performances and sensitivity to motor parameter changes of reactive power based technique used in sensorless control of induction motors. Validity of theoretical results is verified by simulation.

Keywords: adaptive observers, model reference adaptive system, RP-based estimator, sensorless control, stability analysis

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Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

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The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

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Authors: Maria Luisa de la Torre, Javier Aroba, Jose Miguel Davila, Aguasanta M. Sarmiento

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Steel is one of the most widely used materials in polymetallic sulfide mining installations. One of the main problems suffered by these facilities is the economic losses due to the corrosion of this material, which is accelerated and aggravated by the contact with acid waters generated in these mines when sulfides come into contact with oxygen and water. This generation of acidic water, in turn, is accelerated by the presence of acidophilic bacteria. In order to gain a more detailed understanding of this corrosion process and the interaction between steel and acidic water, a laboratory experiment was carried out in which carbon steel plates were introduced into four different solutions for 27 days: distilled water (BK), which tried to assimilate the effect produced by rain on this material, an acid solution from a mine with a high Fe2+/Fe3+ (PO) content, another acid solution of water from another mine with a high Fe3+/Fe2+ (PH) content and, finally, one that reproduced the acid mine water with a high Fe2+/Fe3+ content but in which there were no bacteria (ST). Every 24 hours, physicochemical parameters were measured, and water samples were taken to carry out an analysis of the dissolved elements. The results of these measurements were processed using an explainable AI model based on fuzzy logic. It could be seen that, in all cases, there was an increase in pH, as well as in the concentrations of Fe and, in particular, Fe(II), as a consequence of the oxidation of the steel plates. Proportionally, the increase in Fe concentration was higher in PO and ST than in PH because Fe precipitates were produced in the latter. The rise of Fe(II) was proportionally much higher in PH, especially in the first hours of exposure, because it started from a lower initial concentration of this ion. Although to a lesser extent than in PH, the greater increase in Fe(II) also occurred faster in PO than in ST, a consequence of the action of the catalytic bacteria. On the other hand, Cu concentrations decreased throughout the experiment (with the exception of distilled water, which initially had no Cu, as a result of an electrochemical process that generates a precipitation of Cu together with Fe hydroxides. This decrease is lower in PH because the high total acidity keeps it in solution for a longer time. With the application of an artificial intelligence tool, it has been possible to evaluate the effects of steel corrosion in mining environments, corroborating and extending what was obtained by means of classical statistics.

Keywords: acid mine drainage, artificial intelligence, carbon steel, corrosion, fuzzy logic

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Authors: Yara Bajnaid, Malak Zaidan, Eman Dakkak

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This research explores the use of Artificial Intelligence in Duolingo, a popular mobile application for language learning. Duolingo's success hinges on its gamified approach and adaptive learning system, both heavily reliant on AI functionalities. The research also analyzes user feedback regarding Duolingo's AI functionalities. While a significant majority (70%) consider Duolingo a reliable tool for language learning, there's room for improvement. Overall, AI plays a vital role in personalizing the learning journey and delivering interactive exercises. However, continuous improvement based on user feedback can further enhance the effectiveness of Duolingo's AI functionalities.

Keywords: AI, Duolingo, language learning, application

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Ardak Myrzabekova

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Sentinel epidemiological surveillance (SES) of severe acute respiratory infections (SARI) was introduced in the Republic of Kazakhstan in 2008. The purpose of this study was to analyze SES of flu among SARI patients in the Republic of Kazakhstan during last two flu seasons. Comparative analysis was conducted of SARI morbidity during 40 – 23 weeks of 2014/2015 (season 2014) and 2015/2016 (season 2015) in online base (http:\\ses.dec.kz). In the database during season 2014 were 1,398 SARI patients and 1,985 patients during season 2015. Individual data (clinical, epidemiological and laboratory) of SARI cases were collected based on the questionnaire and were put into the flu electronic system. The studied population was residents of the Republic of Kazakhstan who addressed for medical help in 24 sentinel in-patient clinics in 9 sentinel regions of the country. Swabs from nose and throat were taken for laboratory testing from SARI patients who met the standard case definition. The samples were examined in virology labs of sentinel regions using PCR and 'AmpliSens' test systems made in Russia. The first positive results for flu during season 2014 were obtained on 48 week, during season 2015 – on 46 week. The increase of the number of hospitalized SARI patients was observed during 42 week of 2015 – 01 week of 2016, and during 03 - 06 weeks of 2016, with fluctuating SARI incidence rate from 171 to 444 per 1,000 hospitalized. The highest SARI incidence rate during season 2014 were observed during 01 - 03 weeks of 2015: from 389 to 466 per 1,000 hospitalized. Patients admitted to the ICU during season 2015 were 3.0% (60) SARI patients, compared to 2.7% (38) in 2014 (p=0.3), obtaining oxygen therapy 1.0% (21) compared to 0.3% (5), accordingly, (р=0.009); with shortness of breath 74.8% (1,486) compared to 72.6% (1,015), (р=0.07); with impairment of consciousness 1.0% (21) compared to 0.6% (9), (р=0.11); with muscle pain 19.3% (384) compared to 13.6% (191), (р < 0.001); with joint pain 13.3% (265) compared to 9.3% (131), (p < 0.001). During season 2015 the prevailing subtype of flu А was А/Н1N1-09, it was observed mainly in the age group 30-64: 32.5% (169/520). During season 2014 flu А/Н3N2 was observed mainly in the age group 15-29: 43.6% (106/243). Among children under 14 flu А/Н1N1-09 during season 2015 was 37.3% (194/520), during season 2014 flu А/Н3N2 – 34.9% (85/243). Earlier beginning of the flu season was noted in 2015-2016 and a longer period of hospitalization of SARI patients, with high SARI morbidity rates, unlike season 2014-2015. Season 2015-2016 was characterized by prevailing circulation of virus of flu А/Н1N1-09, mainly in the age group 30-64, and also among children under 14. During season 2014-2015 the virus circulating in the country was А/Н3N2, which was observed mainly in the age group 15-29 and among children under 14.

Keywords: flu, electronic system, sentinel epidemiological surveillance, severe acute respiratory infections

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Authors: David Nchinda Keming

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The present study is focused on both the national and international collective fight against Boko Haram terrorism on Cameroon and the rule played by the Lake Chad Basin Countries (LCBCs) and the global community to suffocate the sect’s activities in the region. Although countries of the Lake Chad Basin include: Cameroon, Chad, Nigeria and Niger others like Benin also joined the course. The justification for the internationalisation of the fight against Boko Haram could be explained by the ecological and international climatic importance of the Lake Chad and the danger posed by the sect not only to the Lake Chad member countries but to global armed, civil servants and the international political economy. The study, therefore, kick start with Cameroon’s reaction to Boko Haram’s terrorist attacks on its territory. It further expounds on Cameroon’s request on bilateral diplomacy from members of the UN Security Council for an international collective support to staple the winds of the challenging sect. The study relies on the hypothesis that Boko Haram advanced terrorism on Cameroon was more challenging to the domestic military intelligence thus forcing the government to seek for bilateral and multilateral international collective support to secure its territory from the powerful sect. This premise is tested internationally via (multilateral cooperation, bilateral response, regional cooperation) and domestically through (solidarity parade, religious discourse, political manifestations, war efforts, the vigilantes and the way forward). To accomplish our study, we made used of the mixed research methodologies to interpret the primary, secondary and tertiary sources consulted. Our results reveal that the collective response was effectively positive justified by the drastic drop in the sect’s operations in Cameroon and the whole LCBCs. Although the sect was incapacitated, terrorism remains an international malaise and Cameroon hosts a fertile ground for terrorists’ activism. Boko Haram was just weakened and not completely defeated and could reappear someday even under a different appellation. Therefore, to absolutely eradicate terrorism in general and Boko Haram in particular, LCBCs must improve their military intelligence on terrorism and continue to collaborate with advanced experienced countries in fighting terrorism.

Keywords: Boko Haram, terrorism, domestic, international, response

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Authors: Ahmad Haidar

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This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

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Authors: Dilip K. De, Olukunle C. Olawole, Emmanuel S. Joel, Moses Emetere

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A good number of electronic properties such as electrical and thermal conductivities depend on charge carrier densities of nanomaterials. By controlling the charge carrier densities during the fabrication (or growth) processes, the physical properties can be tuned. In this paper, we discuss a new technique of estimating the charge carrier densities of nanomaterials from the thermionic emission data using the newly modified Richardson-Dushman equation. We find that the technique yields excellent results for graphene and carbon nanotube.

Keywords: charge carrier density, nano materials, new technique, thermionic emission

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Authors: Andrew Read, Alice Parry, Kate Woods

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Since the advent of the SARS-CoV-2 pandemic, the search for medications that can reduce mortality and morbidity has been a global research priority. Several multi-center trials have recently demonstrated improved mortality associated with the use of Tocilizumab, an interleukin-6 receptor antagonist, in patients with severe SARS-CoV-2 pneumonia. Initial data supported the administration in patients requiring respiratory support (non-invasive or invasive ventilation), but more recent data has shown benefit in all hypoxic patients. At the height of the second wave of COVID-19 infections in London, our hospital introduced the use of Tocilizumab for patients with severe COVID-19. Tocilizumab is licensed for use in chronic inflammatory conditions and has been associated with an increased risk of severe bacterial and fungal infections, as well as reactivation of chronic viral infections (e.g., hepatitis B). It is a specialist drug that suppresses the formation of C-reactive protein (CRP) for 6 – 12 weeks. It is not widely used by the general medical community. We aimed to assess Tocilizumab use in our hospital and to implement changes to the protocol as required to ensure administration was safe and appropriate. A retrospective study design was used to assess prescriptions over an initial 3-week period in both intensive care and on the medical wards. This amounted to a total of 13 patients. The initial data collection identified four key areas of concern: adherence to national and local inclusion & exclusion criteria; a collection of appropriate screening blood prior to administration; documentation of informed consent or best interest decision and documentation of Tocilizumab administration on patient discharge information, to alert future healthcare providers that typical measures of inflammation and infection, such as CRP, are unreliable for up to 3-months. Data were collected from electronic notes, blood results and observation charts, and cross referenced with pharmacy data. Initial results showed that all four key areas were completed in approximately 50% of cases. Of particular concern was adherence to exclusion criteria, such as current evidence of bacterial infection, and ensuring the correct screening blood was sent to exclude infections such as hepatitis. To remedy this and improve patient safety, the initial data was presented to relevant healthcare professionals. Subsequently, three interventions were introduced and education on each provided to hospital staff. An electronic ‘order set’ collating the appropriate screening blood was created simplifying the screening process. Pre-formed electronic documentation which can be inserted into the notes was created to provide a framework for consent discussions and reduce the time needed for junior doctors to complete this task. Additionally, a ‘Tocilizumab’ administration card was created and administered via pharmacy. This was distributed to each patient on discharge to ensure future healthcare professionals were aware of the potential effects of Tocilizumab administration, including suppression of CRP. Following these changes, repeat data collection over two months illustrated that each of the 4 safety aspects was met with a 100% success rate in every patient. Although this demonstrates good progress and effective interventions the challenge will be to maintain this progress. The audit data collection is ongoing

Keywords: education, patient safety , SARS-CoV-2, Tocilizumab

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Authors: Sinead Impey, Gaye Stephens, Declan O’Sullivan

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Mitigating organisational knowledge loss presents challenges for knowledge managers. Expert knowledge is embodied in people and captured in ‘routines, processes, practices and norms’ as well as in the paper system. These knowledge stores have limitations in so far as they make knowledge diffusion beyond geography or over time difficult. However, technology could present a potential solution by facilitating the capture and management of expert knowledge in a codified and sharable format. Before it can be digitised, however, the knowledge of healthcare experts must be captured. Methods: As a first step in a larger project on this topic, a scoping review was conducted to identify how expert healthcare knowledge is captured digitally. The aim of the review was to identify current healthcare knowledge capture practices, identify gaps in the literature, and justify future research. The review followed a scoping review framework. From an initial 3,430 papers retrieved, 22 were deemed relevant and included in the review. Findings: Two broad approaches –direct and indirect- with themes and subthemes emerged. ‘Direct’ describes a process whereby knowledge is taken directly from subject experts. The themes identified were: ‘Researcher mediated capture’ and ‘Digital mediated capture’. The latter was further distilled into two sub-themes: ‘Captured in specified purpose platforms (SPP)’ and ‘Captured in a virtual community of practice (vCoP)’. ‘Indirect’ processes rely on extracting new knowledge using artificial intelligence techniques from previously captured data. Using this approach, the theme ‘Generated using artificial intelligence methods’ was identified. Although presented as distinct themes, some papers retrieved discuss combining more than one approach to capture knowledge. While no approach emerged as superior, two points arose from the literature. Firstly, human input was evident across themes, even with indirect approaches. Secondly, a range of challenges common among approaches was highlighted. These were (i) ‘Capturing an expert’s knowledge’- Difficulties surrounding capturing an expert’s knowledge related to identifying the ‘expert’ say from the very experienced and how to capture their tacit or difficult to articulate knowledge. (ii) ‘Confirming quality of knowledge’- Once captured, challenges noted surrounded how to validate knowledge captured and, therefore, quality. (iii) ‘Continual knowledge capture’- Once knowledge is captured, validated, and used in a system; however, the process is not complete. Healthcare is a knowledge-rich environment with new evidence emerging frequently. As such, knowledge needs to be reviewed, updated, or removed (redundancy) as appropriate. Although some methods were proposed to address this, such as plausible reasoning or case-based reasoning, conclusions could not be drawn from the papers retrieved. It was, therefore, highlighted as an area for future research. Conclusion: The results described two broad approaches – direct and indirect. Three themes were identified: ‘Researcher mediated capture (Direct)’; ‘Digital mediated capture (Direct)’ and ‘Generated using artificial intelligence methods (Indirect)’. While no single approach was deemed superior, common challenges noted among approaches were: ‘capturing an expert’s knowledge’, ‘confirming quality of knowledge’, and ‘continual knowledge capture’. However, continual knowledge capture was not fully explored in the papers retrieved and was highlighted as an important area for future research. Acknowledgments: This research is partially funded by the ADAPT Centre under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.

Keywords: expert knowledge, healthcare, knowledge capture and knowledge management

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Gayathri Devi V, Aravamudan Kannan, Amit Sircar

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In the inner fuel cycle system of a nuclear fusion reactor, the Hydrogen Isotopes Removal System (HIRS) plays a pivoted role. It enables the effective extraction of the hydrogen isotopes from the breeder purge gas which helps to maintain the tritium breeding ratio and sustain the fusion reaction. One of the components of HIRS, Cryogenic Molecular Sieve Bed (CMSB) columns with zeolites adsorbents are considered for the physisorption of hydrogen isotopes at 1 bar and 77 K. Even though zeolites have good thermal stability and reduced activation properties making them ideal for use in nuclear reactor applications, their modest capacity for hydrogen isotopes adsorption is a cause of concern. In order to enhance the adsorbent capacity in an informed manner, it is helpful to understand the adsorption phenomena at the quantum electronic structure level. Physicochemical modifications of the adsorbent material enhances the adsorption capacity through the incorporation of active sites. This may be accomplished through the incorporation of suitable metal ions in the zeolite framework. In this work, molecular hydrogen isotopes adsorption on the active sites of functionalized zeolites are investigated in detail using Density Functional Theory (DFT) study. This involves the utilization of hybrid Generalized Gradient Approximation (GGA) with dispersion correction to account for the exchange and correlation functional of DFT. The electronic energies, adsorption enthalpy, adsorption free energy, Highest Occupied Molecular Orbital (HOMO), Lowest Unoccupied Molecular Orbital (LUMO) energies are computed on the stable 8T zeolite clusters as well as the periodic structure functionalized with different active sites. The characteristics of the dihydrogen bond with the active metal sites and the isotopic effects are also studied in detail. Validation studies with DFT will also be presented for adsorption of hydrogen on metal ion functionalized zeolites. The ab-inito screening analysis gave insights regarding the mechanism of hydrogen interaction with the zeolites under study and also the effect of the metal ion on adsorption. This detailed study provides guidelines for selection of the appropriate metal ions that may be incorporated in the zeolites framework for effective adsorption of hydrogen isotopes in the HIRS.

Keywords: adsorption enthalpy, functionalized zeolites, hydrogen isotopes, nuclear fusion, physisorption

Procedia PDF Downloads 179

Authors: Y. Alqaheem, A. Alomair, F. Altarkait, F. Alswaileh, Nusrat Tanoli

Abstract:

Helium market is continuously growing due to its essential uses in the electronic and healthcare sectors. Currently, helium is produced by cryogenic distillation but the process is uneconomical especially for low production volumes. On the other hand, polymeric membranes can provide a cost-effective solution for helium purification due to their low operating energy. However, the preparation of membranes involves the use of very toxic solvents such as chloroform. In this work, polyetherimide membranes were prepared using a less toxic solvent, n-methylpyrrolidone with a polymer-to-solvent ratio of 27 wt%. The developed membrane showed a superior helium permeability of 15.9 Barrer that surpassed the permeability of membranes made by chloroform.

Keywords: helium separation, polyetherimide, dense membrane, gas permeability

Procedia PDF Downloads 168

Authors: A. Shahsavar, Z. Jakub

Abstract:

Due to the outstanding properties of the 2D metal-organic frameworks (MOF), intensive computational and experimental studies have been done. However, the lack of fundamental studies of MOFs on the graphene backbone is observed. This work studies Fe and Ni as metal and tetracyanoquinodimethane (TCNQ) with a high electron affinity as an organic linker functionalized on graphene. Here we present DFT calculations results to unveil the electronic and magnetic properties of iron and nickel-TCNQ physisorbed on graphene. Adsorption and Fermi energies, structural, and magnetic properties will be reported. Our experimental observations prove Fe- and NiTCNQ@Gr/Ir(111) are thermally highly stable up to 500 and 250°C, respectively, making them promising materials for single-atom catalysts or high-density storage media.

Keywords: DFT, graphene, MTCNQ, self-assembly

Procedia PDF Downloads 132

Authors: M. Strémy, P. Závacký, P. Cuninka, M. Juhás

Abstract:

Main goal of this paper is to introduce our design of private cloud for storing large amount of data, especially pictures, and to provide good technological backend for data analysis based on parallel processing and business intelligence. We have tested hypervisors, cloud management tools, storage for storing all data and Hadoop to provide data analysis on unstructured data. Providing high availability, virtual network management, logical separation of projects and also rapid deployment of physical servers to our environment was also needed.

Keywords: cloud, glusterfs, hadoop, juju, kvm, maas, openstack, virtualization

Procedia PDF Downloads 353

Authors: R. M. Kalayappan, N. Kathiravan

Abstract:

In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

Procedia PDF Downloads 398

Authors: Fatih Sogut

Abstract:

Developments in information technologies have caused significant changes in terms of radio and television broadcasting. With these changes in terms of production format, transmission techniques and service delivery, the distinction between traditional media and New Media has emerged. The viewer/listener, who was in a passive position before, is now in an active position and has a say in many matters, including content production. Visual and auditory data transfer has diversified and become easier thanks to the convergence phenomenon. These transformations and developments also affected one of the oldest electronic communication tools, radio. In this study, in order to adapt to the new era that emerged with the digital age, the change in radio broadcasting and the factors that led to this change were tried to be explained.

Keywords: Internet, radio broadcasting, digital transformation, Internet broadcasting

Procedia PDF Downloads 170

Authors: Syed W. Hasan, Zhiqun Tian

Abstract:

Wet spinning provides a facile and economic route to fabricate graphene nanofibers (GFs) on mass scale. Nevertheless, the pristine GFs exhibit significantly low electrical and mechanical properties owing to stacked graphene sheets and weak inter-atomic bonding. In this report, we present highly conductive Ag-decorated-GFs (Ag/GFs). The SEM micrographs show Ag nanoparticles (NPs) (dia ~10 nm) are homogeneously distributed throughout the cross-section of the fiber. The Ag NPs provide a conductive network for the electrons flow raising the conductivity to 1.8(10^4) S/m which is 4 times higher than the pristine GFs. Our results surpass the conductivities of graphene fibers doped with CNTs, Nanocarbon, fullerene, and Cu. The chemical and structural attributes of Ag/GFs are further elucidated through XPS, AFM and Raman spectroscopy.

Keywords: Ag nanoparticles, Conductive fibers, Graphene, Wet spinning

Procedia PDF Downloads 142

Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

Abstract:

Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

Procedia PDF Downloads 212

Authors: A. R. Bagirzade, A. Sh. Najafova, S. M. Yessirkepova, E. S. Albert

Abstract:

This article describes a text recognition method based on Optical Character Recognition (OCR). The features of the OCR method were examined using the ABBYY FineReader program. It describes automatic text recognition in images. OCR is necessary because optical input devices can only transmit raster graphics as a result. Text recognition describes the task of recognizing letters shown as such, to identify and assign them an assigned numerical value in accordance with the usual text encoding (ASCII, Unicode). The peculiarity of this study conducted by the authors using the example of the ABBYY FineReader, was confirmed and shown in practice, the improvement of digital text recognition platforms developed by Electronic Publication.

Keywords: ABBYY FineReader system, algorithm symbol recognition, OCR/ICR techniques, recognition technologies

Procedia PDF Downloads 168

Authors: R. Venkatesan, A. Sabari

Abstract:

Developments of social networking internet scenario are recommended for the requirements of scalable, authentic, secure group communication model like multicasting. Multicasting is an inter network service that offers efficient delivery of data from a source to multiple destinations. Even though multicast has been very successful at providing an efficient and best-effort data delivery service for huge groups, it verified complex process to expand other features to multicast in a scalable way. Separately, the requirement for secure electronic information had become gradually more apparent. Since multicast applications are deployed for mainstream purpose the need to secure multicast communications will become significant.

Keywords: multicasting, scalability, security, social network

Procedia PDF Downloads 292

Authors: Mustapha Majid

Abstract:

Gone were the days when technicians/mechanics will have to spend too much time trying to identify a mechanical fault and rectify the problem. Now the emphasis is on the use of Automobile diagnosing Equipment through the use of computers and special software. An investigation conducted at Tamale Metropolis and Accra in the Northern and Greater Accra regions of Ghana, respectively. Methodology for data gathering were; questionnaires, physical observation, interviews, and newspaper. The study revealed that majority of mechanics lack computer skills which can enable them use diagnosis tools such as Exhaust Gas Analyzer, Scan Tools, Electronic Wheel Balancing machine, etc.

Keywords: diagnosing, local garages and modern garages, lack of knowledge of diagnosing posing an existential threat, training of local mechanics

Procedia PDF Downloads 161

Authors: Amna Khaliq

Abstract:

In this article, the phenomena of common stereotypes and glass ceiling barriers in women’s career advancement in men dominating society are explored. A brief background is provided on the misconception for women as soft, delicate, polite and compassionate at a workplace in the place of strong head and go-getter. Then, the literature review supports that stereotypes and glass ceiling barriers are still in existence for young women’s leadership. Increased encouragement, emotional intelligence, and better communication skills are recommended to parents, educators, and employers to prepare young women for senior leadership roles. Young women need mentorship from other women with no competition.

Keywords: Gender inequality, Glass ceiling, Stereotypes, Leadership

Procedia PDF Downloads 166